Conventional genetic improvement of disease resistance in aquatic animal species involves challenge tests or using qPCR to quantify viral load that is costly, time-consuming and causing biosecurity concerns. Recent developments in high throughput next generation genome sequencing platforms such as genotyping by sequencing (GBS) have opened new possibilities for improving disease traits based on DNA information. The principal aim of this study was thus to examine potential application of genomic selection to improve resistance to hepatopancreatic parvovirus (HPV) in banana shrimp Fenneropenaeus merguiensis. Specifically, we used a total of 9472 single nucleotide polymorphisms (SNPs) developed de novo from GBS platforms to assess accuracy of genomic prediction for HPV resistance and growth, carcass and quality-related traits in this white shrimp species. Our multi-locus mixed model analysis showed moderate heritabilities for HPV resistance (h2 = 0.46) and other traits studied (0.10 to 0.55). Genetic correlations of HPV titre with growth and carcass traits, estimated using SNPs markers, were negative (i.e., favourable), suggesting that selection for improved growth and carcass traits may have increased HPV resistance (i.e., reduced HPV titre). More importantly, our gBLUP model demonstrated that the accuracy of gBLUP prediction was moderate for HPV disease resistance (0.46). The genomic prediction accuracy was somewhat greater for growth and carcass related traits especially for body weight (0.76) and meat or tail weight (0.77). On the other hand, the prediction accuracy was from 0.25 to 0.41 for quality traits (raw and cooked colour and flesh streaks). Collectively, it is concluded that there are prospects to apply genomic selection in the genetic improvement for increased disease resistance, carcass and quality-related traits in this population of banana shrimp F. merguiensis.
A genome-wide association study (GWAS) and quantitative trait loci (QTL) analysis using two bi-parental (parental cultivars Smooth Cayenne and MD-2) pineapple seedling populations segregating for spiny and spiny-tip leaf margin and 12 wild and pre-Columbian domesticated genotypes were used to identify single nucleotide polymorphism (SNP) and silicoDArT markers associated with the spiny-tip leaf margin phenotype in pineapple. One QTL between the nucleotide positions 14,355,639 and 14,368,806 on linkage group six (LG06) was identified using SNP markers and one QTL between the nucleotide positions 14,330,844 and 14,346,378 using silicoDArT markers. GWAS and QTL analysis methods identified the same most significantly associated SNP and silicoDArT markers. The most significantly associated SNP and silicoDArT markers were positioned at 14,355,639 and 14,341,745 bp respectively, on or very near, a zeaxanthin epoxidase (ZEP) gene, a key gene in the abscisic acid (ABA) pathway. Other associated genes with a high significance by GWAS analysis using at least two algorithms include a detoxification 33-like (DTX) and a resistance gene analog (RGA2-like). It is proposed that a polymorphism in the putative ZEP gene is the main causal variant associated with the spiny-tip leaf margin in ‘Smooth Cayenne’ pineapple and its descendants including ‘MD-2’.
Final grain production and quality in durum wheat are affected by biotic and abiotic stresses. The association mapping (AM) approach is useful for dissecting the genetic control of quantitative traits, with the aim of increasing final wheat production under stress conditions. In this study, we used AM analyses to detect quantitative trait loci (QTL) underlying agronomic and quality traits in a collection of 294 elite durum wheat lines from CIMMYT (International Maize and Wheat Improvement Center), grown under different water regimes over four growing seasons. Thirty-seven significant marker-trait associations (MTAs) were detected for sedimentation volume (SV) and thousand kernel weight (TKW), located on chromosomes 1B and 2A, respectively. The QTL loci found were then confirmed with several AM analyses, which revealed 12 sedimentation index (SDS) MTAs and two additional loci for SV (4A) and yellow rust (1B). A candidate gene analysis of the identified genomic regions detected a cluster of 25 genes encoding blue copper proteins in chromosome 1B, with homoeologs in the two durum wheat subgenomes, and an ubiquinone biosynthesis O-methyltransferase gene. On chromosome 2A, several genes related to photosynthetic processes and metabolic pathways were found in proximity to the markers associated with TKW. These results are of potential use for subsequent application in marker-assisted durum wheat-breeding programs.
In this study, 129 wheat genotypes from globally diverse origins were genotyped using DArTseq (SilicoDArT and SNP) markers. After filtering markers for quality-filtering, 14,270 SilicoDArTs and 6484 SNPs were retained and used for genetic diversity, population structure and linkage disequilibrium analyses. The highest number of SilicoDArT and SNP markers mapped on genome A and B compared to genome D. In both marker types, polymorphism information content (PIC) values ranged from 0.1 to 0.5, while > 0.80% of SilicoDArTs and > 0.44% SNPs showed PIC value more than median (0.25%). Un-weighted Neighbor Joining cluster analysis and Bayesian-based model population structure grouped wheat genotypes into three and four clusters, respectively. Principal component analysis and discriminant analysis of principal component results showed highly match with cluster and population structure analysis. Linkage disequilibrium (LD) was more extensive in both marker types, while graphical display of LD decay for both marker types showed that LD declined in the region close to 15 kbp, where r2-values corresponded to r2 = 0.16. Overall, our genetic diversity analysis showed high level of variation in studied wheat genotypes, even though there was no relationship between wheat grouping and origins. This might be attributed to admixture level that occurred during long-term natural selection of wheat genotypes in different parts of the world. Highly diverse wheat genotypes used in this study may possess unique genes and are useful sources in breeding programs to improve grain yield and quality.
The aim of this study was the identification of molecular markers for the Pc39 gene in cultivated oat (Avena sativa L.). Pc39 is a major race-specific crown rust resistance gene originally found in an Israeli accession of the wild hexaploid Avena sterilis. The effectiveness of this gene in Europe has decreased in recent years, but is still relatively high and breeding programs would benefit from the availability of molecular markers to aid in its mapping and deployment. The complexity of the oat genome poses a significant obstacle to genetic research. No oat rust resistance genes have yet been cloned, and even the number of relevant molecular markers is very limited. Here, genotyping of a segregating population derived from a cross ‘Celer’ (Pc39)/STH9210 (susceptible) was conducted using RAPD- and SRAP-PCR-based methods, as well as microarray-based DArT™ and next-generation sequencing DArTseq™ techniques. Markers associated with Pc39 were placed on the hexaploid oat consensus linkage group Mrg11 at 3.7–6.7 cM. Six new PCR-based markers were developed to allow identification of the resistant Pc39 allele. These tightly linked markers will be useful in marker-assisted selection, with the closest, SCAR_3456624, being within 0.37 cM of Pc39. The newly developed markers could find applications in the fine mapping or positional cloning of this gene. Moreover, easy-to-use PCR-based markers linked to Pc39 could facilitate the utilization of this gene in oat breeding programs, especially as a component of crown rust resistance gene pyramids.
Pea (Pisum sativum) is one of the most important temperate grain legumes in the world, and its production is severely constrained by the pea aphid (Acyrthosiphon pisum). Wild relatives, such as P. fulvum, are valuable sources of allelic diversity to improve the genetic resistance of cultivated pea species against A. pisum attack. To unravel the genetic control underlying resistance to the pea aphid attack, a quantitative trait loci (QTL) analysis was performed using the previously developed high density integrated genetic linkage map originated from an intraspecific recombinant inbred line (RIL) population (P. fulvum: IFPI3260 × IFPI3251).
We accurately evaluated specific resistance responses to pea aphid that allowed the identification, for the first time, of genomic regions that control plant damage and aphid reproduction. Eight QTLs associated with tolerance to pea aphid were identified in LGs I, II, III, IV and V, which individually explained from 17.0% to 51.2% of the phenotypic variation depending on the trait scored, and as a whole from 17.0% to 88.6%. The high density integrated genetic linkage map also allowed the identification of potential candidate genes co‐located with the QTLs identified.