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Identification of quantitative trait loci underlying five major agronomic traits of soybean in three biparental populations by specific length amplified fragment sequencing (SLAF-seq).

ABSTRACT: Flowering time, plant height, branch number, node numbers of main stem and pods per plant are important agronomic traits related to photoperiodic sensitivity, plant type and yield of soybean, which are controlled by multiple genes or quantitative trait loci (QTL). The main purpose of this study is to identify new QTL for five major agronomic traits, especially for flowering time. Three biparental populations were developed by crossing cultivars from northern and central China. Specific loci amplified fragment sequencing (SLAF-seq) was used to construct linkage map and QTL mapping was carried out. A total of 10 QTL for flowering time were identified in three populations, some of which were related to E1 and E2 genes or the other reported QTL listed in Soybase. In the Y159 population (Xudou No.9 × Kenfeng No.16), QTL for flowering time on chromosome 4, qFT4_1 and qFT4_2 were new. Compared with the QTL reported in Soybase, 1 QTL for plant height (PH), 3 QTL for branch number (BR), 5 QTL for node numbers of main stem, and 3 QTL for pods per plant were new QTL. Major E genes were frequently detected in different populations indicating that major the E loci had a great effect on flowering time and adaptation of soybean. Therefore, in order to further clone minor genes or QTL, it may be of great significance to carefully select the genotypes of known loci. These results may lay a foundation for fine mapping and clone of QTL/genes related to plant-type, provided a basis for high yield breeding of soybean.

SUBMITTER: Hu B

PROVIDER: S-EPMC8679901 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Hemp (Cannabis sativa L.), an ancient crop, is a significant source of high-quality fiber that primarily caters to the textile industry worldwide. Fiber content is a crucial quantitative trait for evaluating fiber yield in hemp. Understanding the genetic mechanisms involved in hemp breeding is essential for improving yield. In this study, we developed 660 F1 plants from a cross between Jindao-15 (high fiber content fiber-use variety) and Fire No.1 (low fiber content fiber-use variety), and thirty plants each with high and low fiber content were selected from 305 monoecious plants of this population according to 5%-10% of population size for quantitative traits. The DNA from these plants was extracted to establish two bulk DNA pools and then subjected to the restriction digestion by the enzymes RsaI and HaeIII to obtain 314-364 bp digestion fragments and subjected to sequencing using specific length amplified fragment sequencing (SLAF-seq). Finally, we successfully developed 368,404 SLAF tags, which led to the detection of 25,133 high-quality SNPs. Combing with the resequencing results of parents, the SNPs of mixed pools were then subjected to the SNP-Index correlation algorithm, which revealed four candidate regions related to fiber content traits on Chromosome 1, with a length of 8.68 Mb and containing 389 annotated genes. The annotation information and the comparison results identified 15 genes that were highly likely to modulate the fiber content of hemp. Further, qPCR validation identified six genes (LOC115705530, LOC115705875, LOC115704794, LOC115705371, LOC115705688 and LOC115707511) that were highly positively correlated with influencing the hemp fiber content. These genes were involved in the transcription regulation, auxin and water transportion, one carbon and sugar metabolism. And non-synnoumous mutation SNPs which may play vital role in influencing the fiber content were detected in LOC115705875, LOC115704794, LOC115705688 and LOC115707511. Thus, our study highlights the importance of the combined use of SLAF-Seq and Bulked Segregant analysis (BSA) to locate genes related to hemp fiber content rapidly. Hence, our study provides novel mechanistic inputs for the fast identification of genes related to important agronomic traits of hemp and other crops catering to the textile industry.

Dataset Information

Identification of quantitative trait loci underlying five major agronomic traits of soybean in three biparental populations by specific length amplified fragment sequencing (SLAF-seq).

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