Tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response

Temperature-dependent jumonji demethylase modulates flowering time by targeting H3K36me2/3 in Brassica rapa

Global warming has a severe impact on the flowering time and yield of crops. Histone modifications have been well-documented for their roles in enabling plant plasticity in ambient temperature. However, the factor modulating histone modifications and their involvement in habitat adaptation have remained elusive. In this study, through genome-wide pattern analysis and quantitative-trait-locus (QTL) mapping, we reveal that BrJMJ18 is a candidate gene for a QTL regulating thermotolerance in thermotolerant B. rapa subsp. chinensis var. parachinensis (or Caixin, abbreviated to Par). BrJMJ18 encodes an H3K36me2/3 Jumonji demethylase that remodels H3K36 methylation across the genome. We demonstrate that the BrJMJ18 allele from Par (BrJMJ18Par) influences flowering time and plant growth in a temperature-dependent manner via characterizing overexpression and CRISPR/Cas9 mutant plants. We further show that overexpression of BrJMJ18Par can modulate the expression of BrFLC3, one of the five BrFLC orthologs. Furthermore, ChIP-seq and transcriptome data reveal that BrJMJ18Par can regulate chlorophyll biosynthesis under high temperatures. We also demonstrate that three amino acid mutations may account for function differences in BrJMJ18 between subspecies. Based on these findings, we propose a working model in which an H3K36me2/3 demethylase, while not affecting agronomic traits under normal conditions, can enhance resilience under heat stress in Brassica rapa.

Low-density SNP markers with high prediction accuracy of genomic selection for bacterial wilt resistance in tomato

Bacterial wilt (BW) is a soil-borne disease that leads to severe damage in tomato. Host resistance against BW is considered polygenic and effective in controlling this destructive disease. In this study, genomic selection (GS), which is a promising breeding strategy to improve quantitative traits, was investigated for BW resistance. Two tomato collections, TGC1 (n = 162) and TGC2 (n = 191), were used as training populations. Disease severity was assessed using three seedling assays in each population, and the best linear unbiased prediction (BLUP) values were obtained. The 31,142 SNP data were generated using the 51K Axiom array™ in the training populations. With these data, six GS models were trained to predict genomic estimated breeding values (GEBVs) in three populations (TGC1, TGC2, and combined). The parametric models Bayesian LASSO and RR-BLUP resulted in higher levels of prediction accuracy compared with all the non-parametric models (RKHS, SVM, and random forest) in two training populations. To identify low-density markers, two subsets of 1,557 SNPs were filtered based on marker effects (Bayesian LASSO) and variable importance values (random forest) in the combined population. An additional subset was generated using 1,357 SNPs from a genome-wide association study. These subsets showed prediction accuracies of 0.699 to 0.756 in Bayesian LASSO and 0.670 to 0.682 in random forest, which were higher relative to the 31,142 SNPs (0.625 and 0.614). Moreover, high prediction accuracies (0.743 and 0.702) were found with a common set of 135 SNPs derived from the three subsets. The resulting low-density SNPs will be useful to develop a cost-effective GS strategy for BW resistance in tomato breeding programs.

Exploring the gene expression network involved in the heat stress response of a thermotolerant tomato genotype

BACKGROUND

The increase in temperatures due to the current climate change dramatically affects crop cultivation, resulting in yield losses and altered fruit quality. Tomato is one of the most extensively grown and consumed horticultural products, and although it can withstand a wide range of climatic conditions, heat stress can affect plant growth and development specially on the reproductive stage, severely influencing the final yield. In the present work, the heat stress response mechanisms of one thermotolerant genotype (E42) were investigated by exploring its regulatory gene network. This was achieved through a promoter analysis based on the identification of the heat stress elements (HSEs) mapping in the promoters, combined with a gene co-expression network analysis aimed at identifying interactions among heat-related genes.

RESULTS

Results highlighted 82 genes presenting HSEs in the promoter and belonging to one of the 52 gene networks obtained by the GCN analysis; 61 of these also interact with heat shock factors (Hsfs). Finally, a list of 13 candidate genes including two Hsfs, nine heat shock proteins (Hsps) and two GDSL esterase/lipase (GELPs) were retrieved by focusing on those E42 genes exhibiting HSEs in the promoters, interacting with Hsfs and showing variants, compared to Heinz reference genome, with HIGH and/or MODERATE impact on the translated protein. Among these, the Gene Ontology annotation analysis evidenced that only LeHsp100 (Solyc02g088610) belongs to a network specifically involved in the response to heat stress.

CONCLUSIONS

As a whole, the combination of bioinformatic analyses carried out on genomic and trascriptomic data available for tomato, together with polymorphisms detected in HS-related genes of the thermotolerant E42 allowed to determine a subset of candidate genes involved in the HS response in tomato. This study provides a novel approach in the investigation of abiotic stress response mechanisms and further studies will be conducted to validate the role of the highlighted genes.

Revitalizing agriculture: next-generation genotyping and -omics technologies enabling molecular prediction of resilient traits in the Solanaceae family

This review highlights -omics research in Solanaceae family, with a particular focus on resilient traits. Extensive research has enriched our understanding of Solanaceae genomics and genetics, with historical varietal development mainly focusing on disease resistance and cultivar improvement but shifting the emphasis towards unveiling resilience mechanisms in genebank-preserved germplasm is nowadays crucial. Collecting such information, might help researchers and breeders developing new experimental design, providing an overview of the state of the art of the most advanced approaches for the identification of the genetic elements laying behind resilience. Building this starting point, we aim at providing a useful tool for tackling the global agricultural resilience goals in these crops.

Rapid and low-cost screening for single and combined effects of drought and heat stress on the morpho-physiological traits of African eggplant (Solanum aethiopicum) germplasm

Drought and heat are two stresses that often occur together and may pose significant risks to crops in future climates. However, the combined effects of these two stressors have received less attention than single-stressor investigations. This study used a rapid and straightforward phenotyping method to quantify the variation in 128 African eggplant genotype responses to drought, heat, and the combined effects of heat and drought at the seedling stage. The study found that the morphophysiological traits varied significantly among the 128 eggplants, highlighting variation in response to abiotic stresses. Broad-sense heritability was high (> 0.60) for chlorophyll content, plant biomass and performance index, electrolyte leakage, and total leaf area. Positive and significant relationships existed between biomass and photosynthetic parameters, but a negative association existed between electrolyte leakage and morpho-physiological traits. The plants underwent more significant stress when drought and heat stress were imposed concurrently than under single stresses, with the impact of drought on the plants being more detrimental than heat. There were antagonistic effects on the morphophysiology of the eggplants when heat and drought stress were applied together. Resilient genotypes such as RV100503, RV100501, JAMBA, LOC3, RV100164, RV100169, LOC 3, RV100483, GH5155, RV100430, GH1087, GH1087*, RV100388, RV100387, RV100391 maintained high relative water content, low electrolyte leakage, high Fv/Fm ratio and performance index, and increased biomass production under abiotic stress conditions. The antagonistic interactions between heat and drought observed here may be retained or enhanced during several stress combinations typical of plants' environments and must be factored into efforts to develop climate change-resilient crops. This paper demonstrates improvised climate chambers for high throughput, reliable, rapid, and cost-effective screening for heat and drought and combined stress tolerance in plants.

Simultaneous improvement of grain yield and grain protein concentration in durum wheat by using association tests and weighted GBLUP

KEY MESSAGE

Simultaneous improvement for GY and GPC by using GWAS and GBLUP suggested a significant application in durum wheat breeding. Despite the importance of grain protein concentration (GPC) in determining wheat quality, its negative correlation with grain yield (GY) is still one of the major challenges for breeders. Here, a durum wheat panel of 200 genotypes was evaluated for GY, GPC, and their derived indices (GPD and GYD), under eight different agronomic conditions. The plant material was genotyped with the Illumina 25 k iSelect array, and a genome-wide association study was performed. Two statistical models revealed dozens of marker-trait associations (MTAs), each explaining up to 30%. phenotypic variance. Two markers on chromosomes 2A and 6B were consistently identified by both models and were found to be significantly associated with GY and GPC. MTAs identified for phenological traits co-mapped to well-known genes (i.e., Ppd-1, Vrn-1). The significance values (p-values) that measure the strength of the association of each single nucleotide polymorphism marker with the target traits were used to perform genomic prediction by using a weighted genomic best linear unbiased prediction model. The trained models were ultimately used to predict the agronomic performances of an independent durum wheat panel, confirming the utility of genomic prediction, although environmental conditions and genetic backgrounds may still be a challenge to overcome. The results generated through our study confirmed the utility of GPD and GYD to mitigate the inverse GY and GPC relationship in wheat, provided novel markers for marker-assisted selection and opened new ways to develop cultivars through genomic prediction approaches.

Rapid Identification of High-Temperature Responsive Genes Using Large-Scale Yeast Functional Screening System in Potato

As the third largest global food crop, potato plays an important role in ensuring food security. However, it is particularly sensitive to high temperatures, which seriously inhibits its growth and development, thereby reducing yield and quality and severely limiting its planting area. Therefore, rapid, and high-throughput screening for high-temperature response genes is highly significant for analyzing potato high-temperature tolerance molecular mechanisms and cultivating new high-temperature-tolerant potato varieties. We screened genes that respond to high temperature by constructing a potato cDNA yeast library. After high-temperature treatment at 39 °C, the yeast library was subjected to high-throughput sequencing, and a total of 1931 heat resistance candidate genes were screened. Through GO and KEGG analysis, we found they were mainly enriched in "photosynthesis" and "response to stimuli" pathways. Subsequently, 12 randomly selected genes were validated under high temperature, drought, and salt stress using qRT-PCR. All genes were responsive to high temperature, and most were also induced by drought and salt stress. Among them, five genes ectopically expressed in yeast enhance yeast's tolerance to high temperatures. We provide numerous candidate genes for potato response to high temperature stress, laying the foundation for subsequent analysis of the molecular mechanism of potato response to high temperature.

Genomics for Yield and Yield Components in Durum Wheat

In recent years, many efforts have been conducted to dissect the genetic basis of yield and yield components in durum wheat thanks to linkage mapping and genome-wide association studies. In this review, starting from the analysis of the genetic bases that regulate the expression of yield for developing new durum wheat varieties, we have highlighted how, currently, the reductionist approach, i.e., dissecting the yield into its individual components, does not seem capable of ensuring significant yield increases due to diminishing resources, land loss, and ongoing climate change. However, despite the identification of genes and/or chromosomal regions, controlling the grain yield in durum wheat is still a challenge, mainly due to the polyploidy level of this species. In the review, we underline that the next-generation sequencing (NGS) technologies coupled with improved wheat genome assembly and high-throughput genotyping platforms, as well as genome editing technology, will revolutionize plant breeding by providing a great opportunity to capture genetic variation that can be used in breeding programs. To date, genomic selection provides a valuable tool for modeling optimal allelic combinations across the whole genome that maximize the phenotypic potential of an individual under a given environment.

Developing future heat-resilient vegetable crops

Climate change seriously impacts global agriculture, with rising temperatures directly affecting the yield. Vegetables are an essential part of daily human consumption and thus have importance among all agricultural crops. The human population is increasing daily, so there is a need for alternative ways which can be helpful in maximizing the harvestable yield of vegetables. The increase in temperature directly affects the plants' biochemical and molecular processes; having a significant impact on quality and yield. Breeding for climate-resilient crops with good yields takes a long time and lots of breeding efforts. However, with the advent of new omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics, the efficiency and efficacy of unearthing information on pathways associated with high-temperature stress resilience has improved in many of the vegetable crops. Besides omics, the use of genomics-assisted breeding and new breeding approaches such as gene editing and speed breeding allow creation of modern vegetable cultivars that are more resilient to high temperatures. Collectively, these approaches will shorten the time to create and release novel vegetable varieties to meet growing demands for productivity and quality. This review discusses the effects of heat stress on vegetables and highlights recent research with a focus on how omics and genome editing can produce temperature-resilient vegetables more efficiently and faster.

Genetic architecture of fresh-market tomato yield

BACKGROUND

The fresh-market tomato (Solanum lycopersicum) is bred for direct consumption and is selected for a high yield of large fruits. To understand the genetic variations (distinct types of DNA sequence polymorphism) that influence the yield, we collected the phenotypic variations in the yields of total fruit, extra-large-sized fruit, small-sized fruit, or red-colored fruit from 68 core inbred contemporary U.S. fresh-market tomatoes for three consecutive years and the genomic information in 8,289,741 single nucleotide polymorphism (SNP) positions from the whole-genome resequencing of these tomatoes.

RESULTS

Genome-wide association (GWA) mapping using the SNP data with or without SNP filtering steps using the regularization methods, validated with quantitative trait loci (QTL) linkage mapping, identified 18 significant association signals for traits evaluated. Among them, 10 of which were not located within genomic regions previously identified as being associated with fruit size/shape. When mapping-driven association signals [558 SNPs associated with 28 yield (component) traits] were used to calculate genomic estimated breeding values (GEBVs) of evaluated traits, the prediction accuracies of the extra-large-sized fruit and small-sized fruit yields were higher than those of the total and red-colored fruit yields, as we tested the generated breeding values in inbred tomatoes and F2 populations. Improved accuracy in GEBV calculation of evaluated traits was achieved by using 364 SNPs identified using the regularization methods.

CONCLUSIONS

Together, these results provide an understanding of the genetic variations underlying the heritable phenotypic variability in yield in contemporary tomato breeding and the information necessary for improving such economically important and complex quantitative trait through breeding.

Emerging Strategies Mold Plasticity of Vegetable Plants in Response to High Temperature Stress

As a result of energy consumption and human activities, a large amount of carbon dioxide emissions has led to global warming, which seriously affects the growth and development of plants. Vegetables are an indispensable part of people's diet. In the plant kingdom, a variety of vegetables are highly sensitive to climate change. For them, an increase of just a few degrees above their optimum temperature threshold can result in a loss of yield and quality. Emerging strategies such as practice management and breeding varieties in response to above-optimal temperatures are critical for abiotic stress resistance of vegetable crops. In this study, the function and application of multiple strategies, including breeding improvement, epigenetic modification directed generation of alleles, gene editing techniques, and accumulation of mutations in multigenerational adaptation to abiotic stress, were discussed in vegetable crops. It is believed to be meaningful for plants to build plasticity under high temperature stress, thus generating more genetic structures for heat resistant traits in vegetable products.