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Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short-day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis accessions using genome-wide association (GWA) mapping, and conventional linkage analysis of a recombinant inbred line (RIL) population. Results showed significant genotype by environment interaction (G×E) for all traits in response to different watering regimes. For the RIL population, the observed G×E was reflected in 17 QTL by environment interactions (Q×E), while 17 additional QTLs were mapped not showing Q×E. GWA mapping identified 58 single nucleotide polymorphism (SNPs) associated with loci displaying Q×E and an additional 16 SNPs associated with loci not showing Q×E. Many candidate genes potentially underlying these loci were suggested. The genes for RPS3C and YLS7 were found to contain conserved amino acid differences when comparing Arabidopsis accessions with strongly contrasting drought response phenotypes, further supporting their candidacy. One of these candidate genes co-located with a QTL mapped in the RIL population.

A recombinant inbred line (RIL) population was produced based on a wide cross between the rapid-cycling and self-compatible genotypes L58, a Caixin vegetable type, and R-o-18, a yellow sarson oil type. A linkage map based on 160 F7 lines was constructed using 100 Single nucleotide polymorphisms (SNPs), 130 AFLP®, 27 InDel, and 13 publicly available SSR markers. The map covers a total length of 1150 centiMorgan (cM) with an average resolution of 4.3 cM/marker. To demonstrate the versatility of this new population, 17 traits, related to plant architecture and seed characteristics, were subjected to quantitative trait loci (QTL) analysis. A total of 47 QTLs were detected, each explaining between 6 and 54% of the total phenotypic variance for the concerned trait. The genetic analysis shows that this population is a useful new tool for analyzing genetic variation for interesting traits in B. rapa, and for further exploitation of the recent availability of the B. rapa whole genome sequence for gene cloning and gene function analysis.

Plant growth and productivity are greatly affected by drought, which is likely to become more threatening with the predicted global temperature increase. Understanding the genetic architecture of complex quantitative traits and their interaction with water availability may lead to improved crop adaptation to a wide range of environments. Here, the genetic basis of 20 physiological and morphological traits is explored by describing plant performance and growth in a Brassica rapa recombinant inbred line (RIL) population grown on a sandy substrate supplemented with nutrient solution, under control and drought conditions. Altogether, 54 quantitative trait loci (QTL) were identified, of which many colocated in 11 QTL clusters. Seventeen QTL showed significant QTL–environment interaction (Q×E), indicating genetic variation for phenotypic plasticity. Of the measured traits, only hypocotyl length did not show significant genotype–environment interaction (G×E) in both environments in all experiments. Correlation analysis showed that, in the control environment, stomatal conductance was positively correlated with total leaf dry weight (DW) and aboveground DW, whereas in the drought environment, stomatal conductance showed a significant negative correlation with total leaf DW and aboveground DW. This correlation was explained by antagonistic fitness effects in the drought environment, controlled by a QTL cluster on chromosome A7. These results demonstrate that Q×E is an important component of the genetic variance and can play a great role in improving drought tolerance in future breeding programmes.

Understanding the adaptation mechanisms of sorghum to drought and the underlying genetic architecture may help to improve its production in a wide range of environments. By crossing a high yielding parent (HYP) and a drought tolerant parent (DTP), we obtained 140 recombinant inbred lines (RILs), which were genotyped with 120 DArT and SSR markers covering 14 linkage groups (LGs). A subset of 100 RILs was evaluated three times in control and drought treatments to genetically dissect their response to water availability. Plants with early heading date (HD) in the drought treatment maintained yield (YLD) level by reducing seed number SN and increasing hundred seed weight (HSW). In contrast, early HD in the control treatment increased SN, HSW and YLD. In total, 133 significant QTL associated with the measured traits were detected in ten hotspot regions. Antagonistic, pleiotropic effects of a QTL cluster mapped on LG-6 may explain the observed trade-offs between SN and HSW: Alleles from DTP reduced SN and the alleles from HYP increased HSW under drought stress, but not in the control treatment. Our results illustrate the importance of considering genetic and environmental factors in QTL mapping to better understand plant responses to drought and to improve breeding programs.

Background Cabbage white butterflies (Pieris spp.) can be severe pests of Brassica crops such as Chinese cabbage, Pak choi (Brassica rapa) or cabbages (B. oleracea). Eggs of Pieris spp. can induce a hypersensitive response-like (HR-like) cell death which reduces egg survival in the wild black mustard (B. nigra). Unravelling the genetic basis of this egg-killing trait in Brassica crops could improve crop resistance to herbivory, reducing major crop losses and pesticides use. Here we investigated the genetic architecture of a HR-like cell death induced by P. brassicae eggs in B. rapa. Results A germplasm screening of 56 B. rapa accessions, representing the genetic and geographical diversity of a B. rapa core collection, showed phenotypic variation for cell death. An image-based phenotyping protocol was developed to accurately measure size of HR-like cell death and was then used to identify two accessions that consistently showed weak (R-o-18) or strong cell death response (L58). Screening of 160 RILs derived from these two accessions resulted in three novel QTLs for Pieris brassicae-induced cell death on chromosomes A02 (Pbc1), A03 (Pbc2), and A06 (Pbc3). The three QTLs Pbc1–3 contain cell surface receptors, intracellular receptors and other genes involved in plant immunity processes, such as ROS accumulation and cell death formation. Synteny analysis with A. thaliana suggested that Pbc1 and Pbc2 are novel QTLs associated with this trait, while Pbc3 also contains an ortholog of LecRK-I.1, a gene of A. thaliana previously associated with cell death induced by a P. brassicae egg extract. Conclusions This study provides the first genomic regions associated with the Pieris egg-induced HR-like cell death in a Brassica crop species. It is a step closer towards unravelling the genetic basis of an egg-killing crop resistance trait, paving the way for breeders to further fine-map and validate candidate genes.

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We used three approaches to map the yellow rust resistance gene Yr7 and identify associated SNPs in wheat. First, we used a traditional QTL mapping approach using a double haploid (DH) population and mapped Yr7 to a low-recombination region of chromosome 2B. To fine map the QTL, we then used an association mapping panel. Both populations were SNP array genotyped allowing alignment of QTL and genome-wide association scans based on common segregating SNPs. Analysis of the association panel spanning the QTL interval, narrowed the interval down to a single haplotype block. Finally, we used mapping-bysequencing of resistant and susceptible DH bulks to identify a candidate gene in the interval showing high homology to a previously suggested Yr7 candidate and to populate the Yr7 interval with a higher density of polymorphisms. We highlight the power of combining mapping-by-sequencing, delivering a complete list of gene-based segregating polymorphisms in the interval with the high recombination, low LD precision of the association mapping panel. Our mapping-by-sequencing methodology is applicable to any trait and our results validate the approach in wheat, where with a near complete reference genome sequence, we are able to define a small interval containing the causative gene.