scholarly journals Genome-wide association studies and genomic selection assays made in a large sample of cacao (Theobroma cacao L.)  germplasm reveal significant marker-trait associations and good predictive value for improving yield potential

2021 ◽  
Author(s):  
Frances Louise Bekele ◽  
Claire Lanaud ◽  
Gillian G. Bidaisee ◽  
Mathilde Allegre ◽  
Xavier Argout ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Predictive Value ◽  
Genome Wide Association ◽  
Ex Situ ◽  
Yield Potential ◽  
Width Ratio ◽  
Seed Number ◽  
Seed Length ◽  
Genome Wide ◽  
Trait Associations

A genome-wide association study was undertaken to unravel marker-trait associations (MTAs) between SNP markers and yield-related traits.  It involved a subset of 421 cacao accessions from the large and diverse collection conserved ex situ at the International Cocoa Genebank Trinidad. An average linkage disequilibrium (r 2 ) of 0.10 at 5.2 Mb was found across several chromosomes. Seventeen significant ( P ≤ 8.17 × 10 -5 (–log10 (p) = 4.088)) MTAs of interest, which accounted for 5 to 17% of the explained phenotypic variation, were identified using a Mixed Linear Model in TASSEL version 5.2.50. The most significant MTAs identified were related to seed number and seed length on chromosome 7 and seed number on chromosome 1.  Other significant MTAs involved seed length to width ratio on chromosomes 3 and 5 and seed length on chromosomes 4 and 9.  It was noteworthy that several yield-related traits, viz ., seed length, seed length to width ratio and seed number were associated with markers on different chromosomes, indicating their polygenic nature.  Approximately 40 candidate genes that encode embryo and seed development, protein synthesis, carbohydrate transport and lipid biosynthesis and transport were identified in this study.  A significant association of fruit surface anthocyanin intensity co-localised with MYB-related protein 308 on chromosome 4. Testing of a genomic selection approach revealed good predictive value (GEBV) for economic traits such as seed number (GEBV = 0.611), seed length (0.6199), seed width (0.5435), seed length to width ratio (0.5503), seed/cotyledon mass (0.6014) and ovule number (0.6325). The findings of this study could facilitate genomic selection and marker-assisted breeding of cacao thereby expediting improvement in the yield potential of cacao planting material.

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

Plants ◽  
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.

scholarly journals Genome-wide association study and genomic selection for plant height, maturity, seed weight, and yield in soybean

2019 ◽  
Author(s):  
Waltram Ravelombola ◽  
Jun Qin ◽  
Ainong Shi ◽  
Fengmin Wang ◽  
Yan Feng ◽  
...  
Keyword(s):  
Association Study ◽  
Genomic Selection ◽  
Candidate Genes ◽  
Plant Height ◽  
Seed Weight ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide

Abstract Background Soybean [ Glycine max (L.) Merr.] is a legume of great interest worldwide. Enhancing genetic gain for agronomic traits via molecular approaches has been long considered as the main task for soybean breeders and geneticists. The objectives of this study were to evaluate maturity, plant height, seed weight, and yield in a diverse soybean accession panel, to conduct a genome-wide association study (GWAS) for these traits and identify SNP markers associated with the four traits, and to assess genomic selection (GS) accuracy. Results A total of 250 soybean accessions were evaluated for maturity, plant height, seed weight, and yield over three years. This panel was genotyped with a total of 10,259 high quality SNPs postulated from genotyping by sequencing (GBS). GWAS was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model, and GS was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that a total of 20, 31, 37, 31, and 23 SNPs were significantly associated with the average 3-year data for maturity, plant height, seed weight, and yield, respectively; some significant SNPs were mapped into previously described loci ( E2 , E4 , and Dt1 ) affecting maturity and plant height in soybean and a new locus mapped on chromosome 20 was significantly associated with plant height; Glyma.10g228900 , Glyma.19g200800 , Glyma.09g196700 , and Glyma.09g038300 were candidate genes found in the vicinity of the top or the second best SNP for maturity, plant height, seed weight, and yield, respectively; a 11.5-Mb region of chromosome 10 was associated with both seed weight and yield; and GS accuracy was trait-, year-, and population structure-dependent. Conclusions The SNP markers identified from this study for plant height, maturity, seed weight and yield can be used to improve the four agronomic traits through marker-assisted selection (MAS) and GS in soybean breeding programs. After validation, the candidate genes can be transferred to new cultivars using SNP markers through MAS. The high GS accuracy has confirmed that the four agronomic traits can be selected in molecular breeding through GS.

scholarly journals Genome-Wide Association Mapping for Stomata and Yield Indices in Bread Wheat under Water Limited Conditions

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1646
Author(s):  
Hafiz Ghulam Muhu-Din Ahmed ◽  
Muhammad Nouman Iqbal ◽  
Muhammad Arslan Iqbal ◽  
Yawen Zeng ◽  
Aziz Ullah ◽  
...  
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Significant Snps ◽  
Water Shortage ◽  
Genome Wide Association ◽  
Yield Potential ◽  
Strong Positive Correlation ◽  
Leaf Venation ◽  
Genome Wide ◽  
Stomata Size

Genome-wide association study (GWAS) was performed for stomata- and yield-related attributes with high-density Illumina 90 K Infinium SNP (single nucleotide polymorphism) array in bread wheat to determine genetic potential of germplasm for scarce water resources with sustainable yield potential. Major yield and stomata attributes were phenotyped on a panel of Pakistani and foreign accessions grown in non-stressed and water shortage environments during two seasons. Highly significant variations were shown among accessions in both conditions for examined characteristics. Water shortage conditions reduced the overall wheat yield and strong positive correlation existed among stomatal frequency, leaf venation and grain yield per plant. Population structure analyses based on 90,000 SNP data classified the accessions into four sub-populations which indicated the presence of genetic variability. Marker-trait association (MTA) analyses revealed that 422 significant SNPs at p ≤ 10−3, after crossing the false discovery rate (FDR) <0.05 threshold, were linked with examined attributes. Pleiotropic loci (wsnp_Ex_c8913_14881924 and Tdurum_contig10598_304) were associated with flag leaf area (FLA), stomata size (SS), stomata frequency (SF), leaf venation (LV), number of grain per spike (NGS) and grain yield per plant (GYP), which were located on chromosome 4B and 6B at the positions 173.63cM and 229.64cM, respectively, under water shortage conditions. Pleotropic loci wsnp_Ex_c24167_33416760, wsnp_Ex_c5412_9564046 and Tdurum_contig81797_369 on chromosomes 7A, 2A and 4B at the positions 148.26cM, 261.05cM and 173.63cM, respectively, were significantly linked with stomata and yield indices such as FLA, SS, SF, LV, NGS and GYP under normal and water shortage conditions. The current experiment not only validated several MTAs for studied indices reported in other studies but also discovered novel MTAs significant under water shortage environments. Associated and significant SNPs will be useful in discovering novel genes underpinning water shortage tolerance in bread wheat for producing high-yielding and drought tolerant wheat varieties to fulfill the wheat demand for growing populations.

scholarly journals Genome-Wide Association Studies Reveal Susceptibility Loci for Digital Dermatitis in Holstein Cattle

Animals ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 2009
Author(s):  
Ellen Lai ◽  
Alexa L. Danner ◽  
Thomas R. Famula ◽  
Anita M. Oberbauer
Keyword(s):  
Predictive Value ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Bos Taurus ◽  
Association Studies ◽  
Bayesian Regression ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Digital Dermatitis ◽  
Genome Wide

Digital dermatitis (DD) causes lameness in dairy cattle. To detect the quantitative trait loci (QTL) associated with DD, genome-wide association studies (GWAS) were performed using high-density single nucleotide polymorphism (SNP) genotypes and binary case/control, quantitative (average number of FW per hoof trimming record) and recurrent (cases with ≥2 DD episodes vs. controls) phenotypes from cows across four dairies (controls n = 129 vs. FW n = 85). Linear mixed model (LMM) and random forest (RF) approaches identified the top SNPs, which were used as predictors in Bayesian regression models to assess the SNP predictive value. The LMM and RF analyses identified QTL regions containing candidate genes on Bos taurus autosome (BTA) 2 for the binary and recurrent phenotypes and BTA7 and 20 for the quantitative phenotype that related to epidermal integrity, immune function, and wound healing. Although larger sample sizes are necessary to reaffirm these small effect loci amidst a strong environmental effect, the sample cohort used in this study was sufficient for estimating SNP effects with a high predictive value.

scholarly journals Genome-Wide Association and Genomic Selection for Resistance to Amoebic Gill Disease in Atlantic Salmon

2018 ◽  
Vol 8 (4) ◽  
pp. 1195-1203 ◽  
Author(s):  
Diego Robledo ◽  
Oswald Matika ◽  
Alastair Hamilton ◽  
Ross D. Houston
Keyword(s):  
Atlantic Salmon ◽  
Genomic Selection ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Selection For ◽  
Gill Disease

scholarly journals Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits

PLoS ONE ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. e0169234 ◽  
Author(s):  
Elisa Biazzi ◽  
Nelson Nazzicari ◽  
Luciano Pecetti ◽  
E. Charles Brummer ◽  
Alberto Palmonari ◽  
...  
Keyword(s):  
Association Mapping ◽  
Medicago Sativa ◽  
Genomic Selection ◽  
Forage Quality ◽  
Genome Wide Association ◽  
Quality Traits ◽  
Genome Wide ◽  
Selection For

Genome-wide association and genomic selection in animal breedingThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽  
2010 ◽  
Vol 53 (11) ◽  
pp. 876-883 ◽  
Author(s):  
Ben Hayes ◽  
Mike Goddard
Keyword(s):  
Genomic Selection ◽  
Complex Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Relationship Matrix ◽  
Genome Wide Association Studies ◽  
Simple Method ◽  
Breeding Values ◽  
Genome Wide ◽  
A Genome

Results from genome-wide association studies in livestock, and humans, has lead to the conclusion that the effect of individual quantitative trait loci (QTL) on complex traits, such as yield, are likely to be small; therefore, a large number of QTL are necessary to explain genetic variation in these traits. Given this genetic architecture, gains from marker-assisted selection (MAS) programs using only a small number of DNA markers to trace a limited number of QTL is likely to be small. This has lead to the development of alternative technology for using the available dense single nucleotide polymorphism (SNP) information, called genomic selection. Genomic selection uses a genome-wide panel of dense markers so that all QTL are likely to be in linkage disequilibrium with at least one SNP. The genomic breeding values are predicted to be the sum of the effect of these SNPs across the entire genome. In dairy cattle breeding, the accuracy of genomic estimated breeding values (GEBV) that can be achieved and the fact that these are available early in life have lead to rapid adoption of the technology. Here, we discuss the design of experiments necessary to achieve accurate prediction of GEBV in future generations in terms of the number of markers necessary and the size of the reference population where marker effects are estimated. We also present a simple method for implementing genomic selection using a genomic relationship matrix. Future challenges discussed include using whole genome sequence data to improve the accuracy of genomic selection and management of inbreeding through genomic relationships.

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