P. A. M. R. Valdisser

Genetic Mapping of Resistance to Meloidogyne arenaria in Arachis stenosperma: A New Source of Nematode Resistance for Peanut.

Root-knot nematodes (RKN; Meloidogyne sp.) are a major threat to crops in tropical and subtropical regions worldwide. The use of resistant crop varieties is the preferred method of control because nematicides are expensive, and hazardous to humans and the environment. Peanut (Arachis hypogaea) is infected by four species of RKN, the most damaging being M. arenaria, and commercial cultivars rely on a single source of resistance. In this study, we genetically characterize RKN resistance of the wild Arachis species A. stenosperma using a population of 93 recombinant inbred lines developed from a cross between A. duranensis and A. stenosperma. Four quantitative trait loci (QTL) located on linkage groups 02, 04, and 09 strongly influenced nematode root galling and egg production. Drought-related, domestication and agronomically relevant traits were also evaluated, revealing several QTL. Using the newly available Arachis genome sequence, easy-to-use KASP (kompetitive allele specific PCR) markers linked to the newly identified RKN resistance loci were developed and validated in a tetraploid context. Therefore, we consider that A. stenosperma has high potential as a new source of RKN resistance in peanut breeding programs.

In-depth genome characterization of a Brazilian common bean core collection using DArTseq high-density SNP genotyping

BackgroundCommon bean is a legume of social and nutritional importance as a food crop, cultivated worldwide especially in developing countries, accounting for an important source of income for small farmers. The availability of the complete sequences of the two common bean genomes has dramatically accelerated and has enabled new experimental strategies to be applied for genetic research. DArTseq has been widely used as a method of SNP genotyping allowing comprehensive genome coverage with genetic applications in common bean breeding programs.ResultsUsing this technology, 6286 SNPs (1 SNP/86.5 Kbp) were genotyped in genic (43.3%) and non-genic regions (56.7%). Genetic subdivision associated to the common bean gene pools (K = 2) and related to grain types (K = 3 and K = 5) were reported. A total of 83% and 91% of all SNPs were polymorphic within the Andean and Mesoamerican gene pools, respectively, and 26% were able to differentiate the gene pools. Genetic diversity analysis revealed an average HE of 0.442 for the whole collection, 0.102 for Andean and 0.168 for Mesoamerican gene pools (FST = 0.747 between gene pools), 0.440 for the group of cultivars and lines, and 0.448 for the group of landrace accessions (FST = 0.002 between cultivar/line and landrace groups). The SNP effects were predicted with predominance of impact on non-coding regions (77.8%). SNPs under selection were identified within gene pools comparing landrace and cultivar/line germplasm groups (Andean: 18; Mesoamerican: 69) and between the gene pools (59 SNPs), predominantly on chromosomes 1 and 9. The LD extension estimate corrected for population structure and relatedness (r2SV) was ~ 88 kbp, while for the Andean gene pool was ~ 395 kbp, and for the Mesoamerican was ~ 130 kbp.ConclusionsFor common bean, DArTseq provides an efficient and cost-effective strategy of generating SNPs for large-scale genome-wide studies. The DArTseq resulted in an operational panel of 560 polymorphic SNPs in linkage equilibrium, providing high genome coverage. This SNP set could be used in genotyping platforms with many applications, such as population genetics, phylogeny relation between common bean varieties and support to molecular breeding approaches.

Genome-Wide Association and Regional Heritability Mapping of Plant Architecture, Lodging and Productivity in Phaseolus vulgaris

The availability of high-density molecular markers in common bean has allowed to explore the genetic basis of important complex agronomic traits with increased resolution. Genome-Wide Association Studies (GWAS) and Regional Heritability Mapping (RHM) are two analytical approaches for the detection of genetic variants. We carried out GWAS and RHM for plant architecture, lodging and productivity across two important growing environments in Brazil in a germplasm of 188 common bean varieties using DArTseq genotyping strategies. The coefficient of determination of G × E interaction (c2int) was equal to 17, 21 and 41%, respectively for the traits architecture, lodging, and productivity. Trait heritabilities were estimated at 0.81 (architecture), 0.79 (lodging) and 0.43 (productivity), and total genomic heritability accounted for large proportions (72% to ≈100%) of trait heritability. At the same probability threshold, three marker–trait associations were detected using GWAS, while RHM detected eight QTL encompassing 145 markers along five chromosomes. The proportion of genomic heritability explained by RHM was considerably higher (35.48 to 58.02) than that explained by GWAS (28.39 to 30.37). In general, RHM accounted for larger fractions of the additive genetic variance being captured by markers effects inside the defined regions. Nevertheless, a considerable proportion of the heritability is still missing (∼42% to ∼64%), probably due to LD between markers and genes and/or rare allele variants not sampled. RHM in autogamous species had the potential to identify larger-effect QTL combining allelic variants that could be effectively incorporated into whole-genome prediction models and tracked through breeding generations using marker-assisted selection.

Physiological characterization of common bean (Phaseolus vulgaris L.) under abiotic stresses for breeding purposes

In the Brazilian wet and dry seasons, common beans (Phaseolus vulgaris L.) are grown under rainfed conditions with unexpected episodes of drought and high temperatures. The objective of this study was to evaluate the physiological mechanisms associated with drought adaptation traits in landraces and line/cultivars of beans from the Andean and Mesoamerican gene pools. Twenty-five genotypes, contrasting in terms of drought tolerance, were evaluated in a phenotyping platform under irrigated and rainfed conditions. Agronomic and physiological parameters such as grain yield, shoot structures, gas exchange, water potential, and osmotic adjustment were evaluated. The stress intensity was estimated to be 0.57, and the grain yield reduction ranged from 22 to 89%. Seven accessions, representative of the Andean and Mesoamerican germplasm (CF 200012, CF 240056, CF 250002, CF 900004, CNF 4497, CNF 7382, and SEA 5), presented superior performance in grain yield with and without stresses. The physiological responses under abiotic stresses were highly variable among the genotypes, and two Mesoamerican accessions (CF 200012 and SEA 5) showed more favorable adaptive responses. As the main secondary physiological traits, gas exchange and osmotic adjustment should be evaluated together with the grain yield to increase the selection efficiency of abiotic stresses-tolerant common bean lines.

Genetic diversity of high performance cultivars of upland and irrigated Brazilian rice.

The objective of this study was to analyze the diversity and discrimination of high-performance Brazilian rice cultivars using microsatellite markers. Twenty-nine rice cultivars belonging to EMBRAPA Arroz e Feijão germplasm bank in Brazil were genotyped by 24 SSR markers to establish their structure and genetic discrimination. It was demonstrated that the analyzed germplasm of rice presents an expressive and significant genetic diversity with low heterogeneity among the cultivars. All 29 cultivars were differentiated genetically, and were organized into two groups related to their upland and irrigated cultivation systems. These groups showed a high genetic differentiation, with greater diversity within the group that includes the cultivars for irrigated system. The genotyping data of these cultivars, with the morphological e phenotypical data, are valuable information to be used by rice breeding programs to develop new improved cultivars.