QTL mapping and candidate gene mining for soybean seed weight per plant

Yu, Meng; Liu, Zhangxiong; Jiang, Shanshan; Xu, Ning; Chen, Qingshan; Qi, Zhaoming; Wenhe, Lv

doi:10.1080/13102818.2018.1438851

Cited by 15 publications

(10 citation statements)

References 30 publications

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“…(Devi & Sharma, 2018;R. Kumar et al, 2019;Zangani et al, 2021), jinten (Rebey et al, 2012), bunga matahari (Soheili-Movahhed et al, 2019), gandum (Jafar et al, 2012;Riaziat et al, 2012), kacang tunggak (Can et al, 2020), lobak (, canola (Morshedi, 2011;Shahri et al, 2011), jagung (Jalili & Eyvazi, 2015), paprika (Verma & Mehta, 2019), cabai (V. Kumar et al, 2018), sorgum (Ochieng et al, 2013;Zareian et al, 2012), wijen (Anter, 2020;Ramazani, 2016), terung (Rahman et al, 2017), kacang babi (Wakweya & Meleta, 2016), kacang lentil (Ninou et al, 2019), kedelai (Yu et al, 2018), rami (Abdul Nizar & Mulani, 2015), Oleh karena itu dilakukan penelitian terkait bobot 1000 butir dan kualitas benih dari produksi benih cabai.…”

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confidence: 99%

Bobot 1000 Butir dan Kualitas Benih Tujuh Lot Varietas Cabai Open Pollinated (OP)

Kurniawan¹,

Sayuran²,

Azmi³

2021

Peningkatan Produktivitas Pertanian Era Society 5.0 Pasca Pandemi

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Kualitas benih dapat diketahui setelah pengujian mutu benih di laboratorium. Pengujian mutu benih cabai dilakukan di Laboratorium benih terakreditasi dari tujuh lot benih cabai OP dan diulang dua kali. Pengamatan dilakukan untuk daya berkecambah, kadar air, kemurnian fisik dan bobot 1000 butir. Hasil menunjukkan bahwa varietas dan lot berpengaruh terhadap karakter daya berkecambah, kadar air benih dan bobot 1000 butir.

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mentioning

confidence: 99%

Bobot 1000 Butir dan Kualitas Benih Tujuh Lot Varietas Cabai Open Pollinated (OP)

Kurniawan¹,

Sayuran²,

Azmi³

2021

Peningkatan Produktivitas Pertanian Era Society 5.0 Pasca Pandemi

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“…In the haplotype block, a candidate gene for plant height and number of nodes may be the Dt1 gene in BLG accessions. Similarly, a GWAS with 419 diverse soybean plant introductions from 26 countries reported that the Dt1 gene showed pleotropic effects for plant height and internode number [25].…”

Section: Discussionmentioning

confidence: 98%

“…They indicated that 22 loci showed minor effects on HSW. In addition, many QTLs in multiple environments were detected by QTL mapping through intraspecific and interspecific crossing populations [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Mapping for Seed Weight in Soybean with Black Seed Coats and Green Cotyledons

Lee

2022

Agronomy

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The yield of soybean (Glycine max (L.) Merr.) is based on several components, such as the number of plants per unit area, pod number per plant, number of nodes, and seed weight. Additionally, the hundred-seed weight (HSW) is an important component affecting soybean yield. The HSW trait can determine soy products meant for human consumption. In this study, we conducted genome-wide association studies with 470 accessions of black seed coats with green cotyledons and applied an online tool with publicly available genome sequencing data. The objective of the study was to identify the genomic regions in the soybean genome associated with seed weight and to identify the candidate genes in linkage disequilibrium blocks where the most significant SNPs were located. This study identified significant SNPs for seed weight on chromosomes 2 and 16. Furthermore, this study indicated that GmCYP78A57 (Glyma.02G119600) encoded a cytochrome P450 monooxygenase may be a possible candidate gene for controlling the seed size in soybean. We assumed that another gene on chromosome 16 may play the important role of a small additive genetic effect to reduce seed size along with GmCYP78A57. An online tool was used to identify 12 allelic variations of GmCYP78A57 with publicly available genomic sequence data. The HSW of 45 accessions having a missense mutation from the Germplasm Resources Information Network ranged from 4.4 to 17.6 g. In addition, 19 accessions were shown to be less than 10.0 g of HSW. This information can provide for the development of molecular markers to use in soybean breeding programs to release new cultivars with increased or decreased seed weight.

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“…Similarly, crop breeders usually identify genetic materials with the desired traits in various environments again to eliminate environmental effects and verify stable genotypes. Several researchers have carried out QTL mapping in multiple environments with locations × years by using at least two mapping methods and obtained good results [ 38 , 39 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of quantitative trait loci (QTLs) and candidate genes of seed Iron and zinc content in soybean [Glycine max (L.) Merr.]

et al. 2022

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Background Deciphering the hereditary mechanism of seed iron (Fe) and zinc (Zn) content in soybean is important and sustainable to address the “hidden hunger” that presently affects approximately 2 billion people worldwide. Therefore, in order to detect genomic regions related to soybean seed Fe and Zn content, a recombinant inbred line (RIL) population with 248 lines was assessed in four environments to detect Quantitative Trait Loci (QTLs) related to soybean seed Fe and Zn content. Result Wide variation was found in seed Fe and Zn content in four environments, and genotype, environment, and genotype × environment interactions had significant influences on both the seed Fe and Zn content. A positive correlation was observed between seed Fe content and seed Zn content, and broad-sense heritability (H2) of seed Fe and Zn content were 0.73 and 0.75, respectively. In this study, five QTLs for seed Fe content were detected with 4.57 - 32.71% of phenotypic variation explained (PVE) and logarithm of odds (LOD) scores ranging from 3.60 to 33.79. Five QTLs controlling the seed Zn content were detected, and they individually explained 3.35 to 26.48% of the phenotypic variation, with LOD scores ranging from 3.64 to 20.4. Meanwhile, 409,541 high-quality single-nucleotide variants (SNVs) and 85,102 InDels (except intergenic regions) between two bi-parental lines were identified by whole genome resequencing. A total of 12 candidate genes were reported in one major QTL for seed Fe content and two major QTLs for seed Zn content, with the help of RNA-Seq analysis, gene ontology (GO) enrichment, gene annotation, and bi-parental whole genome sequencing (WGS) data. Conclusions Limited studies were performed about microelement of soybean, so these results may play an important role in the biofortification of Fe and Zn and accelerate the development of marker-assisted selection (MAS) for breeding soybeans fortified with iron and zinc.

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QTL mapping and candidate gene mining for soybean seed weight per plant

Cited by 15 publications

References 30 publications

Bobot 1000 Butir dan Kualitas Benih Tujuh Lot Varietas Cabai Open Pollinated (OP)

Bobot 1000 Butir dan Kualitas Benih Tujuh Lot Varietas Cabai Open Pollinated (OP)

Genome-Wide Association Mapping for Seed Weight in Soybean with Black Seed Coats and Green Cotyledons

Identification of quantitative trait loci (QTLs) and candidate genes of seed Iron and zinc content in soybean [Glycine max (L.) Merr.]

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