Accelerating public sector rice breeding with high-density KASP markers derived from whole genome sequencing of indica rice

Katherine Steele, Mark Quinton-Tulloch, Resham B. Amgai, Rajeev Dhakal, Shambhu P. Khatiwada, Darshna Vyas, Martin Heine, John Witcombe

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    Abstract

    Few public sector rice breeders have the capacity to use NGS-derived markers in their breeding programmes despite rapidly expanding repositories of rice genome sequence data. They rely on >18,000 mapped microsatellites (SSRs) for marker-assisted selection (MAS) using gel analysis. A lack of knowledge about target SNP and InDel variant loci has hampered their uptake of KASP, a proprietary technology of LGC genomics. KASP is a cost-effective single-step genotyping technology, cheaper than SSRs and more flexible than genotyping by sequencing (GBS) or array based genotyping when used in selection programmes. Before this study there were 2,015 rice KASP in the public domain, mainly identified by array-based screening leaving large proportions of the rice genome with no KASP marker coverage. Here we have addressed the urgent need for a wide choice of appropriate rice KASP markers, and demonstrated that NGS can provide full genome marker coverage. Through resequencing of nine indica rice breeding lines or released varieties, this study has identified 2.5 million variant sites. Stringent filtering of variants generated 1.3 million potential KASP assay designs, including 92,500 potential functional markers. This strategy delivers a 650-fold increase in potential selectable KASP markers at a density of 3.1 marker per 1 kb in the indica crosses analysed with 377,178 polymorphic KASP marker design sites on average per cross. This knowledge is available to breeders and has been utilised to improve the efficiency of public sector breeding in Nepal, enabling identification of polymorphic KASP at any mapped trait or QTL in relevant crosses. Validation of 39 new KASP was carried out by genotyping progeny from a range of crosses and detecting segregating alleles to aid trait selection during marker-assisted backcrossing, where target traits included rice blast and BLB resistance. Furthermore, we provide the software for plant breeders to generate KASP designs from their own datasets.
    Original languageEnglish
    Article number38
    JournalMolecular Breeding
    Volume38
    Early online date7 Mar 2018
    DOIs
    Publication statusPublished - Apr 2018

    Keywords

    • Bacterial blight
    • genomic selection
    • KASP
    • marker-assisted selection
    • next generation sequencing
    • physical mapping
    • rice blast
    • single-nucleotide polymorphism
    • allele mining software

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