Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 170

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Human paternal and maternal demographic histories: insights from high-resolution Y chromosome and mtDNA sequences

Lippold, Sebastian, Xu, Hongyang, Ko, Albert, Li, Mingkun, Renaud, Gabriel, Butthof, Anne, Schröder, Roland, Stoneking, Mark·2014·Investigative Genetics

Published version of a preprint

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/2041-2223-5-13

Cites

8 of 8 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 The model of population history used in simulations. We assumed a single out-of-Africa migration and further population divergence events (see text for further details). The model begins with the ancestral population in Africa (at time T1), a single out-of-Africa migration (T2), the first split between Oceania and Eurasia (T3), then Europe and Asia (T4), followed by Central and East Asia (T5), and finally between East Asia and the Americas (T6). We also required T2 to be greater than T3. The model assumes no migration between regions following divergence; in support of this assumption, there is very little sequence sharing between regions. We do allow changes in population size. This model was first used to estimate divergence times with combined mtDNA and NRY sequences, then the model and estimated mean divergence times were used in separate simulations of the mtDNA and NRY sequences to estimate ancestral and current Nf and Nm.
Figure 1 The model of population history used in simulations. We assumed a single out-of-Africa migration and further population divergence events (see text for further details). The model begins with the ancestral population in Africa (at time T1), a single out-of-Africa migration (T2), the first split between Oceania and Eurasia (T3), then Europe and Asia (T4), followed by Central and East Asia (T5), and finally between East Asia and the Americas (T6). We also required T2 to be greater than T3. The model assumes no migration between regions following divergence; in support of this assumption, there is very little sequence sharing between regions. We do allow changes in population size. This model was first used to estimate divergence times with combined mtDNA and NRY sequences, then the model and estimated mean divergence times were used in separate simulations of the mtDNA and NRY sequences to estimate ancestral and current Nf and Nm.CC BY · PubMed Central
Figure 2 Diversity and AMOVA results. (A) Mean number of pairwise differences (and SE bars) for the NRY and mtDNA sequences from each regional group. (B) AMOVA results for the entire worldwide dataset, and for each regional group of populations. Two comparisons are shown for the entire dataset; the left comparison includes regional groups as an additional hierarchical level, while the right one does not. * indicates that the among-population component of diversity does not differ significantly from zero (after Bonferroni adjustment of the P value for multiple comparisons).
Figure 2 Diversity and AMOVA results. (A) Mean number of pairwise differences (and SE bars) for the NRY and mtDNA sequences from each regional group. (B) AMOVA results for the entire worldwide dataset, and for each regional group of populations. Two comparisons are shown for the entire dataset; the left comparison includes regional groups as an additional hierarchical level, while the right one does not. * indicates that the among-population component of diversity does not differ significantly from zero (after Bonferroni adjustment of the P value for multiple comparisons).CC BY · PubMed Central
Figure 3 Bayesian trees and divergence time estimates for mtDNA and NRY haplogroups. (A) mtDNA haplogroups; (B) NRY haplogroups with the fast mutation rate; (C) NRY haplogroups with the slow mutation rate. Red asterisks denote nodes with low support values (<0.95). F* in the NRY trees indicates a sample that was assigned to haplogroup F by SNP genotyping, but does not fall with other haplogroup F samples. Some NRY haplogroup K samples formed a monophyletic clade (labelled K in the trees) while others fell with haplogroup M samples (labelled KM in the trees); see also Additional file 3: Figure S8.
Figure 3 Bayesian trees and divergence time estimates for mtDNA and NRY haplogroups. (A) mtDNA haplogroups; (B) NRY haplogroups with the fast mutation rate; (C) NRY haplogroups with the slow mutation rate. Red asterisks denote nodes with low support values (<0.95). F* in the NRY trees indicates a sample that was assigned to haplogroup F by SNP genotyping, but does not fall with other haplogroup F samples. Some NRY haplogroup K samples formed a monophyletic clade (labelled K in the trees) while others fell with haplogroup M samples (labelled KM in the trees); see also Additional file 3: Figure S8.CC BY · PubMed Central
Figure 4 Bayesian skyline plots of population size change through time for regional groups. Two curves are shown for the NRY data, based on ‘fast’ and ‘slow’ mutation rate estimates.
Figure 4 Bayesian skyline plots of population size change through time for regional groups. Two curves are shown for the NRY data, based on ‘fast’ and ‘slow’ mutation rate estimates.CC BY · PubMed Central
Figure 5 Distribution of Nf and Nm values, based on simulations. The density of the top 1% of the posterior values obtained from simulations of the mtDNA and NRY sequences are shown. (A) ancestral effective population sizes; (B) current effective population sizes. The dashed line in each plot follows a 1:1 ratio.
Figure 5 Distribution of Nf and Nm values, based on simulations. The density of the top 1% of the posterior values obtained from simulations of the mtDNA and NRY sequences are shown. (A) ancestral effective population sizes; (B) current effective population sizes. The dashed line in each plot follows a 1:1 ratio.CC BY · PubMed Central
Figure 6 Pictorial representation of the divergence time and female and male effective population size estimates, based on the simulation results. Red numbers reflect Nf (with ancestral Nf at the point of the red triangle and current Nf at the base of the red triangle) and blue numbers correspondingly reflect ancestral and current Nm. The numbers in the black oval indicate the founding effective sizes for the initial out-of-Africa migration, and dates on arrows indicate divergence times based on the model in Figure 1. Arrows are meant to indicate the schematic direction of migrations and should not be taken as indicating literal migration pathways, for example, the results indicate divergence of the ancestors of Oceanians 61,000 years ago, but not the route(s) people took to get to Oceania.
Figure 6 Pictorial representation of the divergence time and female and male effective population size estimates, based on the simulation results. Red numbers reflect Nf (with ancestral Nf at the point of the red triangle and current Nf at the base of the red triangle) and blue numbers correspondingly reflect ancestral and current Nm. The numbers in the black oval indicate the founding effective sizes for the initial out-of-Africa migration, and dates on arrows indicate divergence times based on the model in Figure 1. Arrows are meant to indicate the schematic direction of migrations and should not be taken as indicating literal migration pathways, for example, the results indicate divergence of the ancestors of Oceanians 61,000 years ago, but not the route(s) people took to get to Oceania.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 8 references

Research works printed but not linked: 73

  1. Jobling MA: The impact of recent events on human genetic diversity. Philos Trans R Soc Lond B Biol Sci. 2012, 367: 793-799. · DOI
  2. Heyer E, Chaix R, Pavard S, Austerlitz F: Sex-specific demographic behaviours that shape human genomic variation. Mol Ecol. 2012, 21: 597-612. · DOI · Paper page
  3. Wilkins JF: Unraveling male and female histories from human genetic data. Curr Opin Genet Dev. 2006, 16: 611-617. · DOI · Paper page
  4. Dupanloup I, Pereira L, Bertorelle G, Calafell F, Prata MJ, Amorim A, Barbujani G: A recent shift from polygyny to monogamy in humans is suggested by the analysis of worldwide Y-chromosome diversity. J Mol Evol. 2003, 57: 85-97. · DOI · Paper page
  5. Wei W, Ayub Q, Xue Y, Tyler-Smith C: A comparison of Y-chromosomal lineage dating using either resequencing or Y-SNP plus Y-STR genotyping. Forensic Sci Int Genet. 2013, 7: 568-572. · DOI
  6. Seielstad MT, Minch E, Cavalli-Sforza LL: Genetic evidence for a higher female migration rate in humans. Nat Genet. 1998, 20: 278-280. · DOI · Paper page
  7. Wilder JA, Kingan SB, Mobasher Z, Pilkington MM, Hammer MF: Global patterns of human mitochondrial DNA and Y-chromosome structure are not influenced by higher migration rates of females versus males. Nat Genet. 2004, 36: 1122-1125. · DOI · Paper page
  8. Hammer MF, Mendez FL, Cox MP, Woerner AE, Wall JD: Sex-biased evolutionary forces shape genomic patterns of human diversity. PLoS Genet. 2008, 4: e1000202- · DOI
  9. Keinan A, Mullikin JC, Patterson N, Reich D: Accelerated genetic drift on chromosome X during the human dispersal out of Africa. Nat Genet. 2009, 41: 66-70. · DOI
  10. Emery LS, Felsenstein J, Akey JM: Estimators of the human effective sex ratio detect sex biases on different timescales. Am J Hum Genet. 2010, 87: 848-856. · DOI
  11. Hammer MF, Woerner AE, Mendez FL, Watkins JC, Cox MP, Wall JD: The ratio of human X chromosome to autosome diversity is positively correlated with genetic distance from genes. Nat Genet. 2010, 42: 830-831. · DOI
  12. Arbiza L, Gottipati S, Siepel A, Keinan A: Contrasting X-linked and autosomal diversity across 14 human populations. Am J Hum Genet. 2014, 94: 827-844. · DOI
  13. Gottipati S, Arbiza L, Siepel A, Clark AG, Keinan A: Analyses of X-linked and autosomal genetic variation in population-scale whole genome sequencing. Nat Genet. 2011, 43: 741-743. · DOI
  14. Francalacci P, Morelli L, Angius A, Berutti R, Reinier F, Atzeni R, Pilu R, Busonero F, Maschio A, Zara I, Sanna D, Useli A, Urru MF, Marcelli M, Cusano R, Oppo M, Zoledziewska M, Pitzalis M, Deidda F, Porcu E, Poddie F, Kang HM, Lyons R, Tarrier B, Gresham JB, Li B, Tofanelli S, Alonso S, Dei M, Lai S, et al: Low-pass DNA sequencing of 1200 Sardinians reconstructs European Y-chromosome phylogeny. Science. 2013, 341: 565-569. · DOI
  15. Poznik GD, Henn BM, Yee MC, Sliwerska E, Euskirchen GM, Lin AA, Snyder M, Quintana-Murci L, Kidd JM, Underhill PA, Bustamante CD: Sequencing Y chromosomes resolves discrepancy in time to common ancestor of males versus females. Science. 2013, 341: 562-565. · DOI · Paper page
  16. Wei W, Ayub Q, Chen Y, McCarthy S, Hou Y, Carbone I, Xue Y, Tyler-Smith C: A calibrated human Y-chromosomal phylogeny based on resequencing. Genome Res. 2013, 23: 388-395. · DOI
  17. Cann HM, de Toma C, Cazes L, Legrand MF, Morel V, Piouffre L, Bodmer J, Bodmer WF, Bonne-Tamir B, Cambon-Thomsen A, Chen Z, Chu J, Carcassi C, Contu L, Du R, Excoffier L, Ferrara GB, Friedlaender JS, Groot H, Gurwitz D, Jenkins T, Herrera RJ, Huang X, Kidd J, Kidd KK, Langaney A, Lin AA, Mehdi SQ, Parham P, Piazza A, et al: A human genome diversity cell line panel. Science. 2002, 296: 261-262. · DOI
  18. Rosenberg NA: Standardized subsets of the HGDP-CEPH Human Genome Diversity Cell Line Panel, accounting for atypical and duplicated samples and pairs of close relatives. Ann Hum Genet. 2006, 70: 841-847. · DOI
  19. Meyer M, Kircher M: Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harb Protoc. 2010, 2010: pdb.prot5448- · DOI
  20. Karolchik D, Hinrichs AS, Furey TS, Roskin KM, Sugnet CW, Haussler D, Kent WJ: The UCSC Table Browser data retrieval tool. Nucleic Acids Res. 2004, 32: D493-D496. · DOI
  21. Hodges E, Xuan Z, Balija V, Kramer M, Molla MN, Smith SW, Middle CM, Rodesch MJ, Albert TJ, Hannon GJ, McCombie WR: Genome-wide in situ exon capture for selective resequencing. Nat Genet. 2007, 39: 1522-1527. · DOI
  22. Hodges E, Rooks M, Xuan Z, Bhattacharjee A: Benjamin Gordon D, Brizuela L, Richard McCombie W, Hannon GJ: Hybrid selection of discrete genomic intervals on custom-designed microarrays for massively parallel sequencing. Nat Protoc. 2009, 4: 960-974. · DOI
  23. Maricic T, Whitten M, Paabo S: Multiplexed DNA sequence capture of mitochondrial genomes using PCR products. PLoS One. 2010, 5: e14004- · DOI
  24. Kircher M, Stenzel U, Kelso J: Improved base calling for the Illumina Genome Analyzer using machine learning strategies. Genome Biol. 2009, 10: R83- · DOI
  25. Li H, Durbin R: Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009, 25: 1754-1760. · DOI · Paper page
  26. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R: Genome Project Data Processing S: The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009, 25: 2078-2079. · DOI · Paper page
  27. DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, Philippakis AA, del Angel G, Rivas MA, Hanna M, McKenna A, Fennell TJ, Kernytsky AM, Sivachenko AY, Cibulskis K, Gabriel SB, Altshuler D, Daly MJ: A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011, 43: 491-498. · DOI
  28. Briggs AW, Good JM, Green RE, Krause J, Maricic T, Stenzel U, Lalueza-Fox C, Rudan P, Brajkovic D, Kucan Z, Gusic I, Schmitz R, Doronichev VB, Golovanova LV, de la Rasilla M, Fortea J, Rosas A, Paabo S: Targeted retrieval and analysis of five Neandertal mtDNA genomes. Science. 2009, 325: 318-321. · DOI
  29. Edgar RC: MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004, 32: 1792-1797. · DOI · Paper page
  30. Kloss-Brandstatter A, Pacher D, Schonherr S, Weissensteiner H, Binna R, Specht G, Kronenberg F: HaploGrep: a fast and reliable algorithm for automatic classification of mitochondrial DNA haplogroups. Hum Mutat. 2011, 32: 25-32. · DOI
  31. Karafet TM, Mendez FL, Meilerman MB, Underhill PA, Zegura SL, Hammer MF: New binary polymorphisms reshape and increase resolution of the human Y chromosomal haplogroup tree. Genome Res. 2008, 18: 830-838. · DOI · Paper page
  32. Underhill PA, Passarino G, Lin AA, Shen P, Mirazon Lahr M, Foley RA, Oefner PJ, Cavalli-Sforza LL: The phylogeography of Y chromosome binary haplotypes and the origins of modern human populations. Ann Hum Genet. 2001, 65: 43-62. · DOI
  33. Excoffier L, Lischer HEL: Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resources. 2010, 10: 564-567. · DOI
  34. Paradis E, Claude J, Strimmer K: APE: Analyses of Phylogenetics and Evolution in R language. Bioinformatics. 2004, 20: 289-290. · DOI · Paper page
  35. Drummond AJ, Suchard MA, Xie D, Rambaut A: Bayesian Phylogenetics with BEAUti and the BEAST 1.7. Mol Biol Evol. 2012, 29: 1969-1973. · DOI
  36. Posada D: jModelTest: Phylogenetic model averaging. Mol Biol Evol. 2008, 25: 1253-1256. · DOI
  37. Soares P, Ermini L, Thomson N, Mormina M, Rito T, Rohl A, Salas A, Oppenheimer S, Macaulay V, Richards MB: Correcting for purifying selection: an improved human mitochondrial molecular clock. Am J Hum Genet. 2009, 84: 740-759. · DOI
  38. Rieux A, Eriksson A, Li M, Sobkowiak B, Weinert LA, Warmuth V, Ruiz-Linares A, Manica A, Balloux F: Improved calibration of the human mitochondrial clock using ancient genomes. Mol Biol Evol. 2014, in press
  39. Xue YL, Wang QJ, Long Q, Ng BL, Swerdlow H, Burton J, Skuce C, Taylor R, Abdellah Z, Zhao YL, Asan , MacArthur DG, Quail MA, Carter NP, Yang H, Tyler-Smith C: Human Y chromosome base-substitution mutation rate measured by direct sequencing in a deep-rooting pedigree. Curr Biol. 2009, 19: 1453-1457. · DOI
  40. Mendez FL, Krahn T, Schrack B, Krahn AM, Veeramah KR, Woerner AE, Fomine FL, Bradman N, Thomas MG, Karafet TM, Hammer MF: An African American paternal lineage adds an extremely ancient root to the human Y chromosome phylogenetic tree. Am J Hum Genet. 2013, 92: 454-459. · DOI
  41. Drummond AJ, Rambaut A, Shapiro B, Pybus OG: Bayesian coalescent inference of past population dynamics from molecular sequences. Mol Biol Evol. 2005, 22: 1185-1192. · DOI
  42. Li JZ, Absher DM, Tang H, Southwick AM, Casto AM, Ramachandran S, Cann HM, Barsh GS, Feldman M, Cavalli-Sforza LL, Myers RM: Worldwide human relationships inferred from genome-wide patterns of variation. Science. 2008, 319: 1100-1104. · DOI
  43. Reich D, Patterson N, Kircher M, Delfin F, Nandineni MR, Pugach I, Ko AM, Ko YC, Jinam TA, Phipps ME, Saitou N, Wollstein A, Kayser M, Paabo S, Stoneking M: Denisova admixture and the first modern human dispersals into Southeast Asia and Oceania. Am J Hum Genet. 2011, 89: 516-528. · DOI · Paper page
  44. Lopez Herraez D, Bauchet M, Tang K, Theunert C, Pugach I, Li J, Nandineni MR, Gross A, Scholz M, Stoneking M: Genetic variation and recent positive selection in worldwide human populations: evidence from nearly 1 million SNPs. PLoS One. 2009, 4: e7888- · DOI
  45. Excoffier L, Foll M: fastsimcoal: a continuous-time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios. Bioinformatics. 2011, 27: 1332-1334. · DOI
  46. Beaumont MA, Zhang W, Balding DJ: Approximate Bayesian computation in population genetics. Genetics. 2002, 162: 2025-2035. · DOI · Paper page
  47. Wilson Sayres MA, Lohmueller KE, Nielsen R: Natural selection reduced diversity on human y chromosomes. PLoS Genet. 2014, 10: e1004064- · DOI · Paper page
  48. Elhaik E, Tatarinova TV, Klyosov AA, Graur D: The ‘extremely ancient’ chromosome that isn’t: a forensic bioinformatic investigation of Albert Perry’s X-degenerate portion of the Y chromosome. Eur J Hum Genet. 2014, 22: 1111-1116. · DOI
  49. Behar DM, Villems R, Soodyall H, Blue-Smith J, Pereira L, Metspalu E, Scozzari R, Makkan H, Tzur S, Comas D, Bertranpetit J, Quintana-Murci L, Tyler-Smith C, Wells RS: Rosset S; Genographic Consortium: The dawn of human matrilineal diversity. Am J Hum Genet. 2008, 82: 1130-1140. · DOI
  50. Zegura SL, Karafet TM, Zhivotovsky LA, Hammer MF: High-resolution SNPs and microsatellite haplotypes point to a single, recent entry of Native American Y chromosomes into the Americas. Mol Biol Evol. 2004, 21: 164-175. · DOI
  51. O’Rourke DH, Raff JA: The human genetic history of the Americas: the final frontier. Curr Biol. 2010, 20: R202-R207. · DOI · Paper page
  52. Ray N, Wegmann D, Fagundes NJ, Wang S, Ruiz-Linares A, Excoffier L: A statistical evaluation of models for the initial settlement of the american continent emphasizes the importance of gene flow with Asia. Mol Biol Evol. 2010, 27: 337-345. · DOI
  53. Shi W, Ayub Q, Vermeulen M, Shao RG, Zuniga S, van der Gaag K, de Knijff P, Kayser M, Xue Y, Tyler-Smith C: A worldwide survey of human male demographic history based on Y-SNP and Y-STR data from the HGDP-CEPH populations. Mol Biol Evol. 2010, 27: 385-393. · DOI
  54. de Filippo C, Barbieri C, Whitten M, Mpoloka SW, Gunnarsdottir ED, Bostoen K, Nyambe T, Beyer K, Schreiber H, de Knijff P, Luiselli D, Stoneking M, Pakendorf B: Y-chromosomal variation in sub-Saharan Africa: insights into the history of Niger-Congo groups. Mol Biol Evol. 2011, 28: 1255-1269. · DOI
  55. Wood ET, Stover DA, Ehret C, Destro-Bisol G, Spedini G, McLeod H, Louie L, Bamshad M, Strassmann BI, Soodyall H, Hammer MF: Contrasting patterns of Y chromosome and mtDNA variation in Africa: evidence for sex-biased demographic processes. Eur J Hum Genet. 2005, 13: 867-876. · DOI
  56. Sikora MJ, Colonna V, Xue Y, Tyler-Smith C: Modeling the contrasting Neolithic male lineage expansions in Europe and Africa. Investig Genet. 2013, 4: 25- · DOI
  57. Botigue LR, Henn BM, Gravel S, Maples BK, Gignoux CR, Corona E, Atzmon G, Burns E, Ostrer H, Flores C, Bertranpetit J, Comas D, Bustamante CD: Gene flow from North Africa contributes to differential human genetic diversity in southern Europe. Proc Natl Acad Sci U S A. 2013, 110: 11791-11796. · DOI · Paper page
  58. Trejaut JA, Kivisild T, Loo JH, Lee CL, He CL, Hsu CJ, Lee ZY, Lin M: Traces of archaic mitochondrial lineages persist in Austronesian-speaking Formosan populations. PLoS Biol. 2005, 3: e247- · DOI
  59. Duggan AT, Evans B, Friedlaender FR, Friedlaender JS, Koki G, Merriwether DA, Kayser M, Stoneking M: Maternal history of Oceania from complete mtDNA genomes: contrasting ancient diversity with recent homogenization due to the Austronesian expansion. Am J Hum Genet. 2014, 94: 721-733. · DOI
  60. Delfin F, Myles S, Choi Y, Hughes D, Illek R, van Oven M, Pakendorf B, Kayser M, Stoneking M: Bridging near and remote Oceania: mtDNA and NRY variation in the Solomon Islands. Mol Biol Evol. 2012, 29: 545-564. · DOI
  61. Scheinfeldt L, Friedlaender F, Friedlaender J, Latham K, Koki G, Karafet T, Hammer M, Lorenz J: Unexpected NRY chromosome variation in Northern Island Melanesia. Mol Biol Evol. 2006, 23: 1628-1641. · DOI
  62. Friedlaender JS, Friedlaender FR, Hodgson JA, Stoltz M, Koki G, Horvat G, Zhadanov S, Schurr TG, Merriwether DA: Melanesian mtDNA complexity. PLoS One. 2007, 2: e248- · DOI
  63. Kayser M, Choi Y, van Oven M, Mona S, Brauer S, Trent RJ, Suarkia D, Schiefenhovel W, Stoneking M: The impact of the Austronesian expansion: evidence from mtDNA and Y chromosome diversity in the Admiralty Islands of Melanesia. Mol Biol Evol. 2008, 25: 1362-1374. · DOI
  64. Schurr TG: The peopling of the New World: Perspectives from molecular anthropology. Ann Rev Anthropol. 2004, 33: 551-583. · DOI
  65. Gunnarsdottir ED, Li M, Bauchet M, Finstermeier K, Stoneking M: High-throughput sequencing of complete human mtDNA genomes from the Philippines. Genome Res. 2011, 21: 1-11. · DOI
  66. Neuenschwander S, Largiader CR, Ray N, Currat M, Vonlanthen P, Excoffier L: Colonization history of the Swiss Rhine basin by the bullhead (Cottus gobio): inference under a Bayesian spatially explicit framework. Mol Ecol. 2008, 17: 757-772. · DOI
  67. Gronau I, Hubisz MJ, Gulko B, Danko CG, Siepel A: Bayesian inference of ancient human demography from individual genome sequences. Nat Genet. 2011, 43: 1031-1034. · DOI
  68. Oota H, Settheetham-Ishida W, Tiwawech D, Ishida T, Stoneking M: Human mtDNA and Y-chromosome variation is correlated with matrilocal versus patrilocal residence. Nat Genet. 2001, 29: 20-21. · DOI · Paper page
  69. Labuda D, Lefebvre JF, Nadeau P, Roy-Gagnon MH: Female-to-male breeding ratio in modern humans-an analysis based on historical recombinations. Am J Hum Genet. 2010, 86: 353-363. · DOI
  70. Wilder JA, Mobasher Z, Hammer MF: Genetic evidence for unequal effective population sizes of human females and males. Mol Biol Evol. 2004, 21: 2047-2057. · DOI · Paper page
  71. Vernot B, Akey JM: Resurrecting surviving Neandertal lineages from modern human genomes. Science. 2014, 343: 1017-1021. · DOI · Paper page
  72. Garrigan D, Kingan SB, Pilkington MM, Wilder JA, Cox MP, Soodyall H, Strassmann B, Destro-Bisol G, de Knijff P, Novelletto A, Friedlaender J, Hammer MF: Inferring human population sizes, divergence times and rates of gene flow from mitochondrial, X and Y chromosome resequencing data. Genetics. 2007, 177: 2195-2207. · DOI
  73. Hellenthal G, Busby GB, Band G, Wilson JF, Capelli C, Falush D, Myers S: A genetic atlas of human admixture history. Science. 2014, 343: 747-751. · DOI · Paper page

Cited by

See all 170

Metadata

Authors
Lippold, S., Xu, H., Ko, A., Li, M., Renaud, G., Butthof, A., Schröder, R., & Stoneking, M.
Venue
Investigative Genetics
Published
2014-09-24
Volume
5
Issue
1
ISSN
2041-2223
Cited by
170
References
8
Language
en

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.

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Human paternal and maternal demographic histories: insights from high-resolution Y chromosome and mtDNA sequences. https://app.cochat.ai/papers/10.1186/2041-2223-5-13
The paper
Lippold, S., Xu, H., Ko, A., Li, M., Renaud, G., Butthof, A., Schröder, R., & Stoneking, M. (2014). Human paternal and maternal demographic histories: insights from high-resolution Y chromosome and mtDNA sequences. Investigative Genetics. https://doi.org/10.1186/2041-2223-5-13