scholarly journals Genotype-by-environment interactions for reproduction, body composition, and growth traits in maternal-line pigs based on single-step genomic reaction norms

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Shi-Yi Chen ◽  
Pedro H. F. Freitas ◽  
Hinayah R. Oliveira ◽  
Sirlene F. Lázaro ◽  
Yi Jian Huang ◽  
...  
Keyword(s):  
Body Composition ◽  
Candidate Genes ◽  
X Chromosome ◽  
Reaction Norm ◽  
Single Step ◽  
Residual Variance ◽  
Large White ◽  
Maternal Line ◽  
Genotype By Environment ◽  
Genomic Regions

Abstract Background There is an increasing need to account for genotype-by-environment (G × E) interactions in livestock breeding programs to improve productivity and animal welfare across environmental and management conditions. This is even more relevant for pigs because selection occurs in high-health nucleus farms, while commercial pigs are raised in more challenging environments. In this study, we used single-step homoscedastic and heteroscedastic genomic reaction norm models (RNM) to evaluate G × E interactions in Large White pigs, including 8686 genotyped animals, for reproduction (total number of piglets born, TNB; total number of piglets born alive, NBA; total number of piglets weaned, NW), growth (weaning weight, WW; off-test weight, OW), and body composition (ultrasound muscle depth, MD; ultrasound backfat thickness, BF) traits. Genetic parameter estimation and single-step genome-wide association studies (ssGWAS) were performed for each trait. Results The average performance of contemporary groups (CG) was estimated and used as environmental gradient in the reaction norm analyses. We found that the need to consider heterogeneous residual variance in RNM models was trait dependent. Based on estimates of variance components of the RNM slope and of genetic correlations across environmental gradients, G × E interactions clearly existed for TNB and NBA, existed for WW but were of smaller magnitude, and were not detected for NW, OW, MD, and BF. Based on estimates of the genetic variance explained by the markers in sliding genomic windows in ssGWAS, several genomic regions were associated with the RNM slope for TNB, NBA, and WW, indicating specific biological mechanisms underlying environmental sensitivity, and dozens of novel candidate genes were identified. Our results also provided strong evidence that the X chromosome contributed to the intercept and slope of RNM for litter size traits in pigs. Conclusions We provide a comprehensive description of G × E interactions in Large White pigs for economically-relevant traits and identified important genomic regions and candidate genes associated with GxE interactions on several autosomes and the X chromosome. Implementation of these findings will contribute to more accurate genomic estimates of breeding values by considering G × E interactions, in order to genetically improve the environmental robustness of maternal-line pigs.

scholarly journals Genotype-by-environment interaction in Holstein heifer fertility traits using single-step genomic reaction norm models

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rui Shi ◽  
Luiz Fernando Brito ◽  
Aoxing Liu ◽  
Hanpeng Luo ◽  
Ziwei Chen ◽  
...  
Keyword(s):  
Heat Stress ◽  
Dairy Cattle ◽  
Candidate Genes ◽  
Heat Tolerance ◽  
Reaction Norm ◽  
Single Step ◽  
Conception Rate ◽  
Critical Periods ◽  
Genotype By Environment ◽  
Fertility Traits

Abstract Background The effect of heat stress on livestock production is a worldwide issue. Animal performance is influenced by exposure to harsh environmental conditions potentially causing genotype-by-environment interactions (G × E), especially in highproducing animals. In this context, the main objectives of this study were to (1) detect the time periods in which heifer fertility traits are more sensitive to the exposure to high environmental temperature and/or humidity, (2) investigate G × E due to heat stress in heifer fertility traits, and, (3) identify genomic regions associated with heifer fertility and heat tolerance in Holstein cattle. Results Phenotypic records for three heifer fertility traits (i.e., age at first calving, interval from first to last service, and conception rate at the first service) were collected, from 2005 to 2018, for 56,998 Holstein heifers raised in 15 herds in the Beijing area (China). By integrating environmental data, including hourly air temperature and relative humidity, the critical periods in which the heifers are more sensitive to heat stress were located in more than 30 days before the first service for age at first calving and interval from first to last service, or 10 days before and less than 60 days after the first service for conception rate. Using reaction norm models, significant G × E was detected for all three traits regarding both environmental gradients, proportion of days exceeding heat threshold, and minimum temperature-humidity index. Through single-step genome-wide association studies, PLAG1, AMHR2, SP1, KRT8, KRT18, MLH1, and EOMES were suggested as candidate genes for heifer fertility. The genes HCRTR1, AGRP, PC, and GUCY1B1 are strong candidates for association with heat tolerance. Conclusions The critical periods in which the reproductive performance of heifers is more sensitive to heat stress are trait-dependent. Thus, detailed analysis should be conducted to determine this particular period for other fertility traits. The considerable magnitude of G × E and sire re-ranking indicates the necessity to consider G × E in dairy cattle breeding schemes. This will enable selection of more heat-tolerant animals with high reproductive efficiency under harsh climatic conditions. Lastly, the candidate genes identified to be linked with response to heat stress provide a better understanding of the underlying biological mechanisms of heat tolerance in dairy cattle.

scholarly journals Genotype-by-environment Interaction in Holstein Heifer Fertility Traits using Single-step Genomic Reaction Norm Models

2020 ◽  
Author(s):  
Rui Shi ◽  
Luiz Brito ◽  
Aoxing Liu ◽  
Hanpeng Luo ◽  
Ziwei Chen ◽  
...  
Keyword(s):  
Heat Stress ◽  
Candidate Genes ◽  
Heat Tolerance ◽  
Reaction Norm ◽  
Single Step ◽  
Conception Rate ◽  
Critical Periods ◽  
Age At First Calving ◽  
Genotype By Environment ◽  
Fertility Traits

Abstract Background: The effect of heat stress on livestock production is a worldwide issue, where animal performance is influenced by exposure to high environmental temperatures, indicating the existence of possible genotype-by-environment interactions (G´E). The main objectives of this study were to (1) detect the time periods in which heifer fertility traits are more sensitive to the exposure to high environmental temperature and/or humidity, (2) investigate G´E due to heat stress in heifer fertility traits, and (3) identify genomic regions associated with heifer fertility and heat stress in Holstein cattle. Results: Phenotypic records for three heifer fertility traits (i.e., age at first calving, interval from first to last service, and conception rate at the first service) were collected, from 2005 to 2018, for 56,998 Holstein heifers raised in 15 herds in the Beijing area (China). By integrating environmental data including hourly air temperature and relative humidity, the critical periods in which the heifers are more sensitive to heat stress were defined as <=30 days before the first service for age at first calving and interval from first to last service, or 10 days before and <= 60 days after the first service for conception rate. Using reaction norm models, significant G´E was detected for all three traits regarding both environmental gradients, proportion of days exceeding heat threshold and minimum temperature humidity index. Through single-step genome-wide association study, PLAG1, AMHR2, SP1, KRT8, KRT18, MLH1, and EOMES were suggested as candidate genes for heifer fertility while HCRTR1, AGRP, PC, and GUCY1B1 were for heat tolerance. Conclusions: The critical periods in which reproductive perfromances of heifers are more sensitive to heat stress are trait-dependent. Thus, detailed analysis should be conducted to determine this particular period for other fertility traits. The considerable magnitude of G´E and sire re-ranking indicates the necessity to consider G´E in breeding schemes. This will enable selection of more heat-tolerant animals with high reproductive efficiency under harsh climatic conditions. The candidate genes identified to be linked with response to heat stress provide a better understanding of the underlying biological mechanisms of heat tolerance in dairy cattle.

scholarly journals Genotype-by-environment interaction of fertility traits in Danish Holstein cattle using a single-step genomic reaction norm model

Heredity ◽  
2019 ◽  
Vol 123 (2) ◽  
pp. 202-214 ◽  
Author(s):  
Zhe Zhang ◽  
Morten Kargo ◽  
Aoxing Liu ◽  
Jørn Rind Thomasen ◽  
Yuchun Pan ◽  
...  
Keyword(s):  
Reaction Norm ◽  
Genotype By Environment Interaction ◽  
Single Step ◽  
Holstein Cattle ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Norm Model ◽  
Fertility Traits

scholarly journals Genome-wide Association Study for Carcass Primal Cut Yields Using Single-step Bayesian Approach in Hanwoo Cattle

2021 ◽  
Vol 12 ◽  
Author(s):  
Masoumeh Naserkheil ◽  
Hossein Mehrban ◽  
Deukmin Lee ◽  
Mi Na Park
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Trait Loci ◽  
Genomic Regions ◽  
Hanwoo Cattle

The importance of meat and carcass quality is growing in beef cattle production to meet both producer and consumer demands. Primal cut yields, which reflect the body compositions of carcass, could determine the carcass grade and, consequently, command premium prices. Despite its importance, there have been few genome-wide association studies on these traits. This study aimed to identify genomic regions and putative candidate genes related to 10 primal cut traits, including tenderloin, sirloin, striploin, chuck, brisket, top round, bottom round, shank, flank, and rib in Hanwoo cattle using a single-step Bayesian regression (ssBR) approach. After genomic data quality control, 43,987 SNPs from 3,745 genotyped animals were available, of which 3,467 had phenotypic records for the analyzed traits. A total of 16 significant genomic regions (1-Mb window) were identified, of which five large-effect quantitative trait loci (QTLs) located on chromosomes 6 at 38–39 Mb, 11 at 21–22 Mb, 14 at 6–7 Mb and 26–27 Mb, and 19 at 26–27 Mb were associated with more than one trait, while the remaining 11 QTLs were trait-specific. These significant regions were harbored by 154 genes, among which TOX, FAM184B, SPP1, IBSP, PKD2, SDCBP, PIGY, LCORL, NCAPG, and ABCG2 were noteworthy. Enrichment analysis revealed biological processes and functional terms involved in growth and lipid metabolism, such as growth (GO:0040007), muscle structure development (GO:0061061), skeletal system development (GO:0001501), animal organ development (GO:0048513), lipid metabolic process (GO:0006629), response to lipid (GO:0033993), metabolic pathways (bta01100), focal adhesion (bta04510), ECM–receptor interaction (bta04512), fat digestion and absorption (bta04975), and Rap1 signaling pathway (bta04015) being the most significant for the carcass primal cut traits. Thus, identification of quantitative trait loci regions and plausible candidate genes will aid in a better understanding of the genetic and biological mechanisms regulating carcass primal cut yields.

scholarly journals Single-step genome-wide association studies (GWAS) and post-GWAS analyses to identify genomic regions and candidate genes for milk yield in Brazilian Girolando cattle

2020 ◽  
Vol 103 (11) ◽  
pp. 10347-10360
Author(s):  
Pamela I. Otto ◽  
Simone E.F. Guimarães ◽  
Mario P.L. Calus ◽  
Jeremie Vandenplas ◽  
Marco A. Machado ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Milk Yield ◽  
Association Studies ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Genomic Regions

scholarly journals Single-step genome-wide association study for resistance toPiscirickettsia salmonisin rainbow trout (Oncorhynchus mykiss)

2019 ◽  
Author(s):  
Rodrigo Marín-Nahuelpi ◽  
Agustín Barría ◽  
Pablo Cáceres ◽  
María E. López ◽  
Liane N. Bassini ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Oncorhynchus Mykiss ◽  
Candidate Genes ◽  
Genetic Improvement ◽  
Genetic Variance ◽  
Snp Array ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Genomic Regions

ABSTRACTOne of the main pathogens affecting rainbow trout (Oncorhynchus mykiss) farming is the facultative intracellular bacteriaPiscirickettsia salmonis. Current treatments, such as antibiotics and vaccines, have not had the expected effectiveness in field conditions. Genetic improvement by means of selection for resistance is proposed as a viable alternative for control. Genomic information can be used to identify the genomic regions associated with resistance and enhance the genetic evaluation methods to speed up the genetic improvement for the trait. The objectives of this study were to i) identify the genomic regions associated with resistance toP. salmonis; and ii) identify candidate genes associated with the trait. We experimentally challenged 2,130 rainbow trout withP. salmonisand genotyped them with a 57 K SNP array. Resistance toP. salmoniswas defined as time to death (TD) and as binary survival (BS). Significant heritabilities were estimated for TD and BS (0.48 ± 0.04 and 0.34 ± 0.04, respectively). A total of 2,047 fish and 26,068 SNPs passed quality control for samples and genotypes. Using a single-step genome wide association analysis (ssGWAS) we identified four genomic regions explaining over 1% of the genetic variance for TD and three for BS. Interestingly, the same genomic region located onOmy27was found to explain the highest proportion of genetic variance for both traits (2.4 and 1.5% for TD and BS, respectively). The identified SNP in this region is located within an exon of a gene related with actin cytoskeletal organization, a protein exploited byP. salmonisduring infection. Other important candidate genes identified are related with innate immune response and oxidative stress. The moderate heritability values estimated in the present study show it is possible to improve resistance toP. salmonisthrough artificial selection in the current rainbow trout population. Furthermore, our results suggest a polygenic genetic architecture and provide novel insights into the candidate genes underpinning resistance toP. salmonisinO. mykiss.

40 Novel Genomic Regions Associated with Igg Antibody Response to PRRSV Vaccination Revealed by Haplotype-based GWAS

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 31-32
Author(s):  
Leticia P Sanglard ◽  
Yijian Huang ◽  
Kent A Gray ◽  
Daniel Linhares ◽  
Jack C Dekkers ◽  
...  
Keyword(s):  
Antibody Response ◽  
Candidate Genes ◽  
Genetic Variance ◽  
Genome Wide Association Study ◽  
Chromosome 7 ◽  
Respiratory Syndrome Virus ◽  
Igg Antibody ◽  
Large White ◽  
Genomic Study ◽  
Genomic Regions

Abstract Previous studies on genomics of antibody response, measured as sample-to-positive (S/P) ratio, to Porcine Reproductive and Respiratory Syndrome virus (PRRSV) have reported a major quantitative trait locus (QTL) on the major histocompatibility complex (MHC) on chromosome 7, explaining ~25% of the genetic variance of this trait. S/P ratio following modified live PRRSV vaccination in crossbred commercial gilts has been proposed as genetic indicator for reproductive performance in non-infected purebred sows and PRRSV-vaccinated crossbred sows. This motivated further genomic study for this trait by performing haplotype-based genome-wide association study (GWAS). 906 naïve F1 (Landrace x Large White) had blood samples taken at ~50d after vaccination for measuring PRRSV ELISA S/P ratio and genotyping. Haplotype-based GWAS identified 8 genomic regions on chromosomes 4 (108 Mb), 7 (15, 21, and 24–27 Mb), and 9 (33 Mb) that were associated (q-value &lt; 0.07) with S/P ratio. From those, only the MHC region (chromosome 7; 24 – 26 Mb) had been identified in the SNP based GWAS. The main SNP identified in the SNP based GWAS (H3GA0020505) was not in LD with the haplotype; thus, we added this SNP to the haplotype model. We observed that the haplotype explained more of the genetic variance compared to the H3GA0020505 SNP, indicating that the MHC haplotype is in stronger LD with the QTL than the H3GA0020505 SNP. All the significant regions associated with S/P ratio included immune-related candidate genes, such as SLA-DOB, TAP2, TAPBP, TMIGD3, and ADORA. This study validated the QTL identified on the MHC region, narrowing the search for causal genes in this region, and identified new genomic regions, along with candidate genes associated with S/P ratio. Identifying novel genomic regions provides more resources for marker-assisted selection and genomic prediction of S/P ratio in purebred and commercial pig populations.

scholarly journals 210 Genotype by environment interaction for pre-weaning survival in commercial crossbred pigs

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 40-41
Author(s):  
Francesco Tiezzi ◽  
Justin Fix ◽  
Clint Schwab
Keyword(s):  
Fixed Effects ◽  
Genotype By Environment Interaction ◽  
Single Step ◽  
Random Regression ◽  
Residual Variance ◽  
Phenotypic Variance ◽  
Environment Interaction ◽  
Genomic Breeding ◽  
Genotype By Environment ◽  
The Impact

Abstract Pre-weaning survival (PWS) is a trait of major importance in swine productions systems. Selection is made difficult by the low heritability of the trait(s) and genotype by environment interaction (GxE) could be present. In addition to that, given the binary nature of the trait, phenotypic variance is virtually null in contemporary group where PWS is large. The objective of this study was to assess the impact of heterogeneous phenotypic variance and GxE on PWS. We used survival to day 5 as a trait of interest, available for 574,828 crossbred piglets raised in a commercial environment. Piglets were progeny of 559 sires (450 genotyped with 60k SNP chip) and raised into 242 contemporary groups (CG). In estimating GxE, the E component was represented by fourth-order Legendre polynomials built on the CG solutions. A Single-Step random-regression sire model with heterogeneous residuals (10 classes) was used, once the CG solutions were obtained by a similar model that neglected GxE. Other (fixed) effects in the models were sow parity, litter size, litter transfer of the piglet, gender of the piglet, dam genetic line and litter (random). Results show an increase in phenotypic and residual variance as PWS decreased, which is expected given the nature of the binary trait. Genetic variance increased following the same trend, which made heritability to be constant (~2%). Genomic breeding values for most represented sires were plotted as a function of CG survival. While no variation among the sires can be found in CG with full survival, larger variance is shown as PWS decreases. Re-ranking among the sires is present as CG change. Results suggest that modeling PWS should account for the heterogeneous variance among CG. A moderate GxE in PWS at day 5 is also suggested.

scholarly journals Identifying SNPs and candidate genes for three litter traits using single-step GWAS across six parities in Landrace and Large White pigs

2018 ◽  
Vol 50 (12) ◽  
pp. 1026-1035 ◽  
Author(s):  
Pingxian Wu ◽  
Kai Wang ◽  
Qiang Yang ◽  
Jie Zhou ◽  
Dejuan Chen ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Major Effect ◽  
Single Step ◽  
Nucleotide Polymorphisms ◽  
Large White ◽  
Gene Effects ◽  
Single Nucleotide ◽  
Litter Traits ◽  
Interesting Candidate ◽  
Major Factors

Total number born (TNB), number born alive (NBA), and litter weight born alive (LWB) are critically important traits in pig production. The sow’s parity is one of the major factors influencing litter traits. Because of monogenic or polygenic contributions and the presence of temporal gene effects in different sows’ parities, it is difficult to clarify the biological and genetic background. To systematically explore the genetic mechanism of litter traits, we conducted 18 GWASs using single-step GWAS (ssGWAS) based on two breeds (908 Landrace and 1,130 Large White sow litter records) for each litter trait in different parities. A total of 300 Landrace and 300 Large White sows were genotyped by sequencing (GBS). ssGWAS was performed separately for each breed and each parity due to population stratification and temporal gene effect. In summary, we identified 80 (15 for Landrace and 65 for Large White), 227 (52 for Landrace, 175 for Large White), and 187 (34 for Landrace, 153 for Large White) single nucleotide polymorphisms (SNPs) affecting TNB, NBA, and LWB, respectively. Of them, we suggest that a total of 22 loci (SSC1: 125098202, SSC1: 117560058, SSC14: 147794697, SSC8: 84823302, SSC9: 143554876, and SSC9: 138766097 for Landrace; SSC1: 4023577, SSC1: 3859573, SSC1: 4891063, SSC16: 5197665, SSC10: 32050819, SSC13: 13552924, SSC13: 92819, SSC17: 3579607, SSC13: 196698221, SSC7: 30918403, SSC16: 46221484, SSC16: 46169204, SSC2: 41988642, SSC2: 44475457, SSC2: 42521875, and SSC7: 58411951 for Large White) are shared by TNB, NBA, and LWB. These results indicate the existence of gene temporal effect in each parity. Furthermore, our findings suggest four interesting candidate genes (FBXL7, ALDH1A2, LEPR, and DDX1) associated with litter traits in different parities that have a major effect on embryonic development progression. In conclusion, 22 crucial SNPs and four interesting candidate genes were identified for three litter traits across six parities. These findings advance our understanding of the genetic architecture of litter traits and confirm the presence of temporal gene effects in different parities. Importantly, functional validation studies for findings of particular interest are recommended in litter traits.

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