Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia (Oreochromis niloticus) Population

Nile tilapia is a key aquaculture species with one of the highest production volumes globally. Genetic improvement of feed efficiency via selective breeding is an important goal, and genomic selection may expedite this process. The aims of this study were to 1) dissect the genetic architecture of feed-efficiency traits in a Nile tilapia breeding population, 2) map the genomic regions associated with these traits and identify candidate genes, 3) evaluate the accuracy of breeding value prediction using genomic data, and 4) assess the impact of the genetic marker density on genomic prediction accuracies. Using an experimental video recording trial, feed conversion ratio (FCR), body weight gain (BWG), residual feed intake (RFI) and feed intake (FI) traits were recorded in 40 full-sibling families from the GIFT (Genetically Improved Farmed Tilapia) Nile tilapia breeding population. Fish were genotyped with a ThermoFisher Axiom 65 K Nile tilapia SNP array. Significant heritabilities, ranging from 0.12 to 0.22, were estimated for all the assessed traits using the genomic relationship matrix. A negative but favourable genetic correlation was found between BWG and the feed-efficiency related traits; −0.60 and −0.63 for FCR and RFI, respectively. While the genome-wide association analyses suggested a polygenic genetic architecture for all the measured traits, there were significant QTL identified for BWG and FI on chromosomes seven and five respectively. Candidate genes previously found to be associated with feed-efficiency traits were located in these QTL regions, including ntrk3a, ghrh and eif4e3. The accuracy of breeding value prediction using the genomic data was up to 34% higher than using pedigree records. A SNP density of approximately 5,000 SNPs was sufficient to achieve similar prediction accuracy as the full genotype data set. Our results highlight the potential of genomic selection to improve feed efficiency traits in Nile tilapia breeding programmes.

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Genome-wide association study and low-cost genomic predictions for growth and fillet yield in Nile tilapia (Oreochromis niloticus)

10.1101/573022 ◽

2019 ◽

Cited By ~ 4

Author(s):

Grazyella M. Yoshida ◽

Jean P. Lhorente ◽

Katharina Correa ◽

Jose Soto ◽

Diego Salas ◽

...

Keyword(s):

Genomic Selection ◽

Nile Tilapia ◽

Cost Effective ◽

Genotype Imputation ◽

Genome Wide Association ◽

Genomic Information ◽

Breeding Programs ◽

Genome Wide ◽

Fillet Yield ◽

Genomic Predictions

ABSTRACTFillet yield (FY) and harvest weight (HW) are economically important traits in Nile tilapia production. Genetic improvement of these traits, especially for FY, are lacking, due to the absence of efficient methods to measure the traits without sacrificing fish and the use of information from relatives to selection. However, genomic information could be used by genomic selection to improve traits that are difficult to measure directly in selection candidates, as in the case of FY. The objectives of this study were: (i) to perform genome-wide association studies (GWAS) to dissect the genetic architecture of FY and HW, (ii) to evaluate the accuracy of genotype imputation and (iii) to assess the accuracy of genomic selection using true and imputed low-density (LD) single nucleotide polymorphism (SNP) panels to determine a cost-effective strategy for practical implementation of genomic information in tilapia breeding programs. The data set consisted of 5,866 phenotyped animals and 1,238 genotyped animals (108 parents and 1,130 offspring) using a 50K SNP panel. The GWAS were performed using all genotyped and phenotyped animals. The genotyped imputation was performed from LD panels (LD0.5K, LD1K and LD3K) to high-density panel (HD), using information from parents and 20% of offspring in the reference set and the remaining 80% in the validation set. In addition, we tested the accuracy of genomic selection using true and imputed genotypes comparing the accuracy obtained from pedigree-based best linear unbiased prediction (PBLUP) and genomic predictions. The results from GWAS supports evidence of the polygenic nature of FY and HW. The accuracy of imputation ranged from 0.90 to 0.98 for LD0.5K and LD3K, respectively. The accuracy of genomic prediction outperformed the estimated breeding value from PBLUP. The use of imputation for genomic selection resulted in an increased relative accuracy independent of the trait and LD panel analyzed. The present results suggest that genotype imputation could be a cost-effective strategy for genomic selection in tilapia breeding programs.

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Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: I: feed efficiency and component traits

BMC Genomics ◽

10.1186/s12864-019-6362-1 ◽

2020 ◽

Vol 21 (1) ◽

Cited By ~ 6

Author(s):

Feng Zhang ◽

Yining Wang ◽

Robert Mukiibi ◽

Liuhong Chen ◽

Michael Vinsky ◽

...

Keyword(s):

Feed Efficiency ◽

Genetic Architecture ◽

Quantitative Traits ◽

Association Studies ◽

Genome Wide Association ◽

Whole Genome Sequence ◽

Genome Wide Association Studies ◽

Whole Genome ◽

Genome Wide ◽

Component Traits

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Genome-wide association analysis and accuracy of genome-enabled breeding value predictions for resistance to infectious hematopoietic necrosis virus in a commercial rainbow trout breeding population

Genetics Selection Evolution ◽

10.1186/s12711-019-0489-z ◽

2019 ◽

Vol 51 (1) ◽

Cited By ~ 6

Author(s):

Roger L. Vallejo ◽

Hao Cheng ◽

Breno O. Fragomeni ◽

Kristy L. Shewbridge ◽

Guangtu Gao ◽

...

Keyword(s):

Rainbow Trout ◽

Association Analysis ◽

Infectious Hematopoietic Necrosis Virus ◽

Breeding Population ◽

Genome Wide Association ◽

Breeding Value ◽

Necrosis Virus ◽

Genome Wide Association Analysis ◽

Genome Wide ◽

Infectious Hematopoietic Necrosis

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Genomic selection using a subset of SNPs identified by genome-wide association analysis for disease resistance traits in aquaculture species

Aquaculture ◽

10.1016/j.aquaculture.2021.736620 ◽

2021 ◽

Vol 539 ◽

pp. 736620

Author(s):

Zheng Luo ◽

Yang Yu ◽

Jianhai Xiang ◽

Fuhua Li

Keyword(s):

Disease Resistance ◽

Genomic Selection ◽

Association Analysis ◽

Genome Wide Association ◽

Genome Wide Association Analysis ◽

Genome Wide ◽

Resistance Traits

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Genome-Wide Association and Prediction of Male and Female Floral Hybrid Potential Traits in Elite Spring Bread Wheat Genotypes

Plants ◽

10.3390/plants10050895 ◽

2021 ◽

Vol 10 (5) ◽

pp. 895

Author(s):

Samira El Hanafi ◽

Souad Cherkaoui ◽

Zakaria Kehel ◽

Ayed Al-Abdallat ◽

Wuletaw Tadesse

Keyword(s):

Genomic Selection ◽

Bread Wheat ◽

Genome Wide Association ◽

Hybrid Breeding ◽

Floral Traits ◽

Phenotypic Variance ◽

Spring Bread Wheat ◽

Genome Wide ◽

Anther Length ◽

Anther Extrusion

Hybrid wheat breeding is one of the most promising technologies for further sustainable yield increases. However, the cleistogamous nature of wheat displays a major bottleneck for a successful hybrid breeding program. Thus, an optimized breeding strategy by developing appropriate parental lines with favorable floral trait combinations is the best way to enhance the outcrossing ability. This study, therefore, aimed to dissect the genetic basis of various floral traits using genome-wide association study (GWAS) and to assess the potential of genome-wide prediction (GP) for anther extrusion (AE), visual anther extrusion (VAE), pollen mass (PM), pollen shedding (PSH), pollen viability (PV), anther length (AL), openness of the flower (OPF), duration of floret opening (DFO) and stigma length. To this end, we employed 196 ICARDA spring bread wheat lines evaluated for three years and genotyped with 10,477 polymorphic SNP. In total, 70 significant markers were identified associated to the various assessed traits at FDR ≤ 0.05 contributing a minor to large proportion of the phenotypic variance (8–26.9%), affecting the traits either positively or negatively. GWAS revealed multi-marker-based associations among AE, VAE, PM, OPF and DFO, most likely linked markers, suggesting a potential genomic region controlling the genetic association of these complex traits. Of these markers, Kukri_rep_c103359_233 and wsnp_Ex_rep_c107911_91350930 deserve particular attention. The consistently significant markers with large effect could be useful for marker-assisted selection. Genomic selection revealed medium to high prediction accuracy ranging between 52% and 92% for the assessed traits with the least and maximum value observed for stigma length and visual anther extrusion, respectively. This indicates the feasibility to implement genomic selection to predict the performance of hybrid floral traits with high reliability.

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A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations

BMC Genomics ◽

10.1186/s12864-020-07288-1 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Shenping Zhou ◽

Rongrong Ding ◽

Fanming Meng ◽

Xingwang Wang ◽

Zhanwei Zhuang ◽

...

Keyword(s):

Candidate Genes ◽

Growth And Development ◽

Genetic Architecture ◽

Association Studies ◽

Meta Analysis ◽

Average Daily Gain ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Daily Gain

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.

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