Evidence map›Paper›PMID 39425030›Full record

ArticleBMC genomics2024

Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle.

Juliane Friedrich, Shuli Liu, Lingzhao Fang, James Prendergast, Pamela Wiener

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Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

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0cells of the map it votes in
9citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Juliane FriedrichDivision of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK. juliane.friedrich@roslin.ed.ac.uk.
Shuli LiuWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China.
Lingzhao FangCenter for Quantitative Genetics and Genomics (QGG), Aarhus University, Aarhus, Denmark.
James PrendergastDivision of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK.
Pamela WienerDivision of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK.

Funding

BBSRC Institute Strategic Program Grant BBS/E/RL/230001AUSDA National Institute of Food and Agriculture 2022-67015-36215
6 · The paper itself

Abstract

backgroundAfrican cattle represent a unique resource of genetic diversity in response to adaptation to numerous environmental challenges. Characterising the genetic landscape of indigenous African cattle and identifying genomic regions and genes of functional importance can contribute to targeted breeding and tackle the loss of genetic diversity. However, pinpointing the adaptive variant and determining underlying functional mechanisms of adaptation remains challenging.

resultsIn this study, we use selection signatures from whole-genome sequence data of eight indigenous African cattle breeds in combination with gene expression and quantitative trait loci (QTL) databases to characterise genomic targets of artificial selection and environmental adaptation and to identify the underlying functional candidate genes. In general, the trait-association analyses of selection signatures suggest the innate and adaptive immune system and production traits as important selection targets. For example, a large genomic region, with selection signatures identified for all breeds except N'Dama, was located on BTA27, including multiple defensin DEFB coding-genes. Out of 22 analysed tissues, genes under putative selection were significantly enriched for those overexpressed in adipose tissue, blood, lung, testis and uterus. Our results further suggest that cis-eQTL are themselves selection targets; for most tissues, we found a positive correlation between allele frequency differences and cis-eQTL effect size, suggesting that positive selection acts directly on regulatory variants.

conclusionsBy combining selection signatures with information on gene expression and QTL, we were able to reveal compelling candidate selection targets that did not stand out from selection signature results alone (e.g. GIMAP8 for tick resistance and NDUFS3 for heat adaptation). Insights from this study will help to inform breeding and maintain diversity of locally adapted, and hence important, breeds.

Indexed as

Quantitative Trait LociSelection, GeneticAdaptation, PhysiologicalAnimalsBreedingCattleGene FrequencyPhenotypePolymorphism, Single NucleotideCattle GTExEnvironmental adaptationGene expressioniHSQTL

Identifiers

PMID39425030
PMCPMC11490109

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.