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

Background African 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. Results In 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. Conclusions By 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. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Friedrich, Juliane [verfasserIn] Liu, Shuli [verfasserIn] Fang, Lingzhao [verfasserIn] Prendergast, James [verfasserIn] Wiener, Pamela [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	iHS QTL Gene expression Environmental adaptation Cattle GTEx

Anmerkung:	© The Author(s) 2024

Übergeordnetes Werk:	Enthalten in: BMC genomics - BioMed Central, 2000, 25(2024), 1 vom: 19. Okt.
Übergeordnetes Werk:	volume:25 ; year:2024 ; number:1 ; day:19 ; month:10

Links:	Volltext

DOI / URN:	10.1186/s12864-024-10852-8

Katalog-ID:	SPR057884781

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spelling	10.1186/s12864-024-10852-8 doi (DE-627)SPR057884781 (SPR)s12864-024-10852-8-e DE-627 ger DE-627 rakwb eng 570 610 VZ 12 ssgn BIODIV DE-30 fid 42.20 bkl 44.48 bkl Friedrich, Juliane verfasserin aut Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Background African 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. Results In 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. Conclusions By 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. iHS (dpeaa)DE-He213 QTL (dpeaa)DE-He213 Gene expression (dpeaa)DE-He213 Environmental adaptation (dpeaa)DE-He213 Cattle GTEx (dpeaa)DE-He213 Liu, Shuli verfasserin aut Fang, Lingzhao verfasserin aut Prendergast, James verfasserin aut Wiener, Pamela verfasserin aut Enthalten in BMC genomics BioMed Central, 2000 25(2024), 1 vom: 19. Okt. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:25 year:2024 number:1 day:19 month:10 https://dx.doi.org/10.1186/s12864-024-10852-8 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.20 VZ 44.48 VZ AR 25 2024 1 19 10
allfields_unstemmed	10.1186/s12864-024-10852-8 doi (DE-627)SPR057884781 (SPR)s12864-024-10852-8-e DE-627 ger DE-627 rakwb eng 570 610 VZ 12 ssgn BIODIV DE-30 fid 42.20 bkl 44.48 bkl Friedrich, Juliane verfasserin aut Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Background African 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. Results In 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. Conclusions By 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. iHS (dpeaa)DE-He213 QTL (dpeaa)DE-He213 Gene expression (dpeaa)DE-He213 Environmental adaptation (dpeaa)DE-He213 Cattle GTEx (dpeaa)DE-He213 Liu, Shuli verfasserin aut Fang, Lingzhao verfasserin aut Prendergast, James verfasserin aut Wiener, Pamela verfasserin aut Enthalten in BMC genomics BioMed Central, 2000 25(2024), 1 vom: 19. Okt. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:25 year:2024 number:1 day:19 month:10 https://dx.doi.org/10.1186/s12864-024-10852-8 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.20 VZ 44.48 VZ AR 25 2024 1 19 10
allfieldsGer	10.1186/s12864-024-10852-8 doi (DE-627)SPR057884781 (SPR)s12864-024-10852-8-e DE-627 ger DE-627 rakwb eng 570 610 VZ 12 ssgn BIODIV DE-30 fid 42.20 bkl 44.48 bkl Friedrich, Juliane verfasserin aut Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Background African 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. Results In 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. Conclusions By 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. iHS (dpeaa)DE-He213 QTL (dpeaa)DE-He213 Gene expression (dpeaa)DE-He213 Environmental adaptation (dpeaa)DE-He213 Cattle GTEx (dpeaa)DE-He213 Liu, Shuli verfasserin aut Fang, Lingzhao verfasserin aut Prendergast, James verfasserin aut Wiener, Pamela verfasserin aut Enthalten in BMC genomics BioMed Central, 2000 25(2024), 1 vom: 19. Okt. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:25 year:2024 number:1 day:19 month:10 https://dx.doi.org/10.1186/s12864-024-10852-8 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.20 VZ 44.48 VZ AR 25 2024 1 19 10
allfieldsSound	10.1186/s12864-024-10852-8 doi (DE-627)SPR057884781 (SPR)s12864-024-10852-8-e DE-627 ger DE-627 rakwb eng 570 610 VZ 12 ssgn BIODIV DE-30 fid 42.20 bkl 44.48 bkl Friedrich, Juliane verfasserin aut Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Background African 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. Results In 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. Conclusions By 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. iHS (dpeaa)DE-He213 QTL (dpeaa)DE-He213 Gene expression (dpeaa)DE-He213 Environmental adaptation (dpeaa)DE-He213 Cattle GTEx (dpeaa)DE-He213 Liu, Shuli verfasserin aut Fang, Lingzhao verfasserin aut Prendergast, James verfasserin aut Wiener, Pamela verfasserin aut Enthalten in BMC genomics BioMed Central, 2000 25(2024), 1 vom: 19. Okt. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:25 year:2024 number:1 day:19 month:10 https://dx.doi.org/10.1186/s12864-024-10852-8 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.20 VZ 44.48 VZ AR 25 2024 1 19 10
language	English
source	Enthalten in BMC genomics 25(2024), 1 vom: 19. Okt. volume:25 year:2024 number:1 day:19 month:10
sourceStr	Enthalten in BMC genomics 25(2024), 1 vom: 19. Okt. volume:25 year:2024 number:1 day:19 month:10
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	iHS QTL Gene expression Environmental adaptation Cattle GTEx
dewey-raw	570
isfreeaccess_bool	true
container_title	BMC genomics
authorswithroles_txt_mv	Friedrich, Juliane @@aut@@ Liu, Shuli @@aut@@ Fang, Lingzhao @@aut@@ Prendergast, James @@aut@@ Wiener, Pamela @@aut@@
publishDateDaySort_date	2024-10-19T00:00:00Z
hierarchy_top_id	326644954
dewey-sort	3570
id	SPR057884781
language_de	englisch
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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. Results In 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. 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author	Friedrich, Juliane
spellingShingle	Friedrich, Juliane ddc 570 ssgn 12 fid BIODIV bkl 42.20 bkl 44.48 misc iHS misc QTL misc Gene expression misc Environmental adaptation misc Cattle GTEx Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle
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topic_title	570 610 VZ 12 ssgn BIODIV DE-30 fid 42.20 bkl 44.48 bkl Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle iHS (dpeaa)DE-He213 QTL (dpeaa)DE-He213 Gene expression (dpeaa)DE-He213 Environmental adaptation (dpeaa)DE-He213 Cattle GTEx (dpeaa)DE-He213
topic	ddc 570 ssgn 12 fid BIODIV bkl 42.20 bkl 44.48 misc iHS misc QTL misc Gene expression misc Environmental adaptation misc Cattle GTEx
topic_unstemmed	ddc 570 ssgn 12 fid BIODIV bkl 42.20 bkl 44.48 misc iHS misc QTL misc Gene expression misc Environmental adaptation misc Cattle GTEx
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title	Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle
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title_full	Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle
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author_browse	Friedrich, Juliane Liu, Shuli Fang, Lingzhao Prendergast, James Wiener, Pamela
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title_sort	insights into trait-association of selection signatures and adaptive eqtl in indigenous african cattle
title_auth	Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle
abstract	Background African 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. Results In 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. Conclusions By 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. © The Author(s) 2024
abstractGer	Background African 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. Results In 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. Conclusions By 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. © The Author(s) 2024
abstract_unstemmed	Background African 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. Results In 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. Conclusions By 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. © The Author(s) 2024
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title_short	Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle
url	https://dx.doi.org/10.1186/s12864-024-10852-8
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author2	Liu, Shuli Fang, Lingzhao Prendergast, James Wiener, Pamela
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Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle

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