Quantitative trait loci associated to agronomic traits and yield components in a Sorghum bicolor L. Moench RIL population cultivated under pre-flowering drought and well-watered conditions

The present study aims to identify QTL influencing agronomic traits and yield components under well-watered and pre-flowering drought stress conditions. One hundred F5 recombinant inbred lines (RIL) and the parental lines of a cross between a drought-tolerant and a susceptible line in a field experiment were carried out at Nong Lam University of Ho Chi Minh City, Vietnam. Drought stress was induced by withholding irrigation water from the plants at four weeks after sowing to flowering. Leaf area of the third leaf, stem diameter, plant height, days to heading, anthesis and maturity, panicle length, number of seeds per plant, hundred kernel weight and grain yield were measured. Plants were genotyped with 117 Diversity Arrays Technology (DArT) and eight expressed sequence tag (EST)-derived simple sequence repeat (SSR) markers. Composite interval mapping was carried out on the traits and significant QTL were claimed at a logarithm of the odds (LOD) score >2.5. A total of 50 QTL were detected on nine chromosomes or 13 linkage groups, respectively. Six promising QTL regions with seven QTL for yield and agronomic traits especially related to pre-flowering drought tolerance were identified on chromosomes SBI-01, SBI-03, SBI-04, SBI-05 and SBI-07.Ministry for Education and Training, Vietna

Genetic variation in sorghum germplasm from Sudan, ICRISAT, and USA assessed by simple sequence repeats (SSRs)

Assessment of genetic variability in crops has a strong impact on plant breeding and conservation of genetic resources. It is particularly useful in the characterization of individuals, accessions, and cultivars in determining duplications in germplasm collections and for selecting parents. The objective of this study was to estimate genetic diversity and to obtain information on the genetic relationship among 96 sorghum [Sorghum bicolor (L.) Moench] accessions from Sudan, ICRISAT, and Nebraska, USA, using 16 simple sequence repeats (SSRs). In total, 117 polymorphic bands were detected with a mean of 7.3 alleles per SSR locus. By this approach each accession is uniquely fingerprinted. Genetic similarity estimates ranged from 0 to 0.91, with a mean of 0.30. The polymorphic information content (PIC) for SSRs ranged from 0.46 (SB4-72) to 0.87 (SBAGF06). Diversity index (DI) for all accessions was 0.71. Within subgroups, DI was 0.63 for Sudanese landraces and improved cultivars, 0.49 for PI accessions, 0.42 for Nebraska derivatives, 0.39 for the ICRISAT advanced breeding lines (ABLs), 0.65 for the Feterita group, 0.71 for the Milo group, 0.63 for a Synthetic group (new breeding materials), 0.68 for the Hegiri group, and 0.47 for the Mugud group. Mantel statistics revealed a good fit of the unweighted pair-grouped method with arithmetic average (UPGMA) cluster to the original genetic similarity (GS) data (r = 0.867). UPGMA clustering produced two main clusters comprising mainly nonimproved germplasm (gene bank accessions and Nebraska population derivatives), and improved genotypes (cultivars, Gadarif collections, and ICRISAT advanced lines). Grouping of accessions by UPGMA cluster analysis matched with the geographical origin and/or pedigree information (Sudan, USA, ICRISAT), the adaptation zone (Gadarif area, Sudan), and morphological characters (Feterita, Mugud, and Milo types), indicating the strong differentiation among the sorghum materials

Common garden experiments in the genomic era : new perspectives and opportunities

PdV was supported by a doctoral studentship from the French Ministère de la Recherche et de l’Enseignement Supérieur. OEG was supported by the Marine Alliance for Science and Technology for Scotland (MASTS)The study of local adaptation is rendered difficult by many evolutionary confounding phenomena (e.g. genetic drift and demographic history). When complex traits are involved in local adaptation, phenomena such as phenotypic plasticity further hamper evolutionary biologists to study the complex relationships between phenotype, genotype and environment. In this perspective paper, we suggest that the common garden experiment, specifically designed to deal with phenotypic plasticity has a clear role to play in the study of local adaptation, even (if not specifically) in the genomic era. After a quick review of some high-throughput genotyping protocols relevant in the context of a common garden, we explore how to improve common garden analyses with dense marker panel data and recent statistical methods. We then show how combining approaches from population genomics and genome-wide association studies with the settings of a common garden can yield to a very efficient, thorough and integrative study of local adaptation. Especially, evidence from genomic (e.g. genome scan) and phenotypic origins constitute independent insights into the possibility of local adaptation scenarios, and genome-wide association studies in the context of a common garden experiment allow to decipher the genetic bases of adaptive traits.PostprintPeer reviewe

Linkage drag constrains the roots of modern wheat

Roots, the hidden half of crop plants, are essential for resource acquisition. However, knowledge about the genetic control of below-ground plant development in wheat, one of the most important small-grain crops in the world, is very limited. The molecular interactions connecting root and shoot development and growth, and thus modulating the plant's demand for water and nutrients along with its ability to access them, are largely unexplored. Here, we demonstrate that linkage drag in European bread wheat, driven by strong selection for a haplotype variant controlling heading date, has eliminated a specific combination of two flanking, highly conserved haplotype variants whose interaction confers increased root biomass. Reversing this inadvertent consequence of selection could recover root diversity that may prove essential for future food production in fluctuating environments. Highly conserved synteny to rice across this chromosome segment suggests that adaptive selection has shaped the diversity landscape of this locus across different, globally important cereal crops. By mining wheat gene expression data, we identified root-expressed genes within the region of interest that could help breeders to select positive variants adapted to specific target soil environments

Linking genetic maps and simulation to optimize breeding for wheat flowering time in current and future climates

In Australian wheat (Triticum aestivum L.) production, optimizing wheat phenology is essential for yield potential and to avoid stress, especially around flowering. Breeding could be accelerated by identifying key loci and developing models to predict genotype flowering times under different pedoclimatic scenarios. Here, association genetics for heading date, earliness components (photoperiod sensitivity [PS]; vernalization requirement [VR]; earliness per se [EPS]) and simulation model (APSIM) phenology parameters from a panel of Australian cultivars and breeding lines identified loci with stable, repeatable effects. Major chromosomal regions with stable effects included the Ppd-D1 region on chromosome 2D for PS and EPS, one region on 5B for PS, one region on 6B for EPS, and the Vrn-A1 region on 5A for VR. Regions with stable, smaller effects were detected on 1A and 2D for PS, on 5A and 6B for EPS, and on 1A and 5D for VR. Other regions with stable effects on heading date and earliness components were located on 1A, 2B, 4B, 5B, 6B and 7B (PS and EPS), 2A, 3A and 7A (EPS and VR). Quantitative trait loci (QTL)-based model parameters were used to simulate heading dates across the Australian wheat belt for set of independent genotypes. Comparisons of average observed and predicted heading dates for four main regions of the Australian wheat belt showed good performance in prediction of independent lines from QTL information alone (r(2) = .61-.83). The model allows testing of putative genotypes under various pedoclimatic scenarios including for adaptation to anticipated climate changes