Signatures of selection reveal candidate genes involved in economic traits and cold acclimation in five Swedish cattle breeds

Ghoreishifar, Seyed Mohammad; Eriksson, Staffan; Johansson, Anna M.; Khansefid, Majid; Moghaddaszadeh-Ahrabi, Sima; Parna, Nahid; Davoudi, Pourya; Javanmard, Arash

doi:10.1186/s12711-020-00571-5

Cited by 53 publications

(45 citation statements)

References 124 publications

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“…Since the cattle skin is the infestation site of tick, the structural protein keratin which makes up the outer layer of skin and hair could act as a barrier [38]. Also, the PRDM2 gene was referred to play a role in resistance to disease and bacterial infection or cellmediated immune response, especially paratuberculosis resistance in ruminants [39,40]. The Paratuberculosis (Johne's disease) caused by Mycobacterium avium subspecies paratuberculosis (MAP) brought about considerable economic losses worldwide.…”

Section: Discussionmentioning

confidence: 99%

Population differentiated copy number variation of Bos taurus, Bos indicus and their African hybrids

et al. 2021

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Background CNV comprises a large proportion in cattle genome and is associated with various traits. However, there were few population-scale comparison studies on cattle CNV. Results Here, autosome-wide CNVs were called by read depth of NGS alignment result and copy number variation regions (CNVRs) defined from 102 Eurasian taurine (EAT) of 14 breeds, 28 Asian indicine (ASI) of 6 breeds, 22 African taurine (AFT) of 2 breeds, and 184 African humped cattle (AFH) of 17 breeds. The copy number of every CNVRs were compared between populations and CNVRs with population differentiated copy numbers were sorted out using the pairwise statistics VST and Kruskal-Wallis test. Three hundred sixty-two of CNVRs were significantly differentiated in both statistics and 313 genes were located on the population differentiated CNVRs. Conclusion For some of these genes, the averages of copy numbers were also different between populations and these may be candidate genes under selection. These include olfactory receptors, pathogen-resistance, parasite-resistance, heat tolerance and productivity related genes. Furthermore, breed- and individual-level comparison was performed using the presence or copy number of the autosomal CNVRs. Our findings were based on identification of CNVs from short Illumina reads of 336 individuals and 39 breeds, which to our knowledge is the largest dataset for this type of analysis and revealed important CNVs that may play a role in cattle adaption to various environments.

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Section: Discussionmentioning

confidence: 99%

Population differentiated copy number variation of Bos taurus, Bos indicus and their African hybrids

et al. 2021

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“…Besides these beneficial attributes, DCMS estimation is also possible with better accuracy even with less demography information. Selection signature analysis in Russian and Swedish local cattle using de-correlated DCMS revealed functional variants under selection related to production, reproduction, and adaptation (Yurchenko et al, 2018;Ghoreishifar et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Scanning for Signatures of Selection Revealed the Putative Genomic Regions and Candidate Genes Controlling Milk Composition and Coat Color Traits in Sahiwal Cattle

et al. 2021

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BackgroundIn the evolutionary time scale, selection shapes the genetic variation and alters the architecture of genome in the organisms. Selection leaves detectable signatures at the genomic coordinates that provide clues about the protein-coding regions. Sahiwal is a valuable indicine cattle adapted to tropical environments with desirable milk attributes. Insights into the genomic regions under putative selection may reveal the molecular mechanisms affecting the quantitative and other important traits. To understand this, the present investigation was undertaken to explore signatures of selection in the genome of Sahiwal cattle using a medium-density genotyping INDUS chip.ResultDe-correlated composite of multiple selection signals (DCMS), which combines five different univariate statistics, was computed in the dataset to detect the signatures of selection in the Sahiwal genome. Gene annotations, Quantitative Trait Loci (QTL) enrichment, and functional analyses were carried out for the identification of significant genomic regions. A total of 117 genes were identified, which affect a number of important economic traits. The QTL enrichment analysis highlighted 14 significant [False Discovery Rate (FDR)-corrected p-value ≤ 0.05] regions on chromosomes BTA 1, 3, 6, 11, 20, and 21. The top three enriched QTLs were found on BTA 6, 20, and 23, which are associated with exterior, health, milk production, and reproduction traits. The present study on selection signatures revealed some key genes related with coat color (PDGFRA, KIT, and KDR), facial pigmentation (LEF), milk fat percent (MAP3K1, HADH, CYP2U1, and SGMS2), sperm membrane integrity (OSTC), lactation persistency (MRPS30, NNT, CCL28, HMGCS1, NIM1K, ZNF131, and CCDC152), milk yield (GHR and ZNF469), reproduction (NKX2-1 and DENND1A), and bovine tuberculosis susceptibility (RNF144B and PAPSS1). Further analysis of candidate gene prioritization identified four hub genes, viz., KIT, KDR, MAP3K1, and LEF, which play a role in coat color, facial pigmentation, and milk fat percentage in cattle. Gene enrichment analysis revealed significant Gene ontology (GO) terms related to breed-specific coat color and milk fat percent.ConclusionThe key candidate genes and putative genomic regions associated with economic traits were identified in Sahiwal using single nucleotide polymorphism data and the DCMS method. It revealed selection for milk production, coat color, and adaptability to tropical climate. The knowledge about signatures of selection and candidate genes affecting phenotypes have provided a background information that can be further utilized to understand the underlying mechanism involved in these traits in Sahiwal cattle.

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“…With cost-effective genotyping technologies, it is possible to genotype several individuals from different breeds to scan their genome to uncover regions that are under putative selection [ 8 ]. The idea behind selection signature detection theory is that the frequency of alleles that are under selection can vary in opposite directions (low or high), resulting in stretches of consecutive homozygous genotypes, or in modifying the length and frequency of haplotypes around the region [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…When selection signatures are identified, they can help us understand the processes that cause diversity among breeds, and locate candidate genes involved in a phenotype of interest. Other studies of selection signatures in sheep [ 10 , 11 , 12 , 13 , 14 , 15 ] and other animal species [ 8 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ] have illustrated how these methods can find genomic regions potentially related to economic or adaptation-related traits. Thus, identification of recent selection signatures in Gotland sheep will help detect novel genomic regions associated with economically important traits, such as pelt and fleece quality.…”

Section: Introductionmentioning

confidence: 99%

Shared Ancestry and Signatures of Recent Selection in Gotland Sheep

Ghoreishifar

Rochus

Moghaddaszadeh-Ahrabi

et al. 2021

Genes

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Gotland sheep, a breed native to Gotland, Sweden (an island in the Baltic Sea), split from the Gute sheep breed approximately 100 years ago, and since, has probably been crossed with other breeds. This breed has recently gained popularity, due to its pelt quality. This study estimates the shared ancestors and identifies recent selection signatures in Gotland sheep using 600 K single nucleotide polymorphism (SNP) genotype data. Admixture analysis shows that the Gotland sheep is a distinct breed, but also has shared ancestral genomic components with Gute (~50%), Karakul (~30%), Romanov (~20%), and Fjällnäs (~10%) sheep breeds. Two complementary methods were applied to detect selection signatures: A Bayesian population differentiation FST and an integrated haplotype homozygosity score (iHS). Our results find that seven significant SNPs (q-value < 0.05) using the FST analysis and 55 significant SNPs (p-value < 0.0001) using the iHS analysis. Of the candidate genes that contain significant markers, or are in proximity to them, we identify several belongings to the keratin genes, RXFP2, ADCY1, ENOX1, USF2, COX7A1, ARHGAP28, CRYBB2, CAPNS1, FMO3, and GREB1. These genes are involved in wool quality, polled and horned phenotypes, fertility, twining rate, meat quality, and growth traits. In summary, our results provide shared founders of Gotland sheep and insight into genomic regions maintained under selection after the breed was formed. These results contribute to the detection of candidate genes and QTLs underlying economic traits in sheep.

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Signatures of selection reveal candidate genes involved in economic traits and cold acclimation in five Swedish cattle breeds

Cited by 53 publications

References 124 publications

Population differentiated copy number variation of Bos taurus, Bos indicus and their African hybrids

Population differentiated copy number variation of Bos taurus, Bos indicus and their African hybrids

Genome-Wide Scanning for Signatures of Selection Revealed the Putative Genomic Regions and Candidate Genes Controlling Milk Composition and Coat Color Traits in Sahiwal Cattle

Shared Ancestry and Signatures of Recent Selection in Gotland Sheep

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