Single Primer Enrichment Technology (SPET) for High-Throughput Genotyping in Tomato and Eggplant Germplasm

Identification of Faba bean genetic loci associated with quantitative resistance to the fungus Botrytis fabae, causal agent of chocolate spot

Introduction

Chocolate spot, caused by the ascomycete fungus Botrytis fabae, is a devastating foliar disease and a major constraint on the quality and yield of faba beans (Vicia faba). The use of fungicides is the primary strategy for controlling the disease. However, high levels of partial genetic resistance have been identified and can be exploited to mitigate the disease.

Methods

The partially resistant V. faba cultivar Maris Bead and susceptible Egyptian accession ig70726 were crossed, and a genetic mapping population of 184 individuals was genotyped in the F2 generation and screened for resistance to B. fabae infection in the F3, F5, and F6 generations in a series of field experiments. A high-density linkage map of V. faba containing 3897 DArT markers spanning 1713.7 cM was constructed.

Results

Multiple candidate quantitative trait loci (QTLs) in 11 separate regions of the V. faba genome were identified; some on chromosomes 2, 3, and 6 overlapped with loci previously linked to resistance to Ascochyta leaf and pod blight caused by the necrotrophic fungus Ascochyta fabae. A transcriptomics experiment was conducted at 18 h post-inoculation in seedlings of both parents of the mapping population, identifying several differentially expressed transcripts potentially involved in early stage defence against B. fabae, including cell-wall associated protein kinases, NLR genes, and genes involved in metabolism and response to reactive oxygen species.

Discussion

This study identified several novel candidate QTLs in the V. faba genome that contribute to partial resistance to chocolate spot, but differences between growing seasons highlighted the importance of multi-year phenotyping experiments when searching for candidate QTLs for partial resistance.

Solanum pennellii (LA5240) backcross inbred lines (BILs) for high resolution mapping in tomato

Wild species are an invaluable source of new traits for crop improvement. Over the years, the tomato community bred cultivated lines that carry introgressions from different species of the tomato tribe to facilitate trait discovery and mapping. The next phase in such projects is to find the genes that drive the identified phenotypes. This can be achieved by genotyping a few thousand individuals resulting in fine mapping that can potentially identify the causative gene. To couple trait discovery and fine mapping, we are presenting large, recombination-rich, Backcross Inbred Line (BIL) populations involving an unexplored accession of the wild, green-fruited species Solanum pennellii (LA5240; the 'Lost' Accession) with two modern tomato inbreds: LEA, determinate, and TOP, indeterminate. The LEA and TOP BILs are in BC2F6-8 generation and include 1400 and 500 lines, respectively. The BILs were genotyped with 5000 SPET markers, showing that in the euchromatic regions there was one recombinant every 17-18 Kb while in the heterochromatin a recombinant every 600-700 Kb (TOP and LEA respectively). To gain perspective on the topography of recombination we compared five independent members of the Self-pruning gene family with their respective neighboring genes; based on PCR markers, in all cases we found recombinants. Further mapping analysis of two known morphological mutations that segregated in the BILs (self-pruning and hairless) showed that the maximal delimited intervals were 73 Kb and 210 Kb, respectively, and included the known causative genes. The 'Lost'_BILs provide a solid framework to study traits derived from a drought-tolerant wild tomato.

Development of a high-density sub-species-specific targeted SNP assay for Rocky Mountain bighorn sheep (Ovis canadensis canadensis)

Due to their abundance and relative ease of genotyping, single nucleotide polymorphisms (SNPs) are a commonly used molecular marker for contemporary population genetic and genomic studies. A high-density and cost-effective way to type SNP loci is Allegro targeted genotyping (ATG), which is a form of targeted genotyping by sequencing developed and offered by Tecan genomics. One major drawback of this technology is the need for a reference genome and information on SNP loci when designing a SNP assay. However, for some non-model species genomic information from other closely related species can be used. Here we describe our process of developing an ATG assay to target 50,000 SNPs in Rocky Mountain bighorn sheep, using a reference genome from domestic sheep and SNP resources from prior bighorn sheep studies. We successfully developed a high accuracy, high-density, and relatively low-cost SNP assay for genotyping Rocky Mountain bighorn sheep that genotyped ~45,000 SNP loci. These loci were relatively evenly distributed throughout the genome. Furthermore, the assay produced genotypes at tens of thousands of SNP loci when tested on other mountain sheep species and subspecies.

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.

Construction of a strawberry breeding core collection to capture and exploit genetic variation

BACKGROUND

Genetic diversity is crucial for the success of plant breeding programs and core collections are important resources to capture this diversity. Many core collections have already been constructed by gene banks, whose main goal is to obtain a panel of a limited number of genotypes to simplify management practices and to improve shareability while retaining as much diversity as possible. However, as gene banks have a different composition and goal than plant breeding programs, constructing a core collection for a plant breeding program should consider different aspects.

RESULTS

In this study, we present a novel approach for constructing a core collection by integrating both genomic and pedigree information to maximize the representation of the breeding germplasm in a minimum subset of genotypes while accounting for future genetic variation within a strawberry breeding program. Our stepwise approach starts with selecting the most important crossing parents of advanced selections and genotypes included for specific traits, to represent also future genetic variation. We then use pedigree-genomic-based relationship coefficients combined with the 'accession to nearest entry' criterion to complement the core collection and maximize its representativeness of the current breeding program. Combined pedigree-genomic-based relationship coefficients allow for accurate relationship estimation without the need to genotype every individual in the breeding program.

CONCLUSIONS

This stepwise construction of a core collection in a strawberry breeding program can be applied in other plant breeding programs to construct core collections for various purposes.

Plant Sample Collection and Shipment for Multi-omic Analyses and Phytosanitary Evaluation

Plant sample preparation for analyses is a fundamental step in high-throughput omics strategies. Especially for plant metabolomics, quenching of hydrolytic enzymes able to affect metabolite concentrations is crucial for the accuracy of results. Given that DNA is usually less labile than metabolites, most sampling and shipment procedures able to preserve the metabolome are also suitable for preventing the degradation of plant DNA or of DNA of pathogens in the plant tissue. In this article, we describe all the steps of sample collection, shipment (including the phytosanitary issues of moving plant samples), and processing for combined genomics and metabolomics from a single sample, as well as the protocols used in our laboratories for downstream approaches for crop plants, allowing collection of multi-omic datasets in large experimental setups. The protocols have been adjusted to apply to both freeze-dried and fresh-frozen material to allow the processing of crop plant samples that will require long-distance transport. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Preparation of freeze-dried leaf disks for multiplexed PCR or DArT-Seq genotyping Basic Protocol 2: Medium-throughput preparation of pathogen-free nucleic acids for most genotyping-resequencing applications or pathogen detection Alternate Protocol: Low-throughput extraction of high-quality DNA for resequencing using commercial kits Support Protocol: DNA quality control Basic Protocol 3: Preparation of freeze-dried plant material for metabolomics Basic Protocol 4: Preparation of fresh-frozen plant material for metabolomics Basic Protocol 5: Preparation and shipment of metabolite extracts for metabolomic analyses Basic Protocol 6: Sample shipping and long-term storage.

Conventional and new genetic resources for an eggplant breeding revolution

Eggplant (Solanum melongena) is a major vegetable crop with great potential for genetic improvement owing to its large and mostly untapped genetic diversity. It is closely related to over 500 species of Solanum subgenus Leptostemonum that belong to its primary, secondary, and tertiary genepools and exhibit a wide range of characteristics useful for eggplant breeding, including traits adaptive to climate change. Germplasm banks worldwide hold more than 19 000 accessions of eggplant and related species, most of which have yet to be evaluated. Nonetheless, eggplant breeding using the cultivated S. melongena genepool has yielded significantly improved varieties. To overcome current breeding challenges and for adaptation to climate change, a qualitative leap forward in eggplant breeding is necessary. The initial findings from introgression breeding in eggplant indicate that unleashing the diversity present in its relatives can greatly contribute to eggplant breeding. The recent creation of new genetic resources such as mutant libraries, core collections, recombinant inbred lines, and sets of introgression lines will be another crucial element and will require the support of new genomics tools and biotechnological developments. The systematic utilization of eggplant genetic resources supported by international initiatives will be critical for a much-needed eggplant breeding revolution to address the challenges posed by climate change.

Development and application of Single Primer Enrichment Technology (SPET) SNP assay for population genomics analysis and candidate gene discovery in lettuce

Single primer enrichment technology (SPET) is a novel high-throughput genotyping method based on short-read sequencing of specific genomic regions harboring polymorphisms. SPET provides an efficient and reproducible method for genotyping target loci, overcoming the limits associated with other reduced representation library sequencing methods that are based on a random sampling of genomic loci. The possibility to sequence regions surrounding a target SNP allows the discovery of thousands of closely linked, novel SNPs. In this work, we report the design and application of the first SPET panel in lettuce, consisting of 41,547 probes spanning the whole genome and designed to target both coding (~96%) and intergenic (~4%) regions. A total of 81,531 SNPs were surveyed in 160 lettuce accessions originating from a total of 10 countries in Europe, America, and Asia and representing 10 horticultural types. Model ancestry population structure clearly separated the cultivated accessions (Lactuca sativa) from accessions of its presumed wild progenitor (L. serriola), revealing a total of six genetic subgroups that reflected a differentiation based on cultivar typology. Phylogenetic relationships and principal component analysis revealed a clustering of butterhead types and a general differentiation between germplasm originating from Western and Eastern Europe. To determine the potentiality of SPET for gene discovery, we performed genome-wide association analysis for main agricultural traits in L. sativa using six models (GLM naive, MLM, MLMM, CMLM, FarmCPU, and BLINK) to compare their strength and power for association detection. Robust associations were detected for seed color on chromosome 7 at 50 Mbp. Colocalization of association signals was found for outer leaf color and leaf anthocyanin content on chromosome 9 at 152 Mbp and on chromosome 5 at 86 Mbp. The association for bolting time was detected with the GLM, BLINK, and FarmCPU models on chromosome 7 at 164 Mbp. Associations were detected in chromosomal regions previously reported to harbor candidate genes for these traits, thus confirming the effectiveness of SPET for GWAS. Our findings illustrated the strength of SPET for discovering thousands of variable sites toward the dissection of the genomic diversity of germplasm collections, thus allowing a better characterization of lettuce collections.

Evaluation of three sets of advanced backcrosses of eggplant with wild relatives from different gene pools under low N fertilization conditions

The development of new cultivars with improved nitrogen use efficiency (NUE) is key for implementing sustainable agriculture practices. Crop wild relatives (CWRs) provide valuable genetic resources for breeding programs aimed at achieving this goal. In this study, three eggplant (Solanum melongena) accessions together with their advanced backcrosses (ABs; BC3 to BC5 generations) were evaluated for 22 morpho-agronomic, physiological, and NUE traits under low nitrogen (LN) fertilization conditions. The ABs were developed with introgressions from the wild relatives Solanum insanum, Solanum dasyphyllum, and Solanum elaeagnifolium. The AB population comprised a total of 25, 59, and 59 genotypes, respectively, with overall donor wild relative genome coverage percentages of 58.8%, 46.3%, and 99.2%. The three S. melongena recurrent parents were also evaluated under control (normal) N fertilization. Reduction of N fertilization in the parents resulted in decreased chlorophyll content-related traits, aerial biomass, stem diameter, and yield and increased NUE, nitrogen uptake efficiency (NUpE), and nitrogen utilization efficiency (NUtE). However, the decrease in yield was moderate, ranging between 62.6% and 72.6%. A high phenotypic variation was observed within each of the three sets of ABs under LN conditions, with some individuals displaying improved transgressive characteristics over the recurrent parents. Using the single primer enrichment technology 5 k probes platform for high-throughput genotyping, we observed a variable but high degree of recurrent parent genome recovery in the ABs attributable to the lines recombination, allowing the successful identification of 16 quantitative trait loci (QTL). Different allelic effects were observed for the introgressed QTL alleles. Several candidate genes were identified in the QTL regions associated with plant growth, yield, fruit size, and NUE-related parameters. Our results show that eggplant materials with introgressions from CWRs can result in a dramatic impact in eggplant breeding for a more sustainable agriculture.

Diversity analyses in two ornamental and large-genome Ranunculaceae species based on a low-cost Klenow NGS-based protocol

Persian buttercup (Ranunculus asiaticus L.) and poppy anemone (Anemone coronaria L.) are ornamental, outcrossing, perennial species belonging to the Ranunculaceae family, characterized by large and highly repetitive genomes. We applied K-seq protocol in both species to generate high-throughput sequencing data and produce a large number of genetic polymorphisms. The technique entails the application of Klenow polymerase-based PCR using short primers designed by analyzing k-mer sets in the genome sequence. To date the genome sequence of both species has not been released, thus we designed primer sets based on the reference the genome sequence of the related species Aquilegia oxysepala var. kansuensis (Brühl). A whole of 11,542 SNPs were selected for assessing genetic diversity of eighteen commercial varieties of R. asiaticus, while 1,752 SNPs for assessing genetic diversity in six cultivars of A. coronaria. UPGMA dendrograms were constructed and in R. asiaticus integrated in with PCA analysis. This study reports the first molecular fingerprinting within Persian buttercup, while the results obtained in poppy anemone were compared with a previously published SSR-based fingerprinting, proving K-seq to be an efficient protocol for the genotyping of complex genetic backgrounds.

The giant diploid faba genome unlocks variation in a global protein crop

Increasing the proportion of locally produced plant protein in currently meat-rich diets could substantially reduce greenhouse gas emissions and loss of biodiversity1. However, plant protein production is hampered by the lack of a cool-season legume equivalent to soybean in agronomic value2. Faba bean (Vicia faba L.) has a high yield potential and is well suited for cultivation in temperate regions, but genomic resources are scarce. Here, we report a high-quality chromosome-scale assembly of the faba bean genome and show that it has expanded to a massive 13 Gb in size through an imbalance between the rates of amplification and elimination of retrotransposons and satellite repeats. Genes and recombination events are evenly dispersed across chromosomes and the gene space is remarkably compact considering the genome size, although with substantial copy number variation driven by tandem duplication. Demonstrating practical application of the genome sequence, we develop a targeted genotyping assay and use high-resolution genome-wide association analysis to dissect the genetic basis of seed size and hilum colour. The resources presented constitute a genomics-based breeding platform for faba bean, enabling breeders and geneticists to accelerate the improvement of sustainable protein production across the Mediterranean, subtropical and northern temperate agroecological zones.

A Compendium for Novel Marker-Based Breeding Strategies in Eggplant

The worldwide production of eggplant is estimated at about 58 Mt, with China, India and Egypt being the major producing countries. Breeding efforts in the species have mainly focused on increasing productivity, abiotic and biotic tolerance/resistance, shelf-life, the content of health-promoting metabolites in the fruit rather than decreasing the content of anti-nutritional compounds in the fruit. From the literature, we collected information on mapping quantitative trait loci (QTLs) affecting eggplant's traits following a biparental or multi-parent approach as well as genome-wide association (GWA) studies. The positions of QTLs were lifted according to the eggplant reference line (v4.1) and more than 700 QTLs were identified, here organized into 180 quantitative genomic regions (QGRs). Our findings thus provide a tool to: (i) determine the best donor genotypes for specific traits; (ii) narrow down QTL regions affecting a trait by combining information from different populations; (iii) pinpoint potential candidate genes.

Genomic Insights into the Origin of a Thermotolerant Tomato Line and Identification of Candidate Genes for Heat Stress

Climate change represents the main problem for agricultural crops, and the constitution of heat-tolerant genotypes is an important breeder’s strategy to reduce yield losses. The aim of the present study was to investigate the whole genome of a heat-tolerant tomato genotype (E42), in order to identify candidate genes involved in its response to high temperature. E42 presented a high variability for chromosomes 1, 4, 7 and 12, and phylogenetic analysis highlighted its relationship with the wild S. pimpinellifolium species. Variants with high (18) and moderate (139) impact on protein function were retrieved from two lists of genes related to heat tolerance and reproduction. This analysis permitted us to prioritize a subset of 35 candidate gene mapping in polymorphic regions, some colocalizing in QTLs controlling flowering in tomato. Among these genes, we identified 23 HSPs, one HSF, six involved in flowering and five in pollen activity. Interestingly, one gene coded for a flowering locus T1 and mapping on chromosome 11 resides in a QTL region controlling flowering and also showed 100% identity with an S. pimpinellifolium allele. This study provides useful information on both the E42 genetic background and heat stress response, and further studies will be conducted to validate these genes.

Next generation sequencing technologies to explore the diversity of germplasm resources: achievements and trends in tomato

Tomato is one of the major vegetable crops grown worldwide and a model species for genetic and biological research. Progress in genomic technologies made possible the development of forefront methods for high-scale sequencing, providing comprehensive insight into the genetic architecture of germplasm resources. This review revisits next-generation sequencing strategies and applications to investigate the diversity of tomato, describing the common platforms used for SNP genotyping of large collections, de novo sequencing, and whole genome resequencing. Significant findings in evolutionary history are outlined, thus discussing how genomics has provided new hints about the processes behind domestication. Finally, achievement and perspectives on pan-genome construction and graphical pan-genome development toward precise mining of the natural variation to be exploited for breeding purposes are presented.

Mutations in the SmAPRR2 transcription factor suppressing chlorophyll pigmentation in the eggplant fruit peel are key drivers of a diversified colour palette

Understanding the mechanisms by which chlorophylls are synthesized in the eggplant (Solanum melongena) fruit peel is of great relevance for eggplant breeding. A multi-parent advanced generation inter-cross (MAGIC) population and a germplasm collection have been screened for green pigmentation in the fruit peel and used to identify candidate genes for this trait. A genome-wide association study (GWAS) performed with 420 MAGIC individuals revealed a major association on chromosome 8 close to a gene similar to APRR2. Two variants in SmAPRR2, predicted as having a high impact effect, were associated with the absence of fruit chlorophyll pigmentation in the MAGIC population, and a large deletion of 5.27 kb was found in two reference genomes of accessions without chlorophyll in the fruit peel. The validation of the candidate gene SmAPRR2 was performed by its sequencing in a set of MAGIC individuals and through its de novo assembly in 277 accessions from the G2P-SOL eggplant core collection. Two additional mutations in SmAPRR2 associated with the lack of chlorophyll were identified in the core collection set. The phylogenetic analysis of APRR2 reveals orthology within Solanaceae and suggests that specialization of APRR2-like genes occurred independently in Cucurbitaceae and Solanaceae. A strong geographical differentiation was observed in the frequency of predominant mutations in SmAPRR2, resulting in a lack of fruit chlorophyll pigmentation and suggesting that this phenotype may have arisen and been selected independently several times. This study represents the first identification of a major gene for fruit chlorophyll pigmentation in the eggplant fruit.

Genetic dissection of fruit maturity date in apricot (P. armeniaca L.) through a Single Primer Enrichment Technology (SPET) approach

Background

Single primer enrichment technology (SPET) is an emerging and increasingly popular solution for high-throughput targeted genotyping in plants. Although SPET requires a priori identification of polymorphisms for probe design, this technology has potentially higher reproducibility and transferability compared to other reduced representation sequencing (RRS) approaches, also enabling the discovery of closely linked polymorphisms surrounding the target one.

Results

The potential for SPET application in fruit trees was evaluated by developing a 25K target SNPs assay to genotype a panel of apricot accessions and progenies. A total of 32,492 polymorphic sites were genotyped in 128 accessions (including 8,188 accessory non-target SNPs) with extremely low levels of missing data and a significant correlation of allelic frequencies compared to whole-genome sequencing data used for array design. Assay performance was further validated by estimating genotyping errors in two biparental progenies, resulting in an overall 1.8% rate. SPET genotyping data were used to infer population structure and to dissect the architecture of fruit maturity date (MD), a quantitative reproductive phenological trait of great agronomical interest in apricot species. Depending on the year, GWAS revealed loci associated to MD on several chromosomes. The QTLs on chromosomes 1 and 4 (the latter explaining most of the phenotypic variability in the panel) were the most consistent over years and were further confirmed by linkage mapping in two segregating progenies.

Conclusions

Besides the utility for marker assisted selection and for paving the way to in-depth studies to clarify the molecular bases of MD trait variation in apricot, the results provide an overview of the performance and reliability of SPET for fruit tree genetics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08901-1.

A novel and diverse set of SNP markers for rangewide genetic studies in Picea abies

We used Double Digest Restriction site associated DNA sequencing (ddRADseq), exome sequencing (exome-seq) and targeted genotyping by sequencing (GBS) to develop new geographically informative nuclear SNP markers in Picea abies. This set of 518 loci consists of 397 loci specifically designed for the geographic differentiation of populations and 121 loci of adaptive markers for drought stress which all were identified from 26 samples in 23 populations distributed over Central Europe. This set of novel markers represents a valuable basis to study the geographic population structure and genetic differentiation of Picea abies in its natural distribution range as well as outside of its native range with a focus on Central Europe.

Toward a Molecular Approach to Chronotype Assessment

The aim of the present study was to develop a Polygenic Score-based model for molecular chronotype assessment. Questionnaire-based phenotypical chronotype assessment was used as a reference. In total, 54 extremely morning/morning (MM/M; 35 females, 39.7 ± 3.8 years) and 44 extremely evening/evening (EE/E; 20 females, 27.3 ± 7.7 years) individuals donated a buccal DNA sample for genotyping by sequencing of the entire genetic variability of 19 target genes known to be involved in circadian rhythmicity and/or sleep duration. Targeted genotyping was performed using the single primer enrichment technology and a specifically designed panel of 5526 primers. Among 2868 high-quality polymorphisms, a cross-validation approach lead to the identification of 83 chronotype predictive variants, including previously known and also novel chronotype-associated polymorphisms. A large (35 single-nucleotide polymorphisms [SNPs]) and also a small (13 SNPs) panel were obtained, both with an estimated predictive validity of approximately 80%. Potential mechanistic hypotheses for the role of some of the newly identified variants in modulating chronotype are formulated. Once validated in independent populations encompassing the whole range of chronotypes, the identified panels might become useful within the setting of both circadian public health initiatives and precision medicine.

Genetic Control of Reproductive Traits under Different Temperature Regimes in Inbred Line Populations Derived from Crosses between S. pimpinellifolium and S. lycopersicum Accessions

In the present work, we study the genetic control of reproductive traits under different heat stress conditions in two populations of inbred lines derived from crosses between two S. pimpinellifolium accessions and two tomato cultivars (E9×L5 and E6203×LA1589). The temperature increase affected the reproductive traits, especially at extremely high temperatures, where only a few lines were able to set fruits. Even though a relative modest number of QTLs was identified, two clusters of QTLs involved in the responses of reproductive traits to heat stress were detected in both populations on chromosomes 1 and 2. Interestingly, several epistatic interactions were detected in the E9×L5 population, which were classified into three classes based on the allelic interaction: dominant (one locus suppressed the allelic effects of a second locus), co-adaptive (the double-homozygous alleles from the same parent alleles showed a higher phenotypic value than the combination of homozygous alleles from alternative parents) and transgressive (the combination of double-homozygous alleles from different parents showed better performance than double-homozygous alleles from the same parents). These results reinforce the important role of non-additive genetic variance in the response to heat stress and the potential of the new allelic combinations that arise after wide crosses.

Newly Developed MAGIC Population Allows Identification of Strong Associations and Candidate Genes for Anthocyanin Pigmentation in Eggplant

Multi-parent advanced generation inter-cross (MAGIC) populations facilitate the genetic dissection of complex quantitative traits in plants and are valuable breeding materials. We report the development of the first eggplant MAGIC population (S3 Magic EGGplant InCanum, S3MEGGIC; 8-way), constituted by the 420 S3 individuals developed from the intercrossing of seven cultivated eggplant (Solanum melongena) and one wild relative (S. incanum) parents. The S3MEGGIC recombinant population was genotyped with the eggplant 5k probes SPET platform and phenotyped for anthocyanin presence in vegetative plant tissues (PA) and fruit epidermis (FA), and for the light-insensitive anthocyanic pigmentation under the calyx (PUC). The 7,724 filtered high-confidence single-nucleotide polymorphisms (SNPs) confirmed a low residual heterozygosity (6.87%), a lack of genetic structure in the S3MEGGIC population, and no differentiation among subpopulations carrying a cultivated or wild cytoplasm. Inference of haplotype blocks of the nuclear genome revealed an unbalanced representation of the founder genomes, suggesting a cryptic selection in favour or against specific parental genomes. Genome-wide association study (GWAS) analysis for PA, FA, and PUC detected strong associations with two myeloblastosis (MYB) genes similar to MYB113 involved in the anthocyanin biosynthesis pathway, and with a COP1 gene which encodes for a photo-regulatory protein and may be responsible for the PUC trait. Evidence was found of a duplication of an ancestral MYB113 gene with a translocation from chromosome 10 to chromosome 1 compared with the tomato genome. Parental genotypes for the three genes were in agreement with the identification of the candidate genes performed in the S3MEGGIC population. Our new eggplant MAGIC population is the largest recombinant population in eggplant and is a powerful tool for eggplant genetics and breeding studies.

Improved genome assembly and pan-genome provide key insights into eggplant domestication and breeding

Eggplant (Solanum melongena L.) is an important horticultural crop and one of the most widely grown vegetables from the Solanaceae family. It was domesticated from a wild, prickly progenitor carrying small, round, non-anthocyanic fruits. We obtained a novel, highly contiguous genome assembly of the eggplant '67/3' reference line, by Hi-C retrofitting of a previously released short read- and optical mapping-based assembly. The sizes of the 12 chromosomes and the fraction of anchored genes in the improved assembly were comparable to those of a chromosome-level assembly. We resequenced 23 accessions of S. melongena representative of the worldwide phenotypic, geographic, and genetic diversity of the species, and one each from the closely related species Solanum insanum and Solanum incanum. The eggplant pan-genome contained approximately 51.5 additional megabases and 816 additional genes compared with the reference genome, while the pan-plastome showed little genetic variation. We identified 53 selective sweeps related to fruit color, prickliness, and fruit shape in the nuclear genome, highlighting selection leading to the emergence of present-day S. melongena cultivars from its wild ancestors. Candidate genes underlying the selective sweeps included a MYBL1 repressor and CHALCONE ISOMERASE (for fruit color), homologs of Arabidopsis GLABRA1 and GLABROUS INFLORESCENCE STEMS2 (for prickliness), and orthologs of tomato FW2.2, OVATE, LOCULE NUMBER/WUSCHEL, SUPPRESSOR OF OVATE, and CELL SIZE REGULATOR (for fruit size/shape), further suggesting that selection for the latter trait relied on a common set of orthologous genes in tomato and eggplant.

Genome-Based Targeted Sequencing as a Reproducible Microbial Community Profiling Assay

Current sequencing-based methods for profiling microbial communities rely on marker gene (e.g., 16S rRNA) or metagenome shotgun sequencing (mWGS) analysis. We present an approach based on a single-primer extension reaction using a highly multiplexed oligonucleotide probe pool. This approach, termed MA-GenTA (microbial abundances from genome tagged analysis), enables quantitative, straightforward, cost-effective microbiome profiling that combines desirable features of both 16S rRNA and mWGS strategies. The use of multiple probes per target genome and rigorous probe design criteria enabled robust determination of relative abundance. To test the utility of the MA-GenTA assay, probes were designed for 830 genome sequences representing bacteria present in mouse stool specimens. Comparison of the MA-GenTA data with mWGS data demonstrated excellent correlation down to 0.01% relative abundance and a similar number of organisms detected per sample. Despite the incompleteness of the reference database, nonmetric multidimensional scaling (NMDS) clustering based on the Bray-Curtis dissimilarity metric of sample groups was consistent between MA-GenTA, mWGS, and 16S rRNA data sets. MA-GenTA represents a potentially useful new method for microbiome community profiling based on reference genomes.

IMPORTANCE New methods for profiling the microbial communities can create new approaches to understanding the composition and function of those communities. In this study, we combined bacterial genome-specific probe design with a highly multiplexed single primer extension reaction as a new method to profile microbial communities, using stool from various mouse strains as a test case. This method, termed MA-GenTA, was benchmarked against 16S rRNA gene sequencing and metagenome sequencing methods and delivered similar relative abundance and clustering data. Since the probes were generated from reference genomes, MA-GenTA was also able to provide functional pathway data for the stool microbiome in the assayed samples. The method is more informative than 16S rRNA analysis while being less costly than metagenome shotgun sequencing.

K-seq, an affordable, reliable, and open Klenow NGS-based genotyping technology

BACKGROUND

K-seq, a new genotyping methodology based on the amplification of genomic regions using two steps of Klenow amplification with short oligonucleotides, followed by standard PCR and Illumina sequencing, is presented. The protocol was accompanied by software developed to aid with primer set design.

RESULTS

As the first examples, K-seq in species as diverse as tomato, dog and wheat was developed. K-seq provided genetic distances similar to those based on WGS in dogs. Experiments comparing K-seq and GBS in tomato showed similar genetic results, although K-seq had the advantage of finding more SNPs for the same number of Illumina reads. The technology reproducibility was tested with two independent runs of the tomato samples, and the correlation coefficient of the SNP coverages between samples was 0.8 and the genotype match was above 94%. K-seq also proved to be useful in polyploid species. The wheat samples generated specific markers for all subgenomes, and the SNPs generated from the diploid ancestors were located in the expected subgenome with accuracies greater than 80%.

CONCLUSION

K-seq is an open, patent-unencumbered, easy-to-set-up, cost-effective and reliable technology ready to be used by any molecular biology laboratory without special equipment in many genetic studies.

An All-In-One Transcriptome-Based Assay to Identify Therapy-Guiding Genomic Aberrations in Nonsmall Cell Lung Cancer Patients

The number of genomic aberrations known to be relevant in making therapeutic decisions for non-small cell lung cancer patients has increased in the past decade. Multiple molecular tests are required to reliably establish the presence of these aberrations, which is challenging because available tissue specimens are generally small. To optimize diagnostic testing, we developed a transcriptome-based next-generation sequencing (NGS) assay based on single primed enrichment technology. We interrogated 11 cell lines, two patient-derived frozen biopsies, nine pleural effusion, and 29 formalin-fixed paraffin-embedded (FFPE) samples. All clinical samples were selected based on previously identified mutations at the DNA level in EGFR, KRAS, ALK, PIK3CA, BRAF, AKT1, MET, NRAS, or ROS1 at the DNA level, or fusion genes at the chromosome level, or by aberrant protein expression of ALK, ROS1, RET, and NTRK1. A successful analysis is dependent on the number of unique reads and the RNA quality, as indicated by the DV200 value. In 27 out of 51 samples with >50 K unique reads and a DV200 >30, all 19 single nucleotide variants (SNVs)/small insertions and deletions (INDELs), three MET exon 14 skipping events, and 13 fusion gene transcripts were detected at the RNA level, giving a test accuracy of 100%. In summary, this lung-cancer-specific all-in-one transcriptome-based assay for the simultaneous detection of mutations and fusion genes is highly sensitive.

Accelerating Tomato Breeding by Exploiting Genomic Selection Approaches

Genomic selection (GS) is a predictive approach that was built up to increase the rate of genetic gain per unit of time and reduce the generation interval by utilizing genome-wide markers in breeding programs. It has emerged as a valuable method for improving complex traits that are controlled by many genes with small effects. GS enables the prediction of the breeding value of candidate genotypes for selection. In this work, we address important issues related to GS and its implementation in the plant context with special emphasis on tomato breeding. Genomic constraints and critical parameters affecting the accuracy of prediction such as the number of markers, statistical model, phenotyping and complexity of trait, training population size and composition should be carefully evaluated. The comparison of GS approaches for facilitating the selection of tomato superior genotypes during breeding programs is also discussed. GS applied to tomato breeding has already been shown to be feasible. We illustrated how GS can improve the rate of gain in elite line selection, and descendent and backcross schemes. The GS schemes have begun to be delineated and computer science can provide support for future selection strategies. A new promising breeding framework is beginning to emerge for optimizing tomato improvement procedures.

A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant

The development of double haploids (DHs) is a straightforward path for obtaining pure lines but has multiple bottlenecks. Among them is the determination of the optimal stage of pollen induction for androgenesis. In this work, we developed Microscan, a deep learning-based system for the detection and recognition of the stages of pollen development. In a first experiment, the algorithm was developed adapting the RetinaNet predictive model using microspores of different eggplant accessions as samples. A mean average precision of 86.30% was obtained. In a second experiment, the anther range to be cultivated in vitro was determined in three eggplant genotypes by applying the Microscan system. Subsequently, they were cultivated following two different androgenesis protocols (Cb and E6). The response was only observed in the anther size range predicted by Microscan, obtaining the best results with the E6 protocol. The plants obtained were characterized by flow cytometry and with the Single Primer Enrichment Technology high-throughput genotyping platform, obtaining a high rate of confirmed haploid and double haploid plants. Microscan has been revealed as a tool for the high-throughput efficient analysis of microspore samples, as it has been exemplified in eggplant by providing an increase in the yield of DHs production.

SILEX: a fast and inexpensive high-quality DNA extraction method suitable for multiple sequencing platforms and recalcitrant plant species

BACKGROUND

The use of sequencing and genotyping platforms has undergone dramatic improvements, enabling the generation of a wealth of genomic information. Despite this progress, the availability of high-quality genomic DNA (gDNA) in sufficient concentrations is often a main limitation, especially for third-generation sequencing platforms. A variety of DNA extraction methods and commercial kits are available. However, many of these are costly and frequently give either low yield or low-quality DNA, inappropriate for next generation sequencing (NGS) platforms. Here, we describe a fast and inexpensive DNA extraction method (SILEX) applicable to a wide range of plant species and tissues.

RESULTS

SILEX is a high-throughput DNA extraction protocol, based on the standard CTAB method with a DNA silica matrix recovery, which allows obtaining NGS-quality high molecular weight genomic plant DNA free of inhibitory compounds. SILEX was compared with a standard CTAB extraction protocol and a common commercial extraction kit in a variety of species, including recalcitrant ones, from different families. In comparison with the other methods, SILEX yielded DNA in higher concentrations and of higher quality. Manual extraction of 48 samples can be done in 96 min by one person at a cost of 0.12 €/sample of reagents and consumables. Hundreds of tomato gDNA samples obtained with either SILEX or the commercial kit were successfully genotyped with Single Primer Enrichment Technology (SPET) with the Illumina HiSeq 2500 platform. Furthermore, DNA extracted from Solanum elaeagnifolium using this protocol was assessed by Pulsed-field gel electrophoresis (PFGE), obtaining a suitable size ranges for most sequencing platforms that required high-molecular-weight DNA such as Nanopore or PacBio.

CONCLUSIONS

A high-throughput, fast and inexpensive DNA extraction protocol was developed and validated for a wide variety of plants and tissues. SILEX offers an easy, scalable, efficient and inexpensive way to extract DNA for various next-generation sequencing applications including SPET and Nanopore among others.

Genomic Dissection of a Wild Region in a Superior Solanum pennellii Introgression Sub-Line with High Ascorbic Acid Accumulation in Tomato Fruit

The Solanum pennellii introgression lines (ILs) have been exploited to map quantitative trait loci (QTLs) and identify favorable alleles that could improve fruit quality traits in tomato varieties. Over the past few years, ILs exhibiting increased content of ascorbic acid in the fruit have been selected, among which the sub-line R182. The aims of this work were to identify the genes of the wild donor S. pennellii harbored by the sub-line and to detect genes controlling ascorbic acid accumulation by using genomics tools. A Genotyping-By-Sequencing (GBS) approach confirmed that no wild introgressions were present in the sub-line besides one region on chromosome 7. By using a dense single nucleotide polymorphism (SNP) map obtained by RNA sequencing (RNA-Seq), the wild region of the sub-line was finely identified; thus, defining 39 wild genes that replaced 33 genes of the ILs genetic background (cv. M82). The differentially expressed genes mapping in the region and the variants detected among the cultivated and the wild alleles evidenced the potential role of the novel genes present in the wild region. Interestingly, one upregulated gene, annotated as a major facilitator superfamily protein, showed a novel structure in R182, with respect to the parental lines. These genes will be further investigated using gene editing strategies.

Fostering Conservation via an Integrated Use of Conventional Approaches and High-Throughput SPET Genotyping: A Case Study Using the Endangered Canarian Endemics Solanum lidii and S. vespertilio (Solanaceae)

Islands provide unique opportunities to integrated research approaches to study evolution and conservation because boundaries are circumscribed, geological ages are often precise, and many taxa are greatly imperiled. We combined morphological and hybridization studies with high-throughput genotyping platforms to streamline relationships in the endangered monophyletic and highly diverse lineage of Solanum in the Canarian archipelago, where three endemic taxa are currently recognized. Inter-taxa hybridizations were performed, and morphological expression was assessed with a common-garden approach. Using the eggplant Single Primer Enrichment Technology (SPET) platform with 5,093 probes, 74 individuals of three endemic taxa (Solanum lidii, S. vespertilio subsp. vespertilio, and S. vespertilio subsp. doramae) were sampled for SNPs. While morphological and breeding studies showed clear distinctions and some continuous variation, inter-taxon hybrids were fertile and heterotic for vigor traits. SPET genotyping revealed 1,421 high-quality SNPs and supported four, not three, distinct taxonomic entities associated with post-emergence geological, ecological and geographic factors of the islands. Given the lack of barriers to hybridization among all the taxa and their molecular differences, great care must be taken in population management. Conservation strategies must take account of the sexual and breeding systems and genotypic distribution among populations to successfully conserve and restore threatened/endangered island taxa, as exemplified by Solanum on the Canary Islands.

A New Intra-Specific and High-Resolution Genetic Map of Eggplant Based on a RIL Population, and Location of QTLs Related to Plant Anthocyanin Pigmentation and Seed Vigour

Eggplant is the second most important solanaceous berry-producing crop after tomato. Despite mapping studies based on bi-parental progenies and GWAS approaches having been performed, an eggplant intraspecific high-resolution map is still lacking. We developed a RIL population from the intraspecific cross ‘305E40’, (androgenetic introgressed line carrying the locus Rfo-Sa1 conferring Fusarium resistance) x ‘67/3’ (breeding line whose genome sequence was recently released). One hundred and sixty-three RILs were genotyped by a genotype-by-sequencing (GBS) approach, which allowed us to identify 10,361 polymorphic sites. Overall, 267 Gb of sequencing data were generated and ~773 M Illumina paired end (PE) reads were mapped against the reference sequence. A new linkage map was developed, including 7249 SNPs assigned to the 12 chromosomes and spanning 2169.23 cM, with iaci@liberoan average distance of 0.4 cM between adjacent markers. This was used to elucidate the genetic bases of seven traits related to anthocyanin content in different organs recorded in three locations as well as seed vigor. Overall, from 7 to 17 QTLs (at least one major QTL) were identified for each trait. These results demonstrate that our newly developed map supplies valuable information for QTL fine mapping, candidate gene identification, and the development of molecular markers for marker assisted selection (MAS) of favorable alleles.

Construction of a high density linkage map in Oil Palm using SPET markers

A high-density genetic linkage map from a controlled cross of two oil palm (Elaeis guineensis) genotypes was constructed based on Single Primer Enrichment Technology (SPET) markers. A 5K panel of hybridization probes were used for this purpose which was derived from previously developed SNP primers in oil palm. Initially, 13,384 SNPs were detected which were reduced to 13,073 SNPs after filtering for only bi-allelic SNP. Around 75% of the markers were found to be monomorphic in the progeny, reducing the markers left for linkage mapping to 3,501. Using Lep-MAP3 software, a linkage map was constructed which contained initially 2,388 markers and had a total length of 1,370 cM. In many cases several adjacent SNP were located on the same locus, due to missing recombination events between them, leading to a total of 1,054 loci on the 16 LG. Nevertheless, the marker density of 1.74 markers per cM (0.57 cM/marker) should allow the detection of QTLs in the future. This study shows that cost efficient SPET markers are suitable for linkage map construction in oil palm and probably, also in other species.

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.

Whole-Genome Resequencing of Seven Eggplant (Solanum melongena) and One Wild Relative (S. incanum) Accessions Provides New Insights and Breeding Tools for Eggplant Enhancement

Whole-genome resequencing provides information of great relevance for crop genetics, evolution, and breeding. Here, we present the first whole-genome resequencing study using seven eggplant (Solanum melongena) and one wild relative (Solanum incanum) accessions. These eight accessions were selected for displaying a high phenotypic and genetic diversity and for being the founder parents of an eggplant multiparent advanced generation intercrosses population. By resequencing at an average depth of 19.8× and comparing to the high-quality reference genome "67/3" over 10 million high-reliable polymorphisms were discovered, of which over 9 million (84.5%) were single nucleotide polymorphisms and more than 700,000 (6.5%) InDels. However, while for the S. melongena accessions, the variants identified ranged from 0.8 to 1.3 million, over 9 million were detected for the wild S. incanum. This confirms the narrow genetic diversity of the domesticated eggplant and suggests that introgression breeding using wild relatives can efficiently contribute to broadening the genetic basis of this crop. Differences were observed among accessions for the enrichment in genes regulating important biological processes. By analyzing the distribution of the variants, we identified the potential footprints of old introgressions from wild relatives that can help to unravel the unclear domestication and breeding history. The comprehensive annotation of these eight genomes and the information provided in this study represents a landmark in eggplant genomics and allows the development of tools for eggplant genetics and breeding.