scholarly journals Genome-wide association analysis with a 50K transcribed gene SNP-chip identifies QTL affecting muscle yield in rainbow trout

2018 ◽  
Author(s):  
Mohamed Salem ◽  
Rafet Al-Tobasei ◽  
Ali Ali ◽  
Daniela Lourenco ◽  
Guangtu Gao ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Muscle Development ◽  
Genetic Variance ◽  
Cold Water ◽  
Additive Genetic Variance ◽  
Genome Wide Association ◽  
Production Traits ◽  
Significant Qtls ◽  
Snp Chip ◽  
Genome Wide

AbstractDetection of coding/functional SNPs that change the biological function of a gene may lead to identification of putative causative alleles within QTL regions and discovery of genetic markers with large effects on phenotypes. Two bioinformatics pipelines, GATK and SAMtools, were used to identify ~21K transcribed SNPs with allelic imbalances associated with important aquaculture production traits including body weight, muscle yield, muscle fat content, shear force, and whiteness in addition to resistance/susceptibility to bacterial cold-water disease (BCWD). SNPs were identified from pooled RNA-Seq data collected from ~620 fish, representing 98 families from growth- and 54 families from BCWD-selected lines with divergent phenotypes. In addition, ~29K transcribed SNPs without allelic-imbalances were strategically added to build a 50K Affymetrix SNP-chip. SNPs selected included two SNPs per gene from 14K genes and ~5K non-synonymous SNPs. The SNP-chip was used to genotype 1728 fish. The average SNP calling-rate for samples passing quality control (QC; 1,641 fish) was ≥ 98.5%. Genome-wide association (GWA) study on 878 fish (representing 197 families from 2 consecutive generations) with muscle yield phenotypes and genotyped for 35K polymorphic markers (passing QC) identified several QTL regions explaining together up to 28.40% of the additive genetic variance for muscle yield in this rainbow trout population. The most significant QTLs were on chromosomes 14 and 16 with 12.71% and 10.49% of the genetic variance, respectively. Many of the annotated genes in the QTL regions were previously reported as important regulators of muscle development and cell signaling. No major QTLs were identified in a previous GWA study using a 57K genomic SNP chip on the same fish population. These results indicate improved detection power of the transcribed gene SNP-chip in the target trait and population, allowing identification of large-effect QTLs for important traits in rainbow trout.

scholarly journals A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana

2014 ◽  
Author(s):  
Jennifer Lachowiec ◽  
Xia Shen ◽  
Christine Queitsch ◽  
Örjan Carlborg
Keyword(s):  
Arabidopsis Thaliana ◽  
Candidate Genes ◽  
Root Length ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Broad Sense ◽  
Genome Wide Association ◽  
Broad Sense Heritability ◽  
Narrow Sense ◽  
Genome Wide

Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the narrow-sense heritability for this trait was statistically zero. This low additive genetic variance likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, the broad-sense heritability for root length was significantly larger, and we therefore also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. This analysis revealed four interacting pairs involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. Explorations of the genotype-phenotype maps for these pairs revealed that the detected epistasis cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. In summary, statistical epistatic analyses were found to be indispensable for confirming known, and identifying several new, functional candidate genes for root length using a population of wild-collected A. thaliana accessions. We also illustrated how epistatic cancellation of the additive genetic variance resulted in an insignificant narrow-sense, but significant broad-sense heritability that could be dissected into the contributions of several individual loci using a combination of careful statistical epistatic analyses and functional genetic experiments.

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.

scholarly journals Genome-wide identification of loci associated with growth in rainbow trout

2020 ◽  
Author(s):  
Ali Ali ◽  
Rafet Al-Tobasei ◽  
Daniela Lourenco ◽  
Tim Leeds ◽  
Brett Kenney ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Additive Genetic Variance ◽  
Chromatin Modification ◽  
Bodyweight Gain ◽  
Single Step ◽  
Production Traits ◽  
Phenotypic Data ◽  
Developmental Processes ◽  
Genome Wide ◽  
A Genome

Abstract Background Growth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout. Results A previously developed 50K gene-transcribed SNP chip, containing ~21K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a single-marker GWA analysis, 33 SNPs were identified in association with bodyweight gain. The highest SNP explaining variation in bodyweight gain was identified in a gene coding for thrombospondin-1 (THBS1) (R 2 = 0.09). Conclusion The majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.

scholarly journals Genome-wide identification of loci associated with growth in rainbow trout

2020 ◽  
Author(s):  
Ali Ali ◽  
Rafet Al-Tobasei ◽  
Daniela Lourenco ◽  
Tim Leeds ◽  
Brett Kenney ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Additive Genetic Variance ◽  
Chromatin Modification ◽  
Bodyweight Gain ◽  
Single Step ◽  
Production Traits ◽  
Phenotypic Data ◽  
Developmental Processes ◽  
Genome Wide ◽  
A Genome

Abstract Background: Growth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout. Results: A previously developed 50K gene-transcribed SNP chip, containing ~21K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a single-marker GWA analysis, 33 SNPs were identified in association with bodyweight gain. The highest SNP explaining variation in bodyweight gain was identified in a gene coding for thrombospondin-1 (THBS1) (R2 = 0.09). Conclusion: The majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.

scholarly journals Genome-wide Association Studies Reveal Similar Genetic Architecture with Shared and Unique QTL for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations

2017 ◽  
Author(s):  
Roger L. Vallejo ◽  
Guangtu Gao ◽  
Sixin Liu ◽  
Breno O. Fragomeni ◽  
Alvaro G. Hernandez ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Cold Water ◽  
Association Studies ◽  
Snp Array ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Bacterial Cold Water Disease ◽  
Breeding Populations ◽  
Genome Wide ◽  
Two Populations

ABSTRACTBacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect QTL for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57K SNP array and a genome physical map have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered.

scholarly journals Genome-wide association analysis for resistance to infectious pancreatic necrosis virus identifies candidate genes involved in viral replication and immune response in rainbow trout (Oncorhynchus mykiss)

2019 ◽  
Author(s):  
Francisco H. Rodríguez ◽  
Raúl Flores-Mara ◽  
Grazyella M. Yoshida ◽  
Agustín Barría ◽  
Ana M. Jedlicki ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Genetic Variance ◽  
Pancreatic Necrosis ◽  
Infectious Pancreatic Necrosis Virus ◽  
Genome Wide Association ◽  
Genomic Information ◽  
Necrosis Virus ◽  
Genome Wide ◽  
Infectious Pancreatic Necrosis ◽  
Pancreatic Necrosis Virus

ABSTRACTInfectious pancreatic necrosis (IPN) is a viral disease with considerable negative impact on the rainbow trout (Oncorhynchus mykiss) aquaculture industry. The aim of the present work was to detect genomic regions that explain resistance to infectious pancreatic necrosis virus (IPNV) in rainbow trout. A total of 2,278 fish from 58 full-sib families were challenged with IPNV. Of the challenged fish, 768 individuals were genotyped (488 resistant and 280 susceptible), using a 57K single nucleotide polymorphisms (SNPs) panel Axiom®, Affymetrix®. A genome-wide association study (GWAS) was performed using the phenotypes time to death (TD) and binary survival (BS), along with the genotypes of the challenged fish using a Bayesian model (Bayes C). Heritabilities for resistance to IPNV estimated using pedigree information, were 0.39 and 0.32 for TD and BS, respectively. Heritabilities for resistance to IPNV estimated using genomic information, were 0.50 and 0.54 for TD and BS, respectively. The Bayesian GWAS detected a SNP located on chromosome 5 explaining 18% of the genetic variance for TD. A SNP located on chromosome 23 was detected explaining 9% of the genetic variance for BS. The proximity of Sentrin-specific protease 5 (SENP5) to a significant SNP makes it a candidate gene for resistance against IPNV. However, the moderate-low proportion of variance explained by the detected marker leads to the conclusion that the incorporation of all genomic information, through genomic selection, would be the most appropriate approach to accelerate genetic progress for the improvement of resistance against IPNV in rainbow trout.

scholarly journals Genome-wide identification of loci associated with growth in rainbow trout

2019 ◽  
Author(s):  
Ali Ali ◽  
Rafet Al-Tobasei ◽  
Daniela Lourenco ◽  
Tim Leeds ◽  
Brett Kenney ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Additive Genetic Variance ◽  
Chromatin Modification ◽  
Bodyweight Gain ◽  
Single Step ◽  
Production Traits ◽  
Phenotypic Data ◽  
Developmental Processes ◽  
Genome Wide ◽  
A Genome

Abstract Background Growth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout. Results A previously developed 50K gene-transcribed SNP chip, containing ~21K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a single-marker GWA analysis, 46 SNPs were identified in association with bodyweight gain. The highest SNP associated with this trait was identified in a gene coding for thrombospondin-1 (THBS1) (R 2 = 0.09). Conclusion The majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.

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