Seed coat color genetics and genotype × environment effects in yellow beans via machine‐learning and genome‐wide association

Abstract Background: Sesame is an important and ancient oilseed crop. Sesame seed coat color is an extremely important agronomic trait, and is related to biochemical functions involved in protein and oil metabolism, and antioxidant content. Because of its complication, the genetic basis of sesame seed coat color remains poorly understood.Results: Genome-wide association study (GWAS) using 42,781 single-nucleotide polymorphisms (SNPs) was performed with a diverse association-mapping panel comprising 366 sesame germplasm lines in 12 environments. In total, 224 significant SNPs (P < 2.34×10−7) explaining approximately 13.34% of the phenotypic variation on average were identified, and 35 significant SNPs were detected in more than 6 environments. Out of 224 significant SNPs, 22 were located in the confidence intervals of previous reported quantitative trait loci. A total of 92 candidate genes were identified in the vicinity of the 4 SNPs that were most significantly associated with sesame seed coat color. Conclusions: The results in this paper will provide new insights into the genetic basis of sesame seed coat color, and should be useful for molecular breeding in sesame.

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Genome-wide association mapping reveals new loci associated with light-colored seed coat at harvest and slow darkening in carioca beans

BMC Plant Biology ◽

10.1186/s12870-021-03122-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Caléo Panhoca de Almeida ◽

Isabella Laporte Santos ◽

Jean Fausto de Carvalho Paulino ◽

Caio Cesar Ferrari Barbosa ◽

Cássia Cristina Augusto Pereira ◽

...

Keyword(s):

Association Mapping ◽

Genetic Control ◽

Seed Coat ◽

Genome Wide Association Study ◽

Coat Color ◽

Genome Wide Association ◽

Seed Coat Color ◽

Market Values ◽

Genome Wide ◽

A Genome

Abstract Background Common bean (Phaseolus vulgaris L.) is a legume whose grain can be stored for months, a common practice among Brazilian growers. Over time, seed coats become darker and harder to cook, traits that are undesirable to consumers, who associate darker-colored beans with greater age. Like commercial pinto and cranberry bean varieties, carioca beans that have darker seeds at harvest time and after storage are subject to decreased market values. Results The goal of our study was to identify the genetic control associated with lightness of seed coat color at harvest (HL) and with tolerance to post-harvest seed coat darkening (PHD) by a genome-wide association study. For that purpose, a carioca diversity panel previously validated for association mapping studies was used with 138 genotypes and 1,516 high-quality SNPs. The panel was evaluated in two environments using a colorimeter and the CIELAB scale. Shelf storage for 30 days had the most expressive results and the L* (luminosity) parameter led to the greatest discrimination of genotypes. Three QTL were identified for HL, two on chromosome Pv04 and one on Pv10. Regarding PHD, results showed that genetic control differs for L* after 30 days and for the ΔL* (final L*—initial L*); only ΔL* was able to properly express the PHD trait. Four phenotypic classes were proposed, and five QTL were identified through six significant SNPs. Conclusions Lightness of seed coat color at harvest showed an oligogenic inheritance corroborated by moderate broad-sense heritability and high genotypic correlation among the experiments. Only three QTL were significant for this trait – two were mapped on Pv04 and one on Pv10. Considering the ΔL, six QTL were mapped on four different chromosomes for PHD. The same HL QTL at the beginning of Pv10 was also associated with ΔL* and could be used as a tool in marker-assisted selection. Several candidate genes were identified and may be useful to accelerate the genetic breeding process.

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Genome-wide association study of seed coat color in sesame (Sesamum indicum L.)

10.21203/rs.2.18296/v1 ◽

2019 ◽

Author(s):

Hongxian Mei ◽

Chengqi Cui ◽

Yanyang Liu ◽

Yan Liu ◽

Xianghua Cui ◽

...

Keyword(s):

Seed Coat ◽

Genetic Basis ◽

Genome Wide Association Study ◽

Coat Color ◽

Sesame Seed ◽

Significant Snps ◽

Sesamum Indicum ◽

Genome Wide Association ◽

Seed Coat Color ◽

Genome Wide

Abstract Background: Sesame (Sesamum indicum L.) is an important and ancient oilseed crop. Sesame seed coat color is an extremely important agronomic trait, and is related to biochemical functions involved in protein and oil metabolism, and antioxidant content. Because of its complication, the genetic basis of sesame seed coat color remains poorly understood.Results: Genome-wide association study (GWAS) using 42,781 SNPs was performed with a diverse association-mapping panel comprising 366 sesame germplasm lines in 12 environments. In total, 224 significant SNPs (P < 2.34×10−7) explaining approximately 13.34% of the phenotypic variation on average were identified, and 35 significant SNPs were detected in more than 6 environments. Out of 224 significant SNPs, 22 were located in the confidence intervals of previous reported quantitative trait loci (QTLs). A total of 92 candidate genes were identified in the vicinity of the 4 SNPs that were most significantly associated with sesame seed coat color. Conclusions: The results in this paper will provide new insights into the genetic basis of sesame seed coat color, and should be useful for molecular breeding in sesame.

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A Genome-wide Combinatorial Strategy Dissects Complex Genetic Architecture of Seed Coat Color in Chickpea

Frontiers in Plant Science ◽

10.3389/fpls.2015.00979 ◽

2015 ◽

Vol 6 ◽

Cited By ~ 16

Author(s):

Deepak Bajaj ◽

Shouvik Das ◽

Hari D. Upadhyaya ◽

Rajeev Ranjan ◽

Saurabh Badoni ◽

...

Keyword(s):

Seed Coat ◽

Genetic Architecture ◽

Coat Color ◽

Seed Coat Color ◽

Genome Wide ◽

A Genome ◽

Combinatorial Strategy

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Further Studies on the Effect of Seed Coat Color on Agronomic and Chemical Characters and Seed Injury in Flax 1

Agronomy Journal ◽

10.2134/agronj1960.00021962005200040010x ◽

1960 ◽

Vol 52 (4) ◽

pp. 210-212 ◽

Cited By ~ 5

Author(s):

J. O. Culbertson ◽

V. E. Comstock ◽

R. A. Frederiksen

Keyword(s):

Seed Coat ◽

Coat Color ◽

Seed Coat Color ◽

Chemical Characters

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Genetic Mapping and Identification of the Candidate Gene for White Seed Coat in Cucurbita maxima

International Journal of Molecular Sciences ◽

10.3390/ijms22062972 ◽

2021 ◽

Vol 22 (6) ◽

pp. 2972

Author(s):

Yuzi Shi ◽

Meng Zhang ◽

Qin Shu ◽

Wei Ma ◽

Tingzhen Sun ◽

...

Keyword(s):

Seed Coat ◽

Molecular Breeding ◽

Coat Color ◽

Recessive Gene ◽

Myb Transcription Factor ◽

Cucurbita Maxima ◽

Seed Coat Color ◽

Rna Seq ◽

Edible Seed ◽

Segregating Population

Seed coat color is an important agronomic trait of edible seed pumpkin in Cucurbita maxima. In this study, the development pattern of seed coat was detected in yellow and white seed coat accessions Wuminglv and Agol. Genetic analysis suggested that a single recessive gene white seed coat (wsc) is involved in seed coat color regulation in Cucurbita maxima. An F2 segregating population including 2798 plants was used for fine mapping and a candidate region containing nine genes was identified. Analysis of 54 inbred accessions revealed four main Insertion/Deletion sites in the promoter of CmaCh15G005270 encoding an MYB transcription factor were co-segregated with the phenotype of seed coat color. RNA-seq analysis and qRT-PCR revealed that some genes involved in phenylpropanoid/flavonoid metabolism pathway displayed remarkable distinction in Wuminglv and Agol during the seed coat development. The flanking InDel marker S1548 was developed to predict the seed coat color in the MAS breeding with an accuracy of 100%. The results may provide valuable information for further studies in seed coat color formation and structure development in Cucurbitaceae crops and help the molecular breeding of Cucurbita maxima.

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Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning

Trends in Microbiology ◽

10.1016/j.tim.2020.12.002 ◽

2021 ◽

Author(s):

Jonathan P. Allen ◽

Evan Snitkin ◽

Nathan B. Pincus ◽

Alan R. Hauser

Keyword(s):

Machine Learning ◽

Association Studies ◽

Bacterial Virulence ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

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Explore the genetics of weedy traits using rice 3K database

Botanical Studies ◽

10.1186/s40529-020-00309-y ◽

2021 ◽

Vol 62 (1) ◽

Author(s):

Yu-Lan Lin ◽

Dong-Hong Wu ◽

Cheng-Chieh Wu ◽

Yung-Fen Huang

Keyword(s):

Seed Coat ◽

Coat Color ◽

Rice Genome ◽

Genome Project ◽

Weedy Rice ◽

Seed Coat Color ◽

Allele Mining ◽

Cultivated Rice ◽

Population Structure Analysis ◽

Public Data

Abstract Background Weedy rice, a conspecific weedy counterpart of the cultivated rice (Oryza sativa L.), has been problematic in rice-production area worldwide. Although we started to know about the origin of some weedy traits for some rice-growing regions, an overall assessment of weedy trait-related loci was not yet available. On the other hand, the advances in sequencing technologies, together with community efforts, have made publicly available a large amount of genomic data. Given the availability of public data and the need of “weedy” allele mining for a better management of weedy rice, the objective of the present study was to explore the genetic architecture of weedy traits based on publicly available data, mainly from the 3000 Rice Genome Project (3K-RGP). Results Based on the results of population structure analysis, we have selected 1378 individuals from four sub-populations (aus, indica, temperate japonica, tropical japonica) without admixed genomic composition for genome-wide association analysis (GWAS). Five traits were investigated: awn color, seed shattering, seed threshability, seed coat color, and seedling height. GWAS was conducted for each sub-population × trait combination and we have identified 66 population-specific trait-associated SNPs. Eleven significant SNPs fell into an annotated gene and four other SNPs were close to a putative candidate gene (± 25 kb). SNPs located in or close to Rc were particularly predictive of the occurrence of seed coat color and our results showed that different sub-populations required different SNPs for a better seed coat color prediction. We compared the data of 3K-RGP to a publicly available weedy rice dataset. The profile of allele frequency, phenotype-genotype segregation of target SNP, as well as GWAS results for the presence and absence of awns diverged between the two sets of data. Conclusions The genotype of trait-associated SNPs identified in this study, especially those located in or close to Rc, can be developed to diagnostic SNPs to trace the origin of weedy trait occurred in the field. The difference of results from the two publicly available datasets used in this study emphasized the importance of laboratory experiments to confirm the allele mining results based on publicly available data.

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