The DOI matches its Crossref record; 91 of the 92 references it cites were found in a registry or an index.
Impacts of Neanderthal-Introgressed Sequences on the Landscape of Human Gene Expression
Open accessAbstract
Regulatory variation influencing gene expression is a key contributor to phenotypic diversity, both within and between species. Unfortunately, RNA degrades too rapidly to be recovered from fossil remains, limiting functional genomic insights about our extinct hominin relatives. Many Neanderthal sequences survive in modern humans due to ancient hybridization, providing an opportunity to assess their contributions to transcriptional variation and to test hypotheses about regulatory evolution. We developed a flexible Bayesian statistical approach to quantify allele-specific expression (ASE) in complex RNA-seq datasets. We identified widespread expression differences between Neanderthal and modern human alleles, indicating pervasive cis-regulatory impacts of introgression. Brain regions and testes exhibited significant downregulation of Neanderthal alleles relative to other tissues, consistent with natural selection influencing the tissue-specific regulatory landscape. Our study demonstrates that Neanderthal-inherited sequences are not silent remnants of ancient interbreeding but have measurable impacts on gene expression that contribute to variation in modern human phenotypes.
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.
Integrity signals
Registry
Cites
Statistics
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.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Second, Neanderthal ancestry is depleted in regions of the genome with annotated molecular functions (e.g., genes and gene regulatory elements), and this depletion is strongest in annotated brain and testis regulatory regions27–29.”
From Quantifying the contribution of Neanderthal introgression to the heritability of complex traits (2021) · cites this paper as [28]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The depletion in cognitive traits suggests that the previously observed strong depletion for Neanderthal alleles in regulatory regions active in the brain may be due to effects on brain-related complex traits5,28,29.”
From Quantifying the contribution of Neanderthal introgression to the heritability of complex traits (2021) · cites this paper as [28]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Indeed, studies conducted primarily on Neanderthal introgressed DNA have suggested a non-negligible contribution to gene expression variation in modern humans [10, 11, 22], with repeated examples of Neanderthal archaic variants falling within regulatory elements or the seed region of mature micro-RNAs predicted to affect transcriptional and post-transcriptional regulatory processes [11, 62].”
From Denisovan introgression has shaped the immune system of present-day Papuans (2022) · cites this paper as [10]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Enhancers, in particular, are amongst the top targeted elements of archaic hominin introgression [10, 11].”
From Denisovan introgression has shaped the immune system of present-day Papuans (2022) · cites this paper as [10]
Experimental — accuracy not yet measured
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
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Fitting Linear Mixed-Effects Models Using lme4
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015) · Journal of Statistical Software · doi:10.18637/jss.v067.i01 · Cited by 86,835
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
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447
A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Kim, D., Pertea, G., Trapnell, C., Pimentel, H., Kelley, R., & Salzberg, S. L. (2013) · Genome Biology · doi:10.1186/gb-2013-14-4-r36 · Cited by 12,668
Fitting Linear Mixed-Effects Models Using lme4Preprint
Bates, D. M., Maechler, M., Bolker, B. M., & Walker, S. (2014) · arXiv (Cornell University) · doi:10.3929/ethz-b-000105397 · Cited by 9,435
An integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711
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
Cited by
Sorted by citations
CADD: predicting the deleteriousness of variants throughout the human genome
Rentzsch, P., Witten, D., Cooper, G. M., Shendure, J., & Kircher, M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1016 · Cited by 3,534
The influence of evolutionary history on human health and disease
Benton, M. L., Abraham, A., LaBella, A. L., Abbot, P., Rokas, A., & Capra, J. A. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-020-00305-9 · Cited by 291
Identifying and Interpreting Apparent Neanderthal Ancestry in African Individuals
Chen, L., Wolf, A. B., Fu, W., Li, L., & Akey, J. M. (2020) · Cell · doi:10.1016/j.cell.2020.01.012 · Cited by 254
Self-citationNeanderthal language revisited: not only us
Dediu, D., & Levinson, S. C. (2018) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2018.01.001 · Cited by 218
Limits of long-term selection against Neandertal introgression
Petr, M., Pääbo, S., Kelso, J., & Vernot, B. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1814338116 · Cited by 211
Metadata
- Authors
- McCoy, R. C., Wakefield, J., & Akey, J. M.
- Affiliations
- University of Washington (US)
- Corresponding author
- Akey, Joshua M.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2017-02
- Volume
- 168
- Issue
- 5
- Pages
- 916-927.e12
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC6219754
- OpenAlex
- W2594204182
- Cited by
- 200
- References
- 92
- Citations by year
- 2026: 17 · 2025: 10 · 2024: 22 · 2023: 23 · 2022: 15 · 2021: 27 · 2020: 37 · 2019: 26 · 2018: 16 · 2017: 7
- FWCI
- 94.65
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH/NHGRI (5T32HG000035-22)
- NIH (R01GM110068)
- Common Fund of the Office of the Director of the NIH
- NCI
- NHGRI
- NHLBI
- NIDA
- NIMH
- NINDS
- NCI\SAIC-Frederick
- Disease Research Interchange (10XS170)
- Roswell Park Cancer Institute (10XS171)
- Science Care (X10S172, HHSN268201000029C)
- The Broad Institute
- Van Andel Institute (10ST1035)
- SAIC-F (HHSN261200800001E)
- University of Miami (DA006227, DA033684, N01MH000028, MH090941, MH101814, MH090951, MH090937, MH101820, MH101825, MH090936, MH101819, MH090948, MH101782, MH101810, MH101822)
- Topics
- Social Sciences › Anthropology › Pleistocene-Era Hominins and Archaeology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- Neanderthal introgression, allele-specific expression, cis-regulatory variation, human gene expression, ancient hybridization, regulatory evolution, natural selection
- MeSH terms
- Animals, Brain, Gene Expression Regulation, Humans, Male, Organ Specificity, Testis, Gene Expression, Evolution, Molecular, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Neanderthals
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
