GWAS-informed genomic selection for cold tolerance in pepper (Capsicum annuum L.).

Abstract

Background Breeding for cold tolerance in pepper (Capsicum annuum L.) is critical to mitigate yield losses caused by unpredictable temperature fluctuations associated with climate change. However, genetic improvement of this trait is hindered by challenges in accurate phenotyping, particularly at the adult stage, and by its complex genetic architecture involving numerous minor-effect loci. While genomic selection (GS) offers a promising solution to accelerate genetic gain, its predictive ability is often limited by statistical noise from uninformative markers within whole-genome marker sets. This study aimed to overcome this limitation by developing a robust phenotypic index and implementing a genome-wide association study (GWAS)-informed GS strategy. Results We phenotyped 192 pepper accessions from a core collection for cold tolerance using a visual survival score (Surv) and a newly developed composite cold-tolerance index (CTI). Both CTI (h 2 = 0.55) and Surv (h 2 = 0.53) showed moderate heritability, suggesting a substantial contribution from additive genetic variance to the phenotypic variation of cold tolerance in adult plants. GWAS identified 13 candidate genomic regions associated with cold tolerance; these regions included TRM9, CAP1, and PP2A-2, genes previously implicated in abiotic stress responses. For genomic prediction, we applied nested CV and LOOCV in which GWAS and marker selection were performed within the training set before fitting the prediction model, so that phenotypic information from the test individuals was not incorporated into the marker selection step. Compared with the full marker set of 73,502 markers, the best GWAS-selected marker sets achieved prediction accuracies of 0.237 for CTI and 0.197 for Surv in nested CV, and 0.349 for CTI and 0.294 for Surv in LOOCV. At the same marker numbers and model conditions, random marker sets showed lower accuracies of 0.205 and 0.166 for the nested CV, and 0.068 and - 0.064 for the LOOCV, respectively. Conclusions Our study demonstrates that assessing cold tolerance via the CTI helps overcome the limitations of discrete survival scoring. By turning ordinal data into a continuous spectrum, the CTI can unmask hidden genetic variation. In addition, GWAS identified candidate genomic regions and genes associated with cold response, and nested CV and LOOCV showed that GWAS-selected marker sets could achieve higher prediction accuracy than the full marker set and random marker sets of the same marker number. This integrated framework offers a practical approach for interpreting the genetic basis of adult-stage cold tolerance in pepper and improving the efficiency of genomic prediction models for complex abiotic stress traits.

Plant phenotyping relevance

成体ペッパーの耐寒性を測定する新規複合表現型指標（CTI）の開発・評価が明示され、単なる形質の routine 測定を超えて表現型取得法の中心的貢献となっている。

Code and data availability

The supplied blocks describe phenotyping of 192 pepper accessions, GWAS, and genomic selection analyses, but contain no public phenotype dataset, image/sensor inputs, author code repository, or trained model with an availability statement or URL. Supplementary tables (e.g., Table S1 accession list) are mentioned but no

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