Single-Nucleotide Polymorphism Chip Platforms in Rice (Oryza sativa) Genomics and Their Potential for Precision Breeding

Abstract

Single-nucleotide polymorphism (SNP) arrays provide reproducible, accurate, and scalable genotyping for rice research and cultivar development. This review critically evaluates the design and development of major rice SNP platforms and defines their value within a rapidly changing genotyping landscape. In contrast to earlier platform-centered summaries, this review connects array selection with the complete breeding pathway from germplasm assessment and locus discovery to functional validation, marker-assisted transfer, genomic selection, varietal authentication, and pre-breeding. SNP arrays are compared with genotyping-by-sequencing, double-digest restriction site-associated DNA sequencing, low-pass sequencing, whole-genome resequencing, targeted sequencing, and long-read sequencing in terms of cost, throughput, data completeness, computational demand, marker discovery, and population transferability. Candidate-locus validation through gene-expression analysis, haplotype analysis, near-isogenic lines, RNA interference, transgenic complementation, clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR/Cas) editing, and field evaluation is also examined. Pangenome resources and the contributions of structural variants, presence/absence variations, and copy number variations to probe design and trait analysis receive particular attention. The review further assesses ascertainment bias, weak detection of rare alleles, genotype-cluster errors, limited portability across distant germplasm, and reduced genomic prediction across populations or environments. Future priorities include multi-omics integration, climate-resilient rice improvement, modular panels, imputation anchor loci, and economical deployment through low-density assays, shared facilities, and kompetitive allele-specific polymerase chain reaction conversion. The value of SNP arrays is greatest when stable genotype calls, large sample numbers, and repeated use across breeding cycles are required. Their practical contribution should be judged by prediction accuracy, selection cost, cycle duration, donor-segment control, realized genetic gain, and cultivar deployment.