Fine Mapping and Candidate Gene Identification for the CapUp Locus Controlling Fruit Orientation in Pepper (Capsicum spp.)

The orientation of fruits is a distinguishing morphological feature of pepper (Capsicum spp.) varieties. The pendent (downward curved) growth of the fruit stalks, known as pedicels, is highly correlated with fruit weight and pedicel length. A previous genetic analysis revealed that the pendent fruit orientation is governed by a dominant gene, and incomplete inheritance is also observed in some Capsicum accessions. To identify and localize this gene, a single quantitative trait locus (QTL) analysis was performed on one F2 and two recombinant inbred line (RIL) populations, and a genome-wide association study (GWAS) was performed using a core collection. Common QTL regions associated with fruit orientation were detected on chromosome 12. A total of 187,966 SNPs were identified in a genotyping-by-sequencing (GBS) for GWAS analysis of 196 Capsicum annuum, 25 Capsicum baccatum, 21 Capsicum chinense, and 14 Capsicum frutescens accessions, representing the germplasm collection of South Korea. The results of these analyses enabled us to narrow down the CapUp region of interest to 200–250 Mbp on chromosome 12. Seven candidate genes were found to be located between two markers that were completely cosegregated with the fruit orientation phenotype. The findings and markers developed in this study will be helpful for additional understanding of pepper fruit development and breeding for fruit orientation.

Quantitative trait locus mapping for common scab resistance in a tetraploid potato full-sib population

Despite the negative impact of common scab (Streptomyces spp.) on the potato industry, little is known about the genetic architecture of resistance to this bacterial disease in the crop. We evaluated a mapping population (~150 full-sibs) derived from a cross between two tetraploid potatoes (‘Atlantic’ × B1829-5) in three environments (MN11, PA11, ME12) under natural common scab pressure. Three measures to common scab reaction, namely percentage of scabby tubers, and disease area and lesion indices, were found to be highly correlated (>0.76). Due to the large environmental effect, heritability values were zero for all three traits in MN11, but moderate to high in PA11 and ME12 (0.44~0.79). We identified a single quantitative trait locus (QTL) for lesion index in PA11, ME12 and joint analyses on linkage group 3, explaining 22~30% of the total variation. The identification of QTL haplotypes and candidate genes contributing to disease resistance can support genomics-assisted breeding approaches in the crop.

Quantitative trait locus mapping for common scab resistance in a tetraploid potato full-sib population

Despite the negative impact of common scab (Streptomyces spp.) to the potato industry, little is known about the genetic architecture of resistance to this bacterial disease in the crop. We evaluated a mapping population (~150 full-sibs) derived from a cross between two tetraploid potatoes (‘Atlantic’ × B1829-5) in three environments (MN11, PA11, ME12) under natural common scab pressure. Three measures to common scab reaction were assessed, namely percentage of scabby tubers, and disease area and lesion indices, which were highly correlated (>0.76). Due to large environmental effect, heritability values were zero for all three traits in MN11, but moderate to high in PA11 and ME12 (0.44~0.79). We identified a single quantitative trait locus (QTL) for lesion index in PA11, ME12 and joint analyses on linkage group 3, explaining 22~30% of the total variation. The identification of QTL haplotypes and candidate genes contributing to disease resistance can support genomics-assisted breeding approaches.

Molecular Characterisation of a Supergene Conditioning Super-High Vitamin C in Kiwifruit Hybrids

During analysis of kiwifruit derived from hybrids between the high vitamin C (ascorbic acid; AsA) species Actinidia eriantha and A. chinensis, we observed bimodal segregation of fruit AsA concentration suggesting major gene segregation. To test this hypothesis, we performed whole-genome sequencing on pools of hybrid genotypes with either high or low AsA fruit. Pool-GWAS (genome-wide association study) revealed a single Quantitative Trait Locus (QTL) spanning more than 5 Mbp on chromosome 26, which we denote as qAsA26.1. A co-dominant PCR marker was used to validate this association in four diploid (A. chinensis × A. eriantha) × A. chinensis backcross families, showing that the A. eriantha allele at this locus increases fruit AsA levels by 250 mg/100 g fresh weight. Inspection of genome composition and recombination in other A. chinensis genetic maps confirmed that the qAsA26.1 region bears hallmarks of suppressed recombination. The molecular fingerprint of this locus was examined in leaves of backcross validation families by RNA sequencing (RNASEQ). This confirmed strong allelic expression bias across this region as well as differential expression of transcripts on other chromosomes. This evidence suggests that the region harbouring qAsA26.1 constitutes a supergene, which may condition multiple pleiotropic effects on metabolism.

Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies

BackgroundSingle Nucleotide Polymorphism (SNP) array and re-sequencing technologies have different properties (e.g. calling rate, minor allele frequency profile) and drawbacks (e.g. ascertainment bias). This lead us to study their complementarity and the consequences of using them separately or combined in diversity analyses and Genome-Wide Association Studies (GWAS). We performed GWAS on three traits (grain yield, plant height and male flowering time) measured in 22 environments on a panel of 247 F1 hybrids obtained by crossing 247 diverse dent maize inbred lines with a same flint line. The 247 lines were genotyped using three genotyping technologies (Genotyping-By-Sequencing, Illumina Infinium 50K and Affymetrix Axiom 600K arrays).ResultsThe effects of ascertainment bias of the 50K and 600K arrays were negligible for deciphering global genetic trends of diversity and for estimating relatedness in this panel. We developed an original approach based on linkage disequilibrium (LD) extent in order to determine whether SNPs significantly associated with a trait and that are physically linked should be considered as a single Quantitative Trait Locus (QTL) or several independent QTLs. Using this approach, we showed that the combination of the three technologies, which have different SNP distributions and densities, allowed us to detect more QTLs (gain in power) and potentially refine the localization of the causal polymorphisms (gain in resolution).ConclusionsConceptually different technologies are complementary for detecting QTLs by tagging different haplotypes in association studies. Considering LD, marker density and the combination of different technologies (SNP-arrays and re-sequencing), the genotypic data available were most likely enough to well represent polymorphisms in the centromeric regions, whereas using more markers would be beneficial for telomeric regions.

Mapping Quantitative Trait Loci for Complex Binary Diseases Using Line Crosses

A composite interval gene mapping procedure for complex binary disease traits is proposed in this paper. The binary trait of interest is assumed to be controlled by an underlying liability that is normally distributed. The liability is treated as a typical quantitative character and thus described by the usual quantitative genetics model. Translation from the liability into a binary (disease) phenotype is through the physiological threshold model. Logistic regression analysis is employed to estimate the effects and locations of putative quantitative trait loci (our terminology for a single quantitative trait locus is QTL while multiple loci are referred to as QTLs). Simulation studies show that properties of this mapping procedure mimic those of the composite interval mapping for normally distributed data. Potential utilization of the QTL mapping procedure for resolving alternative genetic models (e.g., single- or two-trait-locus model) is discussed.