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[PD-0033] Digital Tools for Rice Genomics and Phenomics to Accelerate Breeding
Locedie Mansueto(Locedie Mansueto ),Lord Hendrix Barboza(Lord Hendrix Barboza ),Venice Juanillas(Venice Juanillas ),Jeffrey Detras(Jeffrey Detras ),Songwan Joun(Songwan Joun),Frances Nikki Borja(Franc 한국육종학회 2022 한국육종학회 공동학술발표집 Vol.2022 No.-
Applying High-Throughput SNP Genotyping and Sequencing to Accelerate Progress in Rice Breeding
Michael J. Thomson,Christine Jade Dilla-Ermita,Maria Ymber Reveche,Maria Dwiyanti,Geraldine Malitic,Geisha Sanchez,Nadia Vieira,Venice Juanillas,Ramil Mauleon,Bertrand Collard,Joong Hyoun Chin,Eero Ni 한국육종학회 2014 한국육종학회 심포지엄 Vol.2014 No.07
We are currently developing a high-throughput single nucleotide polymorphism (SNP) genotyping service at IRRI to accelerate progress in rice breeding by providing rapid and cost-effective marker services. SNP marker development and validation is being performed based on cloned genes and QTLs, GWAS hits, and whole genome sequence data to identify predictive SNP markers at important genes for key traits for the breeding programs. Trait-based and targeted SNPs are being deployed in sets of 24 and 96 SNPs on a Fluidigm EP1 system. At the same time, 384 SNP sets and a 6K SNP chip developed by Susan McCouch at Cornell University are being used for higher density genome scans on an Illumina system. Genotyping by sequencing (GBS) approaches with 96 and 384 barcoded samples per sequence lane are also being evaluated in comparison to SNP array technology based on the number of loci, call rates, turnaround times, and cost per sample. An efficient sample processing workflow with an integrated LIMS is also being optimized to enable high throughput genotyping with sample tracking to minimize errors. Moreover, web-based SNP data analysis tools have been deployed through the IRRI Galaxy workbench to speed up SNP data analysis. Future efforts will focus on large-scale deployment of GBS across breeding materials to enable QC genotyping, tracking of donor introgressions, and integration of genome-wide prediction into the variety development pipelines. The large-scale application of high-density markers will help transform IRRI’s rice breeding programs and increase the rate of genetic gain towards developing high-yielding, stress-tolerant varieties for target environments and market segments