scholarly journals Signatures of Recent Positive Selection in Enhancers Across 41 Human Tissues

2019 ◽  
Vol 9 (8) ◽  
pp. 2761-2774 ◽  
Author(s):  
Jiyun M. Moon ◽  
John A. Capra ◽  
Patrick Abbot ◽  
Antonis Rokas
2019 ◽  
Author(s):  
Jiyun M. Moon ◽  
John A. Capra ◽  
Patrick Abbot ◽  
Antonis Rokas

AbstractEvolutionary changes in enhancers are widely associated with variation in human traits and diseases. However, studies comprehensively quantifying levels of selection on enhancers at multiple evolutionary time points during recent human evolution and how enhancer evolution varies across human tissues are lacking. To address these questions, we integrated a dataset of 41,561 transcribed enhancers active in 41 different human tissues (FANTOM Consortium) with whole genome sequences of 1,668 individuals from the African, Asian, and European populations (1000 Genomes Project). Our analyses based on four different metrics (Tajima’s D, FST, H12, nSL) showed that ~5.90% of enhancers considered showed evidence of recent positive selection and that genes associated with enhancers under positive selection are enriched for diverse immune-related functions. The distributions of these metrics for brain and testis enhancers were often statistically significantly different compared to those of other tissues; the same was true for brain and testis enhancers that are tissue-specific compared to those that are tissue-broad and for testis enhancers associated with tissue-enriched and non-tissue-enriched genes. These differences varied considerably across metrics and tissues and were generally due to changes in distributions’ shapes rather than shifts in their values. These results suggest that many human enhancers experienced recent positive selection throughout multiple time periods in human evolutionary history, that this selection occurred in a tissue-dependent and immune-related functional context, and that much like the evolution of their coding counterparts, the evolution of brain and testis enhancers has been markedly different from that of enhancers in other tissues.


2017 ◽  
Vol 34 (8) ◽  
pp. 1936-1946 ◽  
Author(s):  
Kazuhiro Nakayama ◽  
Jun Ohashi ◽  
Kazuhisa Watanabe ◽  
Lkagvasuren Munkhtulga ◽  
Sadahiko Iwamoto

2018 ◽  
Author(s):  
Pier Francesco Palamara ◽  
Jonathan Terhorst ◽  
Yun S. Song ◽  
Alkes L. Price

AbstractInterest in reconstructing demographic histories has motivated the development of methods to estimate locus-specific pairwise coalescence times from whole-genome sequence data. We developed a new method, ASMC, that can estimate coalescence times using only SNP array data, and is 2-4 orders of magnitude faster than previous methods when sequencing data are available. We were thus able to apply ASMC to 113,851 phased British samples from the UK Biobank, aiming to detect recent positive selection by identifying loci with unusually high density of very recent coalescence times. We detected 12 genome-wide significant signals, including 6 loci with previous evidence of positive selection and 6 novel loci, consistent with coalescent simulations showing that our approach is well-powered to detect recent positive selection. We also applied ASMC to sequencing data from 498 Dutch individuals (Genome of the Netherlands data set) to detect background selection at deeper time scales. We observed highly significant correlations between average coalescence time inferred by ASMC and other measures of background selection. We investigated whether this signal translated into an enrichment in disease and complex trait heritability by analyzing summary association statistics from 20 independent diseases and complex traits (average N=86k) using stratified LD score regression. Our background selection annotation based on average coalescence time was strongly enriched for heritability (p = 7×10−153) in a joint analysis conditioned on a broad set of functional annotations (including other background selection annotations), meta-analyzed across traits; SNPs in the top 20% of our annotation were 3.8x enriched for heritability compared to the bottom 20%. These results underscore the widespread effects of background selection on disease and complex trait heritability.


2004 ◽  
Vol 13 (8) ◽  
pp. 783-797 ◽  
Author(s):  
Kun Tang ◽  
Li Peng Wong ◽  
Edmund J.D. Lee ◽  
Samuel S. Chong ◽  
Caroline G.L. Lee

2018 ◽  
Vol 8 (4) ◽  
pp. 1315-1325 ◽  
Author(s):  
Jiyun M. Moon ◽  
David M. Aronoff ◽  
John A. Capra ◽  
Patrick Abbot ◽  
Antonis Rokas

PLoS Biology ◽  
2006 ◽  
Vol 4 (4) ◽  
pp. e154 ◽  
Author(s):  
Benjamin F Voight ◽  
Sridhar Kudaravalli ◽  
Xiaoquan Wen ◽  
Jonathan K Pritchard

PLoS ONE ◽  
2013 ◽  
Vol 8 (5) ◽  
pp. e64280 ◽  
Author(s):  
Yuri Tani Utsunomiya ◽  
Ana Maria Pérez O’Brien ◽  
Tad Stewart Sonstegard ◽  
Curtis Paul Van Tassell ◽  
Adriana Santana do Carmo ◽  
...  

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