Genomic and Phenotypic Diversity of Cultivated and Wild Tomatoes with Varying Levels of Heat Tolerance

Abstract

Assessment of genetic variability in heat-tolerant tomato germplasm is a pre-requisite to improve yield and fruit quality under heat stress. We assessed the population structure and diversity in a panel of three Solanum pimpinellifolium (wild tomatoes) and 42 S. lycopersicum (cultivated tomatoes) lines and accessions with varying heat tolerance levels. The DArTseq marker was used for the sequencing and 5270 informative single nucleotide polymorphism (SNP) markers were retained for the genomic analysis. The germplasm was evaluated under two heat stress environments for five yield and flower related traits. The phenotypic evaluation revealed moderate broad-sense heritabilities for fruit weight per plant and high broad-sense heritabilities for fruit weight, number of inflorescences per plant, and number of flowers per inflorescence. The hierarchical clustering based on identity by state dissimilarity matrix and UPGMA grouped the germplasm into three clusters. The cluster analysis based on heat-tolerance traits separated the germplasm collection into five clusters. The correlation between the phenotypic and genomic-based distance matrices was low (r = 0.2, p < 0.05). The joint phenotypic and genomic-based clustering grouped the germplasm collection into five clusters well defined for their response to heat stress ranging from highly sensitive to highly tolerant groups. The heat-sensitive and heat-tolerant clusters of S. lycopersicum lines were differentiated by a specific pattern of minor allele frequency distribution on chromosome 11. The joint phenotypic and genomic analysis revealed important diversity within the germplasm collection. This study provides the basis for efficient selection of parental lines to breed heat-tolerant varieties.

Combining abilities and heterotic patterns for heat tolerant traits in tomatoes (Solanum lycopersicum)

“…The NCII analysis revealed that the hybrid combinations with the highest SCA effects for FS involved one parent (BJ01, CLN1621L, ATS020, and P005) (Ayenan et al, 2022; Ayenan, Danquah, Agre, et al, 2021; Ayenan, Danquah, Hanson, et al, 2021; Ro et al, 2021). Similarly, the hybrid combinations with the highest SCA estimates for NFP involved one of the following heat‐tolerant parents (CL5915‐93D4‐1‐0‐3, ATS020, BJ01, and CLN2026D) with high performance for NFP (Ayenan et al, 2022; Ayenan, Danquah, Agre, et al, 2021; Ayenan, Danquah, Hanson, et al, 2021).…”

“…These lines were obtained from the World Vegetable Center (WorldVeg), the University of Florida, and the Council for Scientific and Industrial Research ‐ Crops Research Institute (CSIR‐CRI) in Ghana. The lines were selected for their contrasting reaction to heat stress, their origins, and their genetic and phenotypic diversity (Ayenan et al, 2022; Ayenan, Danquah, Agre, et al, 2021).…”

“…In Experiment 2, we generated a second set of hybrids using a stepwise approach. We first assessed the genetic diversity in the germplasm using phenotypic and SNP markers (Ayenan, Danquah, Agre, et al, 2021), followed by a selection of representative parental lines from each of the four clusters. Within each cluster, the parental lines were selected based on our previous success for crosses and fruit quality.…”

“…The genlight object was converted into genind object in dartR 1.9 (Gruber et al, 2018) and was subsequently subjected to the clustering analysis in factoextra (Kassambara & Mundt, 2019) based on the Roger genetic distance and Ward algorithm. The characteristics of the SNPs (distribution across the 12 chromosomes, Mutation transversion and transition, polymorphism information content, minor allele frequency) were presented in Ayenan, Danquah, Agre, et al (2021). The analyses were done in R.4..5 (R Core Team, 2021).…”

“…Breeding for heat tolerance has gained considerable interest in recent years and has become an important breeding objective in tomato improvement. In recent studies, new sources of heat tolerance were identified (Ayenan, Danquah, Agre, et al, 2021; Ayenan, Danquah, Hanson, et al, 2021). However, these genetic resources do not meet farmers' and consumers' preferences to attract high market value.…”