Discovery of genomic regions and candidate genes controlling shelling percentage using QTL‐seq approach in cultivated peanut (Arachis hypogaea L.)

Abstract

Summary Cultivated peanut ( Arachis hypogaea L.) is an important grain legume providing high‐quality cooking oil, rich proteins and other nutrients. Shelling percentage ( SP ) is the 2nd most important agronomic trait after pod yield and this trait significantly affects the economic value of peanut in the market. Deployment of diagnostic markers through genomics‐assisted breeding ( GAB ) can accelerate the process of developing improved varieties with enhanced SP . In this context, we deployed the QTL ‐seq approach to identify genomic regions and candidate genes controlling SP in a recombinant inbred line population (Yuanza 9102 × Xuzhou 68‐4). Four libraries (two parents and two extreme bulks) were constructed and sequenced, generating 456.89–790.32 million reads and achieving 91.85%–93.18% genome coverage and 14.04–21.37 mean read depth. Comprehensive analysis of two sets of data (Yuanza 9102/two bulks and Xuzhou 68‐4/two bulks) using the QTL ‐seq pipeline resulted in discovery of two overlapped genomic regions (2.75 Mb on A09 and 1.1 Mb on B02). Nine candidate genes affected by 10 SNP s with non‐synonymous effects or in UTR s were identified in these regions for SP . Cost‐effective KASP (Kompetitive Allele‐Specific PCR ) markers were developed for one SNP from A09 and three SNP s from B02 chromosome. Genotyping of the mapping population with these newly developed KASP markers confirmed the major control and stable expressions of these genomic regions across five environments. The identified candidate genomic regions and genes for SP further provide opportunity for gene cloning and deployment of diagnostic markers in molecular breeding for achieving high SP in improved varieties.

Next‐generation sequencing identified genomic region and diagnostic markers for resistance to bacterial wilt on chromosome B02 in peanut (Arachis hypogaea L.)

“…According to the original QTL‐seq approach (Takagi et al ., ), only one parent was required to be used as reference to analyse the reads of two extreme bulks, and previous reports followed this principle in multiple crops (Deokar et al ., ; Hua et al ., ; Pandey et al ., ; Singh et al ., ). Recently, in our one such study for shelling percentage in peanut, we found that when both parents were sequenced and used to analyse the reads of two extreme bulks in parallel, the comparative analysis of the two sets of results generated by QTL‐seq increased the mapping efficiency and accuracy of shelling percentage in peanut (Luo et al ., ). Therefore, we used this similar strategy in the present study for mapping BWR (Figure ) and found significance differences between the two sets of results as well.…”

Ethylene‐responsive factor 4 is associated with the desirable rind hardness trait conferring cracking resistance in fresh fruits of watermelon

“…After the release of the watermelon genome (Guo et al , ), watermelon has become an ideal model crop for research on traits such as fruit cracking, size, shape, rind colour, and flesh texture due to being an annual and thus having a shorter life cycle than other perennial fruit crops. With the advancement of next‐generation sequencing (NGS) technology, sequencing‐based gene mining strategies, such as bulk segregant analysis (BSA), genetic mapping and genome‐wide association study (GWAS), have been widely used as affordable, efficient and routine approaches to dissect crop traits in rice (Wang et al , ) tomato (Chapman et al , ; Soyk et al , ), cucumber(Li et al , ; Xu et al , ), peanut(Luo et al , ), chickpea(Deokar et al , ),spinach(She et al , ), apple(Jia et al , ) and melon (Hu et al , ). Recently, genes or QTLs related to sugar transporter (Ren et al , ), dwarfism (Dong et al , ) and lobed leaves (Wei et al , ) have been reported in watermelon.…”

Whole‐genome resequencing‐based QTL‐seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut

“…() and Luo et al . ( and) Luo et al . () have demonstrated the benefits of QTL‐seq approach; identification of candidate gene(s) and development of markers in the candidate genomic region.…”

“…There are several sequencingbased trait-mapping approaches which provide faster discovery of candidate genes and facilitate marker development; and one of such approach for trait mapping is QTL-seq (Pandey et al, 2017;Takagi et al, 2013). It has been successfully deployed in several important crop species for trait dissection such as rice blast disease (Takagi et al, 2013), grain length and weight in rice (Yaobin et al, 2018), flowering time in tomato (Ruangrak et al, 2018), foliar disease resistance (Clevenger et al, 2018;Pandey et al, 2017), shelling percentage (Luo et al, 2019a) and bacterial wilt resistance (Luo et al, 2019b) in groundnut, 100 seed weight and root/total plant dry weight in chickpea (Singh et al, 2016a), plant height in soybean (Zhang et al, 2018), etc. Many of these efforts facilitated successful development of diagnostic markers which are being deployed in GAB.…”

“…Of the available sequencing-based approaches, QTL-seq approach offers great benefits by identifying genomic region(s) and candidate genes leading to development of diagnostic markers. This approach has already been deployed successfully in some legume crops including groundnut for foliar disease (rust and LLS) resistance (Pandey et al, 2017), shelling percentage (Luo et al, 2019a), bacterial wilt (Luo et al, 2019b) and test a colour (Zhao et al, 2019). QTL-seq approach has also been successfully deployed in discovery of genomic regions and candidate genes with high accuracy and precision in some other crops such as cucumber (Lu et al, 2014), tomato (Illa-Berenguer et al, 2015), pigeonpea (Singh et al, 2016a) and chickpea (Das et al, 2015;Singh et al, 2016b).…”