Assessment of Genetic Differentiation and Linkage Disequilibrium in Solanum pimpinellifolium Using Genome-Wide High-Density SNP Markers

Deciphering salt stress responses in Solanum pimpinellifolium through high-throughput phenotyping

Soil salinity is a major environmental stressor affecting agricultural productivity worldwide. Understanding plant responses to salt stress is crucial for developing resilient crop varieties. Wild relatives of cultivated crops, such as wild tomato, Solanum pimpinellifolium, can serve as a useful resource to further expand the resilience potential of the cultivated germplasm, S. lycopersicum. In this study, we employed high-throughput phenotyping in the greenhouse and field conditions to explore salt stress responses of a S. pimpinellifolium diversity panel. Our study revealed extensive phenotypic variations in response to salt stress, with traits such as transpiration rate, shoot mass, and ion accumulation showing significant correlations with plant performance. We found that while transpiration was a key determinant of plant performance in the greenhouse, shoot mass strongly correlated with yield under field conditions. Conversely, ion accumulation was the least influential factor under greenhouse conditions. Through a Genome Wide Association Study, we identified candidate genes not previously associated with salt stress, highlighting the power of high-throughput phenotyping in uncovering novel aspects of plant stress responses. This study contributes to our understanding of salt stress tolerance in S. pimpinellifolium and lays the groundwork for further investigations into the genetic basis of these traits, ultimately informing breeding efforts for salinity tolerance in tomato and other crops.

Conservation priority and run of homozygosity pattern assessment of global chicken genetic resources

The conservation of genetic resources is becoming increasingly important for the sustainable development of the poultry industry. In the present study, we systematically analyzed the population structure, conservation priority, runs of homozygosity (ROH) of chicken breeds globally, and proposed rational conservation strategies. We used a 600K Affymetrix Axiom HD genotyping SNP array dataset of 2,429 chickens from 134 populations. The chickens were divided into 5 groups based on their country of origin and sampling location: Asian chickens (AS-LOC), African chickens (AF), European local chickens (EU-LOC), Asian breeds sampled in Germany (AS-DE), and European breeds sampled in Germany (EU-DE). The results indicated that the population structure was consistent with the actual geographical distribution of the populations. AS-LOC had the highest positive contribution to the total gene (HT, 1.00%,) and allelic diversity (AT, 0.0014%), the lowest inbreeding degree and the fastest linkage disequilibrium (LD) decay rate; the lowest contribution are derived by European ex situ chicken breeds (EU-DE:HT = -0.072%, AT = -0.0014%), which showed the highest inbreeding and slowest LD decay. Breeds farmed in ex situ (AS-DE, EU-DE) conditions exhibited reduced genetic diversity and increased inbreeding due to small population size. Given limited funds, it is a better choice for government to conserve the breeds with the highest contribution to genetic diversity in each group. Therefore, we evaluated the contribution of each breed to genetic and allelic diversity in 5 groups. Among each group, KUR(AF), BANG(AS-LOC), ALxx(EU-LOC), BHwsch(AS-DE), and ARw(EU-DE) had the highest contribution to gene diversity in the order of the above grouping. Similarly, according to the allelic diversity standard (in the same order), ZIMxx, PIxx, ALxx, SHsch, and ARsch had the highest contribution. After analyzing ROH, we found a total of 144,708 fragments and 27 islands. The gene and genome regions identified by the ROH islands and QTLs indicate that chicken breeds have potential for adaptation to different production systems. Based on these findings, it is recommended to prioritize the conservation of breeds with the highest genetic diversity in each group, while paying more attention to the conservation of Asian and African breeds. Furthermore, providing a valuable reference for the conservation and utilization of chicken.

The Genetic Basis of Tomato Aroma

Tomato (Solanum lycopersicum L.) aroma is determined by the interaction of volatile compounds (VOCs) released by the tomato fruits with receptors in the nose, leading to a sensorial impression, such as "sweet", "smoky", or "fruity" aroma. Of the more than 400 VOCs released by tomato fruits, 21 have been reported as main contributors to the perceived tomato aroma. These VOCs can be grouped in five clusters, according to their biosynthetic origins. In the last decades, a vast array of scientific studies has investigated the genetic component of tomato aroma in modern tomato cultivars and their relatives. In this paper we aim to collect, compare, integrate and summarize the available literature on flavour-related QTLs in tomato. Three hundred and 5ifty nine (359) QTLs associated with tomato fruit VOCs were physically mapped on the genome and investigated for the presence of potential candidate genes. This review makes it possible to (i) pinpoint potential donors described in literature for specific traits, (ii) highlight important QTL regions by combining information from different populations, and (iii) pinpoint potential candidate genes. This overview aims to be a valuable resource for researchers aiming to elucidate the genetics underlying tomato flavour and for breeders who aim to improve tomato aroma.

De novo genome assembly of two tomato ancestors, Solanum pimpinellifolium and Solanum lycopersicum var. cerasiforme, by long-read sequencing

The ancestral tomato species are known to possess genes that are valuable for improving traits in breeding. Here, we aimed to construct high-quality de novo genome assemblies of Solanum pimpinellifolium ‘LA1670’ and S. lycopersicum var. cerasiforme ‘LA1673’, originating from Peru. The Pacific Biosciences (PacBio) long-read sequences with 110× and 104× coverages were assembled and polished to generate 244 and 202 contigs spanning 808.8 Mbp for ‘LA1670’ and 804.5 Mbp for ‘LA1673’, respectively. After chromosome-level scaffolding with reference guiding, 14 scaffold sequences corresponding to 12 tomato chromosomes and 2 unassigned sequences were constructed. High-quality genome assemblies were confirmed using the Benchmarking Universal Single-Copy Orthologs and long terminal repeat assembly index. The protein-coding sequences were then predicted, and their transcriptomes were confirmed. The de novo assembled genomes of S. pimpinellifolium and S. lycopersicum var. cerasiforme were predicted to have 71,945 and 75,230 protein-coding genes, including 29,629 and 29,185 non-redundant genes, respectively, as supported by the transcriptome analysis results. The chromosome-level genome assemblies coupled with transcriptome data sets of the two accessions would be valuable for gaining insights into tomato domestication and understanding genome-scale breeding.

Regional differences in the abiotic environment contribute to genomic divergence within a wild tomato species

The wild currant tomato Solanum pimpinellifolium inhabits a wide range of abiotic habitats across its native range of Ecuador and Peru. Although it has served as a key genetic resource for the improvement of domestic cultivars, little is known about the genetic basis of traits underlying local adaptation in this species, nor what abiotic variables are most important for driving differentiation. Here we use redundancy analysis (RDA) and other multivariate statistical methods (structural equation modelling [SEM] and generalized dissimilarity modelling [GDM]) to quantify the relationship of genomic variation (6,830 single nucleotide polymorphisms [SNPs]) with climate and geography, among 140 wild accessions. RDA, SEM and GDM each identified environment as explaining more genomic variation than geography, suggesting that local adaptation to heterogeneous abiotic habitats may be an important source of genetic diversity in this species. Environmental factors describing temporal variation in precipitation and evaporative demand explained the most SNP variation among accessions, indicating that these forces may represent key selective agents. Lastly, by studying how SNP-environment associations vary throughout the genome (44,064 SNPs), we mapped the location and investigated the functions of loci putatively contributing to climatic adaptations. Together, our findings indicate an important role for selection imposed by the abiotic environment in driving genomic differentiation between populations.

The climatic association of population divergence and future extinction risk of Solanum pimpinellifolium

Under intraspecific differentiation driven by differential climatic adaptation, it may be expected that intraspecific genetic groups occur at distinct environments. Populations occupying different niches may therefore differ in their ability to cope with climate change. Here, we addressed this hypothesis with a wild tomato, Solanum pimpinellifolium. This species is distributed from the west side of Andes to the coastal region in Peru and Ecuador and occupies a wide environmental diversity. This environmental diversity is related to the genetic structure of the species providing an ideal material to investigate the isolation by environment hypothesis. While previous hypothesis stated that S. pimpinellifolium originated from northern Peru and migrated northwards and southwards, our results support that S. pimpinellifolium originated from Ecuador and expanded to northern and southern Peru, and during this process, the niche space of S. pimpinellifolium became more associated with cold and drought. We further predicted its fate under anthropogenic climate change. According to our predictions, the northern group will maintain its current extent or even expand to the entire western region of Ecuador. In contrast, we predicted low habitat suitability for the southern group which could potentially lead to the shrinkage of its distribution. In conclusion, we revealed the distinct fates among the differentiated populations driven by environment under global warming conditions.

Applications and Trends of Machine Learning in Genomics and Phenomics for Next-Generation Breeding

Crops are the major source of food supply and raw materials for the processing industry. A balance between crop production and food consumption is continually threatened by plant diseases and adverse environmental conditions. This leads to serious losses every year and results in food shortages, particularly in developing countries. Presently, cutting-edge technologies for genome sequencing and phenotyping of crops combined with progress in computational sciences are leading a revolution in plant breeding, boosting the identification of the genetic basis of traits at a precision never reached before. In this frame, machine learning (ML) plays a pivotal role in data-mining and analysis, providing relevant information for decision-making towards achieving breeding targets. To this end, we summarize the recent progress in next-generation sequencing and the role of phenotyping technologies in genomics-assisted breeding toward the exploitation of the natural variation and the identification of target genes. We also explore the application of ML in managing big data and predictive models, reporting a case study using microRNAs (miRNAs) to identify genes related to stress conditions.