Effective utilization of wild relatives is key to overcoming challenges in genetic improvement of cultivated tomato, which has a narrow genetic basis; however, current efforts to decipher high-quality genomes for tomato wild species are insufficient. Here, we report chromosome-scale tomato genomes from nine wild species and two cultivated accessions, representative of Solanum section Lycopersicon, the tomato clade. Together with two previously released genomes, we elucidate the phylogeny of Lycopersicon and construct a section-wide gene repertoire. We reveal the landscape of structural variants and provide entry to the genomic diversity among tomato wild relatives, enabling the discovery of a wild tomato gene with the potential to increase yields of modern cultivated tomatoes. Construction of a graph-based genome enables structural-variant-based genome-wide association studies, identifying numerous signals associated with tomato flavor-related traits and fruit metabolites. The tomato super-pangenome resources will expedite biological studies and breeding of this globally important crop.

Background Late embryogenesis abundant (LEA) proteins are widely distributed in higher plants and play crucial roles in regulating plant growth and development processes and resisting abiotic stress. Cultivated tomato (Solanum lycopersicum) is an important vegetable crop worldwide; however, its growth, development, yield, and quality are currently severely constrained by abiotic stressors. In contrast, wild tomato species are more tolerant to abiotic stress and can grow normally in extreme environments. The main objective of this study was to identify, characterize, and perform gene expression analysis of LEA protein families from cultivated and wild tomato species to mine candidate genes and determine their potential role in abiotic stress tolerance in tomatoes. Results Total 60, 69, 65, and 60 LEA genes were identified in S. lycopersicum, Solanum pimpinellifolium, Solanum pennellii, and Solanum lycopersicoides, respectively. Characterization results showed that these genes could be divided into eight clusters, with the LEA_2 cluster having the most members. Most LEA genes had few introns and were non-randomly distributed on chromosomes; the promoter regions contained numerous cis-acting regulatory elements related to abiotic stress tolerance and phytohormone responses. Evolutionary analysis showed that LEA genes were highly conserved and that the segmental duplication event played an important role in evolution of the LEA gene family. Transcription and expression pattern analyses revealed different regulatory patterns of LEA genes between cultivated and wild tomato species under normal conditions. Certain S. lycopersicum LEA (SlLEA) genes showed similar expression patterns and played specific roles under different abiotic stress and phytohormone treatments. Gene ontology and protein interaction analyses showed that most LEA genes acted in response to abiotic stimuli and water deficit. Five SlLEA proteins were found to interact with 11 S. lycopersicum WRKY proteins involved in development or resistance to stress. Virus-induced gene silencing of SlLEA6 affected the antioxidant and reactive oxygen species defense systems, increased the degree of cellular damage, and reduced drought resistance in S. lycopersicum. Conclusion These findings provide comprehensive information on LEA proteins in cultivated and wild tomato species and their possible functions under different abiotic and phytohormone stresses. The study systematically broadens our current understanding of LEA proteins and candidate genes and provides a theoretical basis for future functional studies aimed at improving stress resistance in tomato.

Comprehensive screening of rice (Oryza sativa L. subsp. japonica Kato) germplasm resources with different nitrogen (N) efficiency levels is effective for improving N use efficiency (NUE) while reducing pollution and providing high quality, yield, and efficiency agriculture. We investigated 14 indices of 38 varieties under three N application levels to assess differences among genotypes. Rice varieties were classified for screening and identifying N efficient. Descriptive statistical analysis results indicated significant differences in relative yield, and also in NUE indices (agronomic utilization rate and partial productivity of N fertilizer). The genotype main effects and genotype–environment interaction effects (GGE) biplot analysis was used to evaluate suitable varieties, compare the stable and high yield capabilities of different varieties, find the ideal variety, and describe the correlation, discrimination and representativeness of the indices under different N application levels. Descriptive statistical, discrimitiveness and representativeness and factor analysis were used to select indices, in which the panicle number per plant and soil and plant analyzer development (SPAD) value were the key indices for evaluation and identification. Heatmap and hierarchical cluster analysis based on the average value of evaluation indices, and scatter plot based on the comprehensive value of N efficiency (P) according to formula showed that all varieties could be divided into five types under different N treatments. Our findings work toward developing N efficient rice varieties to improve NUE, reduce N fertilizer application and thus N waste, consequently mitigating the effects of rice production on the environment to ensure food security and sustainable agricultural development.