Flowering is an important agronomic trait. Quantile regression (QR) can be used to fit models for all portions of a probability distribution. In Genome-wide association studies (GWAS), QR can estimate SNP (Single Nucleotide Polymorphism) effects on each quantile of interest. The objectives of this study were to estimate genetic parameters and to use QR to identify genomic regions for phenological traits (Days to first flower—DFF; Days for flowering—DTF; Days to end of flowering—DEF) in common bean. A total of 80 genotypes of common beans, with 3 replicates were raised at 4 locations and seasons. Plants were genotyped for 384 SNPs. Traditional single-SNP and 9 QR models, ranging from equally spaced quantiles (τ) 0.1 to 0.9, were used to associate SNPs to phenotype. Heritabilities were moderate high, ranging from 0.32 to 0.58. Genetic and phenotypic correlations were all high, averaging 0.66 and 0.98, respectively. Traditional single-SNP GWAS model was not able to find any SNP-trait association. On the other hand, when using QR methodology considering one extreme quantile (τ = 0.1) we found, respectively 1 and 7, significant SNPs associated for DFF and DTF. Significant SNPs were found on Pv01, Pv02, Pv03, Pv07, Pv10 and Pv11 chromosomes. We investigated potential candidate genes in the region around these significant SNPs. Three genes involved in the flowering pathways were identified, including Phvul.001G214500, Phvul.007G229300 and Phvul.010G142900.1 on Pv01, Pv07 and Pv10, respectively. These results indicate that GWAS-based QR was able to enhance the understanding on genetic architecture of phenological traits (DFF and DTF) in common bean.

-The purpose of this study was to analyze the effect of genotype-environment interaction (GE) on common bean cultivars with

ABSTRACT. We aimed to evaluate 40 common bean cultivars recommended by various Brazilian research institutions between 1970 and 2013 and estimate the genetic progress obtained for grain yield and other agronomic traits. Additionally, we proposed a bi-segmented nonlinear regression model to infer the year in which breeding began to show significant gains in Brazil. The experiment was carried out in Viçosa/MG and Coimbra/MG, in the dry and winter seasons of 2013. For this, a randomized complete block design with three replications was employed. The following traits were evaluated: number of pods per plant (NPP); number of seeds per pod (NSP); 1000-seed weight (W1000); grain yield (Yield); plant architecture (Arch); and grain aspect (GA). Genotypic means were estimated over years using linear mixed models, and genetic gains were estimated using bi-segmented nonlinear regression models. In summary, the methodology proposed in the present study indicated that bean breeding programs in Brazil began to influence Yield beginning in 1990, resulting in a gain of 6.74% per year (68.15 kg/ha per year). The years from which estimated genetic progress for NPP (5.62% per year), NSP (4.59% per year), W1000 (2.08% per year), and GA (1.36% per year) began to increase were 1994, 1990, 1989, and 1986, respectively.

-The purpose of this study was to suggest a division of the State of Santa Catarina in macro-environments for experimentation and bean production. Data of the traits grain yield and plant cycle were evaluated in 10 common bean genotypes grown in nine environments. The data were submitted to the Student-Newman Keuls test, to detect differences between environments, and the Best Linear Unbiased Prediction, to predict the environmental values. The results showed: (a) differences between the regions of Santa Catarina for the traits grain yield and plant cycle, which had a significant positive correlation of 0.26 (b) Based on the genotypes and environments studied the state can be divided in two macro-environments (MA1 and MA2) and four micro-environments (MI1, MI2, MI3 and MI4). The state of Santa Catarina may be roughly divided in at least two macro-environments for the recommendation of new cultivars.

Este trabalho teve como objetivo avaliar genótipos de feijão e classificá-los em tolerantes e sensíveis ao estresse hídrico por meio de avaliação de características morfológicas para utilização em blocos de cruzamentos bem como no estudo da expressão gênica. Foram avaliados nove genótipos de feijão: IAPAR14, IAPAR81, Pérola, IPRColibri, IPRJuriti, IPRChopim, IPRGralha, IPRTiziu e IPRUirapuru. Os genótipos foram submetidos a duas condições hídricas: i) irrigação conforme a necessidade hídrica da cultura durante todo o ciclo e ii) irrigação conforme a necessidade hídrica da cultura até o aparecimento do primeiro botão floral, seguida de supressão da irrigação por 15 dias. O delineamento experimental foi de blocos casualizados com três repetições. As características avaliadas foram: i) estatura de planta; ii) diâmetro do caule; iii) número de legumes por planta; iv) número de grãos por legume; v) comprimento radicular e vi) massa seca radicular. O caráter diâmetro do caule não deve ser utilizado para discriminar os genótipos de feijão como tolerantes ou suscetíveis a falta de água. O genótipo Pérola foi superior para a maioria das características avaliadas, desta forma foram classificados como tolerante ao estresse hídrico no período do florescimento. Os genótipos IAPAR81 e IPRJuriti apresentaram os piores resultados para a maioria das características avaliadas, sendo classificados como suscetíveis ao estresse hídrico no período do florescimento.

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 RESUMO: Objetivou-se incorporar informações genômicas de marcadores SNP ("single nucleotide polymorphism") na avaliação genética das características "stay-green" (SG), arquitetura de planta (AP), aspecto de grãos (AG) e produtividade de grãos (PG) em feijoeiro-comum via modelos Bayesianos. Estes modelos foram comparados quanto a acurácia de predição e habilidade de estimação da herdabilidade para cada característica. Utilizaram-se informações de 80 cultivares genotipadas para 377 marcadores SNP, cujos efeitos de substituição alélica foram estimados por meio de cinco diferentes modelos Bayesianos: Bayes A (BA), B (BB), C (BC), LASSO (BL) e regressão "ridge" (BRR).Embora as acurácias de predição calculadas por meio de análise de validação cruzada tenham sido similares dentro de cada característica, o modelo BB se destacou para a característica SG, enquanto o modelo BRR foi indicado para as demais. As herdabilidades estimadas para SG, AP, AG e PG foram, respectivamente, 0,61, 0,28, 0,32 e 0,29

The increase in grain yield and other agronomic traits, in common bean cultivars, is due, in large part, to its genetic breeding. This study aimed at estimating the genetic progress for grain yield and other important agronomic traits in black common bean cultivars recommended by Brazilian breeding programs between 1960 and 2013. A randomized blocks design was used, with three replications and 40 black common bean cultivars. The following traits were evaluated: grain yield and appearance, plant architecture, number of pods per plant and seeds per pod and 1,000-seed weight. The genetic progress was estimated from the trait averages over the years, using bissegmented linear regression models that allowed the inference of the exact year in which the black common bean breeding began to present significant genetic progress. For grain yield, the genetic progress was observed from 1988, with an annual gain of 2.42 %. Improvements also occurred to grain appearance (1.85 %), plant architecture (1.35 %), number of pods per plant (2.36 %) and seeds per pod (2.24 %) and 1,000-seed weight (1.42 %), mainly after 1989.

The purpose of this study was to predict the genetic progress in the selection for common bean agronomic traits based on the trait expression, using two indices of adaptive selection. The existence of correlation between various traits in common bean breeding is a major restriction, but some tools that allow breeders to predict the expected gains could optimize results. The following traits were evaluated:(1) plant cycle (days), (2) plant height (in cm), (3) stem diameter (cm), (4) insertion of the first pod (cm); (5) number of pods per plant; (6) number of grains per pod; (7) pod length (cm). Results show the possibility of selecting accessions for several agronomically important traits evaluated together. The only genotype selected by both indices was UDESC 03, confirming the possibility of selecting plants with superior agronomic traits among genotypes of common bean landraces.