QTL mapping for yield components and agronomic traits in a Brazilian soybean population

Rodrigues, Josiane Isabela da Silva; Miranda, Fábio Demolinari de; Piovesan, Newton Deniz; Ferreira, Adésio; Ferreira, Márcia Flores da Silva; Cruz, Cosme Damião; Barros, Everaldo Gonçalves de; Moreira, Maurílio Alves

doi:10.1590/1984-70332016v16n4a41

Cited by 6 publications

(2 citation statements)

References 38 publications

(51 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Researchers demonstrated that increased pod setting per plant and NPP highly influence the soybean yield; however, it is sensitive to the environment controlled by multiple genes, most of them with small effects ( Xavier and Rainey, 2020 ). In order to improve the effectiveness of breeding for higher yields while taking the significance of the total NPP into mind, several studies identified QTLs linked to the total number of pods ( Zhang et al., 2010 ; Rodrigues et al., 2016 ; Liu et al., 2017b ). To date, 51 QTLs were reported in the SoyBase for the NPP.…”

Section: Molecular Genetic and Genomics Basis Of Soybean Yield Traitsmentioning

confidence: 99%

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean

Tayade,

Imran,

Ghimire

et al. 2023

Front. Plant Sci.

View full text Add to dashboard Cite

Soybean (Glycine max L. Merr.) is a crucial oilseed cash crop grown worldwide and consumed as oil, protein, and food by humans and feed by animals. Comparatively, soybean seed yield is lower than cereal crops, such as maize, rice, and wheat, and the demand for soybean production does not keep up with the increasing consumption level. Therefore, increasing soybean yield per unit area is the most crucial breeding objective and is challenging for the scientific community. Moreover, yield and associated traits are extensively researched in cereal crops, but little is known about soybeans’ genetics, genomics, and molecular regulation of yield traits. Soybean seed yield is a complex quantitative trait governed by multiple genes. Understanding the genetic and molecular processes governing closely related attributes to seed yield is crucial to increasing soybean yield. Advances in sequencing technologies have made it possible to conduct functional genomic research to understand yield traits’ genetic and molecular underpinnings. Here, we provide an overview of recent progress in the genetic regulation of seed size in soybean, molecular, genetics, and genomic bases of yield, and related key seed yield traits. In addition, phytohormones, such as auxin, gibberellins, cytokinins, and abscisic acid, regulate seed size and yield. Hence, we also highlight the implications of these factors, challenges in soybean yield, and seed trait improvement. The information reviewed in this study will help expand the knowledge base and may provide the way forward for developing high-yielding soybean cultivars for future food demands.

show abstract

Section: Molecular Genetic and Genomics Basis Of Soybean Yield Traitsmentioning

confidence: 99%

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean

Tayade,

Imran,

Ghimire

et al. 2023

Front. Plant Sci.

View full text Add to dashboard Cite

show abstract

“…Alguns trabalhos recentes foram publicados envolvendo o mapeamento de características associadas ao florescimento, à maturidade e à altura de plantas (Zhang et al 2010;Niu et al 2013;Zuo et al 2013;Takeshima et al 2016). Características relacionadas à produtividade de grãos como número, tamanho e peso de sementes, número de vagens e peso de cem sementes também representam variáveis de grande interesse na identificação de QTLs, sendo frequentemente reportados estudos de mapeamento envolvendo essas características (Han et al 2012;Niu et al 2013;Yang et al 2013;Hu et al 2014;Kato et al 2014;Rodrigues et al 2016) Soybase, próximos aos marcadores flanqueando o QTL revelado com a abordagem multivariada, afetando as variáveis altura da planta, maturidade e produtividade de grãos Kim et al 2012). O QTL associado à variável PG, identificado por , está associado ao mesmo marcador Satt194 QTLs foram descritos, próximos ao QTL identificado neste estudo, afetando as variáveis NDF, maturidade, altura de planta, número de sementes e produtividade de grãos (Keim et al 1990;Mansur et al 1996;Orf et al 1999;Tasma et al 2001;Kabelka et al 2004;Wang et al 2004;Zhang et al 2004;Funatsuki et al 2005;Reinprecht et al 2006;Chen et al 2007;Gai et al 2007;Li et al 2008;Du et al 2009;Palomeque et al 2009b;Liu et al 2011;Rossi et al 2013;Sun et al 2013).…”

Section: Mt-mim: Multiunclassified

Identificação de QTLs em soja associados à resistência aos percevejos e a caracteres agronômicos utilizando a abordagem de mapeamento multivariado

Möller¹

View full text Add to dashboard Cite

QTL identification in soybean related to stink bug resistance and agronomic traits using the multivariate multiple interval mapping approach Soybean is the Brazilian crop with the most expansion along the past three decades. Currently, it is a commodity commercialized in large scale as grain, bran and oil. Because it is an important source of protein, it plays a fundamental role in the food industry, both human and animal. Soybean monoculture in large areas has increased crop vulnerability to pathogens and insect pests, with significant consequences on grain production. Among such pest insects, stink bugs are considered a major pest of soybean crop, feeding directly on seeds, reducing yield and seed quality. Losses in crop yield due to stink bugs attack are greater than 30% and seed germination compromising can be greater than 50%. This study aimed to identify QTL (Quantitative Trait Loci), for stink bug resistance traits and agronomic traits using the multivariate multiple interval mapping. An F2 mapping population of 228 plants derived from a biparental cross between IAC-100 and CD-215 was used for genotyping. An F2:3 population was developed to evaluate eight stink bug resistant traits such as graining period, leaf retention, pod number per plant, percentage of pod damage, number of seeds, hundred seed weight, weight of healthy seeds and spotted seed weight. Other seven agronomic traits were evaluated such as number of days to flowering, plant height at flowering, number of days to maturity, plant height at maturity, lodging, agronomic value and grain yield. A total of 417 SNP (Single Nucleotide Polymorphism) markers, 61 SSR (Simple Sequence Repeat), 30 AFLP (Amplified Fragment Length Polymorphism) and 8 TRAP (Target Region Amplification Polymorphism) markers were mapped into 20 soybean linkage groups. The total map length was 2,814.82 cM with an average of 5.46 cM between markers. QTL mapping for those traits was performed using univariate (MIM) and multivariate (MT-MIM) multiple interval mapping, with main QTL effects estimates. MIM analysis identified a total of 60 QTL, through 13 soybean linkage groups, with 29 QTL related to stink bug resistant traits and 31 QTL related to agronomic traits. Phenotypic variation explained by QTL ranged from 14.27% for lodging to 65.45% for number of days to maturity. The traits were divided into nine groups for MT-MIM analysis considering their correlation coefficient. Twenty different genomic regions were identified showing a very high QTL clustering. For most of the traits phenotypic variation estimates for MT-MIM models were higher than MIM models, ranging from 27.98% to 65.30% for plant height at flowering and number of days to maturity, respectively. MT-MIM analysis showed 13 genomic regions controlling at least one of the evaluated traits which were not identified at MIM analysis. Comparison between identified QTL and QTL database at Soybase demonstrated that some QTL were similar to those described in different genetic background. However, 56 QTL detected in the pre...

show abstract

Soybean Breeding

Rani

Kumar

2022

Fundamentals of Field Crop Breeding

View full text Add to dashboard Cite

QTL mapping for yield components and agronomic traits in a Brazilian soybean population

Cited by 6 publications

References 38 publications

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean

Identificação de QTLs em soja associados à resistência aos percevejos e a caracteres agronômicos utilizando a abordagem de mapeamento multivariado

Soybean Breeding

Contact Info

Product

Resources

About