Integrating High-Resolution and Solid-State Magic Angle Spinning NMR Spectroscopy and a Transcriptomic Analysis of Soybean Tissues in Response to Water Deficiency.

INTRODUCTION: Solid-state NMR (SSNMR) spectroscopy methods provide chemical environment and ultrastructural details that are not easily accessible by other non-destructive, high-resolution spectral techniques. High-resolution magic angle spinning (HR-MAS) has been widely used to obtain the metabolic profile of a heterogeneous sample, combining the resolution enhancement provided by MAS in SSNMR with the shimming and locking procedures in liquid-state NMR. OBJECTIVE: In this work, we explored the feasibility of using the HR-MAS and SSNMR techniques to identify metabolic changes in soybean leaves subjected to water-deficient conditions. METHODOLOGY: Control and water-deficient soybean leaves were analysed using one-dimensional (1D) HR-MAS and SSNMR. Total RNA was extracted from the leaves for the transcriptomic analysis. RESULTS: The 1 H HR-MAS and CP-MAS 13 C{1 H} spectra of soybean leaves grown with and without water deficiency stress revealed striking differences in metabolites. A total of 30 metabolites were identified, and the impact of water deficiency on the metabolite profile of soybean leaves was to induce amino acid synthesis. High expression levels of genes required for amino acid biosynthesis were highly correlated with the compounds identified by 1 H HR-MAS. CONCLUSIONS: The integration of the 1 H HR-MAS and SSNMR spectra with the transcriptomic data provided a complete picture of the major changes in the metabolic profile of soybeans in response to water deficiency. Copyright © 2017 John Wiley & Sons, Ltd.

Genome-wide association studies dissect the genetic architecture of seed shape and size in common bean.

Seed weight and size are important yield components. Thus, selecting for large seeds has been a key objective in crop domestication and breeding. In common bean, seed shape is also important since it influences industrial processing and plays a vital role in determining the choices of consumers and farmers. In this study, we performed genome-wide association studies on a core collection of common bean accessions to dissect the genetic architecture and identify genomic regions associated with seed morphological traits related to weight, size, and shape. Phenotypic data were collected by high-throughput image-based approaches, and utilized to test associations with 10,362 single-nucleotide polymorphism markers using multilocus mixed models. We searched within genome-associated regions for candidate genes putatively involved in seed phenotypic variation. The collection exhibited high variability for the entire set of seed traits, and the Andean gene pool was found to produce larger, heavier seeds than the Mesoamerican gene pool. Strong pairwise correlations were verified for most seed traits. Genome-wide association studies identified marker-trait associations accounting for a considerable amount of phenotypic variation in length, width, projected area, perimeter, and circularity in 4 distinct genomic regions. Promising candidate genes were identified, e.g. those encoding an AT-hook motif nuclear-localized protein 8, type 2C protein phosphatases, and a protein Mei2-like 4 isoform, known to be associated with seed size and weight regulation. Moreover, the genes that were pinpointed are also good candidates for functional analysis to validate their influence on seed shape and size in common bean and other related crops.

Genetic mapping reveals complex architecture and candidate genes involved in common bean response to Meloidogyne incognita infection.

Root-knot nematodes (RKNs), particularly Meloidogyne incognita, are among the most damaging and prevalent agricultural pathogens due to their ability to infect roots of almost all crops. The best strategy for their control is through the use of resistant cultivars. However, laborious phenotyping procedures make it difficult to assess nematode resistance in breeding programs. For common bean, this task is especially challenging because little has been done to discover resistance genes or markers to assist selection. We performed genome-wide association studies and quantitative trait loci mapping to explore the genetic architecture and genomic regions underlying the resistance to M. incognita and to identify candidate resistance genes. Phenotypic data were collected by a high-throughput assay, and the number of egg masses and the root-galling index were evaluated. Complex genetic architecture and independent genomic regions were associated with each trait. Single nucleotide polymorphisms on chromosomes Pv06, Pv07, Pv08, and Pv11 were associated with the number of egg masses, and SNPs on Pv01, Pv02, Pv05, and Pv10 were associated with root-galling. A total of 216 candidate genes were identified, including 14 resistance gene analogs and five differentially expressed in a previous RNA sequencing analysis. Histochemical analysis indicated that reactive oxygen species might play a role in the resistance response. Our findings open new perspectives to improve selection efficiency for RKN resistance, and the candidate genes are valuable targets for functional investigation and gene editing approaches.

Improving yield and fruit quality traits in sweet passion fruit: Evidence for genotype by environment interaction and selection of promising genotypes.

Breeding for yield and fruit quality traits in passion fruits is complex due to the polygenic nature of these traits and the existence of genetic correlations among them. Therefore, studies focused on crop management practices and breeding using modern quantitative genetic approaches are still needed, especially for Passiflora alata, an understudied crop, popularly known as the sweet passion fruit. It is highly appreciated for its typical aroma and flavor characteristics. In this study, we aimed to reevaluate 30 genotypes previously selected for fruit quality from a 100 full-sib sweet passion fruit progeny in three environments, with a view to estimating the heritability and genetic correlations, and investigating the GEI and response to selection for nine fruit traits (weight, diameter and length of the fruit; thickness and weight of skin; weight and yield of fruit pulp; soluble solids, and yield). Pairwise genetic correlations among the fruit traits showed mostly intermediate to high values, especially those associated with fruit size and shape. Different genotype rankings were obtained regarding the predicted genetic values of weight of skin, thickness of skin and weight of pulp in each environment. Finally, we used a multiplicative selection index to select simultaneously for weight of pulp and against fruit skin thickness and weight. The response to selection was positive for all traits except soluble solids, and the 20% superior (six) genotypes were ranked. Based on the assumption that incompatibility mechanisms exist in P. alata, the selected genotypes were intercrossed in a complete diallel mating scheme. It is worth noting that all genotypes produced fruits, which is essential to guarantee yields in commercial orchards.

Evidence for Strong Kinship Influence on the Extent of Linkage Disequilibrium in Cultivated Common Beans.

Phaseolus vulgaris is an important grain legume for human consumption. Recently, association mapping studies have been performed for the species aiming to identify loci underlying quantitative variation of traits. It is now imperative to know whether the linkage disequilibrium (LD) reflects the true association between a marker and causative loci. The aim of this study was to estimate and analyze LD on a diversity panel of common beans using ordinary r² and r2 extensions which correct bias due to population structure (rS²), kinship (rV²), and both (rVS²). A total of 10,362 single nucleotide polymorphisms (SNPs) were identified by genotyping by sequencing (GBS), and polymorphisms were found to be widely distributed along the 11 chromosomes. In terms of r2, high values of LD (over 0.8) were identified between SNPs located at opposite chromosomal ends. Estimates for rV² were lower than those for rS². Results for rV² and rVS² were similar, suggesting that kinship may also include information on population structure. Over genetic distance, LD decayed to 0.1 at a distance of 1 Mb for rVS². Inter-chromosomal LD was also evidenced. This study showed that LD estimates decay dramatically according to the population structure, and especially the degree of kinship. Importantly, the LD estimates reported herein may influence our ability to perform association mapping studies on P. vulgaris.

Tratamento de sementes com bioestimulante ao milho submetido a diferentes variabilidades na distribuição espacial das plantas / Seed treatment with biostimulant on maize submitted to different plant spatial variability distribution

RESUMO: A utilização de bioestimulantes pode auxiliar a mitigar os prejuízos ao milho, ocasionados pela má qualidade de estande. Este trabalho foi conduzido objetivando avaliar o efeito do tratamento de sementes com bioestimulante sobre o desempenho agronômico do milho, submetido a diferentes níveis de variabilidade na distribuição espacial das plantas na linha de semeadura. O experimento foi implantado em Lages, SC, durante o ano agrícola de 2013/2014. O delineamento experimental foi de blocos ao acaso, dispostos em parcelas subdivididas. Nas parcelas principais, testaram-se três níveis de desuniformidade espacial na linha: 0, 50 e 100% do Coeficiente de Variação (CV). No nível 0 % de CV, todas as sementes foram uniformemente distribuídas no sulco de semeadura, a uma distância de 17cm entre si. Nos demais níveis de CV, as distâncias entre sementes variaram conforme o tratamento. Nas subparcelas, testou-se a presença ou ausência do tratamento de sementes com bioestimulante. O aumento da variabilidade na distribuição espacial das plantas reduziu a área foliar e o teor de clorofila da folha índice no espigamento, bem como o diâmetro do colmo na colheita, independentemente do tratamento de sementes com bioestimulante. Isso contribuiu para reduzir o número de grãos por espiga e o rendimento de grãos dos tratamentos com 50 e 100% de CV na variabilidade espacial, tanto na presença quanto na ausência do bioestimulante. Portanto, o tratamento de sementes com bioestimulante não mitigou os prejuízos ao rendimento de grãos do milho ocasionados pela distribuição espacial irregular das plantas na linha de semeadura.

ABSTRACT: The use of biostimulants may help to mitigate damages to maize caused by poor stand quality. This research was carried out aiming to evaluate the effect of seed treatment with biostimulant on the agronomic performance of maize submitted to different levels of plant spatial distribution at the sowing row. The experiment was set in Lages, SC, during the 2013/2014 growing season. A randomized block design disposed in split plots was used. Three levels of plant spatial unevenness at the sowing row were tested in the main plots: 0, 50 and 100% of the variation coefficient (CV). At the level 0% of CV all seeds were evenly distributed with a distance of 17cm from each other. At the other levels of CV, the distance between seeds varied according to the treatment. The presence or absence of seed treatment with biostimulant was assessed in the split plots. The increase in plant spatial distribution variability at the sowing row decreased leaf area and leaf chlorophyll content at silking, as well as stem diameter at harvest, regardless of seed treatment with biostimulant. Such behavior contributed to decrease the number of kernels per ear and grain yield of treatments with 50 and 100% C.V. of spatial variability, with and without biostimulant seed treatment. Therefore, seed treatment with biostimulant did not mitigate damages to maize grain yield caused by irregular spatial plant distribution at sowing row.