Research on Plant Genomics and Breeding

Huang, Jie; Li, Zhiyong; Zhang, Jian

doi:10.3390/ijms242015298

Cited by 1 publication

(1 citation statement)

References 23 publications

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“…Recent developments in genomics and biotechnology have paved the way for advancements in crop improvement, and breeders are now able to conduct research on the relationship between single nucleotide polymorphisms (SNPs) and various crop phenotypes at the genome-wide level. As the most prevalent form of genetic variation, genome-wide SNPs are essential for dissecting the genetic foundations of key phenotypic traits such as yield, disease resistance, and drought tolerance [5][6][7]. Leveraging the analysis and processing of genome-wide SNPs in rice breeding can markedly hasten the creation of superior varieties, thereby presenting an effective strategy to bolster food security.…”

Section: Introductionmentioning

confidence: 99%

PlantMine: A Machine-Learning Framework to Detect Core SNPs in Rice Genomics

Tong,

Chen,

Yan

et al. 2024

Genes

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As a fundamental global staple crop, rice plays a pivotal role in human nutrition and agricultural production systems. However, its complex genetic architecture and extensive trait variability pose challenges for breeders and researchers in optimizing yield and quality. Particularly to expedite breeding methods like genomic selection, isolating core SNPs related to target traits from genome-wide data reduces irrelevant mutation noise, enhancing computational precision and efficiency. Thus, exploring efficient computational approaches to mine core SNPs is of great importance. This study introduces PlantMine, an innovative computational framework that integrates feature selection and machine learning techniques to effectively identify core SNPs critical for the improvement of rice traits. Utilizing the dataset from the 3000 Rice Genomes Project, we applied different algorithms for analysis. The findings underscore the effectiveness of combining feature selection with machine learning in accurately identifying core SNPs, offering a promising avenue to expedite rice breeding efforts and improve crop productivity and resilience to stress.

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Section: Introductionmentioning

confidence: 99%