Co-localization of growth QTL with differentially expressed candidate genes in rainbow trout

Kocmarek, Andrea L.; Ferguson, Moira M.; Danzmann, Roy G.

doi:10.1139/gen-2015-0047

Cited by 9 publications

(7 citation statements)

References 62 publications

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“…Although the regions covered by the QTL are still large in physical distance, we were able to better elucidate the location of these QTL, including annotated genes in these regions that can be used to develop additional markers. Others have observed correlations between QTL regions with differentially expressed candidate genes, and it has been suggested that overlapping QTL might share common biochemical pathways ( Schweizer and Stein 2011 ; Kocmarek et al 2015 ); indeed many of the QTL in this study were correlated. Only a few QTL did not co-localize with others, even ones with high correlations, such as 16/64P and PD with r > 0.7.…”

Section: Discussionsupporting

confidence: 61%

Pod and Seed Trait QTL Identification To Assist Breeding for Peanut Market Preferences

Chavarro

Chu

Holbrook

et al. 2020

G3 Genes|Genomes|Genetics

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Although seed and pod traits are important for peanut breeding, little is known about the inheritance of these traits. A recombinant inbred line (RIL) population of 156 lines from a cross of Tifrunner x NC 3033 was genotyped with the Axiom_Arachis1 SNP array and SSRs to generate a genetic map composed of 1524 markers in 29 linkage groups (LG). The genetic positions of markers were compared with their physical positions on the peanut genome to confirm the validity of the linkage map and explore the distribution of recombination and potential chromosomal rearrangements. This linkage map was then used to identify Quantitative Trait Loci (QTL) for seed and pod traits that were phenotyped over three consecutive years for the purpose of developing trait-associated markers for breeding. Forty-nine QTL were identified in 14 LG for seed size index, kernel percentage, seed weight, pod weight, single-kernel, double-kernel, pod area and pod density. Twenty QTL demonstrated phenotypic variance explained (PVE) greater than 10% and eight more than 20%. Of note, seven of the eight major QTL for pod area, pod weight and seed weight (PVE >20% variance) were attributed to NC 3033 and located in a single linkage group, LG B06_1. In contrast, the most consistent QTL for kernel percentage were located on A07/B07 and derived from Tifrunner.

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Section: Discussionsupporting

confidence: 61%

Pod and Seed Trait QTL Identification To Assist Breeding for Peanut Market Preferences

Chavarro

Chu

Holbrook

et al. 2020

G3 Genes|Genomes|Genetics

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“…Several genome-wide association studies (GWAS) that match genetic variants, with or without pedigree records, with the observed phenotype have identified significant loci associated with economically important traits in livestock (Kadarmideen, 2014; Sharma et al, 2015). The aquaculture research community is following this trend, and interesting examples are available for growth and disease resistance traits in Atlantic Salmon (e.g., Correa et al, 2015; Gutierrez et al, 2015), rainbow trout (e.g., Kocmarek et al, 2015; Liu et al, 2015b; Palti et al, 2015b), and catfish (e.g., Geng et al, 2015). …”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Study for Identifying Loci that Affect Fillet Yield, Carcass, and Body Weight Traits in Rainbow Trout (Oncorhynchus mykiss)

et al. 2016

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Fillet yield (FY, %) is an economically-important trait in rainbow trout aquaculture that affects production efficiency. Despite that, FY has received little attention in breeding programs because it is difficult to measure on a large number of fish and cannot be directly measured on breeding candidates. The recent development of a high-density SNP array for rainbow trout has provided the needed tool for studying the underlying genetic architecture of this trait. A genome-wide association study (GWAS) was conducted for FY, body weight at 10 (BW10) and 13 (BW13) months post-hatching, head-off carcass weight (CAR), and fillet weight (FW) in a pedigreed rainbow trout population selectively bred for improved growth performance. The GWAS analysis was performed using the weighted single-step GBLUP method (wssGWAS). Phenotypic records of 1447 fish (1.5 kg at harvest) from 299 full-sib families in three successive generations, of which 875 fish from 196 full-sib families were genotyped, were used in the GWAS analysis. A total of 38,107 polymorphic SNPs were analyzed in a univariate model with hatch year and harvest group as fixed effects, harvest weight as a continuous covariate, and animal and common environment as random effects. A new linkage map was developed to create windows of 20 adjacent SNPs for use in the GWAS. The two windows with largest effect for FY and FW were located on chromosome Omy9 and explained only 1.0–1.5% of genetic variance, thus suggesting a polygenic architecture affected by multiple loci with small effects in this population. One window on Omy5 explained 1.4 and 1.0% of the genetic variance for BW10 and BW13, respectively. Three windows located on Omy27, Omy17, and Omy9 (same window detected for FY) explained 1.7, 1.7, and 1.0%, respectively, of genetic variance for CAR. Among the detected 100 SNPs, 55% were located directly in genes (intron and exons). Nucleotide sequences of intragenic SNPs were blasted to the Mus musculus genome to create a putative gene network. The network suggests that differences in the ability to maintain a proliferative and renewable population of myogenic precursor cells may affect variation in growth and fillet yield in rainbow trout.

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“…Although the regions covered by the QTL are still large in 514 physical distance, we were able to better elucidate the location of these QTL, including 515 annotated genes in these regions that can be used to develop additional markers. Others 516 have observed correlations between QTL regions with differentially expressed candidate 517 genes, and it has been suggested that overlapping QTL might share common biochemical 518 pathways (Schweizer and Stein 2011;Kocmarek et al 2015); indeed many of the QTL in 519 this study were correlated. Only a few QTL did not co-localize with others, even ones 520 with high correlations, such as 16/64P and PD with r > 0.7.…”

Section: Comparison With Previously Reported Qtl 359mentioning

confidence: 68%

Pod and seed trait QTL identification to assist breeding for peanut market preferences

Chavarro

Chu

Holbrook

et al. 2019

Preprint

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ABSTRACTAlthough seed and pod traits are important for peanut breeding, little is known about the inheritance of these traits. A recombinant inbred line (RIL) population of 156 lines from a cross of Tifrunner x NC 3033 was genotyped with the Axiom_Arachis1 SNP array and SSRs to generate a genetic map composed of 1524 markers in 29 linkage groups (LG). The genetic positions of markers were compared with their physical positions on the peanut genome to confirm the validity of the linkage map and explorethe distribution of recombination and potential chromosomal rearrangements. These traits were phenotyped over three consecutive years for the purpose of developing trait-associated markers for breeding. Forty-nine QTL were identified in 14 LG for seed size index, kernel percentage, seed weight, pod weight, single-kernel, double-kernel, pod area and pod density. Twenty QTL demonstrated phenotypic variance explained (PVE) greater than 10% and eight more than 20%. Of note, seven of the eight major QTL for pod area, pod weight and seed weight (PVE >20% variance) were attributed to NC 3033 and located in a single linkage group, LG B06_1. In contrast, the most consistent QTL for kernel percentage were located on A07/B07 and derived from Tifrunner.

show abstract

Co-localization of growth QTL with differentially expressed candidate genes in rainbow trout

Cited by 9 publications

References 62 publications

Pod and Seed Trait QTL Identification To Assist Breeding for Peanut Market Preferences

Pod and Seed Trait QTL Identification To Assist Breeding for Peanut Market Preferences

Genome-Wide Association Study for Identifying Loci that Affect Fillet Yield, Carcass, and Body Weight Traits in Rainbow Trout (Oncorhynchus mykiss)

Pod and seed trait QTL identification to assist breeding for peanut market preferences

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