Browsing by Author "Malik, Ankit"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Rice Pangenome Genotyping Array: an efficient genotyping solution for pangenome-based accelerated genetic improvement in rice
    (John Wiley & Sons, 2022) Daware, Anurag; Malik, Ankit; Srivastava, Rishi; Das, Durdam; Ellur, Ranjith K; Singh, Ashok K; Tyagi, Akhilesh K.; Parida, Swarup K.
    The advent of the pangenome era has unraveled previously unknown genetic variation existing within diverse crop plants, including rice. This untapped genetic variation is believed to account for a major portion of phenotypic variation existing in crop plants. However, the use of conventional single reference-guided genotyping often fails to capture large portion of this genetic variation leading to a reference bias. This makes it difficult to identify and utilize novel population/cultivar-specific genes for crop improvement. Thus, we developed a rice pangenome genotyping array (RPGA) harboring probes assaying 80K single nucleotide polymorphisms (SNPs) and presence-absence variants (PAVs) spanning the entire 3K rice pangenome. This array provides a simple, user-friendly and cost-effective (60 to 80 USD per sample) solution for rapid pangenome-based genotyping in rice. The GWAS conducted using RPGA-SNP genotyping data of a rice diversity panel detected a total of 42 loci, including previously known as well as novel genomic loci regulating grain size/weight traits in rice. Eight of these identified trait-associated loci (dispensable loci) could not be detected with conventional single reference genome-based GWAS. A WD repeat-containing PROTEIN 12 gene underlying one of such dispensable locus on chromosome 7 (qLWR7) along with other non-dispensable loci were subsequently detected using high-resolution QTL mapping confirming authenticity of RPGA-led GWAS. This demonstrates the potential of RPGA-based genotyping to overcome reference bias. The application of RPGA-based genotyping for population structure analysis, hybridity testing, ultra-high-density genetic map construction and chromosome-level genome assembly, and marker-assisted selection was also demonstrated. A web application (http://www.rpgaweb.com) was further developed to provide easy to use platform for the imputation of RPGA-based genotyping data using 3K Rice Reference Panel and subsequent GWAS.