Evidence map›Paper›PMID 41044649›Full record

ArticlePlant methods2025

Accurate detections of the heterozygous SNPs with rice genomic data and prediction of de novo spontaneous mutation rate.

Elias George Balimponya, Maria Stefanie Dwiyanti, Koichi Yamamori, Shuntaro Sakaguchi, Yoshitaka Kanaoka, Yohei Koide, Yuji Kishima

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Article in Plant methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Elias George BalimponyaLaboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita-Ku, Sapporo, 060-8589, Japan. egeorge2012@gmail.com.
Maria Stefanie DwiyantiLaboratory of Applied Plant Genomics, Research Faculty of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita-Ku, Sapporo, 060-8589, Japan.
Koichi YamamoriLaboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita-Ku, Sapporo, 060-8589, Japan.
Shuntaro SakaguchiLaboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita-Ku, Sapporo, 060-8589, Japan.
Yoshitaka KanaokaLaboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita-Ku, Sapporo, 060-8589, Japan.
Yohei KoideLaboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita-Ku, Sapporo, 060-8589, Japan.
Yuji KishimaLaboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita-Ku, Sapporo, 060-8589, Japan. kishima@agr.hokudai.ac.jp.

Funding

Japan Society for the Promotion of Science, Japan (19H00937 and 23H02180Science and Technology Research Partnership for Sustainable Development RiceBACS
6 · The paper itself

Abstract

backgroundThe use of Illumina sequencing technologies has enabled the identification and removal of mutations in various plant species. However, the Illumina sequencing method requires a considerable amount of data to ensure its integrity and quality due to the enormous number of false positives. This study aimed to explore an effective genomic data analysis for the detection of heterozygous variant (HV) in rice varieties.

resultsWe compared the accuracy of four combinations of mapping tools and variant calling pipelines and selected BWA-MEM2 with GATK4.3 HaplotypeCaller. To detect heterozygous de novo polymorphisms such as HVs in the three different rice varieties (Nipponbare, Kitaake, and Hinohikari), we adopted the following cost-saving procedures; secondary references were created in Nipponbare and Kitaake, and generation-based comparison was performed in Hinohikari. The similar HVs were estimated by the three varieties to range from 2.55814 × 10

conclusionsWe have developed a methodology for the detection of true positive HVs within Illumina sequencing techniques. This system removed false positive HVs, allowing for the estimation of true positive HVs and, consequently, the estimation of the mutation rate. The study outlines a clear, step-by-step procedure that can be employed to detect true HVs in different organisms.

Indexed as

False positive variantsHeterozygous variantsIllumina sequencingMutation rateRiceSpontaneous mutation

Identifiers

PMID41044649
PMCPMC12495679

What Socratic holds

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