Multiple haplotype-based analyses provide genetic and evolutionary insights into tomato fruit weight and composition

Haplotype-based breeding: A new insight in crop improvement

Haplotype-based breeding (HBB) is one of the cutting-edge technologies in the realm of crop improvement due to the increasing availability of Single Nucleotide Polymorphisms identified by Next Generation Sequencing technologies. The complexity of the data can be decreased with fewer statistical tests and a lower probability of spurious associations by combining thousands of SNPs into a few hundred haplotype blocks. The presence of strong genomic regions in breeding lines of most crop species facilitates the use of haplotypes to improve the efficiency of genomic and marker-assisted selection. Haplotype-based breeding as a Genomic Assisted Breeding (GAB) approach harnesses the genome sequence data to pinpoint the allelic variation used to hasten the breeding cycle and circumvent the challenges associated with linkage drag. This review article demonstrates ways to identify candidate genes, superior haplotype identification, haplo-pheno analysis, and haplotype-based marker-assisted selection. The crop improvement strategies that utilize superior haplotypes will hasten the breeding progress to safeguard global food security.

Omics-driven exploration and mining of key functional genes for the improvement of food and fiber crops

The deployment of omics technologies has obtained an incredible boost over the past few decades with the advances in next-generation sequencing (NGS) technologies, innovative bioinformatics tools, and the deluge of available biological information. The major omics technologies in the limelight are genomics, transcriptomics, proteomics, metabolomics, and phenomics. These biotechnological advances have modernized crop breeding and opened new horizons for developing crop varieties with improved traits. The genomes of several crop species are sequenced, and a huge number of genes associated with crucial economic traits have been identified. These identified genes not only provide insights into the understanding of regulatory mechanisms of crop traits but also decipher practical grounds to assist in the molecular breeding of crops. This review discusses the potential of omics technologies for the acquisition of biological information and mining of the genes associated with important agronomic traits in important food and fiber crops, such as wheat, rice, maize, potato, tomato, cassava, and cotton. Different functional genomics approaches for the validation of these important genes are also highlighted. Furthermore, a list of genes discovered by employing omics approaches is being represented as potential targets for genetic modifications by the latest genome engineering methods for the development of climate-resilient crops that would in turn provide great impetus to secure global food security.

The ORGAN SIZE (ORG) locus modulates both vegetative and reproductive gigantism in domesticated tomato

BACKGROUND AND AIMS

Gigantism is a key component of the domestication syndrome, a suite of traits that differentiates crops from their wild relatives. Allometric gigantism is strongly marked in horticultural crops, causing disproportionate increases in the size of edible parts such as stems, leaves or fruits. Tomato (Solanum lycopersicum) has attracted attention as a model for fruit gigantism, and many genes have been described controlling this trait. However, the genetic basis of a corresponding increase in size of vegetative organs contributing to isometric gigantism has remained relatively unexplored.

METHODS

Here, we identified a 0.4-Mb region on chromosome 7 in introgression lines (ILs) from the wild species Solanum pennellii in two different tomato genetic backgrounds (cv. 'M82' and cv. 'Micro-Tom') that controls vegetative and reproductive organ size in tomato. The locus, named ORGAN SIZE (ORG), was fine-mapped using genotype-by-sequencing. A survey of the literature revealed that ORG overlaps with previously mapped quantitative trait loci controlling tomato fruit weight during domestication.

KEY RESULTS

Alleles from the wild species led to lower cell number in different organs, which was partially compensated by greater cell expansion in leaves, but not in fruits. The result was a proportional reduction in leaf, flower and fruit size in the ILs harbouring the alleles from the wild species.

CONCLUSIONS

Our findings suggest that selection for large fruit during domestication also tends to select for increases in leaf size by influencing cell division. Since leaf size is relevant for both source-sink balance and crop adaptation to different environments, the discovery of ORG could allow fine-tuning of these parameters.

Fruit quality and shelf-life of Sardinian tomato (Solanum lycopersicum L.) landraces

The conservation and characterization of landraces have key roles in the safeguarding and valorization of agrobiodiversity. Indeed, these plant genetic resources represent an important crop heritage with quality and sensory characteristics that can be of great use to consumers and industry. In addition, the preservation of genetic resources from the risk of progressive genetic erosion, and the enhancement of their potential can contribute to food security and improve the nutritional value of food. Accordingly, this study aimed to investigate a collection of Sardinian tomato landraces for parameters that have determinant roles in evaluating their responses to conservation, and therefore to consumer acceptance. Six Sardinian landraces and two commercial varieties were cultivated in a two-years off-season trial, harvested at two different maturity stages (turning, red-ripe) and characterized using 14 fruit-related quality parameters that define the marketability, nutritional value, and flavor of the fruit. Data were collected at intervals of 10 days, starting from the harvest date and over 30 days of storage under refrigeration. The simultaneous analysis of all the qualitative characteristics for the different genotypes allowed to clearly differentiate the local varieties from the commercial varieties and a few landraces emerged for their satisfactory performances, e.g. "Tamatta kaki" ad "Tamatta groga de appiccai". In particular, the "Tamatta groga de appiccai" showed satisfactory lycopene content at marketable stages (average 5.65 mg 100g-1 FF), a peculiar orange-pink color with the highest hue angle values (range: H°T0 = 72.55-H°T30 = 48.26), and the highest firmness among the landraces of the red-ripe group (range: EpT0 = 1.64-EpT30 = 0.54 N mm-1). These results highlight the potential of some of the Sardinian tomato landraces for developing new varieties or promoting their direct valorization in local markets and could considerably increase the effectiveness and efficiency of agrobiodiversity conservation strategies.

Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton (Gossypium hirsutum L.)

Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.

A physical map of traits of agronomic importance based on potato and tomato genome sequences

Potato, tomato, pepper, and eggplant are worldwide important crop and vegetable species of the Solanaceae family. Molecular linkage maps of these plants have been constructed and used to map qualitative and quantitative traits of agronomic importance. This research has been undertaken with the vision to identify the molecular basis of agronomic characters on the one hand, and on the other hand, to assist the selection of improved varieties in breeding programs by providing DNA-based markers that are diagnostic for specific agronomic characters. Since 2011, whole genome sequences of tomato and potato became available in public databases. They were used to combine the results of several hundred mapping and map-based cloning studies of phenotypic characters between 1988 and 2022 in physical maps of the twelve tomato and potato chromosomes. The traits evaluated were qualitative and quantitative resistance to pathogenic oomycetes, fungi, bacteria, viruses, nematodes, and insects. Furthermore, quantitative trait loci for yield and sugar content of tomato fruits and potato tubers and maturity or earliness were physically mapped. Cloned genes for pathogen resistance, a few genes underlying quantitative trait loci for yield, sugar content, and maturity, and several hundred candidate genes for these traits were included in the physical maps. The comparison between the physical chromosome maps revealed, in addition to known intrachromosomal inversions, several additional inversions and translocations between the otherwise highly collinear tomato and potato genomes. The integration of the positional information from independent mapping studies revealed the colocalization of qualitative and quantitative loci for resistance to different types of pathogens, called resistance hotspots, suggesting a similar molecular basis. Synteny between potato and tomato with respect to genomic positions of quantitative trait loci was frequently observed, indicating eventual similarity between the underlying genes.

Genetic control of tomato fruit quality: from QTL mapping to Genome Wide Association studies and breeding

Consumers began to complain about the taste of tomato varieties in the late 1990's. Although tomato taste is influenced by environmental and post-harvest conditions, varieties show a large diversity for fruit quality traits. We herein review our past and present research work intended to improve tomato fruit quality. First, results from sensory analysis allowed identifying important traits for consumer preferences. Then, we dissected the genetic control of flavor related traits by mapping several QTL in the last 20 years, and identified the genes corresponding to a few major QTL. Since the availability of the tomato genome sequence, genome-wide association studies were performed on several panels of tomato accessions. We discovered a large number of associations for fruit composition and identified relevant allele combinations for breeding. We then performed a meta-analysis combining the results of several studies. We also checked the inheritance of quality traits at the hybrid level and assessed how genomic prediction could help selecting better tomato varieties.

Targeted approaches to improve tomato fruit taste

Tomato (Solanum lycopersicum) is the most valuable fruit and horticultural crop species worldwide. Compared with the fruits of their progenitors, those of modern tomato cultivars are, however, often described as having unsatisfactory taste or lacking flavor. The flavor of a tomato fruit arises from a complex mix of tastes and volatile metabolites, including sugars, acids, amino acids, and various volatiles. However, considerable differences in fruit flavor occur among tomato varieties, resulting in mixed consumer experiences. While tomato breeding has traditionally been driven by the desire for continual increases in yield and the introduction of traits that provide a long shelf-life, consumers are prepared to pay a reasonable premium for taste. Therefore, it is necessary to characterize preferences of tomato flavor and to define its underlying genetic basis. Here, we review recent conceptual and technological advances that have rendered this more feasible, including multi-omics-based QTL and association analyses, along with the use of trained testing panels, and machine learning approaches. This review proposes how the comprehensive datasets compiled to date could allow a precise rational design of tomato germplasm resources with improved organoleptic quality for the future.

Population-specific, recent positive selection signatures in cultivated Cucumis sativus L. (cucumber)

Population-specific, positive selection promotes the diversity of populations and drives local adaptations in the population. However, little is known about population-specific, recent positive selection in the populations of cultivated cucumber (Cucumis sativus L.). Based on a genomic variation map of individuals worldwide, we implemented a Fisher’s combination method by combining 4 haplotype-based approaches: integrated haplotype score (iHS), number of segregating sites by length (nSL), cross-population extended haplotype homozygosity (XP-EHH), and Rsb. Overall, we detected 331, 2,147, and 3,772 population-specific, recent positive selective sites in the East Asian, Eurasian, and Xishuangbanna populations, respectively. Moreover, we found that these sites were related to processes for reproduction, response to abiotic and biotic stress, and regulation of developmental processes, indicating adaptations to their microenvironments. Meanwhile, the selective genes associated with traits of fruits were also observed, such as the gene related to the shorter fruit length in the Eurasian population and the gene controlling flesh thickness in the Xishuangbanna population. In addition, we noticed that soft sweeps were common in the East Asian and Xishuangbanna populations. Genes involved in hard or soft sweeps were related to developmental regulation and abiotic and biotic stress resistance. Our study offers a comprehensive candidate dataset of population-specific, selective signatures in cultivated cucumber populations. Our methods provide guidance for the analysis of population-specific, positive selection. These findings will help explore the biological mechanisms of adaptation and domestication of cucumber.

Inferring Signatures of Positive Selection in Whole-Genome Sequencing Data: An Overview of Haplotype-Based Methods

Signatures of positive selection in the genome are a characteristic mark of adaptation that can reveal an ongoing, recent, or ancient response to environmental change throughout the evolution of a population. New sources of food, climate conditions, and exposure to pathogens are only some of the possible sources of selective pressure, and the rise of advantageous genetic variants is a crucial determinant of survival and reproduction. In this context, the ability to detect these signatures of selection may pinpoint genetic variants that are responsible for a significant change in gene regulation, gene expression, or protein synthesis, structure, and function. This review focuses on statistical methods that take advantage of linkage disequilibrium and haplotype determination to reveal signatures of positive selection in whole-genome sequencing data, showing that they emerge from different descriptions of the same underlying event. Moreover, considerations are provided around the application of these statistics to different species, their suitability for ancient DNA, and the usefulness of discovering variants under selection for biomedicine and public health in an evolutionary medicine framework.

Two decades of association mapping: Insights on disease resistance in major crops

Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.