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Although wheat (Triticum aestivum L.) is the main staple crop in the world and a major source of carbohydrates and proteins, functional genomics and allele mining are still big challenges. Given the advances in next-generation sequencing (NGS) technologies, the identification of causal variants associated with a target phenotype has become feasible. For these reasons, here, by combining sequence capture and target-enrichment methods with high-throughput NGS re-sequencing, we were able to scan at exome-wide level 46 randomly selected bread wheat individuals from a recombinant inbred line population and to identify and classify a large number of single nucleotide polymorphisms (SNPs). For technical validation of results, eight randomly selected SNPs were converted into Kompetitive Allele-Specific PCR (KASP) markers. This resource was established as an accessible and reusable molecular toolkit for allele data mining. The dataset we are making available could be exploited for novel studies on bread wheat genetics and as a foundation for starting breeding programs aimed at improving different key agronomic traits.

Pea (Pisum sativum L. subsp. sativum) is one of the oldest domesticated species and a widely cultivated legume. In this study, we combined next generation sequencing (NGS) data referring to two genotyping-by-sequencing (GBS) libraries, each one prepared from a different Pisum germplasm collection. The selection of single nucleotide polymorphism (SNP) loci called in both germplasm collections caused some loss of information; however, this did not prevent the obtainment of one of the largest datasets ever used to explore pea biodiversity, consisting of 652 accessions and 22 127 markers. The analysis of population structure reflected genetic variation based on geographic patterns and allowed the definition of a model for the expansion of pea cultivation from the domestication centre to other regions of the world. In genetically distinct populations, the average decay of linkage disequilibrium (LD) ranged from a few bases to hundreds of kilobases, thus indicating different evolutionary histories leading to their diversification. Genome-wide scans resulted in the identification of putative selective sweeps associated with domestication and breeding, including genes known to regulate shoot branching, cotyledon colour and resistance to lodging, and the correct mapping of two Mendelian genes. In addition to providing information of major interest for fundamental and applied research on pea, our work describes the first successful example of integration of different GBS datasets generated from ex situ collections – a process of potential interest for a variety of purposes, including conservation genetics, genome-wide association studies, and breeding.

Almond [Prunus dulcisMiller (D.A. Webb)] is the main tree nut species worldwide. Here, genotyping-by-sequencing (GBS) was applied to 149 almond cultivars from the ex situ collections of the Italian Council for Agricultural Research (CREA) and the Spanish National Research Council (CSIC), leading to the detection of 93,119 single-nucleotide polymorphisms (SNPs). The study of population structure outlined four distinct genetic groups and highlighted diversification between the Mediterranean and Californian gene pools. Data on SNP diversity and runs of homozygosity (ROHs) allowed the definition of kinship, inbreeding, and linkage disequilibrium (LD) decay in almond cultivated germplasm. Four-year phenotypic observations, gathered on 98 cultivars of the CREA collection, were used to perform a genome-wide association study (GWAS) and, for the first time in a crop species, homozygosity mapping (HM), resulting in the identification of genomic associations with nut, shell, and seed weight. Both GWAS and HM suggested that loci controlling nut and seed weight are mostly independent. Overall, this study provides insights on the almond cultivation history and delivers information of major interest for almond genetics and breeding. In a broader perspective, our results encourage the use of ROHs in crop science to estimate inbreeding, choose parental combinations minimizing the risk of inbreeding depression, and identify genomic footprints of selection for specific traits.

The first breeding program in the world for durum wheat was conceived in Italy in the early 1900s. Over the decades, pressure exerted by natural and artificial selection could have progressively reduced the genetic diversity of the durum wheat germplasm. In the present study, a large panel of Italian durum wheat accessions that includes landraces, old and modern cultivars was subjected to genotyping using the Illumina iSelect 15K wheat SNP array. The aim was to assess the impact that selection has in shaping Italian durum wheat genetic diversity and to exploit the patterns of genetic diversity between populations to identify molecular signatures of divergence and selection. Relatively small differences in genetic diversity have been observed among accessions, which have been selected and cultivated in Italy over the past 150 years. Indeed, directional selection combined with that operated by farmers/breeders resulted in the increase of linkage disequilibrium (LD) and in changes of the allelic frequencies in DNA regions that control important agronomic traits. Results from this study also show that major well-known genes and/or QTLs affecting plant height (RHT), earliness (VRN, PPD) and grain quality (GLU, PSY, PSD, LYC, PPO, LOX3) co-localized with outlier SNP loci. Interestingly, many of these SNPs fall in genomic regions where genes involved in nitrogen metabolism are. This finding highlights the key role these genes have played in the transition from landraces to modern cultivars. Finally, our study remarks on the need to fully exploit the genetic diversity of Italian landraces by intense pre-breeding activities aimed at introducing a new source of adaptability and resistance in the genetic background of modern cultivars, to contrast the effect of climate change. The list of divergent loci and loci under selection associated with useful agronomic traits represents an invaluable resource to detect new allelic variants for target genes and for guiding new genomic selection programs in durum wheat.

While durum wheat is a major food source in Mediterranean countries, storage (i.e., gluten) proteins are however responsible for celiac disease (CD), a serious autoimmune disease that occurs in genetically predisposed subjects. Different gluten epitopes—defined as “immunogenic” (IP) and “toxic” (TP) peptides—are involved in the pathology and their content in wheat grain depends on environmental and genetic factors. Detection of IP and TP is not trivial, and no work has been conducted so far to identify the genomic regions associated with their accumulation in wheat. In the present study, a genome-wide association study was performed on a durum wheat collection to identify marker–trait associations (MTAs) between 5730 high quality SNPs and the accumulation of CD-related peptides and gluten protein composition measured in two consecutive cropping seasons (2015/2016 and 2016/2017). High-molecular-weight glutenin subunits (HMW-GS) were more stable between the two years, and differences in total gluten proteins were mainly due to low-molecular-weight glutenin subunits (LMW-GS) and accumulation of gliadins. In the first instance, association tests were conducted on yellow pigment content (YP), a highly inheritable trait with a well-known genetic basis, and several significant MTAs were found corresponding to loci already known for being related to YP. These findings showed that MTAs found for the rest of the measured traits were reliable. In total, 28 significant MTAs were found for gluten composition, while 14 were found to be associated with IP and TP. Noteworthy, neither significant (−log10p > 4.7) nor suggestive (−log10p > 3.3) MTAs for the accumulation of CD-triggering epitopes were found on Gli-A1/Glu-A3 and Gli-B1/Glu-B3 loci, thus suggesting regulatory rather than structural gene effect. A PBF transcription factor on chromosome 5B, known to be involved in the regulation of the expression of CD-related peptides, was identified among the positional candidate genes in the LD-decay range around significant SNPs. Results obtained in the present study provide useful insights and resources for the long-term objective of selecting low-toxic durum wheat varieties while maintaining satisfactory gluten quality. info:eu-repo/semantics/publishedVersion

Information on the distribution of genetic variation is essential to preserve olive germplasm from erosion and to recover alleles lost through selective breeding. In addition, knowledge on population structure and genotype–phenotype associations is crucial to support modern olive breeding programs that must respond to new environmental conditions imposed by climate change and novel biotic/abiotic stressors. To further our understanding of genetic variation in the olive, we performed genotype-by-sequencing on a panel of 94 Italian olive cultivars. A reference-based and a reference-independent SNP calling pipeline generated 22,088 and 8,088 high-quality SNPs, respectively. Both datasets were used to model population structure via parametric and non parametric clustering. Although the two pipelines yielded a 3-fold difference in the number of SNPs, both described wide genetic variability among our study panel and allowed individuals to be grouped based on fruit weight and the geographical area of cultivation. Multidimensional scaling analysis on identity-by-state allele-sharing values as well as inference of population mixtures from genome-wide allele frequency data corroborated the clustering pattern we observed. These findings allowed us to formulate hypotheses about geographical relationships of Italian olive cultivars and to confirm known and uncover novel cases of synonymy.

Extra virgin olive oil (EVOO) has elevated commercial value due to its health appeal, desirable characteristics and quantitatively limited production, and thus it has become an object of intentional adulteration. As EVOOs on the market might consist of a blend of olive varieties or sometimes even of a mixture of oils from different botanical species, an array of DNA-fingerprinting methods have been developed to check the varietal composition of the blend. Starting from a comparison between publicly available DNA extraction protocols, we set up a timely, low-cost, reproducible and effective DNA isolation protocol, which allows an adequate amount of DNA to be recovered even from commercial filtered EVOOs. Then, in order to verify the effectiveness of the DNA extraction protocol herein proposed, we applied PCR-based fingerprinting methods starting from the DNA extracted from three EVOO samples of unknown composition. In particular, genomic regions harboring nine simple sequence repeats (SSRs) and eight genotyping-by-sequencing-derived single nucleotide polymorphism (SNP) markers were amplified for authentication and traceability of the three EVOO samples. The whole investigation strategy herein described might favor producers in terms of higher revenues and consumers in terms of price transparency and food safety.

Background: The olive tree is a typical crop of the Mediterranean basin where it shows a wide diversity, accounting for more than 2,600 cultivars. The ability to discriminate olive cultivars and determine their genetic variability is pivotal for an optimal exploitation of olive genetic resources. Methods: We investigated the genetic diversity within 128 olive accessions belonging to four countries in the Mediterranean Basin (Italy, Algeria, Syria, and Malta), with the purpose of better understanding the origin and spread of the olive genotypes across Mediterranean Basin countries. Eleven highly polymorphic simple sequence repeat (SSR) markers were used and proved to be very informative, producing a total of 179 alleles. Results: Cluster analysis distinguished three main groups according to their geographical origin, with the current sample of Maltese accessions included in the Italian group. Phylogenetic analysis further differentiated Italian and Maltese olive accessions, clarifying the intermediate position of Maltese accessions along the x/y-axes of principal coordinate analysis (PCoA). Model-based and neighbor clustering, PCoA, and migration analysis suggested the existence of two different gene pools (Algerian and Syrian) and that the genetic exchange occurred between the Syrian, Italian and Maltese populations. Discussion: The close relationship between Syrian and Italian and Maltese olives was consistent with the historical domestication and migration of olive tree from the North Levant to eastern Mediterranean basin. This study lays the foundations for a better understanding of olive genetic diversity in the Mediterranean basin and represents a step toward an optimal conservation and exploitation of olive genetic resources., peer-reviewed

Climate change, associated with global warming, extreme weather events, and increasing incidence of weeds, pests and pathogens, is strongly influencing major cropping systems. In this challenging scenario, miscellaneous strategies are needed to expedite the rate of genetic gains with the purpose of developing novel varieties. Large plant breeding populations, efficient high-throughput technologies, big data management tools, and downstream biotechnology and molecular techniques are the pillars on which next generation breeding is based. In this review, we describe the toolbox the breeder has to face the challenges imposed by climate change, remark on the key role bioinformatics plays in the analysis and interpretation of big “omics” data, and acknowledge all the benefits that have been introduced into breeding strategies with the biotechnological and digital revolution.

The exploitation of genetic variation in crops is essential to establish innovative breeding programs in the frame of global population increase and the sustainable intensification of agriculture. The advent of next generation sequencing technologies and the availability of complete or draft genome sequences of many crops allowed the development of several methods for SNP discovery. Genotyping by sequencing (GBS) has recently emerged as a promising approach to simultaneously allow SNP identification and genotyping. GBS provides a rapid, highly informative, high-throughput and cost-effective tool for exploring plant genetic diversity on a genome-wide scale and does not require any a priori knowledge on the genome of the species of interest. The features of GBS make it an attractive technology for (1) the assessment of population structure of germplasm collections; (2) the development of high density linkage maps and (3) genetic mapping studies. Herein, we present an overview of the GBS method and describe the main protocols in use, the principal methods for genetic diversity analysis and potential applications of the results in crop breeding programs. Finally, we illustrate the strategy we adopted to investigate the genetic diversity in cultivated pepper (Capsicum annuum).