QTL mapping of drought tolerance traits in soybean with SLAF sequencing

Ren, Honglei; Han, Ji; Wang, Xingrong; Zhang, Bo; Yu, Lili; Gao, Huawei; Hong, Huilong; Sun, Rongli; Tian, Yu; Qi, Xusheng; Liu, Zhangxiong; Wu, Xiaoxia; Qiu, Lijuan

doi:10.1016/j.cj.2020.04.004

Cited by 25 publications

(13 citation statements)

References 57 publications

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“…In recent years, SNP as a class of ideal marker, has been extensively used as an effective tool to construct high-density maps basing on next-generation sequencing techniques ( Liu et al, 2013 ; Zhou et al, 2018 ; Jian et al, 2019 ). SLAF-seq technology, a cost-effective platform, is recently developed for SNP exploitation, domestication analysis, high-density linkage map construction, genome-wide linkage analysis, and association analysis of agronomic traits ( Sun et al, 2013 ; Zhou et al, 2017 ; Zheng et al, 2019 ; Ren et al, 2020 ). This technology was adopted in our study, through which, 3,356 high-quality SNPs were obtained, and a high-resolution genetic map was constructed ( Supplementary Table S2 and Supplementary Figure S3 ).…”

Section: Discussionmentioning

confidence: 99%

Quantitative Trait Locus Mapping and Identification of Candidate Genes Controlling Flowering Time in Brassica napus L.

Zhang

et al. 2021

Front. Plant Sci.

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Flowering time plays a vital role in determining the life-cycle period, yield, and seed quality of rapeseed (Brassica napus L.) in certain environments. Quantitative trait locus (QTL) mapping to identify the genetic architecture of genes controlling flowering time helps accelerate the early maturity breeding process. In this study, simple sequence repeats (SSR) and specific-locus amplified fragment sequencing (SLAF-seq) technologies were adopted to map the QTLs for flowering time in four environments. As a result, three target intervals, FTA09, FTA10, and FTC05 were identified. Among this, FTA09 was considered as a novel interval, FTA10 and FTC05 as stable regions. Based on the parental re-sequencing data, 7,022 single nucleotide polymorphisms (SNPs) and 2,195 insertion-deletions (InDels) between the two parents were identified in these three target regions. A total of 186 genes possessed genetic variations in these intervals, 14 of which were related to flowering time involved in photoperiod, circadian clock, vernalization, and gibberellin pathways. Six InDel markers linked to flowering time were developed in the three target intervals, indicating that the results were credible in this study. These results laid a good foundation for further genetic studies on flowering-time regulation in B. napus L.

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Section: Discussionmentioning

confidence: 99%

Quantitative Trait Locus Mapping and Identification of Candidate Genes Controlling Flowering Time in Brassica napus L.

Zhang

et al. 2021

Front. Plant Sci.

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“…The SLAF‐seq technology has many SNP markers compared with other molecular technologies (Ren et al., 2020). This technology uses a combination of site‐specific amplification and high‐throughput sequencing.…”

Section: Discussionmentioning

confidence: 99%

“…The specific length amplified fragment sequencing (SLAF‐seq) technology, as a simplified genome sequencing technology, can realize the development of high‐throughput molecular markers (SNP, insertion–deletion markers) at one time (Sun et al., 2013). Specific length amplified fragment sequencing has been widely used in constructing positive genetic maps of various plants (Liu et, al., 2016; Shang et al., 2016; Zhao et al., 2016; Wang et al., 2017; Li et al., 2019; Ren et al., 2020). Simple sequence repeat (SSR) markers, also known as short tandem repeats, have been widely used in genetic map construction, germplasm resource identification, and genetic diversity analysis because of their reproducibility, high polymorphism, and codominant inheritance (Dong et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

QTL analysis of flowering‐related traits by specific length amplified fragment sequencing in melon

et al. 2021

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Melon (Cucumis melo L., 2n = 24) belongs to the family Cucurbitaceae and is an important vegetable crop. This study aimed to investigate the quantitative trait loci (QTL) of flowering‐related traits to understand the genetic inheritance and candidate gene of flowering‐related traits. The specific length amplified fragment sequencing (SLAF‐seq) technology was used to construct a genetic map of 115 individual plants in the melon F2 population. A total of 82.6 Gb of data were generated using SLAF‐seq. A genetic map was constructed with 10,596 specific length amplified fragment markers in 12 linkage groups, which spanned 1,383.88 cM with an average distance of 0.13 cM between markers. Ten QTL of flowering‐related traits were detected, which explained 2.16–19.34% of the phenotypic variance. The logarithm of the odds (LOD) values ranged from 3.5 to 24.9. Ninety‐four F2:3 families were used for mapping mft and fft in candidate regions by simple sequence repeat (SSR) and cleaved amplified polymorphic sequences (CAPS) markers. The mapping results showed that mft2.1 and fft2.1 were located in the same region, between CmSSR07071 and CmSSR07102. By gene annotation, 36 candidate genes were detected in this region, 26 of which were annotated. Quantitative reverse transcription–polymerase chain reaction (PCR) showed that candidate genes, including WRKY transcription factor and AP2/ERF and B3 domain‐containing transcription factor, were differentially expressed in female and male flowers in the flower budding stages. These genes may provide the theoretical foundation for gene cloning and genetic transformation in melons.

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“…The bin markers that met the criteria were used to construct a high-density genetic map. As per general genetic coding rules, the model "aa × bb" was used to analyze the genotype bin markers in the 158 RILs (Ren et al, 2020).…”

Section: Whole-genome Resequencing Snp Calling and Genotypingmentioning

confidence: 99%

Genome-Wide Association Analysis Combined With Quantitative Trait Loci Mapping and Dynamic Transcriptome Unveil the Genetic Control of Seed Oil Content in Brassica napus L.

et al. 2022

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Rapeseed, an allotetraploid oil crop, provides vegetable oil for human consumption. The growing demand for oilseeds has necessitated the development of rapeseed varieties with improved quality. Therefore, a clear understanding of the genetic basis underlying the seed oil content (SOC) is required. In this study, a natural population comprising 204 diverse accessions and recombinant inbred lines (RILs) derived from Brassica napus and Sinapis alba via distant hybridization were collected for genome-wide association analysis (GWAS) and quantitative trait loci (QTL) mapping of the SOC trait, respectively. The variable coefficient of the RIL and natural populations ranged from 7.43 to 10.43% and 8.40 to 10.91%. Then, a high-density linkage map was constructed based on whole genome re-sequencing (WGS); the map harbored 2,799 bin markers and covered a total distance of 1,835.21 cM, with an average marker interval of 0.66 cM. The QTLs for SOC on chromosome A07 were stably detected in both single and multiple environments. Finally, a novel locus qA07.SOC was identified as the major QTL for SOC based on the GWAS and RIL populations. In addition, the RNA-seq results showed that photosynthesis, lipid biosynthesis proteins, fatty acid metabolism, and unsaturated fatty acid biosynthesis were significantly different between the developed seeds of the two parents of the RIL population. By comparing the variation information and expression levels of the syntenic genes within qA07.SOC and its syntenic genomic regions, as well as through haplotype analysis via GWAS, BnaA07.STR18, BnaA07.NRT1, and BnaA07g12880D were predicted as candidate genes in the qA07.SOC interval. These stable QTLs containing candidate genes and haplotypes can potentially provide a reliable basis for marker-assisted selection in B. napus breeding for SOC.

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QTL mapping of drought tolerance traits in soybean with SLAF sequencing

Cited by 25 publications

References 57 publications

Quantitative Trait Locus Mapping and Identification of Candidate Genes Controlling Flowering Time in Brassica napus L.

Quantitative Trait Locus Mapping and Identification of Candidate Genes Controlling Flowering Time in Brassica napus L.

QTL analysis of flowering‐related traits by specific length amplified fragment sequencing in melon

Genome-Wide Association Analysis Combined With Quantitative Trait Loci Mapping and Dynamic Transcriptome Unveil the Genetic Control of Seed Oil Content in Brassica napus L.

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