Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations

South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape...
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Autor*in:	Nompilo L. Hlongwane [verfasserIn] Edgar F. Dzomba [verfasserIn] Khanyisile Hadebe [verfasserIn] Magriet A. van der Nest [verfasserIn] Rian Pierneef [verfasserIn] Farai C. Muchadeyi [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	genetic signatures pigs gene enrichment analyses

Übergeordnetes Werk:	In: Animals - MDPI AG, 2011, 14(2024), 2, p 236
Übergeordnetes Werk:	volume:14 ; year:2024 ; number:2, p 236

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/ani14020236

Katalog-ID:	DOAJ096398574

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spelling	10.3390/ani14020236 doi (DE-627)DOAJ096398574 (DE-599)DOAJ57a5001c72344ee89d27765223fa67e5 DE-627 ger DE-627 rakwb eng SF600-1100 QL1-991 Nompilo L. Hlongwane verfasserin aut Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer’s extension of the <i<Fst</i< statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations’ ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations. genetic signatures <i<iHS</i< <i<XP-EHH</i< <i<HapFLK</i< pigs gene enrichment analyses Veterinary medicine Zoology Edgar F. Dzomba verfasserin aut Khanyisile Hadebe verfasserin aut Magriet A. van der Nest verfasserin aut Rian Pierneef verfasserin aut Farai C. Muchadeyi verfasserin aut In Animals MDPI AG, 2011 14(2024), 2, p 236 (DE-627)657589306 (DE-600)2606558-7 20762615 nnns volume:14 year:2024 number:2, p 236 https://doi.org/10.3390/ani14020236 kostenfrei https://doaj.org/article/57a5001c72344ee89d27765223fa67e5 kostenfrei https://www.mdpi.com/2076-2615/14/2/236 kostenfrei https://doaj.org/toc/2076-2615 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 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_2021 GBV_ILN_2025 GBV_ILN_2031 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_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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 AR 14 2024 2, p 236
allfields_unstemmed	10.3390/ani14020236 doi (DE-627)DOAJ096398574 (DE-599)DOAJ57a5001c72344ee89d27765223fa67e5 DE-627 ger DE-627 rakwb eng SF600-1100 QL1-991 Nompilo L. Hlongwane verfasserin aut Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer’s extension of the <i<Fst</i< statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations’ ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations. genetic signatures <i<iHS</i< <i<XP-EHH</i< <i<HapFLK</i< pigs gene enrichment analyses Veterinary medicine Zoology Edgar F. Dzomba verfasserin aut Khanyisile Hadebe verfasserin aut Magriet A. van der Nest verfasserin aut Rian Pierneef verfasserin aut Farai C. Muchadeyi verfasserin aut In Animals MDPI AG, 2011 14(2024), 2, p 236 (DE-627)657589306 (DE-600)2606558-7 20762615 nnns volume:14 year:2024 number:2, p 236 https://doi.org/10.3390/ani14020236 kostenfrei https://doaj.org/article/57a5001c72344ee89d27765223fa67e5 kostenfrei https://www.mdpi.com/2076-2615/14/2/236 kostenfrei https://doaj.org/toc/2076-2615 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 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_2021 GBV_ILN_2025 GBV_ILN_2031 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_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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 AR 14 2024 2, p 236
allfieldsGer	10.3390/ani14020236 doi (DE-627)DOAJ096398574 (DE-599)DOAJ57a5001c72344ee89d27765223fa67e5 DE-627 ger DE-627 rakwb eng SF600-1100 QL1-991 Nompilo L. Hlongwane verfasserin aut Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer’s extension of the <i<Fst</i< statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations’ ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations. genetic signatures <i<iHS</i< <i<XP-EHH</i< <i<HapFLK</i< pigs gene enrichment analyses Veterinary medicine Zoology Edgar F. Dzomba verfasserin aut Khanyisile Hadebe verfasserin aut Magriet A. van der Nest verfasserin aut Rian Pierneef verfasserin aut Farai C. Muchadeyi verfasserin aut In Animals MDPI AG, 2011 14(2024), 2, p 236 (DE-627)657589306 (DE-600)2606558-7 20762615 nnns volume:14 year:2024 number:2, p 236 https://doi.org/10.3390/ani14020236 kostenfrei https://doaj.org/article/57a5001c72344ee89d27765223fa67e5 kostenfrei https://www.mdpi.com/2076-2615/14/2/236 kostenfrei https://doaj.org/toc/2076-2615 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 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_2021 GBV_ILN_2025 GBV_ILN_2031 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_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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 AR 14 2024 2, p 236
allfieldsSound	10.3390/ani14020236 doi (DE-627)DOAJ096398574 (DE-599)DOAJ57a5001c72344ee89d27765223fa67e5 DE-627 ger DE-627 rakwb eng SF600-1100 QL1-991 Nompilo L. Hlongwane verfasserin aut Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer’s extension of the <i<Fst</i< statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations’ ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations. genetic signatures <i<iHS</i< <i<XP-EHH</i< <i<HapFLK</i< pigs gene enrichment analyses Veterinary medicine Zoology Edgar F. Dzomba verfasserin aut Khanyisile Hadebe verfasserin aut Magriet A. van der Nest verfasserin aut Rian Pierneef verfasserin aut Farai C. Muchadeyi verfasserin aut In Animals MDPI AG, 2011 14(2024), 2, p 236 (DE-627)657589306 (DE-600)2606558-7 20762615 nnns volume:14 year:2024 number:2, p 236 https://doi.org/10.3390/ani14020236 kostenfrei https://doaj.org/article/57a5001c72344ee89d27765223fa67e5 kostenfrei https://www.mdpi.com/2076-2615/14/2/236 kostenfrei https://doaj.org/toc/2076-2615 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 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_2021 GBV_ILN_2025 GBV_ILN_2031 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_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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 AR 14 2024 2, p 236
language	English
source	In Animals 14(2024), 2, p 236 volume:14 year:2024 number:2, p 236
sourceStr	In Animals 14(2024), 2, p 236 volume:14 year:2024 number:2, p 236
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	genetic signatures <i<iHS</i< <i<XP-EHH</i< <i<HapFLK</i< pigs gene enrichment analyses Veterinary medicine Zoology
isfreeaccess_bool	true
container_title	Animals
authorswithroles_txt_mv	Nompilo L. Hlongwane @@aut@@ Edgar F. Dzomba @@aut@@ Khanyisile Hadebe @@aut@@ Magriet A. van der Nest @@aut@@ Rian Pierneef @@aut@@ Farai C. Muchadeyi @@aut@@
publishDateDaySort_date	2024-01-01T00:00:00Z
hierarchy_top_id	657589306
id	DOAJ096398574
language_de	englisch
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callnumber-first	S - Agriculture
author	Nompilo L. Hlongwane
spellingShingle	Nompilo L. Hlongwane misc SF600-1100 misc QL1-991 misc genetic signatures misc <i<iHS</i< misc <i<XP-EHH</i< misc <i<HapFLK</i< misc pigs misc gene enrichment analyses misc Veterinary medicine misc Zoology Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations
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topic_title	SF600-1100 QL1-991 Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations genetic signatures <i<iHS</i< <i<XP-EHH</i< <i<HapFLK</i< pigs gene enrichment analyses
topic	misc SF600-1100 misc QL1-991 misc genetic signatures misc <i<iHS</i< misc <i<XP-EHH</i< misc <i<HapFLK</i< misc pigs misc gene enrichment analyses misc Veterinary medicine misc Zoology
topic_unstemmed	misc SF600-1100 misc QL1-991 misc genetic signatures misc <i<iHS</i< misc <i<XP-EHH</i< misc <i<HapFLK</i< misc pigs misc gene enrichment analyses misc Veterinary medicine misc Zoology
topic_browse	misc SF600-1100 misc QL1-991 misc genetic signatures misc <i<iHS</i< misc <i<XP-EHH</i< misc <i<HapFLK</i< misc pigs misc gene enrichment analyses misc Veterinary medicine misc Zoology
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title	Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations
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title_full	Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations
author_sort	Nompilo L. Hlongwane
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author_browse	Nompilo L. Hlongwane Edgar F. Dzomba Khanyisile Hadebe Magriet A. van der Nest Rian Pierneef Farai C. Muchadeyi
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author-letter	Nompilo L. Hlongwane
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title_sort	identification of signatures of positive selection that have shaped the genomic landscape of south african pig populations
callnumber	SF600-1100
title_auth	Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations
abstract	South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer’s extension of the <i<Fst</i< statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations’ ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations.
abstractGer	South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer’s extension of the <i<Fst</i< statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations’ ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations.
abstract_unstemmed	South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer’s extension of the <i<Fst</i< statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations’ ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations.
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container_issue	2, p 236
title_short	Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations
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Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations

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