An Unexpectedly Complex Architecture for Skin Pigmentation in Africans
Open accessPublished version of a preprint
Abstract
Approximately 15 genes have been directly associated with skin pigmentation variation in humans, leading to its characterization as a relatively simple trait. However, by assembling a global survey of quantitative skin pigmentation phenotypes, we demonstrate that pigmentation is more complex than previously assumed, with genetic architecture varying by latitude. We investigate polygenicity in the KhoeSan populations indigenous to southern Africa who have considerably lighter skin than equatorial Africans. We demonstrate that skin pigmentation is highly heritable, but known pigmentation loci explain only a small fraction of the variance. Rather, baseline skin pigmentation is a complex, polygenic trait in the KhoeSan. Despite this, we identify canonical and non-canonical skin pigmentation loci, including near SLC24A5, TYRP1, SMARCA2/VLDLR, and SNX13, using a genome-wide association approach complemented by targeted resequencing. By considering diverse, under-studied African populations, we show how the architecture of skin pigmentation can vary across humans subject to different local evolutionary pressures.
AI snapshot
Written from the paper’s full text.
TL;DR
Skin pigmentation in KhoeSan populations is highly heritable, but known pigmentation loci explain only a small fraction of variation, indicating a more polygenic architecture than in Eurasians. The study identifies both canonical and non-canonical associations and shows that global pigmentation variance varies with latitude.
Key findings
- In a global survey of 4,712 individuals across 32 populations, absolute latitude was associated with mean skin pigmentation (R²=0.53, β=−1.18 on M index scale, p<2e-16) and negatively associated with the standard deviation in melanin (R²=0.41, p=5.0e-5); lighter populations had reduced phenotypic variance.
- Among 479 phenotyped KhoeSan (277 ‡Khomani, 202 Nama), baseline upper-arm M index was 57.57±10.12 in ‡Khomani and 52.12±8.93 in Nama; ‡Khomani were significantly darker (p=3.6e-10). Baseline pigmentation was highly heritable: h²pedigree=0.96±0.12, h²g=0.97±0.15, h²exome=0.95±0.26, and h²IBD=0.97±0.15, while tanning-status heritability estimates were not significantly greater than 0.
- Known pigmentation gene sets explained little heritability: GS1 σ²=0.08 vs genome σ²=0.82 (p=2.7e-5); GS2 σ²=0.09 vs genome σ²=0.79 (p=3.3e-4); GS3 σ²=0.23±0.13 (p=0.027) vs genome σ²=0.64±0.08. Fixed admixture effects explained 34% of skin-color variation.
- Associations included SLC24A5 rs1426654 (β=−3.58, p=9.8e-9) and rs2470102 (β=−3.4, p=3.6e-12), an upstream TYRP1 signal (chr9:12088112, β=−13.6, p=1.1e-7), SNX13 rs2110015 (β=−3.1, p=1.3e-7), and low-frequency signals near SMARCA2/VLDLR (rs7866411 p=8.91e-5; rs2093835 p=1.17e-4). Most previously identified pigmentation associations did not replicate.
Methods
- Skin pigmentation was measured quantitatively with a DermaSpectrometer DSMII; baseline M index was taken from upper inner arms, and tanning status was wrist minus baseline. The study phenotyped 479 individuals and genotyped 465 KhoeSan (278 ‡Khomani, 187 Nama), with exome and targeted resequencing in subsets.
- A two-stage GWAS used imputed variants in phase 1 (107 ‡Khomani, 109 Nama), added 240 individuals in phase 2, and meta-analyzed results. Linear mixed models included admixture covariates and a REAP kinship matrix; targeted resequencing covered candidate pigmentation regions in 451 KhoeSan (269 ‡Khomani, 182 Nama) per the Results.
- Heritability and variance partitioning used SOLAR pedigree analysis, GCTA REML with REAP/GCTA/IBD/exome matrices, and gene-set comparisons (GS1, GS2, GS3 vs rest of genome). Ancestry was estimated with ADMIXTURE/PCA and local ancestry with RFMix.
Limitations
- The paper states that most known pigmentation associations did not replicate, potentially due to low allele frequencies, power limitations, differentiated LD structure where tag SNPs are non-causal, or epistatic effects. It also states that three possible evolutionary scenarios for elevated SLC24A5 variant frequencies require future work, and that fuller characterization is needed to distinguish directional versus stabilizing selection.
- The paper notes that continental Africans remain understudied and that the study focuses on two KhoeSan populations, the ‡Khomani San and Nama, both with recent European and Bantu admixture.
- Evident from the text: targeted resequencing was limited to candidate regions, imputation relied on reference panels, and GWAS sample sizes were modest relative to large complex-trait studies; baseline phenotype was upper inner-arm M index, while tanning status was largely environmental.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 35 cited sources checked · 0 supported · 0 flagged
- Findingown data
Skin pigmentation is strongly associated with absolute latitude; populations further from the equator have lighter skin pigmentation.
“As previously observed (Byard, 1981; Jablonski and Chaplin, 2010; Zaidi et al., 2017), we find that skin pigmentation is strongly associated with absolute latitude (R2=0.53, β=−1.18 on M index scale, p<2e-16); populations further from the equator have lighter skin pigmentation.”
Quote in the paperSubstantial claim0 of 3 sources checked - Findingown data
Known pigmentation loci explain only a small fraction of the variance in skin pigmentation in the KhoeSan.
“We demonstrate that skin pigmentation is highly heritable, but known pigmentation loci explain only a small fraction of the variance.”
Quote in the paperSubstantial claim - Findingown data
Canonical and non-canonical skin pigmentation loci were identified near SLC24A5, TYRP1, SMARCA2/VLDLR, and SNX13.
“Despite this, we identify canonical and non-canonical skin pigmentation loci, including near SLC24A5, TYRP1, SMARCA2/VLDLR, and SNX13 using a genome-wide association approach complemented by targeted resequencing.”
Quote in the paperSubstantial claim - Findingown data
Skin pigmentation is highly heritable in the KhoeSan.
“We demonstrate that skin pigmentation is highly heritable, but known pigmentation loci explain only a small fraction of the variance.”
Quote in the paperSubstantial claim - Findingown data
In the larger resequencing sample, more variants are significantly associated with pigmentation than expected by chance in the resequencing regions.
“In this larger sample, we observe more variants significantly associated with pigmentation than expected by chance in the resequencing regions (Figure 5A).”
Quote in the paperSubstantial claim
- Findingown data
rs1800417 is not significantly associated with skin pigmentation (p=0.87).
“We identified a missense mutation in OCA2 (rs1800417, ns with skin pigmentation: p=0.87) with a derived allele (G) frequency of 0.32 in the KhoeSan (Table S6A) that is at low frequency in all other populations surveyed (global allele frequency = 0.016 in Phase 3 1000 Genomes and 0.0058 in the Exome Aggregation Consortium, ExAC).”
Quote in the paperSubstantial claim - Findingown data
The majority of heritable variation in skin pigmentation remains to be explained.
“We find that the GS3 loci explain significantly more of the heritable variation in skin pigmentation than previously identified pigmentation candidate genes in the KhoeSan, but that the majority of heritable variation remains to be explained (Figure 3B, σ2GS3=0.23±0.13, pGS3=0.027 vs σ2Genome=0.64±0.08, pGenome<1e-5).”
Quote in the paperSubstantial claim - Findingown data
Tanning status is not significantly associated with admixture proportions.
“Tanning status is significantly associated with both sex (male β=6.2 increase in M index, p = 4.2e-4) and age (β=0.18 increase in M index per year, p=1.8e-4), but not with admixture proportions.”
Quote in the paperNot a substantial claim - Findingown data
Skin pigmentation is lighter in the KhoeSan than the majority of other African populations.
“Skin pigmentation is lighter in the KhoeSan than the majority of other African populations, with baseline upper arm M index = 57.57 ± 10.12 (mean ± sd) in the ‡Khomani San.”
Quote in the paperSubstantial claim - Findingown data
Derived SLC24A5 SNPs, including rs1426654, are significantly associated with lighter skin.
“We identify significant associations between lighter skin and derived SLC24A5 SNPs, including the putatively causal p.Thr111Ala rs1426654 allele (β=−3.58 on M index scale, p=9.8e-9), which has previously been associated with skin pigmentation in Eurasians.”
Quote in the paperSubstantial claim - Findingown data
Variance in pigmentation is significantly greater in more admixed individuals.
“Interestingly, the mean pigmentation of Nama and ‡Khomani individuals with <90% KhoeSan ancestry is not significantly different from individuals with >90% KhoeSan ancestry (p=0.94), although the variance is significantly greater in more admixed individuals (admixture from either/both European or Bantu ancestries, p=2.2e-3).”
Quote in the paperSubstantial claim - Findingown data
There is considerable divergence in many canonical pigmentation genes when comparing regions of the genome across KhoeSan, West African, and European populations.
“We find considerable divergence in many canonical pigmentation genes when comparing regions of the genome across populations (Figure 4A–B).”
Quote in the paperSubstantial claim - Findingown data
The variance in skin pigmentation is not significantly different between ‡Khomani and Nama.
“The ‡Khomani are on average significantly darker than the Nama (p=3.6e-10, Figure 1C), but the variance is not significantly different (p>0.05).”
Quote in the paperNot a substantial claim - Findingown data
Divergence in SLC24A5 is among the highest in the genome, especially between KhoeSan and European populations.
“The divergence in SLC24A5 is among the highest in the genome, especially between the KhoeSan and European populations (Figure 4D).”
Quote in the paperNot a substantial claim - Findingnone given
rs1426654 derived allele frequencies are 99.7% in Europeans vs 5.5% in Africans in 1000 Genomes excluding ASW/ACB.
“These variants are strongly differentiated between Europeans and Africans, with rs1426654 having derived allele frequencies of 99.7% vs 5.5% in 1000 Genomes (excluding ASW and ACB populations with recent European admixture), respectively.”
Quote in the paperSubstantial claim - Findingown data
GS3 explains a small but significant fraction of the heritability of skin pigmentation.
“GS3 explains a small but significant fraction of the heritability, as discussed below.”
Quote in the paperSubstantial claim - Findingown data
None of the tanning status heritability estimates are significantly greater than 0.
“None of the tanning status h2 estimates, including pedigree-, IBD-, exome-, and SNP array-based estimates, are significantly greater than 0 (Table 1), consistent with previous observations that tanning status is largely environmentally determined by UV exposure (Clark et al., 1981; Nan et al., 2009).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Clark et al., 1981 source
Not checked in the free run.
- cites Nan et al., 2009
Not checked in the free run.
- Findingown data
Exome sequence-based heritability of baseline skin pigmentation in ‡Khomani is 0.95 ± 0.26.
“We find consistent results from exome sequence data, where we estimate that hexome2=0.95±0.26 in the ‡Khomani.”
Quote in the paperSubstantial claim - Findingown data
The strongest signal comes from SNPs in SLC24A5, 8 of which are in high pairwise LD on a high frequency haplotype.
“The strongest signal comes from SNPs in SLC24A5, 8 of which are all in high pairwise LD (R2 > 0.6) on a high frequency haplotype (Figure 5B).”
Quote in the paperSubstantial claim - Findingown data
A missense mutation in OCA2 (rs1800417) has derived allele frequency 0.32 in KhoeSan.
“We identified a missense mutation in OCA2 (rs1800417, ns with skin pigmentation: p=0.87) with a derived allele (G) frequency of 0.32 in the KhoeSan (Table S6A) that is at low frequency in all other populations surveyed (global allele frequency = 0.016 in Phase 3 1000 Genomes and 0.0058 in the Exome Aggregation Consortium, ExAC).”
Quote in the paperSubstantial claim - Findingown data
The remainder of the genome explains the overwhelming majority of the heritability of skin pigmentation in KhoeSan.
“Rather, the remainder of the genome explains the overwhelming majority of the heritability (Figure 3B, σ2GS1=0.08 vs σ2Genome=0.82, pGenome=2.7e-5; σ2GS2=0.09 vs σ2Genome=0.79, pGenome=3.3e-4; and σ2GS1=0.08 vs σ2GS2=0.09 vs σ2Genome=0.71, pGenome=2.5e-3, respectively).”
Quote in the paperSubstantial claim - Findingown data
Tanning status is significantly associated with age (β=0.18 increase in M index per year).
“Tanning status is significantly associated with both sex (male β=6.2 increase in M index, p = 4.2e-4) and age (β=0.18 increase in M index per year, p=1.8e-4), but not with admixture proportions.”
Quote in the paperNot a substantial claim - Findingown data
Melanin distributions are heteroskedastic, with the coefficient of variation decreasing with increasing distance from the equator.
“Further, melanin distributions are heteroskedastic (i.e. the variance is not constant—rather, it changes over the range of observed M index), with the coefficient of variation, a standardized metric of phenotypic dispersion, decreasing with increasing distance from the equator (cv=σ/μ, R2=0.14, p=0.03, Table S1).”
Quote in the paperSubstantial claim - Findingown data
GS1 and GS2 gene sets do not explain a significant fraction of the heritability of skin pigmentation in KhoeSan.
“The GS1 and GS2 gene sets do not explain a significant fraction of the heritability; that is, the heritability estimates overlap with zero.”
Quote in the paperSubstantial claim - Findingown data
European ancestry is strongly correlated with light skin in a multivariate mixed model.
“In a multivariate mixed model with the significant European and Bantu admixture components, European and Bantu ancestry are strongly correlated with light (β = −18.09, p=2.9e-03) and dark skin (β = 25.60, p=1.8e-09), respectively.”
Quote in the paperSubstantial claim - Findingcitation
The western African fraction in the Nama is significantly more variable among individuals.
“The western African fraction in the Nama is significantly more variable among individuals (p=1.08e-5), resulting from recent Damara gene flow (Uren et al., 2016a).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Uren et al., 2016a
Not checked in the free run.
- Findingown data
Baseline upper arm M index in Nama is 52.12 ± 8.93.
“Baseline upper arm pigmentation in the Nama is slightly lower, with M index = 52.12 ± 8.93.”
Quote in the paperNot a substantial claim - Findingown data
Populations with lighter skin have significantly reduced phenotypic variance than expected by chance.
“A sign test comparing variances in lighter versus darker population pairs within the same study indicates that populations with lighter skin have significantly reduced phenotypic variance than expected by chance (p=2.01e-8).”
Quote in the paperSubstantial claim - Findingown data
Less-studied equatorial and admixed populations vary considerably more in skin pigmentation than lightly pigmented European and East Asian populations.
“Less-studied equatorial and admixed populations, including Melanesians, Ghanaians, Cape Verdeans, South African admixed Coloured, and South Asians vary considerably more in skin pigmentation (Figure 1B).”
Quote in the paperSubstantial claim - Findingown data
Absolute latitude is significantly negatively associated with the standard deviation in melanin.
“We find that absolute latitude is also significantly negatively associated with the standard deviation in melanin (R2=0.41, p=5.0e-5).”
Quote in the paperSubstantial claim - Findingown data
rs1800417 is at low frequency in all other populations surveyed.
“We identified a missense mutation in OCA2 (rs1800417, ns with skin pigmentation: p=0.87) with a derived allele (G) frequency of 0.32 in the KhoeSan (Table S6A) that is at low frequency in all other populations surveyed (global allele frequency = 0.016 in Phase 3 1000 Genomes and 0.0058 in the Exome Aggregation Consortium, ExAC).”
Quote in the paperNot a substantial claim - Findingown data
Mean pigmentation of Nama and ‡Khomani individuals with <90% KhoeSan ancestry is not significantly different from individuals with >90% KhoeSan ancestry.
“Interestingly, the mean pigmentation of Nama and ‡Khomani individuals with <90% KhoeSan ancestry is not significantly different from individuals with >90% KhoeSan ancestry (p=0.94), although the variance is significantly greater in more admixed individuals (admixture from either/both European or Bantu ancestries, p=2.2e-3).”
Quote in the paperSubstantial claim - Findingown data
Different regions of OCA2 exhibit elevated divergence between the KhoeSan and European comparison versus the KhoeSan and West African comparison.
“Interestingly, different regions of OCA2 exhibit elevated divergence between the KhoeSan and European comparison versus the KhoeSan and West African comparison (Figure 4C).”
Quote in the paperNot a substantial claim - Findingown data
rs1800404 is not associated with skin pigmentation in KhoeSan (p=0.53).
“We confirm its elevated allele frequency on KhoeSan haplotypes (65%), but do not find an association with skin pigmentation (p=0.53).”
Quote in the paperSubstantial claim - Findingown data
IBD-based heritability of baseline skin pigmentation in ‡Khomani and Nama is 0.97 ± 0.15.
“We then used the familial relationships (Figure S1) and population-level endogamy to estimate heritability from IBD sharing among all individuals in the ‡Khomani and Nama; we obtain a similar estimate of hIBD2=0.97±0.15 (Methods, see also (Zaitlen et al., 2013)).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Zaitlen et al., 2013 source
Not checked in the free run.
- Findingown data
The derived rs1426654 allele frequency is significantly greater than expected from ~11% European admixture alone.
“The frequency of the derived rs1426654 allele is 40% in the combined Nama + ‡Khomani dataset, which is significantly greater than expected from ~11% European admixture alone (binomial test p=7.8e-52, Table S6A, STAR Methods).”
Quote in the paperSubstantial claim - Findingown data
Baseline upper arm M index in ‡Khomani San is 57.57 ± 10.12.
“Skin pigmentation is lighter in the KhoeSan than the majority of other African populations, with baseline upper arm M index = 57.57 ± 10.12 (mean ± sd) in the ‡Khomani San.”
Quote in the paperSubstantial claim - Findingown data
Among Melanesians, islands at similar latitudes with more lightly pigmented individuals on average show less variance than those with more darkly pigmented individuals.
“Among Melanesians, islands at similar latitudes with more lightly pigmented individuals on average show less variance than those with more darkly pigmented individuals (e.g. one-sided F test comparing variance among more lightly pigmented New Britain individuals versus individuals from Bougainville, p=2.89e-9, Figure 1B).”
Quote in the paperSubstantial claim - Findingown data
Multiple low-frequency (<5%) SNPs near EPM2A, FREM1, SMARCA2/VLDLR, and TYRP1 are above the 95% confidence interval of expected versus observed significance.
“Multiple low frequency (<5%) SNPs near several additional genes, including EPM2A, FREM1, SMARCA2/VLDLR, and TYRP1, are above the 95% confidence interval of expected versus observed significance (Figure 5).”
Quote in the paperSubstantial claim - Findingown data
At k=7, KhoeSan ancestry partitions into northern Kalahari ancestry shared with Ju|'hoansi and a distinct southern or circum-Kalahari ancestry present in the Nama and the ‡Khomani.
“For k=7, which gives most stable ancestry estimates, we observe a partitioning of the KhoeSan ancestry into ‘northern Kalahari’ ancestry shared with Ju|’hoansi and a distinct southern or circum-Kalahari ancestry present in the Nama and the ‡Khomani.”
Quote in the paperSubstantial claim - Findingown data
SNP array-based heritability (REAP GRM) of baseline skin pigmentation across both populations is 0.97 ± 0.15.
“We estimate hg2=0.97±0.15 (standard error) in an unconstrained model across both populations using the REAP GRM.”
Quote in the paperSubstantial claim - Findingown data
Bantu ancestry is strongly correlated with dark skin in a multivariate mixed model.
“In a multivariate mixed model with the significant European and Bantu admixture components, European and Bantu ancestry are strongly correlated with light (β = −18.09, p=2.9e-03) and dark skin (β = 25.60, p=1.8e-09), respectively.”
Quote in the paperSubstantial claim - Findingown data
Most previously identified pigmentation associations do not replicate with genome-wide significance or nominally in ‡Khomani and Nama.
“However, most previously identified pigmentation associations do not replicate with genome-wide significance or nominally in the ‡Khomani and Nama, with a few exceptions (STAR Methods).”
Quote in the paperSubstantial claim - Findingown data
Pedigree-based heritability of baseline skin color in KhoeSan is 0.96 ± 0.12.
“Via traditional pedigree-based estimation, we estimate an hpedigree2 of 0.96 ± 0.12 for baseline skin color (STAR Methods).”
Quote in the paperSubstantial claim - Findingown data
Tanning status is significantly associated with sex (male β=6.2 increase in M index).
“Tanning status is significantly associated with both sex (male β=6.2 increase in M index, p = 4.2e-4) and age (β=0.18 increase in M index per year, p=1.8e-4), but not with admixture proportions.”
Quote in the paperNot a substantial claim - Findingown data
GS3 loci explain significantly more heritable variation in skin pigmentation than previously identified pigmentation candidate genes in KhoeSan.
“We find that the GS3 loci explain significantly more of the heritable variation in skin pigmentation than previously identified pigmentation candidate genes in the KhoeSan, but that the majority of heritable variation remains to be explained (Figure 3B, σ2GS3=0.23±0.13, pGS3=0.027 vs σ2Genome=0.64±0.08, pGenome<1e-5).”
Quote in the paperSubstantial claim - Findingown data
Fixed admixture effects explained 34% of the variation in skin color.
“Together, we estimate that fixed admixture effects explained 34% of the variation in skin color (adjusted R2); by comparison, 44% of pigmentation variation in Cape Verdeans is explained by admixture effects (Beleza et al., 2013).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Beleza et al., 2013
Not checked in the free run.
- Findingown data
The derived T allele of rs1800404 in OCA2 has elevated frequency on KhoeSan haplotypes (65%).
“We confirm its elevated allele frequency on KhoeSan haplotypes (65%), but do not find an association with skin pigmentation (p=0.53).”
Quote in the paperSubstantial claim - Findingown data
The ‡Khomani are on average significantly darker than the Nama.
“The ‡Khomani are on average significantly darker than the Nama (p=3.6e-10, Figure 1C), but the variance is not significantly different (p>0.05).”
Quote in the paperNot a substantial claim - Findingown data
There is more than an order of magnitude difference in variance between the lightest and darkest populations (Irish vs Ghanaian).
“There is more than an order of magnitude difference in variance between the lightest and darkest populations (i.e. Irish vs Ghanaian F=0.03, p=6.7e-23).”
Quote in the paperSubstantial claim - Findingown data
The derived rs1426654 allele frequency is 40% in combined Nama+‡Khomani dataset.
“The frequency of the derived rs1426654 allele is 40% in the combined Nama + ‡Khomani dataset, which is significantly greater than expected from ~11% European admixture alone (binomial test p=7.8e-52, Table S6A, STAR Methods).”
Quote in the paperSubstantial claim - Findingown data
All gene sets, including previously associated loci, canonical pigmentation genes, and the most significantly associated variants in this study, explained a small fraction of the phenotypic variance (σ2GS1=0.08, σ2GS2=0.09, σ2GS3=0.23).
“All gene sets, including previously associated loci, canonical pigmentation genes, and the most significantly associated variants in this study, explained a small fraction of the phenotypic variance (σ2GS1=0.08, σ2GS2=0.09, σ2GS3=0.23, respectively).”
Quote in the paperSubstantial claim - Findingown data
There is a strong correlation between absolute latitude and average skin pigmentation reflectance caused by melanin content.
“we find a strong correlation between absolute latitude and average skin pigmentation reflectance caused by melanin content.”
Quote in the paperSubstantial claim - Findingown data
Two tanning status associations met genome-wide significance in the second-phase GWAS meta-analysis.
“While two tanning status associations met genome-wide significance, none of the loci contained linkage peaks, suggesting that they are most likely spurious as expected from a phenotype with low heritability.”
Quote in the paperNot a substantial claim - Findingown data
Four SNPs in SLC45A2 (rs16891982, p=1.2e-3), KITLG (rs12821256, p=0.02), and SLC24A5 (rs1426654, p=9.8e-9 and rs2470102, p=1.1e-8) marginally replicate in the ‡Khomani + Nama under an additive model.
“Four SNPs in the genes SLC45A2 (rs16891982, p=1.2e-3), KITLG (rs12821256, p=0.02), and SLC24A5 (rs1426654, p=9.8e-9 and rs2470102, p=1.1e-8) marginally replicate in the ‡Khomani + Nama under an additive model.”
Quote in the paperSubstantial claim - Findingown data
Baseline skin pigmentation is virtually completely heritable in the KhoeSan sample.
“We assessed the heritability of baseline skin pigmentation, and find that it is virtually completely heritable in our KhoeSan sample.”
Quote in the paperSubstantial claim - Findingown data
There are several independent associations near SMARCA2 and VLDLR.
“Specifically, we find several independent associations near SMARCA2 and VLDLR.”
Quote in the paperSubstantial claim - Findingown data
The strongest association is in SLC24A5.
“The strongest association is in SLC24A5”
Quote in the paperNot a substantial claim - Findingown data
Multiple enhancer and DNAse peaks identified in skin, including melanocytes and/or keratinocytes, overlap top tag and/or perfectly linked SNPs near these peaks.
“We used HaploReg to infer regulatory activity in/near these peaks and identify multiple enhancer and DNAse peaks identified in skin, including melanocytes and/or keratinocytes, overlapping top tag and/or perfectly linked SNPs (Table S6B).”
Quote in the paperSubstantial claim - Findingown data
None of the loci for the two genome-wide significant tanning status associations contained linkage peaks.
“While two tanning status associations met genome-wide significance, none of the loci contained linkage peaks, suggesting that they are most likely spurious as expected from a phenotype with low heritability.”
Quote in the paperSubstantial claim - Findingown data
There are more than five independent low-frequency signals with p<1e-3 within or near SMARCA2 and VLDLR.
“In contrast, there are >5 independent low frequency signals with p<1e-3 within/near SMARCA2 and VLDLR, with rs7866411 (p=8.91e-5) and rs2093835 (p=1.17e-4) being most significantly associated with skin pigmentation.”
Quote in the paperSubstantial claim - Findingown data
A suggestive association with skin pigmentation was identified upstream of TYRP1 (chr9:12088112, frequency=0.014, β = −13.6, p=1.1e-07).
“and a suggestive association upstream of TYRP1 (chr9:12088112, frequency=0.014, β = −13.6, p=1.1e-07 Figure S6B–C, Figure S6F–G).”
Quote in the paperSubstantial claim - Findingown data
Few known loci replicate with genome-wide significance or even marginally in the KhoeSan populations studied here.
“Few known loci replicate with genome-wide significance or even marginally in the KhoeSan populations studied here.”
Quote in the paperSubstantial claim - Findingown data
rs7866411 (p=8.91e-5) and rs2093835 (p=1.17e-4) are the most significantly associated with skin pigmentation among the SMARCA2/VLDLR signals.
“In contrast, there are >5 independent low frequency signals with p<1e-3 within/near SMARCA2 and VLDLR, with rs7866411 (p=8.91e-5) and rs2093835 (p=1.17e-4) being most significantly associated with skin pigmentation.”
Quote in the paperSubstantial claim - Findingown data
The vast majority of previously observed skin pigmentation associations do not replicate in the dataset.
“We do not replicate the vast majority of previously observed skin pigmentation associations in our dataset”
Quote in the paperSubstantial claim - Findingown data
These SLC24A5 variants are segregating at higher frequency than expected by recent European admixture alone.
“Notably, these variants are segregating at higher frequency than expected by recent European admixture alone.”
Quote in the paperSubstantial claim - Findingown data
A low-frequency variant rs34803545 (p=3.7e-4) is associated with skin pigmentation approximately 600 kb upstream of TYRP1.
“We also identify a low frequency association (rs34803545, p=3.7e-4) ~600 kb upstream of TYRP1.”
Quote in the paperSubstantial claim - Findingown data
Aggregating a large set of quantitative skin pigmentation phenotypes (N=4,712) from globally diverse populations demonstrated heteroskedasticity as a function of latitude.
“By aggregating a large set of quantitative skin pigmentation phenotypes (N=4,712) from globally diverse populations, we have demonstrated heteroskedasticity as a function of latitude.”
Quote in the paperSubstantial claim - Findingown data
A predictive model based on 9 SNPs shows no significant association between predicted skin color and spectrophotometrically measured skin M index in the Nama and ‡Khomani San populations.
“We applied a predictive model based on these SNPs to the Nama and ‡Khomani San populations, and find no significant association between predicted skin color and spectrophotometrically measured skin M index”
Quote in the paperSubstantial claim - Findingown data
An additional suggestive novel association with skin pigmentation was identified in and near SNX13, with common derived T alleles of rs2110015 associated with light skin (β = −3.1, p=1.3e-07).
“We identified an additional suggestive novel association in and near SNX13, with common derived T alleles of rs2110015 associated with light skin (β = −3.1, p=1.3e-07, Figure S6H)”
Quote in the paperSubstantial claim- Rests on an assumption: SNX13 has not previously been associated with skin pigmentation.
- Findingown data
SNPs in OCA2, SLC24A5 and GRM5/TYR are at much higher frequencies in both the ‡Khomani and Nama than expected from European admixture alone.
“Interestingly, however, SNPs in OCA2, SLC24A5 and GRM5/TYR are at much higher frequencies in both the ‡Khomani and Nama than expected from European admixture alone, as estimated from global ancestry”
Quote in the paperSubstantial claim - Findingown data
The forensic models based on only seven SNPs that claim very high prediction accuracy of skin color across populations (>99%) did not show a significant association with quantitatively measured M index (p=0.31).
“It is therefore unsurprising that when we applied forensic models based on only seven SNPs that claim very high prediction accuracy of skin color across populations (>99%) (Hart et al., 2013b; Spichenok et al., 2011), we did not find a significant association with quantitatively measured M index (p=0.31, Figure S5B).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Hart et al., 2013b
Not checked in the free run.
- cites Spichenok et al., 2011 source
Not checked in the free run.
- Findingown data
A genome-wide significant association with skin pigmentation was identified in SLC24A5 (rs2470102 derived allele β = −3.4, p=3.6e-12).
“we identified a genome-wide significant association in SLC24A5 (rs2470102 derived allele β = −3.4, p=3.6e-12)”
Quote in the paperSubstantial claim - Findingown data
Across all GWAS efforts, there is a significant enrichment of genes related to melanogenesis.
“Across all GWAS efforts, we find a significant enrichment of genes related to melanogenesis.”
Quote in the paperSubstantial claim - Findingown data
There is a suggestive association upstream of TYRP1.
“We also find a suggestive association upstream of TYRP1 (Figure 5A, Figure S6G).”
Quote in the paperNot a substantial claim - Interpretationreasoning
Baseline skin pigmentation is a complex, polygenic trait in the KhoeSan.
“Rather, baseline skin pigmentation is a complex, polygenic trait in the KhoeSan.”
Quote in the paperSubstantial claim - Interpretationown data
The architecture of skin pigmentation can vary across humans subject to different local evolutionary pressures.
“By considering diverse, under-studied African populations, we show how the architecture of skin pigmentation can vary across humans subject to different local evolutionary pressures.”
Quote in the paperSubstantial claim - Interpretationown data
The vast majority of variation in KhoeSan skin pigmentation arises from pigmentation genes yet to be discovered.
“This result contrasts with conclusions from previous studies and indicates that the vast majority of variation in KhoeSan skin pigmentation arises from pigmentation genes yet to be discovered, providing strong evidence for a complex, polygenic architecture.”
Quote in the paperSubstantial claim - Interpretationreasoning
These patterns suggest that selection is acting differently at different latitudes.
“These patterns suggest that selection is acting differently at different latitudes.”
Quote in the paperSubstantial claim - Study design and conductown data
The best model fit, measured via AIC, included Bantu, European, East African, and Hadza ancestries.
“The best model fit, measured via AIC, included Bantu, European, East African, and Hadza ancestries, although the latter two components comprise ≤ 1% of individuals’ total ancestry on average and are likely imprecise.”
Quote in the paperSubstantial claim - Interpretationcitation
Genetic risk prediction is strongly affected by population structure.
“As expected from previous work (Martin et al., 2017), our results indicate that genetic risk prediction is strongly affected by population structure.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Martin et al., 2017 source
Not checked in the free run.
- Interpretationreasoning
The evolution of the pigmentation phenotype in these populations cannot be explained in terms of only a few variants segregating in Eurasians.
“The evolution of the pigmentation phenotype in these populations cannot be explained in terms of only a few variants segregating in Eurasians.”
Quote in the paperSubstantial claim - Interpretationown data
The 9-SNP predictive model fails to capture the genetic variation driving skin pigmentation in the KhoeSan.
“showing that this estimation fails to capture the genetic variation driving the phenotype in the KhoeSan.”
Quote in the paperSubstantial claim - Interpretationreasoning
The distributions of skin pigmentation globally suggest different forces of selection operating at various latitudes.
“We argue that the distributions of skin pigmentation globally suggest different forces of selection operating at various latitudes.”
Quote in the paperSubstantial claim - Interpretationown data
Pigmentation in African populations cannot simply be explained by the small number of large effect alleles discovered in Eurasians.
“and we show that pigmentation in African populations cannot simply be explained by the small number of large effect alleles discovered in Eurasians.”
Quote in the paperSubstantial claim- Rests on an assumption: African populations often carry the ancestral (i.e. dark) allele for skin pigmentation genes identified in Eurasians.
- Interpretationown data
The two genome-wide significant tanning status associations are most likely spurious, as expected from a phenotype with low heritability.
“While two tanning status associations met genome-wide significance, none of the loci contained linkage peaks, suggesting that they are most likely spurious as expected from a phenotype with low heritability.”
Quote in the paperSubstantial claim - Premisecitation
In European populations, predictive models based on only 9 SNPs capture up to 16% of the variance in skin pigmentation.
“In European populations, predictive models based on only 9 SNPs capture up to 16% of the variance in skin pigmentation (Liu et al., 2015), highlighting its relative simplicity.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Liu et al., 2015 source
Not checked in the free run.
- Interpretationreasoning
Pigmentation in far northern European and Asian populations has been under directional selection for decreased melanin production, reflected by very narrow distributions.
“In stark contrast, pigmentation in far northern European and Asian populations has been under directional selection for decreased melanin production, reflected by very narrow distributions.”
Quote in the paperNot a substantial claim - Interpretationcitation
The most parsimonious explanation for the intermediate-latitude pattern is that stabilizing selection affects the light and dark tails of the pigmentation distribution.
“The most parsimonious explanation for this pattern is that stabilizing selection affects the light and dark tails of the pigmentation distribution (Barton, 1999).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Barton, 1999 source
Not checked in the free run.
- Premisecitation
Southern African KhoeSan populations are the most polymorphic modern human populations yet studied.
“Southern African KhoeSan populations are the most polymorphic modern human populations yet studied (Henn et al., 2011)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Henn et al., 2011 source
Not checked in the free run.
- Interpretationreasoning
Light skin pigmentation in the KhoeSan appears to be due to a combination of many small-effect mutations as well as some large-effect variants.
“Given our heritability results and the observed variability in baseline pigmentation; light skin pigmentation in the KhoeSan appears to be due to a combination of many small-effect mutations as well as some large-effect variants.”
Quote in the paperSubstantial claim - Interpretationown data
Most of the pigmentation variability in KhoeSan populations is not explained by previously identified loci.
“Most of the pigmentation variability in KhoeSan populations is not explained by previously identified loci”
Quote in the paperSubstantial claim - Interpretationown data
The paper observes enrichments of molecular pathways involved in pigmentation beyond those previously identified as associated with the phenotype in non-African populations.
“Thus, we observe enrichments of molecular pathways involved in pigmentation beyond those previously identified as associated with the phenotype in non-African populations.”
Quote in the paperSubstantial claim - Premisecitation
VLDLR knockout mice exhibit hypopigmented retinas.
“Additionally, VLDLR knockout mice exhibit hypopigmented retinas (Xia et al., 2013b).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Xia et al., 2013b
Not checked in the free run.
- May combine two claims. 33
- Classified as probably not a substantial claim. 28
May combine two claims.
Findingown dataSkin pigmentation is more complex than previously assumed, with genetic architecture varying by latitude.
“However, by assembling a global survey of quantitative skin pigmentation phenotypes, we demonstrate that pigmentation is more complex than previously assumed with genetic architecture varying by latitude.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown datars2555364 is the most strongly associated SNP (β=−3.58, p=6.7e-9) and is tightly linked with rs1426654 (LD R2=0.81).
“The most strongly associated SNP (rs2555364, β=−3.58 on M index scale, p=6.7e-9) is tightly linked with rs1426654 (LD R2=0.81).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataBoth Nama and ‡Khomani have ~75-80% KhoeSan-specific ancestry.
“At k=3, we observe distinct clustering between Europeans, Bantu-speaking and West African populations, and KhoeSan populations; both the Nama and the ‡Khomani have ~75–80% KhoeSan-specific ancestry.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataBoth GS1 and GS2 explain more phenotypic variation than random genes with a 10% false discovery rate across both KhoeSan populations.
“After regressing out the effect of variable numbers of SNPs per gene set (STAR Methods), we find that both GS1 and GS2 explain more than random genes with a 10% false discovery rate (FDR=0.016 and FDR = 0.079, Figure 3C–D, respectively) across both KhoeSan populations.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown datars1426654 has β=−3.58 on M index scale, p=9.8e-9.
“We identify significant associations between lighter skin and derived SLC24A5 SNPs, including the putatively causal p.Thr111Ala rs1426654 allele (β=−3.58 on M index scale, p=9.8e-9), which has previously been associated with skin pigmentation in Eurasians.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe strongest signals across genotyped ‡Khomani and Nama cohorts were near canonical pigmentation genes, genes associated with pigmentation-related disorders, or genes implicated in pigmentation in model organisms and in vitro studies.
“Further, the strongest signals across the genotyped ‡Khomani and Nama cohorts were near canonical pigmentation genes (e.g. TYRP1 and SLC24A5), genes associated with pigmentation-related disorders (e.g. TYRP1), or genes implicated in pigmentation in model organisms and in vitro studies (e.g. VLDLR, SMARCA2, and others) (Sturm, 2009) (Keenen et al., 2009a; Xia et al., 2013a).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Sturm, 2009 source
Not checked in the free run.
- cites Keenen et al., 2009a
Not checked in the free run.
- cites Xia et al., 2013a
Not checked in the free run.
May combine two claims.
Findingown dataEuropeans and East Asians have significantly less variation than South Asians.
“Europeans and East Asians have significantly less variation than South Asians (F=0.25, p=1.06e-14 and F=0.30, p=1.27e-10, respectively, Figure 1B).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataCape Verdeans with the highest quartile of European admixture have lighter, less variable skin color than individuals with the lowest quartile of European ancestry.
“Cape Verdeans with the highest quartile of European admixture have lighter, less variable skin color than individuals with the lowest quartile of European ancestry (p=4.28e-9, although notably ancestry proportions are bimodal across individuals).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe derived allele frequencies of the associated SNPs in SLC45A2 and KITLG are low in the KhoeSan, consistent with ~10% admixture from recent European gene flow.
“The derived allele frequencies of the associated SNPs in SLC45A2 and KITLG are low in the KhoeSan, consistent with ~10% admixture from recent European gene flow.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataTanning status is primarily environmental, with heritability estimates not significantly different from zero.
“In contrast, tanning status is primarily environmental, with heritability estimates which are not significantly different from zero.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe strongest allelic associations include previously associated variants, noncoding regions near canonical pigmentation genes, and novel genes shown in model organisms to have a role in pigmentation.
“The strongest allelic associations include previously associated variants, noncoding regions near canonical pigmentation genes, and novel genes shown in model organisms to have a role in pigmentation.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown datars34803545 is perfectly linked with multiple conserved variants, one of which exhibits enhancer activity and DNAse hypersensitivity specifically in skin.
“This variant is perfectly linked with multiple conserved variants, one of which exhibits enhancer activity and DNAse hypersensitivity specifically in skin (Table S6B).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataDerived variants in SLC24A5 are at high frequency in the KhoeSan, including missense mutations that influence skin and eye pigmentation.
“We find that derived variants in SLC24A5 are at high frequency in the KhoeSan, including missense mutations that influence skin and eye pigmentation (Table 2).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based).
Findingnone givenSkin pigmentation varies more in Africa than any other continent.
“Here, we reiterate that skin pigmentation varies more in Africa than any other continent”
Quote in the paperNot a substantial claimMay combine two claims.
FindingcitationPopulations at intermediate latitudes have increased variance and higher means than populations in northern Eurasia, but less than equatorial populations.
“Finally, populations at intermediate latitudes have increased variance and higher means than populations in northern Eurasia, but less than equatorial populations.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataPopulations with lighter skin have reduced variation within any given study: populations furthest from the equator have narrower distributions, while populations closest to the equator have wider distributions.
“We also observe that populations with lighter skin have reduced variation within any given study: populations furthest from the equator have narrower distributions, while populations closest to the equator have wider distributions.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationPigmentation variation has been characterized as relatively simple, with only a handful of SNPs highly predictive of skin, eye, and hair color across populations.
“The relative paucity of loci identified from GWAS efforts has led to the characterization of pigmentation variation as relatively simple, with only a handful of SNPs being highly predictive of skin, eye, and hair color across populations (Hart et al., 2013a; Spichenok et al., 2011; Walsh et al., 2013).”
Quote in the paperSubstantial claim0 of 3 sources checkedClassified as probably not a substantial claim.
PremisecitationApproximately 15 genes have been directly associated with skin pigmentation variation in humans.
“While ~171 genes have been implicated in variability across model organisms (e.g. the Color Genes database: http://www.espcr.org/micemut/), only ~15 genes have been associated with skin color differences in humans (Table 2).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Table 2
Not checked in the free run.
May combine two claims.
Interpretationown dataThere is reduced genetic heterogeneity and/or reduced variance in the population distribution of causal effect sizes contributing to lighter versus darker pigmentation.
“These results suggest that there is reduced genetic heterogeneity and/or reduced variance in the population distribution of causal effect sizes contributing to lighter versus darker pigmentation.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataAdmixture increases phenotypic variance, but pigmentation alleles on KhoeSan haplotypes contribute more to overall heterogeneity than those on European or Bantu haplotypes.
“These results suggest that while admixture increases phenotypic variance, pigmentation alleles on KhoeSan haplotypes contribute more to the overall heterogeneity than those on European or Bantu haplotypes.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThe high baseline pigmentation heritability estimates do not simply arise from pedigree and population structure and socioeconomic factors are unlikely to have significant effect.
“The stark contrast of the baseline pigmentation and tanning status heritability estimates, and the consistency of h2 across methods indicates that our high baseline pigmentation heritability estimates do not simply arise from pedigree and population structure and that socioeconomic factors are unlikely to have significant effect on our heritability estimates.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe spectrophotometer was calibrated to 0 as suggested by the manufacturer twice a day while sampling.
“The device was calibrated to 0 as suggested by the manufacturer twice a day while sampling.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSLC24A5 is a well-known pigmentation gene.
“which is a well-known pigmentation gene (Lamason, 2005)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Lamason, 2005 source
Not checked in the free run.
Classified as probably not a substantial claim.
Study design and conductown dataThe proportion of European and Bantu ancestry estimated via ADMIXTURE was included as fixed effect covariates for baseline pigmentation and tanning status, as chosen in forward stepwise regression.
“We included the proportion of European and Bantu ancestry estimated via ADMIXTURE as fixed effect covariates for baseline pigmentation and tanning status, as chosen in forward stepwise regression.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
InterpretationreasoningThere may be biological constraints on the lower boundary of skin pigmentation, and/or due to strong positive selection acting on a few large-effect alleles, there is little genetic variability left at these pigmentation loci.
“There may be biological constraints on the lower boundary of skin pigmentation, and/or due to the strong positive selection acting on a few large-effect alleles, there is little genetic variability left at these pigmentation loci.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe Nama and ‡Khomani San appear to be two instances of intermediate variation within Africa, likely attributable to their geographic distance from the equator in far southern Africa (~24-29 degrees South).
“The Nama and ‡Khomani San appear to be two such instances of this intermediate variation within Africa, likely attributable to their geographic distance from the equator in far southern Africa (~24–29 degrees South).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenIRB approval was obtained from Stanford University, Stony Brook University, and the University of Stellenbosch, South Africa.
“Institutional review board (IRB) approval was obtained from Stanford University, Stony Brook University, and the University of Stellenbosch, South Africa.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductown dataImputation accuracy was assessed by concordance with low-pass genome sequences and high-coverage exome sequencing, and by PCA; the primary source of aggregated imputed variation was concluded to be population/familial structure rather than technical artifacts.
“We assessed the accuracy of the imputation in three ways. First, we assessed the homozygous reference, heterozygous, and homozygous non-reference concordance between the imputed output and two low-pass genome sequences from individuals SA1000 and SA1025 at sites that passed variant call filters and with > 5 reads.”
- Also stated in: § METHOD DETAILS · plain
“By investigating the top PCs, we concluded the latter.”
Quote in the paperSubstantial claim- Also stated in: § METHOD DETAILS · plain
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
InterpretationreasoningThe observed mean and variance differences across the full spectrum of skin pigmentation by latitude may be driven by imbalanced opposing adaptive pressures, where selective forces to produce vitamin D and protect folate from photolysis are unequal and change in response to UV radiation exposure.
“The observed mean and variance differences across the full spectrum of skin pigmentation by latitude may be driven by imbalanced opposing adaptive pressures, where selective forces to produce vitamin D and protect folate from photolysis are unequal and change in response to UV radiation exposure.”
Quote in the paperNot a substantial claim- Rests on an assumption: Selective forces to produce vitamin D and protect folate from photolysis are unequal and change in response to UV radiation exposure.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataAge and sex covariates were included for tanning, and they were significantly associated with the phenotype.
“We also included age and sex covariates for tanning, which were significantly associated with the phenotype.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningIn equatorial regions, strong directional selection for darker pigmentation has shifted the distribution means in some populations to M indices greater than 90, but with wide variances.
“In equatorial regions, strong directional selection for darker pigmentation has shifted the distribution means in some populations to M indices greater than 90, but with wide variances.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationPigmentation has been described previously as a relatively simple trait with few loci of large effect contributing to the phenotype.
“Pigmentation has been described previously as a relatively simple trait with few loci of large effect contributing to the phenotype (Sulem et al., 2007; Walsh et al., 2013).”
Quote in the paperSubstantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationSLC24A5 is among the most differentiated regions of the genome between European and African populations, indicative of strong positive selection in northern Europeans.
“and is among the most differentiated regions of the genome between European and African populations–indicative of strong positive selection in northern Europeans (Sturm and Duffy, 2012).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Sturm and Duffy, 2012
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe total genomic length of inferred cumulative IBD between pairs of individuals was verified by comparing to pedigree relationships identified from ethnographic interviews and verified with IBD inferred from genotyping arrays.
“We verified the total genomic length of the inferred cumulative IBD between pairs of individuals by comparing to pedigree relationships identified from ethnographic interviews and verified with IBD inferred here from the genotyping arrays.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningSkin pigmentation is a far more complex trait than previously discussed, analogous to numerous other complex traits discussed in biomedical literature.
“This suggests that skin pigmentation is a far more complex trait than previously discussed, analogous to numerous other complex traits discussed in biomedical literature.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenAll individuals gave signed written and verbal consent with a witness present before participating.
“All individuals gave signed written and verbal consent with a witness present before participating.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductown dataThe REAP kinship matrix correlated best with true relationships and was used to correct for kinship in all regression models unless otherwise noted.
“We used the REAP matrix to correct for kinship in all regression models unless otherwise noted because it correlated best with true relationships (e.g. heritability analyses with different kinship matrices).”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningMore than 50 loci, and likely far more, with a distribution of mostly small effects contribute to variation in pigmentation in the KhoeSan.
“suggesting that more than 50 loci (and indeed, likely far more, given our genomic heritability estimates) with a distribution of mostly small effects contribute to variation in pigmentation in the KhoeSan.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationreasoningThis would simplify the genomic architecture, with relatively few alleles of large effect driving the phenotype, particularly alleles that lighten skin at extreme northern latitudes, and could explain why prior investigations observed an almost Mendelian inheritance of large effect light pigmentation alleles.
“This would simplify the genomic architecture, with relatively few alleles of large effect driving the phenotype, particularly alleles that lighten skin at extreme northern latitudes, and could explain why prior investigations observed an almost Mendelian inheritance of large effect light pigmentation alleles.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataEven in light to moderately pigmented KhoeSan populations, the polygenicity of skin pigmentation is much greater than Eurasians, encompassing both known pigmentation genes as well as novel loci.
“Even in light to moderately pigmented KhoeSan populations, the polygenicity of skin pigmentation is much greater than Eurasians, encompassing both known pigmentation genes as well as novel loci.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataThe equatorial pattern is consistent with a threshold model in which the protective benefit of melanin needs to meet some minimum threshold but with no penalty to darker pigmentation; alternatively, diversifying selection could maintain the wide variance.
“This is consistent with a ‘threshold’ model (Chaplin, 2004) in which the protective benefit of melanin needs to meet some minimum threshold but with no penalty to darker pigmentation; alternatively, diversifying selection could maintain the wide variance.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Chaplin, 2004 source
Not checked in the free run.
May combine two claims.
Study design and conductown dataSex and age do not significantly correlate with baseline skin pigmentation, suggesting that the quantitative measure of underarm reflectance is not significantly affected by UV exposure.
“Sex and age do not significantly correlate with baseline skin pigmentation, suggesting that our quantitative measure of underarm reflectance is not significantly affected by UV exposure.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationThis recruitment is required for normal expression of many MITF target genes, including TYR, TYRP1, DCT, RAB27A, BCL2, among others.
“This recruitment is required for normal expression of many MITF target genes, including TYR, TYRP1, DCT, RAB27A, BCL2, among others (Keenen et al., 2009b).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Keenen et al., 2009b
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSMARCA2 has a known role in folate biosynthesis.
“SMARCA2 has a known role in folate biosynthesis, in vitamin D-coupled transcription regulation, and is differentially expressed across CEU and YRI populations in lymphoblastoid cell lines (Duan et al., 2009).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Duan et al., 2009 source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationTYRP1 mutations cause nearly Mendelian inheritance of blond hair in Solomon Islanders.
“TYRP1 mutations in humans have been associated with oculocutaneous albinism and shown to cause nearly Mendelian inheritance of blond hair in Solomon Islanders (Kenny et al., 2012b; Sarangarajan and Boissy, 2001).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Kenny et al., 2012b
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataThe resequencing efforts yielded large amounts of high-quality data for each pool with on average 84% of reads in target regions, achieving a median depth of coverage of 29× per sample.
“The resequencing efforts yielded large amounts of high-quality data for each pool with on average 84% of reads in target regions, achieving a median depth of coverage of 29× per sample.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe resequencing design was successful for all targets.
“The resequencing design was successful for all targets, although the regions targeting SNPs previously associated with pigmentation in MC1R and TPCN2 had significantly lower coverage than the other regions.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataVariant calls and genotypes for samples that were genotyped on an array achieved an average of >99% concordance.
“We compared variant calls and genotypes for samples that were genotyped on an array and achieved an average of > 99% concordance (Figure S7).”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationMITF recruits critical components of the SWI/SNF chromatin remodeling complex (including SMARCA2) to the promoter region of its targets.
“MITF, the transcription factor known as the “master regulator of melanogenesis” due to its ability to activate many melanocyte-specific genes (Praetorius et al., 2013), recruits critical components of the SWI/SNF chromatin remodeling complex (including SMARCA2), to the promoter region of its targets (Vachtenheim et al., 2010).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Vachtenheim et al., 2010 source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSMARCA2 has a known role in vitamin D-coupled transcription regulation.
“SMARCA2 has a known role in folate biosynthesis, in vitamin D-coupled transcription regulation, and is differentially expressed across CEU and YRI populations in lymphoblastoid cell lines (Duan et al., 2009).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Duan et al., 2009 source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMITF is the transcription factor known as the 'master regulator of melanogenesis' due to its ability to activate many melanocyte-specific genes.
“MITF, the transcription factor known as the “master regulator of melanogenesis” due to its ability to activate many melanocyte-specific genes (Praetorius et al., 2013), recruits critical components of the SWI/SNF chromatin remodeling complex (including SMARCA2), to the promoter region of its targets (Vachtenheim et al., 2010).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Praetorius et al., 2013 source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationTYRP1 mutations in humans have been associated with oculocutaneous albinism.
“TYRP1 mutations in humans have been associated with oculocutaneous albinism and shown to cause nearly Mendelian inheritance of blond hair in Solomon Islanders (Kenny et al., 2012b; Sarangarajan and Boissy, 2001).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Sarangarajan and Boissy, 2001
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe regions targeting SNPs previously associated with pigmentation in MC1R and TPCN2 had significantly lower coverage than the other regions.
“The resequencing design was successful for all targets, although the regions targeting SNPs previously associated with pigmentation in MC1R and TPCN2 had significantly lower coverage than the other regions.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSMARCA2 is differentially expressed across CEU and YRI populations in lymphoblastoid cell lines.
“SMARCA2 has a known role in folate biosynthesis, in vitamin D-coupled transcription regulation, and is differentially expressed across CEU and YRI populations in lymphoblastoid cell lines (Duan et al., 2009).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Duan et al., 2009 source
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
Study design and conductown dataA total of 46,429 SNPs and indels with a MAF > 1% passed quality control filters, resulting in a Bonferroni threshold of 1.08e-6.
“We discovered a total of 46,429 SNPs and indels with a MAF > 1% that passed our quality control filters, resulting in a Bonferoni threshold of 1.08e-6.”
Quote in the paperSubstantial claim
The paper relies on this without support.
Quantitative skin pigmentation phenotypes aggregated from different studies and populations are comparable enough to analyze together.
“For comparison, we aggregated quantitative skin pigmentation across 32 globally diverse populations (4,712 individuals) assayed with a Derma Spectrometer (DSMI or DSMII) (Basu Mallick et al., 2013; Beleza et al., 2013; Candille et al., 2012; Coussens et al., 2015; Durazo-Arvizu et al., 2014; Edwards et al., 2010; Norton et al., 2006) (Figure 1A–B, Table S1).”
The paper relies on this without support.
The M index measured on the upper inner arm reflects baseline skin pigmentation.
“We quantitatively phenotyped baseline skin color in 479 individuals (277 ‡Khomani, 202 Nama, Table S4) via narrow-band reflectometry to measure hemoglobin and melanin of both the left and right upper inner arms (STAR Methods), with M index = log10(1 / % red reflectance).”
The paper relies on this without support.
Populations living in continental Africa have been largely ignored in genetic studies with quantitative phenotypes.
“However, populations living in continental Africa, where humans have the greatest genetic diversity and pigmentation variability, have been largely ignored in genetic studies with quantitative phenotypes.”
The paper relies on this without support.
EPM2A and FREM1 have no known role in skin pigmentation in humans or model organisms.
“Two of these loci are near EPM2A and FREM1, neither of which have any known role in skin pigmentation in humans or model organisms.”
The paper relies on this without support.
SNX13 has not previously been associated with skin pigmentation.
“SNX13 regulates lysosomal degradation and G-protein signaling, but has not previously been associated with skin pigmentation.”
The paper relies on this without support.
African populations often carry the ancestral (i.e. dark) allele for skin pigmentation genes identified in Eurasians.
“Because African populations often carry the ancestral (i.e. dark) allele for skin pigmentation genes identified in Eurasians, allusions to African skin pigmentation have ignored the great variability in this phenotype across Africa.”
The paper relies on this without support.
Selective forces to produce vitamin D and protect folate from photolysis are unequal and change in response to UV radiation exposure.
“where selective forces to produce vitamin D and protect folate from photolysis are unequal and change in response to UV radiation exposure.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Some machine learning approaches may modestly improve PRS accuracy beyond current approaches for some phenotypes, but most likely for atypical traits with simpler architectures, known interactions, and poor prediction generalizability across populations, such as skin pigmentation.
“Some machine learning approaches may thus modestly improve PRS accuracy beyond current approaches for some phenotypes52, but most likely for atypical traits with simpler architectures, known interactions, and poor prediction generalizability across populations, such as skin pigmentation53.”
From Clinical use of current polygenic risk scores may exacerbate health disparities (2019) · cites this paper as [53]
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredA light skinned phenotype may have been common in the Levant_ChL population.
“suggesting that a light skinned phenotype may have been common in this population”
From Ancient DNA from Chalcolithic Israel reveals the role of population mixture in cultural transformation (2018) · cites this paper as [42]
The Introduction discusses light-skin alleles in western Eurasian populations and light pigmentation among the KhoeSan, but it does not address the Levant_ChL population. Searches for Levant_ChL and Chalcolithic Levantine pigmentation found no passage assessing whether light skin was common in that population. (LLM, conf=0.76)
Experimental — accuracy not yet measuredRecent genomic studies have identified several novel and non-canonical pigmentation genes, such as KLF6, COMMD3, SNX13, SMARCA2, ADAM17, and ADAMTS20, that extend beyond the classical melanogenic pathways.
“Recent genomic studies ( Bajpai et al., 2023 ; Martin et al., 2017 ) have identified several novel and non-canonical pigmentation genes, such as KLF6 , COMMD3 , SNX13 , SMARCA2 , ADAM17 , ADAMTS20 , that extend beyond the classical melanogenic pathways.”
From The genetic architecture of human skin pigmentation: evolution and adaptation across global populations (2026) · cites this paper as Martin et al., 2017
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Targeted-resequencing sample counts disagree
MajorThe Results report 451 resequenced samples, including 182 Nama, whereas the Methods report 441, including 172 Nama. Both give 269 ‡Khomani.
“successfully resequenced 36 candidate pigmentation regions (Table S7, Figure S6) across a larger set of 451 KhoeSan samples”
“For 441 KhoeSan samples (N=269 ‡Khomani and N=172 Nama), we performed targeted resequencing.”
Direction of the rs1426654 amino-acid change reverses
MinorThe same derived SLC24A5 allele is described as Ala111Thr in the Introduction but as Thr111Ala in the Results. Those names specify opposite amino-acid changes.
“the derived Ala111Thr allele (rs1426654) of SLC24A5”
“derived SLC24A5 SNPs, including the putatively causal p.Thr111Ala rs1426654 allele”
Genotyped ‡Khomani count exceeds the phenotyped count
MinorThe paper describes 278 genotyped ‡Khomani individuals as having matched pigmentation phenotypes, but later reports phenotyping only 277 ‡Khomani individuals.
“a total of 465 genotyped KhoeSan individuals (278 ‡Khomani San and 187 Nama), with targeted resequencing at associated pigmentation loci and matched quantitative spectrophotometric phenotype data”
“We quantitatively phenotyped baseline skin color in 479 individuals (277 ‡Khomani, 202 Nama, Table S4)”
Targeted-resequencing region counts disagree
MinorThe Results state that 36 candidate regions were resequenced, but the Methods say 35 regions were chosen for the resequencing capture.
“successfully resequenced 36 candidate pigmentation regions (Table S7, Figure S6)”
“We chose 35 regions totaling 7.1 Mb and used the NimbleGen SeqCap EZ Choice Enrichment Kit to enrich for these loci.”
Cites
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895 · see citing works
Self-citationSecond-generation PLINK: rising to the challenge of larger and richer datasets
Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015) · Gigascience · doi:10.1186/s13742-015-0047-8 · Cited by 12,709 · see citing works
Fast model-based estimation of ancestry in unrelated individuals
Alexander, D. H., Novembre, J., & Lange, K. (2009) · Genome Research · doi:10.1101/gr.094052.109 · Cited by 9,898 · see citing works
GCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279 · see citing works
The Ensembl Variant Effect Predictor
McLaren, W., Gil, L., Hunt, S. E., Riat, H. S., Ritchie, G. R. S., Thormann, A., Flicek, P., & Cunningham, F. (2016) · Genome Biology · doi:10.1186/s13059-016-0974-4 · Cited by 8,099 · see citing works
Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool
Chen, E. Y., Tan, C. M., Kou, Y., Duan, Q., Wang, Z., Meirelles, G. V., Clark, N. R., & Ma’ayan, A. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-128 · Cited by 7,814 · see citing works
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577 · see citing works
METAL: fast and efficient meta-analysis of genomewide association scans
Willer, C. J., Li, Y., & Abecasis, G. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq340 · Cited by 5,205 · see citing works
Common SNPs explain a large proportion of the heritability for human height
Yang, J., Benyamin, B., McEvoy, B. P., Gordon, S., Henders, A. K., Nyholt, D. R., Madden, P. A., Heath, A. C., Martin, N. G., Montgomery, G. W., et al. (2010) · Nature Genetics · doi:10.1038/ng.608 · Cited by 4,446 · see citing works
Howie, B. N., Donnelly, P., & Marchini, J. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000529 · Cited by 3,928 · see citing works
Robust relationship inference in genome-wide association studies
Manichaikul, A., Mychaleckyj, J. C., Rich, S. S., Daly, K., Sale, M., & Chen, W.-M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq559 · Cited by 3,541 · see citing works
Browning, S. R., & Browning, B. L. (2007) · The American Journal of Human Genetics · doi:10.1086/521987 · Cited by 3,138 · see citing works
Integrating common and rare genetic variation in diverse human populations
The International HapMap 3 Consortium (2010) · Nature · doi:10.1038/nature09298 · Cited by 3,026 · see citing works
Multipoint Quantitative-Trait Linkage Analysis in General Pedigrees
Almasy, L. A., & Blangero, J. (1998) · The American Journal of Human Genetics · doi:10.1086/301844 · Cited by 3,007 · see citing works
A Map of Recent Positive Selection in the Human Genome
Voight, B. F., Kudaravalli, S., Wen, X., & Pritchard, J. K. (2006) · PLoS Biology · doi:10.1371/journal.pbio.0040072 · Cited by 2,912 · see citing works
Variance component model to account for sample structure in genome-wide association studies
Kang, H. M., Sul, J. H., Service, S. K., Zaitlen, N. A., Kong, S.-Y., Freimer, N. B., Sabatti, C., & Eskin, E. (2010) · Nature Genetics · doi:10.1038/ng.548 · Cited by 2,817 · see citing works
Liu, J. Z., van Sommeren, S., Huang, H., Ng, S. C., Alberts, R., Takahashi, A., Ripke, S., Lee, J. C., Jostins, L., Shah, T., et al. (2015) · Nature Genetics · doi:10.1038/ng.3359 · Cited by 2,603 · see citing works
Self-citationWard, L. D., & Kellis, M. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr917 · Cited by 2,229 · see citing works
Genome-wide detection and characterization of positive selection in human populations
The International HapMap Consortium, Sabeti, P. C., Varilly, P., Fry, B., Lohmueller, J., Hostetter, E., Cotsapas, C., Xie, X., Byrne, E. H., McCarroll, S. A., et al. (2007) · Nature · doi:10.1038/nature06250 · Cited by 2,131 · see citing works
Association of Trypanolytic ApoL1 Variants with Kidney Disease in African Americans
Genovese, G., Friedman, D. J., Ross, M. D., Lecordier, L., Uzureau, P., Freedman, B. I., Bowden, D. W., Langefeld, C. D., Oleksyk, T. K., Uscinski Knob, A. L., et al. (2010) · Science · doi:10.1126/science.1193032 · Cited by 2,028 · see citing works
Worldwide Human Relationships Inferred from Genome-Wide Patterns of Variation
Li, J. Z., Absher, D. M., Tang, H., Southwick, A. M., Casto, A. M., Ramachandran, S., Cann, H. M., Barsh, G. S., Feldman, M. W., Cavalli-Sforza, L. L., et al. (2008) · Science · doi:10.1126/science.1153717 · Cited by 1,947 · see citing works
Self-citationThe Electronic Medical Records and Genomics (eMERGE) Consortium, Wood, A. R., The MIGen Consortium, The PAGE Consortium, Study, T. L. C., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., et al. (2014) · Nature Genetics · doi:10.1038/ng.3097 · Cited by 1,853 · see citing works
Sequencing of 50 Human Exomes Reveals Adaptation to High Altitude
Yi, X., Liang, Y., Huerta-Sanchez, E., Jin, X., Cuo, Z. X. P., Pool, J. E., Xu, X., Jiang, H., Vinckenbosch, N., Korneliussen, T. S., et al. (2010) · Science · doi:10.1126/science.1190371 · Cited by 1,611 · see citing works
Self-citationThe Genetic Structure and History of Africans and African Americans
Tishkoff, S. A., Reed, F. A., Friedlaender, F. R., Ehret, C., Ranciaro, A., Froment, A., Hirbo, J. B., Awomoyi, A. A., Bodo, J.-M., Doumbo, O., et al. (2009) · Science · doi:10.1126/science.1172257 · Cited by 1,573 · see citing works
Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations
Martin, A. R., Gignoux, C. R., Walters, R. K., Wojcik, G. L., Neale, B. M., Gravel, S., Daly, M. J., Bustamante, C. D., & Kenny, E. E. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.03.004 · Cited by 1,391 · see citing works
Self-citationRamachandran, S., Deshpande, O., Roseman, C. C., Rosenberg, N. A., Feldman, M. W., & Cavalli-Sforza, L. L. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0507611102 · Cited by 1,103 · see citing works
Self-citationSLC24A5, a putative cation exchanger, affects pigmentation in zebrafish and humans
Lamason, R. L., Mohideen, M.-A. P. K., Mest, J. R., Wong, A. C., Norton, H. L., Aros, M. C., Jurynec, M. J., Mao, X., Humphreville, V. R., Humbert, J. E., et al. (2005) · Science · doi:10.1126/science.1116238 · Cited by 1,043 · see citing works
RFMix: A Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference
Maples, B. K., Gravel, S., Kenny, E. E., & Bustamante, C. D. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.06.020 · Cited by 900 · see citing works
Self-citationGreat ape genetic diversity and population history
Prado-Martinez, J., Sudmant, P. H., Kidd, J. M., Li, H., Kelley, J. L., Lorente-Galdós, B., Veeramah, K. R., Woerner, A. E., O’Connor, T. D., Santpere, G., et al. (2013) · Nature · doi:10.1038/nature12228 · Cited by 873 · see citing works
Self-citationGenetic determinants of hair, eye and skin pigmentation in Europeans
Sulem, P., Gudbjartsson, D. F., Stacey, S. N., Helgason, A., Rafnar, T., Magnusson, K. P., Manolescu, A., Karason, A., Palsson, A., Thorleifsson, G., et al. (2007) · Nature Genetics · doi:10.1038/ng.2007.13 · Cited by 750 · see citing works
Human skin pigmentation as an adaptation to UV radiation
Jablonski, N. G., & Chaplin, G. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0914628107 · Cited by 728 · see citing works
A General Approach for Haplotype Phasing across the Full Spectrum of Relatedness
O'Connell, J., Gurdasani, D., Delaneau, O., Pirastu, N., Ulivi, S., Cocca, M., Traglia, M., Huang, J., Huffman, J. E., Rudan, I., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004234 · Cited by 593 · see citing works
Self-citationBayesian inference of ancient human demography from individual genome sequences
Gronau, I., Hubisz, M. J., Gulko, B., Danko, C. G., & Siepel, A. C. (2011) · Nature Genetics · doi:10.1038/ng.937 · Cited by 580 · see citing works
Partitioning Heritability of Regulatory and Cell-Type-Specific Variants across 11 Common Diseases
Gusev, A., Lee, S. H., Trynka, G., Finucane, H., Vilhjálmsson, B. J., Xu, H., Zang, C., Ripke, S., Bulik-Sullivan, B., Stahl, E., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.10.004 · Cited by 544 · see citing works
Self-citationHunter-gatherer genomic diversity suggests a southern African origin for modern humans
Henn, B. M., Gignoux, C. R., Jobin, M., Granka, J. M., Macpherson, J. M., Kidd, J. M., Rodríguez-Botigué, L., Ramachandran, S., Hon, L., Brisbin, A., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1017511108 · Cited by 502 · see citing works
Self-citationComplete Khoisan and Bantu genomes from southern Africa
Schuster, S. C., Miller, W., Ratan, A., Tomsho, L. P., Giardine, B. M., Kasson, L. R., Harris, R. S., Petersen, D. C., Zhao, F., Qi, J., et al. (2010) · Nature · doi:10.1038/nature08795 · Cited by 500 · see citing works
A population genetic signal of polygenic adaptation
Berg, J. J., & Coop, G. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004412 · Cited by 487 · see citing works
Web-Based, Participant-Driven Studies Yield Novel Genetic Associations for Common Traits
Eriksson, N., Macpherson, J. M., Tung, J. Y., Hon, L., Naughton, B., Saxonov, S., Avey, L., Wojcicki, A., Pe’er, I., & Mountain, J. L. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000993 · Cited by 480 · see citing works
Genomic Variation in Seven Khoe-San Groups Reveals Adaptation and Complex African History
Schlebusch, C. M., Skoglund, P., Sjödin, P., Gattepaille, L. M., Hernandez, D. G., Jay, F., Li, S., de Jongh, M., Singleton, A., Blum, M. G. B., et al. (2012) · Science · doi:10.1126/science.1227721 · Cited by 457 · see citing works
Whole population, genome-wide mapping of hidden relatedness
Gusev, A., Lowe, J. K., Stoffel, M., Daly, M. J., Altshuler, D., Breslow, J. L., Friedman, J. M., & Pe'er, I. (2009) · Genome Research · doi:10.1101/gr.081398.108 · Cited by 450 · see citing works
Self-citationThe HIrisPlex system for simultaneous prediction of hair and eye colour from DNA
Walsh, S., Liu, F., Wollstein, A., Kovatsi, L., Ralf, A., Kosiniak-Kamysz, A., Branicki, W., & Kayser, M. (2013) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2012.07.005 · Cited by 428 · see citing works
Variant of TYR and Autoimmunity Susceptibility Loci in Generalized Vitiligo
Jin, Y., Birlea, S. A., Fain, P. R., Gowan, K., Riccardi, S. L., Holland, P. J., Mailloux, C. M., Sufit, A., Hutton, S. M., Amadi‐Myers, A., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa0908547 · Cited by 415 · see citing works
Genetic evidence for the convergent evolution of light skin in Europeans and East Asians
Norton, H. L., Kittles, R. A., Parra, E., McKeigue, P., Mao, X., Cheng, K., Canfield, V. A., Bradley, D. G., McEvoy, B., & Shriver, M. D. (2006) · Molecular Biology and Evolution · doi:10.1093/molbev/msl203 · Cited by 410 · see citing works
Model-free Estimation of Recent Genetic Relatedness
Conomos, M. P., Reiner, A. P., Weir, B. S., & Thornton, T. A. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.11.022 · Cited by 397 · see citing works
Miller, C. T., Beleza, S., Pollen, A. A., Schluter, D., Kittles, R. A., Shriver, M. D., & Kingsley, D. M. (2007) · Cell · doi:10.1016/j.cell.2007.10.055 · Cited by 388 · see citing works
Self-citationMolecular genetics of human pigmentation diversity
Sturm, R. A. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp003 · Cited by 379 · see citing works
Two newly identified genetic determinants of pigmentation in Europeans
Sulem, P., Gudbjartsson, D. F., Stacey, S. N., Helgason, A., Rafnar, T., Jakobsdottir, M., Steinberg, S., Gudjonsson, S. A., Palsson, A., Thorleifsson, G., et al. (2008) · Nature Genetics · doi:10.1038/ng.160 · Cited by 368 · see citing works
Paşaniuc, B., & Zaitlen, N. (2013) · eScholarship (California Digital Library) · Cited by 362 · see citing works
Loci associated with skin pigmentation identified in African populations
Crawford, N. G., Kelly, D., Hansen, M. E. B., Beltrame, M., Fan, S.-H., Bowman, S. L., Jewett, E., Ranciaro, A., Thompson, S., Lo, Y., et al. (2017) · Science · doi:10.1126/science.aan8433 · Cited by 345 · see citing works
The genetic prehistory of southern Africa
Pickrell, J. K., Patterson, N. J., Barbieri, C., Berthold, F., Gerlach, L., Güldemann, T., Kure, B., Mpoloka, S. W., Nakagawa, H., Naumann, C., et al. (2012) · Nature Communications · doi:10.1038/ncomms2140 · Cited by 342 · see citing works
Self-citationAncient west Eurasian ancestry in southern and eastern Africa
Pickrell, J. K., Patterson, N., Loh, P.-R., Lipson, M., Berger, B., Stoneking, M., Pakendorf, B., & Reich, D. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1313787111 · Cited by 300 · see citing works
A portable instrument for quantifying erythema induced by ultraviolet radiation
Diffey, B. L., Oliver, R., & Farr, P. M. (1984) · British Journal of Dermatology · doi:10.1111/j.1365-2133.1984.tb14149.x · Cited by 300 · see citing works
Tishkoff, S. A., Gonder, M. K., Henn, B. M., Mortensen, H. M., Knight, A., Gignoux, C. R., Fernandopulle, N. D., Lema, G., Nyambo, T., Ramakrishnan, U., et al. (2007) · Molecular Biology and Evolution · doi:10.1093/molbev/msm155 · Cited by 276 · see citing works
Self-citationEstimation of height from the length of long bones in a Portuguese adult population
de Mendonça, M. C. (2000) · American Journal of Physical Anthropology · doi:10.1002/(sici)1096-8644(200005)112:1 · Cited by 260 · see citing works
Kayser, M., Liu, F., Janssens, A. C. J. W., Rivadeneira, F., Lao, O., van Duijn, K., Vermeulen, M., Arp, P., Jhamai, M. M., van IJcken, W. F. J., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2007.10.003 · Cited by 260 · see citing works
Carlson, C. S., Matise, T. C., North, K. E., Haiman, C. A., Fesinmeyer, M. D., Buyske, S. G., Schumacher, F. R., Peters, U., Franceschini, N., Ritchie, M. D., et al. (2013) · PLoS Biology · doi:10.1371/journal.pbio.1001661 · Cited by 258 · see citing works
Wilde, S., Timpson, A., Kirsanow, K., Kaiser, E., Kayser, M., Unterländer, M., Hollfelder, N., Potekhina, I. D., Schier, W., Thomas, M. G., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1316513111 · Cited by 257 · see citing works
Distance from sub-Saharan Africa predicts mutational load in diverse human genomes
Henn, B. M., Botigué, L. R., Peischl, S., Dupanloup, I., Lipatov, M., Maples, B. K., Martin, A. R., Musharoff, S. A., Cann, H. M., Snyder, M. P., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510805112 · Cited by 257 · see citing works
Self-citationDuffy, D. L., Montgomery, G. W., Chen, W., Zhao, Z. Z., Le, L., James, M. R., Hayward, N. K., Martin, N. G., & Sturm, R. A. (2007) · The American Journal of Human Genetics · doi:10.1086/510885 · Cited by 240 · see citing works
Lao, O., de Gruijter, J. M., van Duijn, K., Navarro, A., & Kayser, M. (2007) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2006.00341.x · Cited by 231 · see citing works
A polymorphism in IRF4 affects human pigmentation through a tyrosinase-dependent MITF/TFAP2A pathway
Praetorius, C., Grill, C., Stacey, S. N., Metcalf, A. M., Gorkin, D. U., Robinson, K. C., Van Otterloo, E., Kim, R. S. Q., Bergsteinsdottir, K., Ogmundsdottir, M. H., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.022 · Cited by 228 · see citing works
The Genetic Architecture of Adaptations to High Altitude in Ethiopia
Alkorta‐Aranburu, G., Beall, C. M., Witonsky, D., Gebremedhin, A., Pritchard, J. K., & Rienzo, A. D. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1003110 · Cited by 212 · see citing works
Estimating Kinship in Admixed Populations
Thornton, T. A., Tang, H., Hoffmann, T. J., Ochs‐Balcom, H. M., Caan, B. J., & RISCH, N. J. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.05.024 · Cited by 206 · see citing works
Human pigmentation genes under environmental selection
Sturm, R. A., & Duffy, D. L. (2012) · Genome biology · doi:10.1186/gb-2012-13-9-248 · Cited by 203 · see citing works
BARTON, N. H. (1999) · Genetical Research · doi:10.1017/s001667239900422x · Cited by 181 · see citing works
Reconstructing Native American Migrations from Whole-Genome and Whole-Exome Data
Gravel, S., Zakharia, F., Moreno‐Estrada, A., Byrnes, J., Muzzio, M., Rodríguez-Flores, J. L., Kenny, E. E., Gignoux, C. R., Maples, B. K., Guiblet, W. M., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1004023 · Cited by 179 · see citing works
Self-citationLiu, F., Visser, M., Duffy, D. L., Hysi, P. G., Jacobs, L. C., Lao, O., Zhong, K., Walsh, S., Chaitanya, L., Wollstein, A., et al. (2015) · Human Genetics · doi:10.1007/s00439-015-1559-0 · Cited by 172 · see citing works
Genetic Architecture of Skin and Eye Color in an African-European Admixed Population
Beleza, S., Johnson, N. A., Candille, S. I., Absher, D. M., Coram, M. A., Lopes, J., Campos, J., Araújo, I. I., Anderson, T. M., Vilhjálmsson, B. J., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003372 · Cited by 161 · see citing works
The timing of pigmentation lightening in Europeans
Beleza, S., Santos, A. M., McEvoy, B., Alves, I., Martinho, C., Cameron, E., Shriver, M. D., Parra, E. J., & Rocha, J. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mss207 · Cited by 156 · see citing works
Geographic distribution of environmental factors influencing human skin coloration
Chaplin, G. (2004) · American Journal of Physical Anthropology · doi:10.1002/ajpa.10263 · Cited by 154 · see citing works
McEvoy, B., Beleza, S., & Shriver, M. D. (2006) · Human Molecular Genetics · doi:10.1093/hmg/ddl217 · Cited by 148 · see citing works
Fine-Scale Human Population Structure in Southern Africa Reflects Ecogeographic Boundaries
Uren, C., Kim, M., Martin, A. R., Bobo, D., Gignoux, C. R., van Helden, P. D., Möller, M., Hoal, E. G., & Henn, B. M. (2016) · Genetics · doi:10.1534/genetics.116.187369 · Cited by 145 · see citing works
Self-citationGenome-Wide Association Study of Tanning Phenotype in a Population of European Ancestry
Nan, H., Kraft, P., Qureshi, A. A., Guo, Q., Chen, C., Hankinson, S. E., Hu, F. B., Thomas, G. D., Hoover, R. N., Chanock, S. J., et al. (2009) · Journal of Investigative Dermatology · doi:10.1038/jid.2009.62 · Cited by 139 · see citing works
Veeramah, K. R., Wegmann, D., Woerner, A. E., Mendez, F. L., Watkins, J. C., Destro‐Bisol, G., Soodyall, H., Louie, L. G., & Hammer, M. F. (2011) · Molecular Biology and Evolution · doi:10.1093/molbev/msr212 · Cited by 139 · see citing works
Zhou, D., Udpa, N., Ronen, R., Stobdan, T., Liang, J., Appenzeller, O., Zhao, H. W., Yin, Y., Du, Y., Guo, L., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.07.011 · Cited by 134 · see citing works
Population differences of two coding SNPs in pigmentation-related genes SLC24A5 and SLC45A2
Soejima, M., & Koda, Y. (2006) · International Journal of Legal Medicine · doi:10.1007/s00414-006-0112-z · Cited by 128 · see citing works
Edwards, M., Bigham, A., Tan, J., Li, S., Gozdzik, A., Ross, K., Jin, L., & Parra, E. J. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000867 · Cited by 128 · see citing works
Tyrp1 and Oculocutaneous Albinism Type 3
Sarangarajan, R., & Boissy, R. E. (2001) · Pigment Cell Research · doi:10.1034/j.1600-0749.2001.140603.x · Cited by 127 · see citing works
Melanesian Blond Hair Is Caused by an Amino Acid Change in TYRP1
Kenny, E. E., Timpson, N. J., Sikora, M., Yee, M., Moreno‐Estrada, A., Eng, C. S., Huntsman, S., Burchard, E. G., Stoneking, M., Bustamante, C. D., et al. (2012) · Science · doi:10.1126/science.1217849 · Cited by 126 · see citing works
Self-citationPrediction of eye and skin color in diverse populations using seven SNPs
Spichenok, O., Budimlija, Z. M., Mitchell, A. A., Jenny, A., Kovacevic, L., Marjanovic, D., Caragine, T., Prinz, M., & Wurmbach, E. (2011) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2010.10.005 · Cited by 121 · see citing works
The Light Skin Allele of SLC24A5 in South Asians and Europeans Shares Identity by Descent
Mallick, C. B., Iliescu, F. M., Möls, M., Hill, S. C., Tamang, R., Chaubey, G., Goto, R., Ho, S. Y. W., Romero, I. G., Crivellaro, F., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003912 · Cited by 120 · see citing works
A scan for signatures of positive selection in candidate loci for skin pigmentation in humans
Izagirre, N., García, I., Junquera, C., de la Rúa, C., & Alonso, S. (2006) · Molecular Biology and Evolution · doi:10.1093/molbev/msl030 · Cited by 119 · see citing works
Investigating the case of human nose shape and climate adaptation
Zaidi, A. A., Mattern, B. C., Claes, P., McEcoy, B., Hughes, C., & Shriver, M. D. (2017) · PLOS Genetics · doi:10.1371/journal.pgen.1006616 · Cited by 117 · see citing works
Updates of reactive oxygen species in melanoma etiology and progression
Liu, F., Dellinger, R. W., & Meyskens, F. L. (2014) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2014.04.007 · Cited by 116 · see citing works
Candille, S. I., Absher, D. M., Beleza, S., Bauchet, M., McEvoy, B., Garrison, N. A., Li, J. Z., Myers, R. M., Barsh, G. S., Tang, H., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048294 · Cited by 111 · see citing works
de la Serna, I. L., Ohkawa, Y., Higashi, C., Dutta, C., Osias, J., Kommajosyula, N., Tachibana, T., & Imbalzano, A. N. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.m512052200 · Cited by 101 · see citing works
Studies on the inheritance of human skin colour
HARRISON, G. A., & OWEN, J. J. T. (1964) · Annals of Human Genetics · doi:10.1111/j.1469-1809.1964.tb00457.x · Cited by 100 · see citing works
Teruel, B. M., Parra, E. J., Fuentes-Smith, E., Salas, A., Buttenschøn, H. N., Demontis, D., Torres, M. L., Padrón, L. C. M., Gómez-Cabezas, E. J., Álvarez‐Iglesias, V., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004488 · Cited by 93 · see citing works
Keenen, B., Qi, H., Saladi, S. V., Yeung, M. L., & de la Serna, I. L. (2009) · Oncogene · doi:10.1038/onc.2009.304 · Cited by 91 · see citing works
Improved eye- and skin-color prediction based on 8 SNPs
Hart, K. L., Kimura, S. L., Mushailov, V., Budimlija, Z. M., Prinz, M., & Wurmbach, E. (2013) · Croatian Medical Journal · doi:10.3325/cmj.2013.54.248 · Cited by 90 · see citing works
Vitamin D and the evolution of human depigmentation
Chaplin, G., & Jablonski, N. G. (2009) · American Journal of Physical Anthropology · doi:10.1002/ajpa.21079 · Cited by 87 · see citing works
Evidence for recent positive selection at the human AIM1 locus in a European population
Soejima, M., Tachida, H., Ishida, T., Sano, A., & Koda, Y. (2006) · Molecular Biology and Evolution · doi:10.1093/molbev/msj018 · Cited by 84 · see citing works
RAB8B Is Required for Activity and Caveolar Endocytosis of LRP6
Demir, K., Kirsch, N., Beretta, C. A., Erdmann, G., Ingelfinger, D., Moro, E., Argenton, F., Carl, M., Niehrs, C., & Boutros, M. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.08.008 · Cited by 78 · see citing works
Pośpiech, E., Wojas‐Pelc, A., Walsh, S., Liu, F., Maeda, H., Ishikawa, T., Skowron, M., Kayser, M., & Branicki, W. (2014) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2014.01.012 · Cited by 70 · see citing works
Durazo-Arvizú, R., Camacho, P. M., Bovet, P., Forrester, T., Lambert, E. V., Plange‐Rhule, J., Hoofnagle, A. N., Aloia, J. F., Tayo, B. O., Dugas, L. R., et al. (2014) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.113.066605 · Cited by 69 · see citing works
RelateAdmix: a software tool for estimating relatedness between admixed individuals
Moltke, I., & Albrechtsen, A. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt652 · Cited by 66 · see citing works
A reduced representation approach to population genetic analyses and applications to human evolutionPreprint
Luca, F., Hudson, R. R., Witonsky, D., & Rienzo, A. D. (2011) · Genome Research · doi:10.1101/gr.119792.110 · Cited by 65 · see citing works
Coussens, A. K., Naude, C. E., Goliath, R. T., Chaplin, G., Wilkinson, R. J., & Jablonski, N. G. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1500909112 · Cited by 64 · see citing works
Leveraging population admixture to characterize the heritability of complex traits
Zaitlen, N., Pasaniuc, B., Sankararaman, S., Bhatia, G., Zhang, J., Gusev, A., Young, T., Tandon, A., Pollack, S., Vilhjálmsson, B. J., et al. (2014) · Nature Genetics · doi:10.1038/ng.3139 · Cited by 63 · see citing works
Quantitative genetics of human skin color
Byard, P. J. (1981) · American Journal of Physical Anthropology · doi:10.1002/ajpa.1330240506 · Cited by 57 · see citing works
A Genetic Mechanism for Convergent Skin Lightening during Recent Human Evolution
Yang, Z., Zhong, H., Chen, J., Zhang, X., Zhang, H., Luo, X., Xu, S., Chen, H., Lu, D., Han, Y., et al. (2016) · Molecular Biology and Evolution · doi:10.1093/molbev/msw003 · Cited by 57 · see citing works
A twin study of skin reflectance
Clark, P., Stark, A. E., Walsh, R. J., Jardine, R., & Martin, N. G. (1981) · Annals of Human Biology · doi:10.1080/03014468100005371 · Cited by 55 · see citing works
Efficient analysis of large datasets and sex bias with ADMIXTURE
Shringarpure, S., Bustamante, C. D., Lange, K. L., & Alexander, D. H. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1082-x · Cited by 50 · see citing works
Self-citationVachtenheim, J., Ondrušová, L., & Borovanský, J. (2010) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2010.01.048 · Cited by 48 · see citing works
The Evolution of Skin Pigmentation and Hair Texture in People of African Ancestry
Jablonski, N. G., & Chaplin, G. (2013) · Dermatologic Clinics · doi:10.1016/j.det.2013.11.003 · Cited by 46 · see citing works
Skin and hair pigmentation variation in Island Melanesia
Norton, H. L., Friedlaender, J. S., Merriwether, D. A., Koki, G., Mgone, C. S., & Shriver, M. D. (2006) · American Journal of Physical Anthropology · doi:10.1002/ajpa.20343 · Cited by 36 · see citing works
Human skin color diversity is highest in sub-Saharan African populations.
Relethford, J. H. (2000) · PubMed · Cited by 34 · see citing works
Frisancho, A. R., Wainwright, R., & Way, A. (1981) · American Journal of Physical Anthropology · doi:10.1002/ajpa.1330550207 · Cited by 34 · see citing works
Zaitlen, N., Kraft, P., Patterson, N., Pasaniuc, B., Bhatia, G., Pollack, S., & Price, A. L. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003520 · Cited by 32 · see citing works
Expression and alternative splicing of folate pathway genes in HapMap lymphoblastoid cell lines
Duan, S., Huang, R. S., Zhang, W., Mi, S., Bleibel, W. K., Kistner, E. O., Cox, N. J., & Dolan, M. E. (2009) · Pharmacogenomics · doi:10.2217/pgs.09.8 · Cited by 16 · see citing works
Gene mapping study for constitutive skin color in an isolated Mongolian population
Paik, S. H., Kim, H., Son, H., Lee, S., Im, S.-W., Ju, Y. S., Yeon, J. H., Jo, S. J., Eun, H. C., Seo, J., et al. (2012) · Experimental & Molecular Medicine · doi:10.3858/emm.2012.44.3.020 · Cited by 12 · see citing works
Deletion of LRP5 in VLDLR Knockout Mice Inhibits Retinal Neovascularization
Xia, C., Lu, E., Zeng, J., & Gong, X. (2013) · PLoS ONE · doi:10.1371/journal.pone.0075186 · Cited by 11 · see citing works
Skin color variation in Africa
Tang, H., & Barsh, G. S. (2017) · Science · doi:10.1126/science.aaq1322 · Cited by 8 · see citing works
Flagged first, then by citations
3 of the 117 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Keenen, 2010, Heterogeneous SWI/SNF chromatin remodeling complexes promote expression of microphthalmia-associated transcription factor target genes in melanoma, Oncogene, 29, 81, 10.1038/onc.2009.304 · DOI
Cited by
Sorted by citations
Clinical use of current polygenic risk scores may exacerbate health disparities
Martin, A. R., Kanai, M., Kamatani, Y., Okada, Y., Neale, B. M., & Daly, M. J. (2019) · Nature Genetics · doi:10.1038/s41588-019-0379-x · Cited by 2,831 · see citing works
Self-citationChaitanya, L., Breslin, K., Zuñiga, S., Wirken, L., Pośpiech, E., Kukla-Bartoszek, M., Sijen, T., Knijff, P. D., Liu, F., Branicki, W., et al. (2018) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2018.04.004 · Cited by 335 · see citing works
Del Bino, S., Duval, C., & Bernerd, F. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19092668 · Cited by 315 · see citing works
Skin Pigmentation Types, Causes and Treatment—A Review
Thawabteh, A. M., Jibreen, A., Karaman, D., Thawabteh, A., & Karaman, R. (2023) · Molecules · doi:10.3390/molecules28124839 · Cited by 233 · see citing works
Adhikari, K., Mendoza‐Revilla, J., Sohail, A., Fuentes‐Guajardo, M., Lampert, J. E., Chacón-Duque, J. C., Hurtado, M., Villegas, V., Granja, V., Acuña-Alonzo, V., et al. (2019) · Nature Communications · doi:10.1038/s41467-018-08147-0 · Cited by 182 · see citing works
Natural anti-aging skincare: role and potential
Ahmed, I. A., Mikail, M. A., Zamakshshari, N. H., & Abdullah, A.-S. H. (2020) · Biogerontology · doi:10.1007/s10522-020-09865-z · Cited by 180 · see citing works
Zhang, W., Zeng, W., Jiang, A., He, Z. X., Shen, X., Dong, X., Feng, J., & Lü, H. (2021) · Cancer Medicine · doi:10.1002/cam4.4046 · Cited by 170 · see citing works
The Genetics of Human Skin and Hair Pigmentation.
Pavan, W., & Sturm, R. (2019) · Annual review of genomics and human genetics (Print) · doi:10.1146/annurev-genom-083118-015230 · Cited by 141 · see citing works
The selection landscape and genetic legacy of ancient Eurasians
Irving-Pease, E. K., Refoyo-Martínez, A., Barrie, W., Ingason, A., Pearson, A., Fischer, A., Sjögren, K.-G., Halgren, A. S., Macleod, R., Demeter, F., et al. (2024) · Nature · doi:10.1038/s41586-023-06705-1 · Cited by 147 · see citing works
Harney, É., May, H., Shalem, D., Rohland, N., Mallick, S., Lazaridis, I., Sarig, R., Stewardson, K., Nordenfelt, S., Patterson, N., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05649-9 · Cited by 141 · see citing works
A curated gene list for expanding the horizons of pigmentation biology
Baxter, L. L., Watkins‐Chow, D. E., Pavan, W. J., & Loftus, S. K. (2019) · Pigment Cell & Melanoma Research · doi:10.1111/pcmr.12743 · Cited by 136 · see citing works
Melanosome Biogenesis in the Pigmentation of Mammalian Skin
Le, L., Sirés-Campos, J., Raposo, G., Delevoye, C., & Marks, M. S. (2021) · Integrative and Comparative Biology · doi:10.1093/icb/icab078 · Cited by 119 · see citing works
SLC45A2 protein stability and regulation of melanosome pH determine melanocyte pigmentation
Le, L., Escobar, I. E., Ho, T., Lefkovith, A. J., Latteri, E., Haltaufderhyde, K. D., Dennis, M. K., Plowright, L., Sviderskaya, E. V., Bennett, D. C., et al. (2020) · Molecular Biology of the Cell · doi:10.1091/mbc.e20-03-0200 · Cited by 111 · see citing works
Jablonski, N. G. (2021) · Pigment Cell & Melanoma Research · doi:10.1111/pcmr.12976 · Cited by 93 · see citing works
Fan, S., Spence, J. P., Feng, Y., Hansen, M. E. B., Terhorst, J., Beltrame, M. H., Ranciaro, A., Hirbo, J. B., Beggs, W. R., Thomas, N., et al. (2023) · Cell · doi:10.1016/j.cell.2023.01.042 · Cited by 90 · see citing works
Localization of adaptive variants in human genomes using averaged one-dependence estimation
Sugden, L. A., Atkinson, E. G., Fischer, A. P., Rong, S., Henn, B. M., & Ramachandran, S. (2018) · Nature Communications · doi:10.1038/s41467-018-03100-7 · Cited by 88 · see citing works
Self-citationThe evolution of skin pigmentation-associated variation in West Eurasia
Ju, D., & Mathieson, I. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2009227118 · Cited by 81 · see citing works
Skin colour and vitamin D: An update
Hänel, A., & Carlberg, C. (2020) · Experimental Dermatology · doi:10.1111/exd.14142 · Cited by 76 · see citing works
NNT mediates redox-dependent pigmentation via a UVB- and MITF-independent mechanism
Allouche, J., Rachmin, I., Adhikari, K., Pardo, L. M., Lee, J. H., McConnell, A. M., Kato, S., Fan, S., Kawakami, A., Suita, Y., et al. (2021) · Cell · doi:10.1016/j.cell.2021.06.022 · Cited by 72 · see citing works
The Critical Needs and Challenges for Genetic Architecture Studies in Africa
Martin, A. R., Teferra, S., Möller, M., Hoal, E. G., & Daly, M. J. (2018) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2018.08.005 · Cited by 76 · see citing works
Self-citationA genome-wide genetic screen uncovers determinants of human pigmentation
Bajpai, V. K., Swigut, T., Mohammed, J., Tycko, J., Naqvi, S., Villanueva, M. A., Kim, T. C., Arora, N., Pritchard, J. K., Bassik, M. C., et al. (2023) · Science · doi:10.1126/science.ade6289 · Cited by 65 · see citing works
Shades of complexity: New perspectives on the evolution and genetic architecture of human skin
Quillen, E. E., Norton, H. L., Parra, E. J., Lona‐Durazo, F., Ang, K. C., Illiescu, F. M., Pearson, L. N., Shriver, M. D., Lasisi, T., Gokcumen, O., et al. (2019) · American Journal of Physical Anthropology · doi:10.1002/ajpa.23737 · Cited by 67 · see citing works
Self-citationPopulation differentiation of polygenic score predictions under stabilizing selection
Yair, S., & Coop, G. (2022) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2020.0416 · Cited by 58 · see citing works
The Eumelanin Human Skin Colour Scale: a proof‐of‐concept study
Dadzie, O. E., Sturm, R. A., Fajuyigbe, D., Petit, A., & Jablonski, N. G. (2022) · British Journal of Dermatology · doi:10.1111/bjd.21277 · Cited by 61 · see citing works
Selecting microhaplotypes optimized for different purposes
Kidd, K., Pakstis, A., Speed, W. C., Lagacé, R., Wootton, S., & Chang, J. (2018) · Electrophoresis · doi:10.1002/elps.201800092 · Cited by 46 · see citing works
Male-biased migration from East Africa introduced pastoralism into southern Africa
Vicente, M., Lankheet, I., Russell, T., Hollfelder, N., Coetzee, V., Soodyall, H., de Jongh, M., & Schlebusch, C. M. (2021) · BMC Biology · doi:10.1186/s12915-021-01193-z · Cited by 59 · see citing works
High Levels of Genetic Diversity within Nilo-Saharan Populations: Implications for Human Adaptation
Mulindwa, J., Noyes, H. A., Ilboudo, H., Pagani, L., Nyangiri, O. A., Kimuda, M. P., Ahouty, B., Asina, O. F., Ofon, E. A., Kamoto, K., et al. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.07.007 · Cited by 59 · see citing works
Negative selection on complex traits limits phenotype prediction accuracy between populations
Durvasula, A., & Lohmueller, K. E. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.02.013 · Cited by 57 · see citing works
Limitations of principal components in quantitative genetic association models for human studies
Yao, Y., & Ochoa, A. (2023) · eLife · doi:10.7554/elife.79238 · Cited by 54 · see citing works
African genetic diversity provides novel insights into evolutionary history and local adaptations
Choudhury, A., Aron, S., Sengupta, D., Hazelhurst, S., & Ramsay, M. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy161 · Cited by 54 · see citing works
Lona‐Durazo, F., Hernandez‐Pacheco, N., Fan, S., Zhang, T., Choi, J., Kovacs, M. A., Loftus, S. K., Le, P., Edwards, M., Fortes‐Lima, C., et al. (2019) · BMC Genetics · doi:10.1186/s12863-019-0765-5 · Cited by 53 · see citing works
Reconstruction of the human amylase locus reveals ancient duplications seeding modern-day variation
Yilmaz, F., Karageorgiou, C., Kim, K., Pajic, P., Scheer, K., Beck, C. R., Torregrossa, A., Lee, C., Gökçümen, Ö., Audano, P. A., et al. (2024) · Science · doi:10.1126/science.adn0609 · Cited by 52 · see citing works
Putting RFMix and ADMIXTURE to the test in a complex admixed population
Uren, C., Hoal, E. G., & Möller, M. (2020) · BMC Genetics · doi:10.1186/s12863-020-00845-3 · Cited by 52 · see citing works
Self-citationThe Evolutionary History of Human Skin Pigmentation
Rocha, J. (2019) · Journal of Molecular Evolution · doi:10.1007/s00239-019-09902-7 · Cited by 50 · see citing works
Genetic Resistance to Mycobacterium tuberculosis Infection and Disease
Möller, M., Kinnear, C. J., Orlova, M., Kroon, E. E., van Helden, P. D., Schurr, E., & Hoal, E. G. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.02219 · Cited by 50 · see citing works
Self-citationPolygenic Scores in Developmental Psychology: Invite Genetics In, Leave Biodeterminism Behind
Raffington, L., Mallard, T. T., & Harden, K. P. (2020) · Annual Review of Developmental Psychology · doi:10.1146/annurev-devpsych-051820-123945 · Cited by 42 · see citing works
Current clinical use of polygenic scores will risk exacerbating health disparities
Martin, A. R., Kanai, M., Kamatani, Y., Okada, Y., Neale, B. M., & Daly, M. J. (2018) · doi:10.1101/441261 · Cited by 2,813 · see citing works
Self-citationGenetic adaptation of skin pigmentation in highland Tibetans
Yang, Z., Bai, C., Pu, Y., Kong, Q., Guo, Y., Ouzhuluobu, Gengdeng, Liu, X., Zhao, Q., Qiu, Z., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2200421119 · Cited by 43 · see citing works
Self-citationYang, Z., Shi, H., Ma, P., Zhao, S., Kong, Q., Bian, T., Gong, C., Zhao, Q., Liu, Y., Qi, X., et al. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msy136 · Cited by 42 · see citing works
Lin, M. H., Park, D. S., Zaitlen, N., Henn, B. M., & Gignoux, C. R. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.673167 · Cited by 36 · see citing works
Self-citationA Sex-Stratified Genome-Wide Association Study of Tuberculosis Using a Multi-Ethnic Genotyping Array
Schurz, H., Kinnear, C. J., Gignoux, C. R., Wojcik, G. L., van Helden, P. D., Tromp, G. C., Henn, B. M., Hoal, E. G., & Möller, M. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2018.00678 · Cited by 42 · see citing works
Self-citationTrue colors: A literature review on the spatial distribution of eye and hair pigmentation
Katsara, M., & Nothnagel, M. (2019) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2019.01.001 · Cited by 42 · see citing works
High-coverage genome of the Tyrolean Iceman reveals unusually high Anatolian farmer ancestry
Wang, K., Prüfer, K., Krause‐Kyora, B., Childebayeva, A., Schuenemann, V. J., Coia, V., Maixner, F., Zink, A., Schiffels, S., & Krause, J. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100377 · Cited by 39 · see citing works
Human races are not like dog breeds: refuting a racist analogy
Norton, H., Quillen, E. E., Bigham, A. W., Pearson, L. N., & Dunsworth, H. M. (2019) · Evolution Education and Outreach · doi:10.1186/s12052-019-0109-y · Cited by 40 · see citing works
Guo, J., Bakshi, A., Wang, Y., Jiang, L., Yengo, L., Goddard, M. E., Visscher, P. M., & Yang, J. (2021) · Scientific Reports · doi:10.1038/s41598-021-84739-z · Cited by 33 · see citing works
Lucock, M. D. (2022) · American Journal of Biological Anthropology · doi:10.1002/ajpa.24564 · Cited by 35 · see citing works
Sun, X., Niu, Q., Jiang, J., Wang, G., Zhou, P., Li, J., Chen, C., Liu, L., Xu, L., & Ren, H. (2023) · Genes · doi:10.3390/genes14061183 · Cited by 34 · see citing works
Evolutionary genetics of skin pigmentation in African populations
Feng, Y., McQuillan, M. A., & Tishkoff, S. A. (2021) · Human Molecular Genetics · doi:10.1093/hmg/ddab007 · Cited by 31 · see citing works
Human genetic admixture through the lens of population genomics
Gopalan, S., Smith, S. P., Korunes, K. L., Hamid, I., Ramachandran, S., & Goldberg, A. (2022) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2020.0410 · Cited by 34 · see citing works
Batai, K., Cui, Z., Arora, A., Shah‐Williams, E., Hernandez, W., Ruden, M., Hollowell, C. M. P., Hooker, S. E., Bathina, M., Murphy, A. B., et al. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009319 · Cited by 35 · see citing works
Markiewicz, E., & Idowu, O. C. (2020) · Clinical Cosmetic and Investigational Dermatology · doi:10.2147/ccid.s245043 · Cited by 33 · see citing works
Genome of Peştera Muierii skull shows high diversity and low mutational load in pre-glacial Europe
Svensson, E., Günther, T., Hoischen, A., Hervella, M., Munters, A. R., Ioana, M. I., Ridiche, F., Edlund, H., van Deuren, R. C., Soficaru, A., et al. (2021) · Current Biology · doi:10.1016/j.cub.2021.04.045 · Cited by 31 · see citing works
Feng, Y., Xie, N., Inoue, F., Fan, S., Saskin, J., Zhang, C., Zhang, F., Hansen, M. E. B., Nyambo, T., Mpoloka, S. W., et al. (2024) · Nature Genetics · doi:10.1038/s41588-023-01626-1 · Cited by 31 · see citing works
The Emergence of Genomic Research in Africa and New Frameworks for Equity in Biomedical Research
Bentley, A. R., Callier, S., & Rotimi, C. N. (2019) · Ethnicity & Disease · doi:10.18865//ed.29.s1.179 · Cited by 30 · see citing works
Contaminating DNA in human saliva alters the detection of variants from whole genome sequencing
Samson, C., Whitford, W., Snell, R. G., Jacobsen, J. C., & Lehnert, K. (2020) · Scientific Reports · doi:10.1038/s41598-020-76022-4 · Cited by 27 · see citing works
Quantitative Human Paleogenetics: What can Ancient DNA Tell us About Complex Trait Evolution?
Irving-Pease, E. K., Muktupavela, R., Dannemann, M., & Racimo, F. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.703541 · Cited by 24 · see citing works
Advances in integrative African genomics
Zhang, C., Hansen, M. E. B., & Tishkoff, S. A. (2021) · Trends in Genetics · doi:10.1016/j.tig.2021.09.013 · Cited by 23 · see citing works
Predicting Physical Appearance from DNA Data—Towards Genomic Solutions
Pośpiech, E., Teisseyre, P., Mielniczuk, J., & Branicki, W. (2022) · Genes · doi:10.3390/genes13010121 · Cited by 23 · see citing works
Rapid evolution of a skin-lightening allele in southern African KhoeSan
Lin, M. H., Siford, R. L., Martin, A. R., Nakagome, S., Möller, M., Hoal, E. G., Bustamante, C. D., Gignoux, C. R., & Henn, B. M. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1801948115 · Cited by 24 · see citing works
Self-citationLai-Net: Local-Ancestry Inference with Neural Networks
Montserrat, D. M., Bustamante, C. D., & Ioannidis, A. G. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053662 · Cited by 23 · see citing works
Self-citationAmatya, B., Lee, H., Asico, L. D., Konkalmatt, P. R., Armando, I., Felder, R. A., & José, P. A. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22052319 · Cited by 22 · see citing works
Lucock, M. D., Jones, P. R., Veysey, M. J., Thota, R. N., Garg, M. L., Furst, J. E., Martin, C., Yates, Z. R., Scarlett, C. J., Jablonski, N. G., et al. (2021) · American Journal of Human Biology · doi:10.1002/ajhb.23667 · Cited by 22 · see citing works
Yelmen, B., Mondal, M., Marnetto, D., Pathak, A. K., Montinaro, F., Romero, I. G., Kivisild, T., Metspalu, M., & Pagani, L. (2019) · Molecular Biology and Evolution · doi:10.1093/molbev/msz037 · Cited by 22 · see citing works
A large Canadian cohort provides insights into the genetic architecture of human hair colour
Lona‐Durazo, F., de Aquino, M. M., Thakur, R., Funderburk, K. M., Zhang, T., Kovacs, M. A., Choi, J., Brown, K. M., & Parra, E. J. (2021) · Communications Biology · doi:10.1038/s42003-021-02764-0 · Cited by 22 · see citing works
Reading tea leaves? Polygenic scores and differences in traits among groupsPreprint
Coop, G. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1909.00892 · Cited by 28 · see citing works
Shi, X., Wu, J.-P., Lang, X., Wang, C.-L., Bai, Y., Riley, D., Liu, L., & Ma, X.-M. (2021) · PeerJ · doi:10.7717/peerj.11122 · Cited by 18 · see citing works
GWAS Identifies Multiple Genetic Loci for Skin Color in Korean Women
Seo, J. Y., You, S. W., Shin, J., Kim, Y., Park, S. G., Won, H., & Kang, N. G. (2021) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2021.08.440 · Cited by 21 · see citing works
Skin colour: A window into human phenotypic evolution and environmental adaptation
Liu, J., Bitsue, H. K., & Yang, Z. (2024) · Molecular Ecology · doi:10.1111/mec.17369 · Cited by 25 · see citing works
Chen, Y., André, M., Adhikari, K., Blin, M., Bonfante, B., Mendoza‐Revilla, J., Fuentes‐Guajardo, M., Palmal, S., Chacón-Duque, J. C., Hurtado, M., et al. (2021) · British Journal of Dermatology · doi:10.1111/bjd.20436 · Cited by 21 · see citing works
Prediction of eye, hair and skin colour in Latin Americans.
Palmal, S., Adhikari, K., Mendoza-Revilla, J., Fuentes-Guajardo, M., de Cerqueira, C. C. S., Bonfante, B., Chacón-Duque, J., Sohail, A., Hurtado, M., Villegas, V., et al. (2021) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2021.102517 · Cited by 21 · see citing works
Forensic DNA phenotyping: Inferring phenotypic traits from crime scene DNA.
Dabas, P., Jain, S., Khajuria, H., & Nayak, B. (2022) · Journal of Forensic and Legal Medicine · doi:10.1016/j.jflm.2022.102351 · Cited by 24 · see citing works
Inclusive and Accurate Clinical Diagnostics Using Intelligent Computation and Smartphone Imaging
Chen, J., Zhao, D., Shi, H. C., Duan, Q., Jajesniak, P., Li, Y., Shen, W., Zhang, J., Reboud, J., Cooper, J. M., et al. (2024) · ACS Sensors · doi:10.1021/acssensors.4c01588 · Cited by 20 · see citing works
Lasisi, T. (2021) · American Journal of Physical Anthropology · doi:10.1002/ajpa.24264 · Cited by 16 · see citing works
Genetic Connections and Convergent Evolution of Tropical Indigenous Peoples in Asia
Deng, L., Pan, Y., Wang, Y., Chen, H., Yuan, K., Chen, S., Lu, D., Lü, Y., Mokhtar, S. S., Rahman, T. H. A., et al. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab361 · Cited by 20 · see citing works
Smith, S. P., Shahamatdar, S., Cheng, W., Zhang, S., Paik, J., Graff, M., Haiman, C. A., Matise, T. C., North, K. E., Peters, U., et al. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.03.005 · Cited by 17 · see citing works
Self-citationSWI/SNF Chromatin Remodeling Enzymes in Melanoma
Dreier, M. R., & de la Serna, I. L. (2022) · Epigenomes · doi:10.3390/epigenomes6010010 · Cited by 19 · see citing works
A sequence of SVA retrotransposon insertions in ASIP shaped human pigmentation
Kamitaki, N., Hujoel, M. L. A., Mukamel, R. E., Gebara, E., McCarroll, S. A., & Loh, P. (2024) · Nature Genetics · doi:10.1038/s41588-024-01841-4 · Cited by 18 · see citing works
Genome-Wide Analysis Identifies Candidate Genes Encoding Beak Color of Duck
Guo, Q., Jiang, Y. Q., Wang, Z., Bi, Y., Chen, G., Bai, H., & Chang, G. (2022) · Genes · doi:10.3390/genes13071271 · Cited by 17 · see citing works
Kim, B., Kim, D. S., Shin, J., Leem, S., Cho, M., Kim, H., Gu, K., Seo, J. Y., You, S. W., Martin, A. R., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-49031-4 · Cited by 16 · see citing works
Self-citationFrontiers in pigment cell and melanoma research
Filipp, F. V., Birlea, S. A., Bosenberg, M., Brash, D. E., Cassidy, P. B., Chen, S., D'Orazio, J. A., Fujita, M., Goh, B. K., Herlyn, M., et al. (2018) · Pigment Cell & Melanoma Research · doi:10.1111/pcmr.12728 · Cited by 16 · see citing works
Genetics of yellow-orange color variation in a pair of sympatric sulphur butterflies
Hanly, J. J., Francescutti, C. M., Loh, L. S., Corning, O. B. W. H., Long, D. J., Nakatani, M. A., Porter, A. H., & Martin, A. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112820 · Cited by 15 · see citing works
Self-citationThe evolutionary history of Southern Africa
Montinaro, F., & Capelli, C. (2018) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2018.11.003 · Cited by 15 · see citing works
Cross-ancestry analyses identify new genetic loci associated with 25-hydroxyvitamin D
Wang, X., Hivert, V., Groot, S., Wang, Y., Yengo, L., McGrath, J. J., Kemper, K. E., Visscher, P. M., Wray, N. R., & Revez, J. A. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1011033 · Cited by 15 · see citing works
The color of normal: How a Eurocentric focus erases pigmentation complexity
Norton, H. (2020) · American Journal of Human Biology · doi:10.1002/ajhb.23554 · Cited by 14 · see citing works
Omics in a Digital World: The Role of Bioinformatics in Providing New Insights Into Human Aging
Dato, S., Crocco, P., Migliore, N. R., & Lescai, F. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.689824 · Cited by 14 · see citing works
Saitou, M., Masuda, N., & Gökçümen, Ö. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab313 · Cited by 17 · see citing works
Expanded taxonomies of human memory
Finley, J. R. (2025) · Frontiers in Cognition · doi:10.3389/fcogn.2024.1505549 · Cited by 14 · see citing works
Markiewicz, E., & Idowu, O. C. (2022) · Clinical Cosmetic and Investigational Dermatology · doi:10.2147/ccid.s383790 · Cited by 12 · see citing works
Evolution, genetic diversity, and health
Palma-Martínez, M. J., Posadas-García, Y. S., Shaukat, A., López-Ángeles, B. E., & Sohail, M. (2025) · Nature Medicine · doi:10.1038/s41591-025-03558-1 · Cited by 9 · see citing works
Class-Conditional VAE-GAN for Local-Ancestry SimulationPreprint
Montserrat, D. M., Bustamante, C. D., & Ioannidis, A. G. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1911.13220 · Cited by 16 · see citing works
Self-citationDissecting dynamics and differences of selective pressures in the evolution of human pigmentation
Huang, X., Wang, S., Li, J., & He, Y. (2021) · Biology Open · doi:10.1242/bio.056523 · Cited by 12 · see citing works
Ganguly, K., Saha, T., Saha, A., Dutta, T., Banerjee, S., Sengupta, D., Bhattacharya, S., Ghosh, S., & Sengupta, M. (2019) · Archives of Dermatological Research · doi:10.1007/s00403-019-01891-3 · Cited by 10 · see citing works
Hernandez, M., & Perry, G. H. (2021) · Evolutionary Anthropology Issues News and Reviews · doi:10.1002/evan.21893 · Cited by 10 · see citing works
Weasel, L. H. (2022) · The American Naturalist · doi:10.1086/720130 · Cited by 10 · see citing works
van Eeden, G., Uren, C., Pless, E., Mastoras, M., van der Spuy, G. D., Tromp, G. C., Henn, B. M., & Möller, M. (2022) · Genome biology · doi:10.1186/s13059-022-02744-5 · Cited by 10 · see citing works
Self-citationRapid adaptive increase of amylase gene copy number in Indigenous Andeans
Scheer, K., Landau, L. J. B., Jorgensen, K. C., Karageorgiou, C., Siao, L., Alkan, C., Rivera, A. M. M., Osborne, C. A., Garcia, O. A., Pearson, L., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-71450-8 · Cited by 9 · see citing works
Grogan, K. E., & Perry, G. H. (2020) · Evolutionary Anthropology Issues News and Reviews · doi:10.1002/evan.21825 · Cited by 9 · see citing works
XGMix: Local-Ancestry Inference with Stacked XGBoostPreprint
Kumar, A., Montserrat, D. M., Bustamante, C. D., & Ioannidis, A. G. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.21.053876 · Cited by 8 · see citing works
Self-citationThe Genetics and Evolution of Human Pigmentation
Guermazi, D., & Saliba, E. (2025) · Biology · doi:10.3390/biology14081026 · Cited by 8 · see citing works
Wide-scale geographical analysis of genetic ancestry in the South African Coloured population
Lankheet, I., Hammarén, R., Caballero, L. X. A., Larena, M., Malmström, H., Jolly, C., Soodyall, H., de Jongh, M., & Schlebusch, C. M. (2025) · BMC Biology · doi:10.1186/s12915-025-02317-5 · Cited by 7 · see citing works
- Authors
- Martin, A. R., Lin, M., Granka, J. M., Myrick, J. W., Liu, X., Sockell, A., Atkinson, E. G., Werely, C. J., Möller, M., Sandhu, M. S., Kingsley, D. M., Hoal, E. G., Liu, X., Daly, M. J., Feldman, M. W., Gignoux, C. R., Bustamante, C. D., & Henn, B. M.
- Affiliations
- Broad Institute (US)
- Stony Brook University (US)
- Stanford University (US)
- BGI Group (China) (CN)
- Stellenbosch University (ZA)
- Wellcome Sanger Institute (GB)
- Corresponding author
- Martin, Alicia R.
- Henn, Brenna M.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2017-11
- Volume
- 171
- Issue
- 6
- Pages
- 1340-1353.e14
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC5884124
- OpenAlex
- W2764167548
- Cited by
- 156
- References
- 117
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 16 · 2023: 15 · 2022: 20 · 2021: 29 · 2020: 18 · 2019: 14 · 2018: 25
- FWCI
- 8.31
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Stanford University
- NIH (NIA P30 AG017253-12, 5T32GM007790, NIH K12 GM102778)
- Stanford Center for Computational, Evolutionary and Human Genomics
- Stanford NIH Genome Training Program (5T32HG000044)
- South African Medical Research Council
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › melanin and skin pigmentation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Race, Genetics, and Society
- Keywords
- skin pigmentation, polygenic architecture, Khoesan, Africans, heritability, latitude, SLC24A5, TRP-1, genetic loci, evolutionary pressure, quantitative phenotypes
- MeSH terms
- Africa, Humans, Skin Pigmentation, Polymorphism, Single Nucleotide, Black People
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review