scholarly journals Genome-wide selection signatures detection in Shanghai Holstein cattle population identified genes related to adaption, health and reproduction traits

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Dengying Liu ◽  
Zhenliang Chen ◽  
Wei Zhao ◽  
Longyu Guo ◽  
Hao Sun ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Artificial Selection ◽  
Sequence Data ◽  
Holstein Cattle ◽  
Cattle Population ◽  
Economic Traits ◽  
Selection Signatures ◽  
Wide Range ◽  
Candidate Regions ◽  
Genomic Regions

Abstract Background Over several decades, a wide range of natural and artificial selection events in response to subtropical environments, intensive pasture and intensive feedlot systems have greatly changed the customary behaviour, appearance, and important economic traits of Shanghai Holstein cattle. In particular, the longevity of the Shanghai Holstein cattle population is generally short, approximately the 2nd to 3rd lactation. In this study, two complementary approaches, integrated haplotype score (iHS) and runs of homozygosity (ROH), were applied for the detection of selection signatures within the genome using genotyping by genome-reduced sequence data from 1092 cows. Results In total, 101 significant iHS genomic regions containing selection signatures encompassing a total of 256 candidate genes were detected. There were 27 significant |iHS| genomic regions with a mean |iHS| score > 2. The average number of ROH per individual was 42.15 ± 25.47, with an average size of 2.95 Mb. The length of 78 % of the detected ROH was within the range of 1–2 MB and 2–4 MB, and 99 % were shorter than 8 Mb. A total of 168 genes were detected in 18 ROH islands (top 1 %) across 16 autosomes, in which each SNP showed a percentage of occurrence > 30 %. There were 160 and 167 genes associated with the 52 candidate regions within health-related QTL intervals and 59 candidate regions within reproduction-related QTL intervals, respectively. Annotation of the regions harbouring clustered |iHS| signals and candidate regions for ROH revealed a panel of interesting candidate genes associated with adaptation and economic traits, such as IL22RA1, CALHM3, ITGA9, NDUFB3, RGS3, SOD2, SNRPA1, ST3GAL4, ALAD, EXOSC10, and MASP2. In a further step, a total of 1472 SNPs in 256 genes were matched with 352 cis-eQTLs in 21 tissues and 27 trans-eQTLs in 6 tissues. For SNPs located in candidate regions for ROH, a total of 108 cis-eQTLs in 13 tissues and 4 trans-eQTLs were found for 1092 SNPs. Eighty-one eGenes were significantly expressed in at least one tissue relevant to a trait (P value < 0.05) and matched the 256 genes detected by iHS. For the 168 significant genes detected by ROH, 47 gene-tissue pairs were significantly associated with at least one of the 37 traits. Conclusions We provide a comprehensive overview of selection signatures in Shanghai Holstein cattle genomes by combining iHS and ROH. Our study provides a list of genes associated with immunity, reproduction and adaptation. For functional annotation, the cGTEx resource was used to interpret SNP-trait associations. The results may facilitate the identification of genes relevant to important economic traits and can help us better understand the biological processes and mechanisms affected by strong ongoing natural or artificial selection in livestock populations.

scholarly journals Shared Ancestry and Signatures of Recent Selection in Gotland Sheep

Genes ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 433
Author(s):  
Seyed Mohammad Ghoreishifar ◽  
Christina Marie Rochus ◽  
Sima Moghaddaszadeh-Ahrabi ◽  
Pourya Davoudi ◽  
Siavash Salek Ardestani ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Growth Traits ◽  
Significant Snps ◽  
P Value ◽  
Economic Traits ◽  
Selection Signatures ◽  
Shared Ancestry ◽  
The Baltic ◽  
Genomic Regions ◽  
Recent Selection

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.

scholarly journals Detection and evaluation of selection signatures in sheep

2018 ◽  
Vol 53 (5) ◽  
pp. 527-539 ◽  
Author(s):  
Tiago do Prado Paim ◽  
Patrícia Ianella ◽  
Samuel Rezende Paiva ◽  
Alexandre Rodrigues Caetano ◽  
Concepta Margaret McManus Pimentel
Keyword(s):  
Statistical Methods ◽  
Phenotypic Diversity ◽  
Selection Process ◽  
Genomic Data ◽  
Research Field ◽  
Economic Traits ◽  
Selection Signatures ◽  
Important Species ◽  
Challenges And Opportunities ◽  
Genomic Regions

Abstract: The recent development of genome-wide single nucleotide polymorphism (SNP) arrays made it possible to carry out several studies with different species. The selection process can increase or reduce allelic (or genic) frequencies at specific loci in the genome, besides dragging neighboring alleles in the chromosome. This way, genomic regions with increased frequencies of specific alleles are formed, caracterizing selection signatures or selective sweeps. The detection of these signatures is important to characterize genetic resources, as well as to identify genes or regions involved in the control and expression of important production and economic traits. Sheep are an important species for theses studies as they are dispersed worldwide and have great phenotypic diversity. Due to the large amounts of genomic data generated, specific statistical methods and softwares are necessary for the detection of selection signatures. Therefore, the objectives of this review are to address the main statistical methods and softwares currently used for the analysis of genomic data and the identification of selection signatures; to describe the results of recent works published on selection signatures in sheep; and to discuss some challenges and opportunities in this research field.

scholarly journals Genome-Wide Runs of Homozygosity, Effective Population Size, and Detection of Positive Selection Signatures in Six Chinese Goat Breeds

Genes ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 938 ◽  
Author(s):  
Islam ◽  
Li ◽  
Liu ◽  
Berihulay ◽  
Abied ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Genetic Differentiation ◽  
Positive Selection ◽  
Candidate Genes ◽  
Runs Of Homozygosity ◽  
Selection Signatures ◽  
Effective Population ◽  
Signature Of Selection ◽  
Genomic Regions ◽  
Insight Into

: Detection of selection footprints provides insight into the evolution process and the underlying mechanisms controlling the phenotypic diversity of traits that have been exposed to selection. Selection focused on certain characters, mapping certain genomic regions often shows a loss of genetic diversity with an increased level of homozygosity. Therefore, the runs of homozygosity (ROHs), homozygosity by descent (HBD), and effective population size (Ne) are effective tools for exploring the genetic diversity, understanding the demographic history, foretelling the signature of directional selection, and improving the breeding strategies to use and conserve genetic resources. We characterized the ROH, HBD, Ne, and signature of selection of six Chinese goat populations using single nucleotide polymorphism (SNP) 50K Illumina beadchips. Our results show an inverse relationship between the length and frequency of ROH. A long ROH length, higher level of inbreeding, long HBD segment, and smaller Ne in Guangfeng (GF) goats suggested intensive selection pressure and recent inbreeding in this breed. We identified six reproduction-related genes within the genomic regions with a high ROH frequency, of which two genes overlapped with a putative selection signature. The estimated pair-wise genetic differentiation (FST) among the populations is 9.60% and the inter- and intra-population molecular variations are 9.68% and 89.6%, respectively, indicating low to moderate genetic differentiation. Our selection signatures analysis revealed 54 loci harboring 86 putative candidate genes, with a strong signature of selection. Further analysis showed that several candidate genes, including MARF1, SYCP2, TMEM200C, SF1, ADCY1, and BMP5, are involved in goat fecundity. We identified 11 candidate genes by using cross-population extended haplotype homozygosity (XP-EHH) estimates, of which MARF1 and SF1 are under strong positive selection, as they are differentiated in high and low reproduction groups according to the three approaches used. Gene ontology enrichment analysis revealed that different biological pathways could be involved in the variation of fecundity in female goats. This study provides a new insight into the ROHs patterns for maintenance of within breed diversity and suggests a role of positive selection for genetic variation influencing fecundity in Chinese goat.

scholarly journals Identifying genomic regions and candidate genes selected during the breeding of rice in Vietnam

2021 ◽  
Author(s):  
Janet Higgins ◽  
Bruno Santos ◽  
Tran Dang Khanh ◽  
Khuat Huu Trung ◽  
Tran Duy Duong ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Continuous Improvement ◽  
Rice Genome ◽  
Selection Signatures ◽  
Genome Scanning ◽  
Selective Pressures ◽  
Rice Landraces ◽  
Rich Diversity ◽  
Genomic Regions ◽  
New Generation

Background and aims: Vietnam harnesses a rich diversity of rice landraces adapted to a broad range of conditions, which constitute a largely untapped source of genetic diversity for the continuous improvement of rice cultivars. We previously identified a strong population structure in Vietnamese rice, which is captured in five Indica and four Japonica subpopulations, including an outlying Indica-5 group. Here, we leveraged on that strong differentiation, and the 672 rice genomes generated, to identify genes within genomic regions putatively selected during domestication and breeding of rice in Vietnam. Methodology: We identified significant distorted patterns in allele frequency (XP-CLR method) and population differentiation scores (FST), resulting from differential selective pressures between native subpopulations, and compared them with QTLs previously identified by GWAS in the same panel. We particularly focused on the outlying Indica-5 subpopulation because of its likely novelty and differential evolution. Results: We identified selection signatures in each of the Vietnamese subpopulations and carried out a comprehensive annotation of the 52 regions selected in Indica-5, which represented 8.1% of the rice genome. We annotated the 4,576 genes in these regions, verified the overlap with QTLs identified in the same diversity panel and the comparison with a FST analysis between subpopulations, to select sixty-five candidate genes as promising breeding targets, several of which harboured alleles with non-synonymous substitutions. Conclusions: Our results highlight genomic differences between traditional Vietnamese landraces, which are likely the product of adaption to multiple environmental conditions and regional culinary preferences in a very diverse country. We also verified the applicability of this genome scanning approach to identify potential regions harbouring novel loci and alleles to breed a new generation of sustainable and resilient rice.

scholarly journals Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242200
Author(s):  
Natalia Anatolievna Zinovieva ◽  
Arsen Vladimirovich Dotsev ◽  
Alexander Alexandrovich Sermyagin ◽  
Tatiana Evgenievna Deniskova ◽  
Alexandra Sergeevna Abdelmanova ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Candidate Genes ◽  
High Density ◽  
Fixation Index ◽  
Nucleotide Polymorphism ◽  
Selection Signatures ◽  
Single Nucleotide ◽  
Cattle Breeds ◽  
Native Cattle ◽  
Genomic Regions

Native cattle breeds can carry specific signatures of selection reflecting their adaptation to the local environmental conditions and response to the breeding strategy used. In this study, we comprehensively analysed high-density single nucleotide polymorphism (SNP) genotypes to characterise the population structure and detect the selection signatures in Russian native Yaroslavl and Kholmogor dairy cattle breeds, which have been little influenced by introgression with transboundary breeds. Fifty-six samples of pedigree-recorded purebred animals, originating from different breeding farms and representing different sire lines, of the two studied breeds were genotyped using a genome-wide bovine genotyping array (Bovine HD BeadChip). Three statistical analyses—calculation of fixation index (FST) for each SNP for the comparison of the pairs of breeds, hapFLK analysis, and estimation of the runs of homozygosity (ROH) islands shared in more than 50% of animals—were combined for detecting the selection signatures in the genome of the studied cattle breeds. We confirmed nine and six known regions under putative selection in the genomes of Yaroslavl and Kholmogor cattle, respectively; the flanking positions of most of these regions were elucidated. Only two of the selected regions (localised on BTA 14 at 24.4–25.1 Mbp and on BTA 16 at 42.5–43.5 Mb) overlapped in Yaroslavl, Kholmogor and Holstein breeds. In addition, we detected three novel selection sweeps in the genome of Yaroslavl (BTA 4 at 4.74–5.36 Mbp, BTA 15 at 17.80–18.77 Mbp, and BTA 17 at 45.59–45.61 Mbp) and Kholmogor breeds (BTA 12 at 82.40–81.69 Mbp, BTA 15 at 16.04–16.62 Mbp, and BTA 18 at 0.19–1.46 Mbp) by using at least two of the above-mentioned methods. We expanded the list of candidate genes associated with the selected genomic regions and performed their functional annotation. We discussed the possible involvement of the identified candidate genes in artificial selection in connection with the origin and development of the breeds. Our findings on the Yaroslavl and Kholmogor breeds obtained using high-density SNP genotyping and three different statistical methods allowed the detection of novel putative genomic regions and candidate genes that might be under selection. These results might be useful for the sustainable development and conservation of these two oldest Russian native cattle breeds.

scholarly journals Identification of genomic regions and candidate genes for chicken meat ultimate pH by combined detection of selection signatures and QTL

BMC Genomics ◽  
2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Elisabeth Le Bihan-Duval ◽  
Christelle Hennequet-Antier ◽  
Cécile Berri ◽  
Stéphane A. Beauclercq ◽  
Marie Christine Bourin ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Chicken Meat ◽  
Selection Signatures ◽  
Genomic Regions ◽  
Combined Detection

scholarly journals Genome-wide scan for runs of homozygosity identifies potential candidate regions associated with growth traits in beef cattle

2020 ◽  
Author(s):  
Guoyao Zhao ◽  
Tianliu Zhang ◽  
Yuqiang Liu ◽  
Zezhao Wang ◽  
Lei Xu ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Growth Traits ◽  
Farm Animals ◽  
Valuable Insight ◽  
Potential Candidate ◽  
Cattle Population ◽  
Runs Of Homozygosity ◽  
Genome Wide ◽  
Candidate Regions

Abstract Background: Runs of homozygosity (ROH) are continuous homozygous regions that generally exist in the DNA sequence of diploid organisms. Identifications of regions of the genome lead to reduction in performance can provide valuable insight into the genetic architecture of complex traits. Here, we evaluated genome-wide patterns of homozygosity and their association with growth traits in a commercial beef cattle population.Results: We identified a total of 29,271 ROH segments with an average number of 63.36 and an average length of 0.98 Mb in this commercial beef cattle population, representing ~2.53% (~63.36Mb) of the genome. To evaluate the enrichment of ROH across genomes, we initially identified 280 ROH regions by merging ROH events identified across all individuals. Of these, nine regions were significantly associated with six growth phenotype traits (body height, chest circumference, fat coverage, backfat thickness, ribeye area, carcass length; P<0.01), which contain 187 candidate genes. Furthermore, we found 26 consensus ROH regions with frequencies exceeding 10%, and several of these consensus overlapped with QTLs which are associated with weight gain, calving difficulty and stillbirth. To precisely locate locus within each ROH for every studied trait, we further utilized loci-based methods for association analysis among these identified regions. Totally, we obtained 9,360 loci within ROH, and 1,631 loci displaying significant association (P<0.01) for eight traits. In addition, we found that 67 genes embedded with homozygous loci. Several identified candidate genes, including EBF2, SLC20A2, SH3BGRL2, HMGA1 and ACSL1, were related to growth traits.Conclusions: This study assessed genome-wide autozygosity pattern and inbreeding level in a commercial beef cattle population. Our study identified many candidate regions and genes with ROH for growth traits in beef cattle, which can provide important insights into investigating homozygosity across genome in other farm animals. Our findings may further be unitized to assist the design of selection mating strategy.

scholarly journals Deciphering signatures of natural selection via deep learning

2021 ◽  
Author(s):  
Xinghu Qin ◽  
Charleston W.K. Chiang ◽  
Oscar E Gaggiotti
Keyword(s):  
Deep Learning ◽  
Natural Selection ◽  
Quantitative Traits ◽  
Predictive Power ◽  
Spatial Location ◽  
Human Genetic Variation ◽  
Environmental Attributes ◽  
Wide Range ◽  
Candidate Regions ◽  
Genomic Regions

Identifying genomic regions influenced by natural selection provides fundamental insights into a wide range of problems including human health, animal and plant breeding, and the understanding of local adaptation. We propose a new method, DeepGenomeScan, that can be used to address all these problems. It is based on the principle that the genotypes of individuals can be used to predict any associated trait; not only their phenotype but also their spatial location or the environmental attributes of the habitat they live in. We, therefore,implemented a deep learning method to detect candidate regions under selection by identifying loci that contribute the most to the predictive power of the deep neural network. Using simulations, we show that our method can successfully identify loci underlying quantitative traits subject to complex spatial patterns of selection. We apply DeepGenomeScan to a European human genetic variation dataset and posit that the loci that contribute the most to the prediction of latitude and longitude are located in genomic regions under selection. Using this approach, we identified many SNPs located within well-known genes, some of which were not identified using existing population genetics approaches, e.g. MCM6, MGAT5, TMEM163.

scholarly journals Genome-Wide Analysis Reveals Selection Signatures Involved in Meat Traits and Local Adaptation in Semi-Feral Maremmana Cattle

2021 ◽  
Vol 12 ◽  
Author(s):  
Slim Ben-Jemaa ◽  
Gabriele Senczuk ◽  
Elena Ciani ◽  
Roberta Ciampolini ◽  
Gennaro Catillo ◽  
...  
Keyword(s):  
Muscle Development ◽  
Single Nucleotide Polymorphism Array ◽  
Reference Population ◽  
Selection Signatures ◽  
Genomic Signatures ◽  
Genome Wide ◽  
Parasite Infections ◽  
Breeding Schemes ◽  
Candidate Regions ◽  
Genomic Regions

The Maremmana cattle is an ancient Podolian-derived Italian breed raised in semi-wild conditions with distinctive morphological and adaptive traits. The aim of this study was to detect potential selection signatures in Maremmana using medium-density single nucleotide polymorphism array. Putative selection signatures were investigated combining three statistical approaches designed to quantify the excess of haplotype homozygosity either within (integrated haplotype score, iHS) or among pairs of populations (Rsb and XP-EHH), and contrasting the Maremmana with a single reference population composed of a pool of seven Podolian-derived Italian breeds. Overall, the three haplotype-based analyses revealed selection signatures distributed over 19 genomic regions. Of these, six relevant candidate regions were identified by at least two approaches. We found genomic signatures of selective sweeps spanning genes related to mitochondrial function, muscle development, growth, and meat traits (SCIN, THSD7A, ETV1, UCHL1, and MYOD1), which reflects the different breeding schemes between Maremmana (semi-wild conditions) and the other Podolian-derived Italian breeds (semi-extensive). We also identified several genes linked to Maremmana adaptation to the environment of the western-central part of Italy, known to be hyperendemic for malaria and other tick-borne diseases. These include several chemokine (C-C motif) ligand genes crucially involved in both innate and adaptive immune responses to intracellular parasite infections and other genes playing key roles in pulmonary disease (HEATR9, MMP28, and ASIC2) or strongly associated with malaria resistance/susceptibility (AP2B1). Our results provide a glimpse into diverse selection signatures in Maremmana cattle and can be used to enhance our understanding of the genomic basis of environmental adaptation in cattle.

scholarly journals Genomewide Mapping of Selection Signatures and Genes for Extreme Feather Pecking in Two Divergently Selected Laying Hen Lines

Animals ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 262 ◽  
Author(s):  
Hanna Iffland ◽  
Robin Wellmann ◽  
Markus Schmid ◽  
Siegfried Preuß ◽  
Jens Tetens ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Posterior Probability ◽  
Negative Binomial ◽  
Laying Hen ◽  
Chromosome 1 ◽  
Selection Signatures ◽  
Genomewide Association Study ◽  
Feather Pecking ◽  
Binomial Distributions ◽  
Genomic Regions

Feather pecking (FP) is a longstanding serious problem in commercial flocks of laying hens. It is a highly polygenic trait and the genetic background is still not completely understood. In order to find genomic regions influencing FP, selection signatures between laying hen lines divergently selected for high and low feather pecking were mapped using the intra-population iHS and the inter-population FST approach. In addition, the existence of an extreme subgroup of FP hens (EFP) across both selected lines has been demonstrated by fitting a mixture of negative binomial distributions to the data and calculating the posterior probability of belonging to the extreme subgroup (pEFP) for each hen. A genomewide association study (GWAS) was performed for the traits pEFP and FP delivered (FPD) with a subsequent post GWAS analysis. Mapping of selection signatures revealed no clear regions under selection. GWAS revealed a region on Chromosome 1, where the existence of a QTL influencing FP is likely. The candidate genes found in this region are a part of the GABAergic system, which has already been linked to FP in previous studies. Despite the polygenic nature of FP, selection on these candidate genes may reduce FP.

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