Population genomics and genome-wide association studies (GWAS) for drought tolerance and yield in common bean (Phaseolus vulgaris L.)

Orientador: Maria Imaculada Zucchi, Rosana Pereira VianelloDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de BiologiaResumo: O feijoeiro comum é uma importante fonte de proteínas e fibras, sendo considerado o mais importante legume de grãos para o consumo humano direto no mundo. Fatores como o aumento da população, mudanças climáticas globais, diminuição da disponibilidade de água para a agricultura e redução das áreas cultiváveis têm causado grande preocupação quanto à estabilidade e manutenção da produção agrícola em níveis que possam atender à demanda de consumo do grão. Diante disto, se torna fundamental a busca por alternativas que possam incrementar a produção, tais como o desenvolvimento de novas cultivares com características vantajosas e com maior potencial produtivo. O uso dos recursos genéticos presentes nos bancos de germoplasma é uma importante estratégia para busca de novos alelos e incorporação de variabilidade genética nos programas de melhoramento, permitindo o desenvolvimento de cultivares com combinações alélicas novas e favoráveis. Entretanto, para a conservação e uso eficiente destes recursos genéticos é necessária uma adequada caracterização molecular e fenotípica. Atualmente, a caracterização molecular de alta densidade pode ser realizada a custos bastante reduzidos, graças à utilização da metodologia de genotipagem por sequenciamento (GbS), a partir da qual milhares de polimorfismos de base única (SNPs) são identificados e utilizados na genotipagem de acessos de bancos de germoplasma. Associado a esse nível de resolução de genoma, estão disponíveis métodos de mensuração, em larga escala, de fenótipos relacionados a caracteres de importância econômica, como os componentes de produtividade em condições de seca. Através da correlação entre os fenótipos e genótipos é possível explorar a associação não aleatória entre alelos de diferentes locos, a determinado caráter de interesse, através do estudo de associação genômica ampla (GWAS). Neste contexto, o objetivo deste trabalho foi caracterizar, molecularmente, variedades de feijão pertencentes à Coleção Nuclear de Feijão da Embrapa (CONFE) e identificar, através da análise de GWAS, regiões do genoma potencialmente associadas ao controle da tolerância a seca em feijão. No primeiro capítulo, um total de 6286 SNPs foram obtidos através da metodologia DArTseq, sendo utilizados para estimar a diversidade (HE = 0,442) e divergência genética (FST = 0,747) nos acessos da CONFE, o decaimento do desequilíbrio de ligação (88 kb, variando de ~ 395 kb no Andino a ~ 130 kb no Mesoamericano), os locos que, possivelmente, estão sob seleção devido aos processos de domesticação e seleção artificial (59 SNPs entre os pools gênicos), além da seleção de um conjunto de 560 SNPs para compor um painel altamente informativo, para uso na caracterização do germoplasma de origens diversas (Andina e Mesoamericana). No segundo capítulo, utilizando um conjunto de 8789 SNPs, derivados das metodologias DArTseq e Capture-Seq, foram identificados, através de GWAS, 212 SNPs significativamente associados aos componentes de produtividade coletados em ambientes com e sem deficiência hídrica. Estes SNPs estão dentro ou, em provável, desequilíbrio de ligação com genes que codificam proteínas putativas que participam dos processos moleculares relacionados a tolerância à seca. Adicionalmente, foram identificados genótipos com desempenho superior em ambientes com e sem déficit hídrico. Ao final destes estudos, foi possível obter: 1) um painel de 560 SNPs para caracterizar amplamente o germoplasma de feijoeiro; 2) um painel de 343 indivíduos genotipados que podem ser utilizados em estudos de GWAS para caracteres de interesse dos programas de melhoramento; 3) um conjunto de SNPs com potencial de uso na seleção assistida para tolerância à secaAbstract: The common bean is an important source of protein and fiber and it is considered the most important grain legume for direct human consumption in the world. Factors such as population growth, global climate change, scarcity water for agriculture and reduction of arable land have caused great concern about the stability and maintenance of agricultural production at levels that can meet the consumption demand of the grain. Because of this, the search for alternatives that can increase production is fundamental, such as the development of new cultivars with advantageous traits and with greater productive potential. The use of the genetic resources present in germplasm banks is an important strategy to search for new alleles and to incorporate genetic variability in breeding programs, allowing the development of cultivars with new and favorable allelic combinations. However, for the conservation and efficient use of these genetic resources an adequate molecular and phenotypic characterization is necessary. Nowadays, the high-density molecular characterization can be realized at low cost because of the use of genotyping by sequencing (GbS) methodology, from which thousands of single nucleotide polymorphisms (SNPs) are identified and genotyped. Associated with this level of genome resolution, methods for large-scale measurement of phenotypes related to economically important traits are available, such as productivity components under drought conditions. Through the correlation between phenotypes and genotypes, it is possible to explore the non-random association between alleles of different loci, to the trait of interest, through the genome-wide association studies (GWAS). In this context, the aim of this work is to characterize molecularly bean varieties belonging to the Core Collection of Beans (CONFE) of the Embrapa and to identify genome regions potentially associated with drought tolerance in common bean through GWAS. In the first chapter, a total of 6,286 SNPs were obtained from DArTseq methodology, being used to estimate the diversity (HE = 0.442) and genetic divergence (FST = 0.747) in the CONFE accessions, to determine the decay of the linkage disequilibrium (88 kb, ranging from ~ 395 kb in the Andean to ~ 130 kb in the Mesoamerican) and to detect the loci that are possibly under selection due to the processes of domestication and artificial selection (59 SNPs between the gene pools). Besides, it was selected a set of 560 SNPs to compose a highly informative panel for use in the characterization of germplasm from diverse origins (Andean and Mesoamerican). In the second chapter, using a set of 8,789 SNPs derived from the DArTseq and Capture-Seq methodologies, 212 SNPs significantly associated with the productivity components collected in environments with and without water deficiency were identified through GWAS. These SNPs are within or likely in linkage disequilibrium with genes encoding putative proteins that participate in molecular processes related to drought tolerance. In addition, genotypes with superior performance were identified in environments with and without water deficit. At the end of these studies it was possible to obtain: 1) a panel of 560 SNPs to broadly characterize common bean germplasm; 2) a panel of 343 genotyped individuals that can be used in GWAS for traits of interest to breeding programs; 3) a set of SNPs with potential use in marker-assisted selection for drought toleranceMestradoBioinformaticaMestra em Genética e Biologia Molecula

Genome-wide analysis of the transcriptional response to drought stress in root and leaf of common bean

Genes related to the response to drought stress in leaf and root tissue of drought-susceptible (DS) and tolerant (DT) genotypes were characterized by RNA-Seq. In total, 54,750 transcripts, representative of 28,590 genes, were identified; of these, 1,648 were of high-fidelity (merge of 12 libraries) and described for the first time in the Andean germplasm. From the 1,239 differentially expressed genes (DEGs), 458 were identified in DT, with a predominance of genes in categories of oxidative stress, response to stimulus and kinase activity. Most genes related to oxidation-reduction terms in roots were early triggered in DT (T75) compared to DS (T150) suggestive of a mechanism of tolerance by reducing the damage from ROS. Among the KEGG enriched by DEGs up-regulated in DT leaves, two related to the formation of Sulfur-containing compounds, which are known for their involvement in tolerance to abiotic stresses, were common to all treatments. Through qPCR, 88.64% of the DEGs were validated. A total of 151,283 variants were identified and functional effects estimated for 85,780. The raw data files were submitted to the NCBI database. A transcriptome map revealed new genes and isoforms under drought. These results supports a better understanding of the drought tolerance mechanisms in beans

Genome prediction accuracy of common bean via Bayesian models

<div><p>ABSTRACT: We aimed to apply genomic information based on SNP (single nucleotide polymorphism) markers for the genetic evaluation of the traits “stay-green” (SG), plant architecture (PA), grain aspect (GA) and grain yield (GY) in common bean through Bayesian models. These models were compared in terms of prediction accuracy and ability for heritability estimation for each one of the mentioned traits. A total of 80 cultivars were genotyped for 377 SNP markers, whose effects were estimated by five different Bayesian models: Bayes A (BA), B (BB), C (BC), LASSO (BL) e Ridge regression (BRR). Although, prediction accuracies calculated by means of cross-validation have been similar within each trait, the BB model stood out for the trait SG, whereas the BRR was indicated for the remaining traits. The heritability estimates for the traits SG, PA, GA and GY were 0.61, 0.28, 0.32 and 0.29, respectively. In summary, the Bayesian methods applied here were effective and ease to be implemented. The used SNP markers can help in the early selection of promising genotypes, since incorporating genomic information increase the prediction accuracy of the estimated genetic merit.</p></div

Supplemental Material for Resende et al., 2018

<div><p></p><p><b>1) Phenotypic_Data - Phenotypic data taken in both environments and joint analysis for 181 individuals</b><br></p><p></p> <p><b>2) Marker_DArT - DArT marker genotyping data</b></p> <p><b>3) Marker_SNP - SNP marker genotyping data</b></p></div><div><br></div

Mapping QTLs for drought tolerance in a SEA 5 x AND 277 common bean cross with SSRs and SNP markers

<div><p>Abstract The common bean is characterized by high sensitivity to drought and low productivity. Breeding for drought resistance in this species involves genes of different genetic groups. In this work, we used a SEA 5 x AND 277 cross to map quantitative trait loci associated with drought tolerance in order to assess the factors that determine the magnitude of drought response in common beans. A total of 438 polymorphic markers were used to genotype the F8 mapping population. Phenotyping was done in two greenhouses, one used to simulate drought and the other to simulate irrigated conditions. Fourteen traits associated with drought tolerance were measured to identify the quantitative trait loci (QTLs). The map was constructed with 331 markers that covered all 11 chromosomes and had a total length of 1515 cM. Twenty-two QTLs were discovered for chlorophyll, leaf and stem fresh biomass, leaf biomass dry weight, leaf temperature, number of pods per plant, number of seeds per plant, seed weight, days to flowering, dry pod weight and total yield under well-watered and drought (stress) conditions. All the QTLs detected under drought conditions showed positive effects of the SEA 5 allele. This study provides a better understanding of the genetic inheritance of drought tolerance in common bean.</p></div

A drought transcriptional map reveals new genes for the Mesoamerican common bean germplasm. [Complementary files].

This repository contains annotation files for <i>Phaseolus vulgaris</i> L. (Common bean) transcriptome assembly under drought conditions, including gene and exon annotations, non-coding RNAs prediction, ORFs prediction and variants annotations. The files are originated in analyse of RNA-Seq data. <br