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Regulatory and evolutionary signatures of sex-biased genes on both the X chromosome and the autosomes

Overview of attention for article published in Biology of Sex Differences, November 2017
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1 Facebook page

Citations

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Title
Regulatory and evolutionary signatures of sex-biased genes on both the X chromosome and the autosomes
Published in
Biology of Sex Differences, November 2017
DOI 10.1186/s13293-017-0156-4
Pubmed ID
Authors

Jiangshan J. Shen, Ting-You Wang, Wanling Yang

Abstract

Sex is an important but understudied factor in the genetics of human diseases. Analyses using a combination of gene expression data, ENCODE data, and evolutionary data of sex-biased gene expression in human tissues can give insight into the regulatory and evolutionary forces acting on sex-biased genes. In this study, we analyzed the differentially expressed genes between males and females. On the X chromosome, we used a novel method and investigated the status of genes that escape X-chromosome inactivation (escape genes), taking into account the clonality of lymphoblastoid cell lines (LCLs). To investigate the regulation of sex-biased differentially expressed genes (sDEG), we conducted pathway and transcription factor enrichment analyses on the sDEGs, as well as analyses on the genomic distribution of sDEGs. Evolutionary analyses were also conducted on both sDEGs and escape genes. Genome-wide, we characterized differential gene expression between sexes in 462 RNA-seq samples and identified 587 sex-biased genes, or 3.2% of the genes surveyed. On the X chromosome, sDEGs were distributed in evolutionary strata in a similar pattern as escape genes. We found a trend of negative correlation between the gene expression breadth and nonsynonymous over synonymous mutation (dN/dS) ratios, showing a possible pleiotropic constraint on evolution of genes. Genome-wide, nine transcription factors were found enriched in binding to the regions surrounding the transcription start sites of female-biased genes. Many pathways and protein domains were enriched in sex-biased genes, some of which hint at sex-biased physiological processes. These findings lend insight into the regulatory and evolutionary forces shaping sex-biased gene expression and their involvement in the physiological and pathological processes in human health and diseases.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 37%
Researcher 7 23%
Professor 2 7%
Student > Master 2 7%
Student > Bachelor 1 3%
Other 3 10%
Unknown 4 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 57%
Agricultural and Biological Sciences 5 17%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Computer Science 1 3%
Medicine and Dentistry 1 3%
Other 1 3%
Unknown 4 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 March 2021.
All research outputs
#12,702,938
of 20,535,273 outputs
Outputs from Biology of Sex Differences
#265
of 397 outputs
Outputs of similar age
#181,258
of 338,797 outputs
Outputs of similar age from Biology of Sex Differences
#24
of 31 outputs
Altmetric has tracked 20,535,273 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 397 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.5. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 338,797 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.