Genome-wide analysis of genetic diversity and selection signatures in three Indian sheep breeds

Saravanan, K.A.; Panigrahi, Manjit; Kumar, Harshit; Bhushan, Bharat; Dutt, Triveni; Mishra, Bishnu Prasad

doi:10.1016/j.livsci.2020.104367

Cited by 31 publications

(13 citation statements)

References 57 publications

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“…However, linkage disequilibrium-based methods are more powerful than population differentiated-based methods ( Jacobs et al, 2016 ). These methods have been used in cattle ( Cheruiyot et al, 2018 ; Tijjani et al, 2019 ), goats ( Henkel et al, 2019 ; Islam et al, 2019 ), and sheep ( Saravanan et al, 2021 ; Zhang et al, 2021 ). To enhance the accuracy of selection sweep detection and also to exclude unknown biasness, it is essential to combine various statistical approaches ( Qanbari and Simianer, 2014 ).…”

Section: Discussionmentioning

confidence: 99%

Selection Signature Analyses Revealed Genes Associated With Adaptation, Production, and Reproduction in Selected Goat Breeds in Kenya

et al. 2022

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Artificial and natural selection in livestock is expected to leave unique footprints on their genomes. Goat breeds in Kenya have evolved for survival, breeding, and production in various harsh ecological areas, and their genomes are likely to have acquired unique alleles for adaptation to such diverse production environments and other traits of economic importance. To investigate signals of selection for some selected goat breeds in Kenya, Alpine (n = 29), Galla (n = 12), Saanen (n = 24), and Toggenburg (n = 31) were considered. A total of 53,347 single-nucleotide polymorphisms (SNPs) generated using the Illumina GoatSNP50 BeadChip were analyzed. After quality control, 47,663 autosomal single-nucleotide polymorphisms remained for downstream analyses. Several complementary approaches were applied for the following analyses: integrated Haplotype Score (iHS), cross-population-extended haplotype homozygosity (XP-EHH), hapFLK, and FLK. A total of 404 top genomic regions were identified across all the four breeds, based on the four complementary analyses. Out of the 16 identified putative selection signature regions by the intersection of multiple-selective signal analyses, most of the putative regions were found to overlap significantly with the iHS and XP-EHH analyses on chromosomes 3, 4, 10, 15, 22, and 26. These regions were enriched with some genes involved in pathways associated directly or indirectly with environmental adaptation regulating immune responses (e.g., HYAL1 and HYAL3), milk production (e.g., LEPR and PDE4B), and adaptability (e.g., MST1 and PCK). The results revealed few intersect between breeds in genomic selection signature regions. In general, this did not present the typical classic selection signatures as predicted due to the complex nature of the traits. The results support that some various selection pressures (e.g., environmental challenges, artificial selection, and genome admixture challenges) have molded the genome of goat breeds in Kenya. Therefore, the research provides new knowledge on the conservation and utilization of these goat genetic resources in Kenya. In-depth research is needed to detect precise genes connected with adaptation and production in goat breeds in Kenya.

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Section: Discussionmentioning

confidence: 99%

Selection Signature Analyses Revealed Genes Associated With Adaptation, Production, and Reproduction in Selected Goat Breeds in Kenya

et al. 2022

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“…Copy Number Variations Regions hostspots located on OAR5 (CNVR18 and CNVR19; Table 2) span genes that have been reported to be associated with differences between thin‐ and fat‐tailed sheep ( SKP1 and TCF7 ; Moradi et al., 2012), with meat quality traits in cattle ( JADE2 and UBE2B ; Saravanan et al., 2021) or that have been reported to be involved in cholesterol and triglycerides metabolism ( SAR1B ; Fryer et al., 2014) but also with differential expression in mammary gland in sheep ( SEC24A ; Paten et al., 2015), dairy cattle ( UBE2B ; Dai et al., 2018) and beef cattle ( CDKN2AIPNL ; Dervishi et al., 2017).…”

Section: Discussionmentioning

confidence: 99%

Functional characterization of Copy Number Variations regions in Djallonké sheep

Fernández

Tapsoba

Traoré

et al. 2021

J Animal Breeding Genetics

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A total of 184 Djallonké (West African Dwarf) sheep of Burkina Faso were analysed for Copy Number Variations (CNV) using Ovine 50 K SNP BeadChip genotyping data and two different CNV calling platforms: PennCNV and QuantiSNP. Analyses allowed to identify a total of 63 candidate Copy Number Variations Regions (CNVR) on 11 different ovine chromosomes covering about 82.5 Mb of the sheep genome. Gene‐annotation enrichment analysis allowed to identify a total of 751 potential candidate ovine genes located in the candidate CNVR bounds. Functional annotation allowed to identify five statistically significant Functional Clusters (FC; enrichment factor > 1.3) involving 61 candidate genes. All genes forming significantly enriched FC were located on ovine chromosome (OAR) 21. FC1 (22 genes including PAG4 and PAG6) and FC5 (three genes: CTSC, CTSW and CTSF), coding proteases (peptidases and cathepsins, respectively), were involved in reproductive performance and modulation of gestation. Both FC3 and FC4 were involved in inflammatory and immunologic response through coding serum amyloid A and B‐box‐type zinc finger proteins, respectively. Finally, FC2 consisted of 27 genes (including OR10G6 and OR8B8) involved in olfactory receptor activity, key for animals adapting to new food resources. CNVR identified on at least 15% of individuals were considered CNVR hotspots and further overlapped with previously reported quantitative trait loci (QTL). CNVR hotspots spanning genes putatively involved with lipid metabolism (SKP1, TCF7, JADE2, UBE2B and SAR1B) and differential expression in mammary gland (SEC24A and CDKN2AIPNL) on OAR5 and dairy traits (CCDC198 and SLC35F4) on OAR7 overlapped with QTL associated with lipid metabolism, milk protein yield and milk fat percentage. Information obtained from local sheep populations naturally adapted to harsh environments contributes to increase our understanding of the genomic importance of CNV.

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“…According to a very recent study, the NTRK2 was shown to be a novel candidate gene for litter size in sheep [ 37 ]. RMI1 was shown to be associated with growth in sheep [ 38 ]. The KIF27 gene was involved in fertility [ 39 ].…”

Section: Resultsmentioning

confidence: 99%

Within- and between-Breed Selection Signatures in the Original and Improved Valachian Sheep

Mészárosová

Mészáros

Moravčíková

et al. 2022

Animals

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This study explored the genomic diversity and selection signatures in two Slovakian national breeds, the Original Valachian and the Improved Valachian sheep. As they are an important animal genetic resource within the country, but with decreasing population size, our aim is to identify potentially valuable genomic regions. A total of 97 sheep (18 male and 79 female) from the Original Valachian, and 69 sheep (25 male and 44 female) from the Improved Valachian populations were genotyped using the GeneSeek GGP Ovine 50 K chip. The inbreeding levels were assessed with runs of homozygosity (ROH). The selection signatures within breeds were identified based on the top 1% of most homozygous regions within the breed, the so-called ROH islands. The selection signatures between breeds were assessed based on variance in linkage disequilibrium. Overall, we have identified selection signatures with quantitative trait loci (QTL) and genes pointing towards all three production purposes of the Valachian sheep, milk, meat, and wool, including their quality characteristics. Another group with apparent large importance was the various traits related to health and resistance to parasites, which is well in line with the sturdy nature of this breed.

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Genome-wide analysis of genetic diversity and selection signatures in three Indian sheep breeds

Cited by 31 publications

References 57 publications

Selection Signature Analyses Revealed Genes Associated With Adaptation, Production, and Reproduction in Selected Goat Breeds in Kenya

Selection Signature Analyses Revealed Genes Associated With Adaptation, Production, and Reproduction in Selected Goat Breeds in Kenya

Functional characterization of Copy Number Variations regions in Djallonké sheep

Within- and between-Breed Selection Signatures in the Original and Improved Valachian Sheep

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