The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
The landscape of sex-differential transcriptome and its consequent selection in human adults
Open accessAbstract
BACKGROUND: The prevalence of several human morbid phenotypes is sometimes much higher than intuitively expected. This can directly arise from the presence of two sexes, male and female, in one species. Men and women have almost identical genomes but are distinctly dimorphic, with dissimilar disease susceptibilities. Sexually dimorphic traits mainly result from differential expression of genes present in both sexes. Such genes can be subject to different, and even opposing, selection constraints in the two sexes. This can impact human evolution by differential selection on mutations with dissimilar effects on the two sexes. RESULTS: We comprehensively mapped human sex-differential genetic architecture across 53 tissues. Analyzing available RNA-sequencing data from 544 adults revealed thousands of genes differentially expressed in the reproductive tracts and tissues common to both sexes. Sex-differential genes are related to various biological systems, and suggest new insights into the pathophysiology of diverse human diseases. We also identified a significant association between sex-specific gene transcription and reduced selection efficiency and accumulation of deleterious mutations, which might affect the prevalence of different traits and diseases. Interestingly, many of the sex-specific genes that also undergo reduced selection efficiency are essential for successful reproduction in men or women. This seeming paradox might partially explain the high incidence of human infertility. CONCLUSIONS: This work provides a comprehensive overview of the sex-differential transcriptome and its importance to human evolution and human physiology in health and in disease.
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.
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
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
The genetical theory of natural selection
Fisher, R. A. (1930) · doi:10.5962/bhl.title.27468 · Cited by 17,617
ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
Wang, K., Li, M., & Hakonarson, H. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq603 · Cited by 14,621
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
Finding groups in data: an introduction to cluster analysis
(1991) · Choice Reviews Online · doi:10.5860/choice.28-4558 · Cited by 10,474
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
Kumar, P., Henikoff, S., & Ng, P. C. (2009) · Nature Protocols · doi:10.1038/nprot.2009.86 · Cited by 6,521
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062
Intra-sexual selection in Drosophila
Bateman, A. J. (1948) · Heredity · doi:10.1038/hdy.1948.21 · Cited by 3,643
Cited by
Sex Differences in Gene Expression and Regulatory Networks across 29 Human Tissues
Lopes-Ramos, C. M., Chen, C.-Y., Kuijjer, M. L., Paulson, J. N., Sonawane, A. R., Fagny, M., Platig, J., Glass, K., Quackenbush, J., & DeMeo, D. L. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107795 · Cited by 445
ImmGen report: sexual dimorphism in the immune system transcriptome
Gal-Oz, S. T., Maier, B., Yoshida, H., Seddu, K., Elbaz, N., Czysz, C., Zuk, O., Stranger, B. E., Ner-Gaon, H., & Shay, T. (2019) · Nature Communications · doi:10.1038/s41467-019-12348-6 · Cited by 274
The role of sex in the genomics of human complex traits
Khramtsova, E. A., Davis, L. K., & Stranger, B. E. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-018-0083-1 · Cited by 303
Egan, B., & Sharples, A. P. (2023) · Physiological Reviews · doi:10.1152/physrev.00054.2021 · Cited by 278
Sex differences in obesity, lipid metabolism, and inflammation—A role for the sex chromosomes?
Zore, T., Palafox, M., & Reue, K. (2018) · Molecular Metabolism · doi:10.1016/j.molmet.2018.04.003 · Cited by 239
Metadata
- Authors
- Gershoni, M., & Pietrokovski, S.
- Venue
- BMC Biology
- Published
- 2017-02-07
- Volume
- 15
- Issue
- 1
- Pages
- 7-7
- ISSN
- 1741-7007 (ISSN-L)
- OpenAlex
- W2586476886
- Cited by
- 266
- References
- 69
- FWCI
- 13.58
- Type
- journal article
- Language
- en
- Open access
- gold
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: The landscape of sex-differential transcriptome and its consequent selection in human adults. https://app.cochat.ai/papers/10.1186/s12915-017-0352-z
- The paper
- Gershoni, M., & Pietrokovski, S. (2017). The landscape of sex-differential transcriptome and its consequent selection in human adults. BMC Biology. https://doi.org/10.1186/s12915-017-0352-z
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.