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

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.

The sequences of 150,119 genomes in the UK biobank

We describe the analysis of whole genome sequencing (WGS) of 150,119 individuals from the UK biobank (UKB). This yielded a set of high quality variants, including 585,040,410 SNPs, representing 7.0% of all possible human SNPs, and 58,707,036 indels. The large set of variants allows us to characterize selection based on sequence variation within a population through a Depletion Rank (DR) score for windows along the genome. DR analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UKB, a large British Irish cohort (XBI) and smaller African (XAF) and South Asian (XSA) cohorts. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large scale WGS studies. Using this formidable new resource, we provide several noteworthy examples of trait associations with rare variants with large effects not found previously through studies based on exome sequencing and/or imputation.

Multi-model genome-wide association and genomic prediction analysis of 16 agronomic, physiological and quality related traits in ICARDA spring wheat

Identification and exploration of the genetic architecture of traits related to yield, quality, and drought and heat tolerance is important for yield and quality improvement of wheat through marker-assisted selection. One hundred and ninety-two spring wheat genotypes were tested at two heat-stress locations in Sudan (Wad Medani and Dongula), a drought stress site in Morocco (Marchouch) and a site with high yield potential in Egypt (Sids) in replicated trials during the 2015–2016 and 2016–2017 cropping seasons. A total of 10,577 single nucleotide polymorphism markers identified from the 15 K wheat SNP assay were used in a genome-wide association (GWA) study and genomic prediction for 16 phenotypic traits related to yield, quality and drought and heat tolerance. Significant marker-trait associations were detected across GWAS models for all traits. Most detected marker-trait associations (MTAs) were environment-specific, signifying the presence of high quantitative trait loci-by-environment (QTL x E) interaction. Chromosome arm 5AL had significant multi-model MTAs for grain yield and yield-related traits at the heat-stress locations. Highly significant QTLs were detected on chromosome 2D for waxiness. Homoeologous group 2 and 6 chromosomes were with significant MTAs for grain protein content, gluten content, alveograph strength and Zeleny sedimentation test while chromosome arm 3BL was significant for both Z and W traits. Genomic prediction analysis with ridge regression-best linear unbiased prediction model estimated the breeding values of the studied traits with prediction accuracies ranging from 0.16 for leaf rolling to 0.72 for peduncle length. The identified QTLs could be targeted for marker-assisted selection or further studies aimed at fine mapping and cloning the causative genes and detecting favorable haplotypes with positive effects for agronomic, physiological or quality-related traits.

Genetic Dissection Uncovers Genome-Wide Marker-Trait Associations for Plant Growth, Yield, and Yield-Related Traits Under Varying Nitrogen Levels in Nested Synthetic Wheat Introgression Libraries

Nitrogen is one of the most important macronutrients for crop growth and metabolism. To identify marker-trait associations for complex nitrogen use efficiency (NUE)-related agronomic traits, field experiments were conducted on nested synthetic wheat introgression libraries at three nitrogen input levels across two seasons. The introgression libraries were genotyped using the 35K Axiom® Wheat Breeder's Array and genetic diversity and population structure were examined. Significant phenotypic variation was observed across genotypes, treatments, and their interactions across seasons for all the 22 traits measured. Significant positive correlations were observed among grain yield and yield-attributing traits and root traits. Across seasons, a total of 233 marker-trait associations (MTAs) associated with fifteen traits of interest at different levels of nitrogen (N0, N60, and N120) were detected using 9,474 genome-wide single nucleotide polymorphism (SNP) markers. Of these, 45 MTAs for 10 traits in the N0 treatment, 100 MTAs for 11 traits in the N60 treatment, and 88 MTAs for 11 traits in the N120 treatment were detected. We identified putative candidate genes underlying the significant MTAs which were associated directly or indirectly with various biological processes, cellular component organization, and molecular functions involving improved plant growth and grain yield. In addition, the top 10 lines based on N response and grain yield across seasons and treatments were identified. The identification and introgression of superior alleles/donors improving the NUE while maintaining grain yield may open new avenues in designing next generation nitrogen-efficient high-yielding wheat varieties.

Genetic diversity may help evolutionary rescue in a clonal endemic plant species of Western Himalaya

Habitat loss due to climate change may cause the extinction of the clonal species with a limited distribution range. Thus, determining the genetic diversity required for adaptability by these species in sensitive ecosystems can help infer the chances of their survival and spread in changing climate. We studied the genetic diversity and population structure of Sambucus wightiana—a clonal endemic plant species of the Himalayan region for understanding its possible survival chances in anticipated climate change. Eight polymorphic microsatellite markers were used to study the allelic/genetic diversity and population structure. In addition, ITS1–ITS4 Sanger sequencing was used for phylogeny and SNP detection. A total number of 73 alleles were scored for 37 genotypes at 17 loci for 8 SSRs markers. The population structural analysis using the SSR marker data led to identifying two sub-populations in our collection of 37 S. wightiana genotypes, with 11 genotypes having mixed ancestry. The ITS sequence data show a specific allele in higher frequency in a particular sub-population, indicating variation in different S. wightiana accessions at the sequence level. The genotypic data of SSR markers and trait data of 11 traits of S. wightiana, when analyzed together, revealed five significant Marker-Trait Associations (MTAs) through Single Marker Analysis (SMA) or regression analysis. Most of the SSR markers were found to be associated with more than one trait, indicating the usefulness of these markers for working out marker-trait associations. Moderate to high genetic diversity observed in the present study may provide insurance against climate change to S. wightiana and help its further spread.