Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

BACKGROUND: The tetraploid durum wheat (Triticum turgidum L. ssp. durum Desf. Husnot) is an important crop which provides the raw material for pasta production and a valuable source of genetic diversity for breeding hexaploid wheat (Triticum aestivum L.). Future breeding efforts to enhance yield potential and climate resilience will increasingly rely on genomics-based approaches to identify and select beneficial alleles. A deeper characterisation of the molecular and functional diversity of the durum wheat transcriptome will be instrumental to more effectively harness its genetic diversity. RESULTS: We report on the de novo transcriptome assembly of durum wheat cultivar 'Svevo'. The transcriptome of four tissues/organs (shoots and roots at the seedling stage, reproductive organs and developing grains) was assembled de novo, yielding 180,108 contigs, with a N50 length of 1121\u2009bp and mean contig length of 883\u2009bp. Alignment against the transcriptome of nine plant species identified 43% of transcripts with homology to at least one reference transcriptome. The functional annotation was completed by means of a combination of complementary software. The presence of differential expression between the A- and B-homoeolog copies of the durum wheat tetraploid genome was ascertained by phase reconstruction of polymorphic sites based on the T. urartu transcripts and inferring homoeolog-specific sequences. We observed greater expression divergence between A and B homoeologs in grains rather than in leaves and roots. The transcriptomes of 13 durum wheat cultivars spanning the breeding period from 1969 to 2005 were analysed for SNP diversity, leading to 95,358 non-rare, hemi-SNPs shared among two or more cultivars and 33,747 locus-specific (diploid inheritance) SNPs. CONCLUSIONS: Our study updates and expands the de novo transcriptome reference assembly available for durum wheat. Out of 180,108 assembled transcripts, 13,636 were specific to the Svevo cultivar as compared to the only other reference transcriptome available for durum, thus contributing to the identification of the tetraploid wheat pan-transcriptome. Additionally, the analysis of 13 historically relevant hallmark varieties produced a SNP dataset that could successfully validate the genotyping in tetraploid wheat and provide a valuable resource for genomics-assisted breeding of both tetraploid and hexaploid wheats

CSGM Designer: a platform for designing cross-species intron-spanning genic markers linked with genome information of legumes.

BackgroundGenetic markers are tools that can facilitate molecular breeding, even in species lacking genomic resources. An important class of genetic markers is those based on orthologous genes, because they can guide hypotheses about conserved gene function, a situation that is well documented for a number of agronomic traits. For under-studied species a key bottleneck in gene-based marker development is the need to develop molecular tools (e.g., oligonucleotide primers) that reliably access genes with orthology to the genomes of well-characterized reference species.ResultsHere we report an efficient platform for the design of cross-species gene-derived markers in legumes. The automated platform, named CSGM Designer (URL: http://tgil.donga.ac.kr/CSGMdesigner), facilitates rapid and systematic design of cross-species genic markers. The underlying database is composed of genome data from five legume species whose genomes are substantially characterized. Use of CSGM is enhanced by graphical displays of query results, which we describe as "circular viewer" and "search-within-results" functions. CSGM provides a virtual PCR representation (eHT-PCR) that predicts the specificity of each primer pair simultaneously in multiple genomes. CSGM Designer output was experimentally validated for the amplification of orthologous genes using 16 genotypes representing 12 crop and model legume species, distributed among the galegoid and phaseoloid clades. Successful cross-species amplification was obtained for 85.3% of PCR primer combinations.ConclusionCSGM Designer spans the divide between well-characterized crop and model legume species and their less well-characterized relatives. The outcome is PCR primers that target highly conserved genes for polymorphism discovery, enabling functional inferences and ultimately facilitating trait-associated molecular breeding

Genetic mapping of legume orthologs reveals high conservation of synteny between lentil species and the sequenced genomes of Medicago and chickpea.

Lentil (Lens culinaris Medik.) is a global food crop with increasing importance for food security in south Asia and other regions. Lens ervoides, a wild relative of cultivated lentil, is an important source of agronomic trait variation. Lens is a member of the galegoid clade of the Papilionoideae family, which includes other important dietary legumes such as chickpea (Cicer arietinum) and pea (Pisum sativum), and the sequenced model legume Medicago truncatula. Understanding the genetic structure of Lens spp. in relation to more fully sequenced legumes would allow leveraging of genomic resources. A set of 1107 TOG-based amplicons were identified in L. ervoides and a subset thereof used to design SNP markers for mapping. A map of L. ervoides consisting of 377 SNP markers spread across seven linkage groups was developed using a GoldenGate genotyping array and single SNP marker assays. Comparison with maps of M. truncatula and L. culinaris documented considerable shared synteny and led to the identification of a few major translocations and a major inversion that distinguish Lens from M. truncatula, as well as a translocation that distinguishes L. culinaris from L. ervoides. The identification of chromosome-level differences among Lens spp. will aid in the understanding of introgression of genes from L. ervoides into cultivated L. culinaris, furthering genetic research and breeding applications in lentil

Transcriptomic Studies in Non-Model Plants: Case of Pisum sativum L. and Medicago lupulina L.

Transcriptomics is a dynamically developing branch of biology highly important for geneticists and molecular ecologists alike. A large number of studies concerning differential gene expression, mapping of genes and quantitative trait loci (QTL), analysis of genotyping variations and so on has been conducted recently on several non‐model plants using next‐generation sequencing techniques. One example of non‐model legumes is garden pea (Pisum sativum L.), a valuable pulse crop capable of forming nitrogen‐fixing nodules and arbuscular mycorrhiza. Adaptation of standardised RNA‐seq approaches and data analysis developed for model plants to P. sativum should facilitate both studying of pea molecular genetics and breeding of new cultivars possessing agriculturally important traits. Another non‐model legume is black medick Medicago lupulina L. (a close relative of model legume plant barrel medick, Medicago truncatula Gaertn.), for which unique genetic lines almost obligatory dependent on arbuscular mycorrhiza symbiosis formation have been obtained. Such lines show promise as the perfect model for studying the genetic bases of arbuscular mycorrhiza development. In this chapter, we give a brief description of the current developments in the field of garden pea and black medick transcriptomics. Our aim is to provide a quick start guide to the non‐expert researchers for next‐generation sequencing (NGS)‐based transcriptome analysis

Single feature polymorphisms (SFPs) for drought tolerance in pigeonpea (Cajanus spp.)

Single feature polymorphisms (SFPs) are microarray-based molecular markers that are detected by hybridization of DNA or cRNA to oligonucleotide probes. With an objective to identify the potential polymorphic markers for drought tolerance in pigeonpea [Cajanus cajan (L.) Millspaugh], an important legume crop for the semi-arid tropics but deficient in genomic resources, Affymetrix Genome Arrays of soybean (Glycine max), a closely related species of pigeonpea were used on cRNA of six parental genotypes of three mapping populations of pigeonpea segregating for agronomic traits like drought tolerance and pod borer (Helicoverpa armigiera) resistance. By using robustified projection pursuit method on 15 pair-wise comparisons for the six parental genotypes, 5,692 SFPs were identified. Number of SFPs varied from 780 (ICPL 8755 × ICPL 227) to 854 (ICPL 151 × ICPL 87) per parental combination of the mapping populations. Randomly selected 179 SFPs were used for validation by Sanger sequencing and good quality sequence data were obtained for 99 genes of which 75 genes showed sequence polymorphisms. While associating the sequence polymorphisms with SFPs detected, true positives were observed for 52.6% SFPs detected. In terms of parental combinations of the mapping populations, occurrence of true positives was 34.48% for ICPL 151 × ICPL 87, 41.86% for ICPL 8755 × ICPL 227, and 81.58% for ICP 28 × ICPW 94. In addition, a set of 139 candidate genes that may be associated with drought tolerance has been identified based on gene ontology analysis of the homologous pigeonpea genes to the soybean genes that detected SFPs between the parents of the mapping populations segregating for drought tolerance

Transcriptome Analysis in Chickpea (Cicer arietinum L.): Applications in Study of Gene Expression, Non-Coding RNA Prediction, and Molecular Marker Development

Extensive analyses of transcriptome have been carried out in chickpea, which is the third most important legume valued as a source of dietary protein and micronutrients. Over the last two decades, several laboratories have used a wide range of techniques encompassing expressed sequence tag (EST) analysis, serial analysis of gene expression (SAGE), microarray and next-generation sequencing (NGS) technologies for analysing the chickpea transcriptomes. However, chickpea transcriptome analysis witnessed significant progress with the advent of the NGS platforms. Gene expression analyses using NGS platforms were carried out in the vegetative and reproductive tissues such as shoot, root, mature leaf, flower bud, young pod, seed and nodule by various groups which resulted in identification of several tissue-specific transcripts. Some laboratories have utilized transcriptomics to explore the response of chickpea to abiotic and biotic stresses such as drought, salinity, heat, cold, Fusarium oxysporum and Ascochyta rabiei differentially expressed genes and also established crosstalk between biotic and abiotic stress responses. Transcriptome analysis has been utilized extensively to identify non-coding RNAs such as miRNAs and long intergenic non-coding (LINC) RNAs. Transcriptome analysis has facilitated the development of molecular markers such as simple sequence repeats (SSRs), single-nucleotide polymorphisms (SNPs) and potential intron polymorphisms (PIPs) that are being used to expedite the chickpea breeding programmes. The available chickpea transcriptomes will continue to serve as the foundation for devising strategies for chickpea improvement

Generation and application of genomic tools as important prerequisites for sugar beet genome analyses.

Genetic and physical maps of a genome are essential tools for structural, functional and applied genomics. Genetic maps allow the detection of quantitative trait loci (QTLs), the characterisation of QTL effects and facilitate marker-assisted selection (MAS). The characterisation of genome structure and analysis of evolution is augmented by physical maps. Whole genome physical maps or ultimately complete genomic sequences, respectively, of a species display frameworks that provide essential information for understanding processes in respect to physiology, morphology, development and genetics. However, comprehensive annotation underpins the values a genome sequence or physical map represents. An important task of genome annotation is the linkage of genetic traits to the genome sequence, which is facilitated by integrated genetic and physical maps. In the context of this study several sugar beet (Beta vulgaris L.) genomic tools were developed and applied for evolutionary studies and linkage analysis. A new technique allowing high-throughput identification and genotyping of genetic markers was developed, utilising representational oligonucleotide microarray analysis (ROMA). We tested the performance of the method in sugar beet as a model for crop plants with little sequence information available. Genomic representations of both parents of a mapping population were hybridised on microarrays containing custom oligonucleotides based on sugar beet bacterial artificial chromosome (BAC) end sequences (BESs) and expressed sequence tags (ESTs). Subsequent analysis identified potential polymorphic oligonucleotides, which were placed on new microarrays used for screening of 184 F2 individuals. Exploiting known co-dominant anchor markers, we obtained 511 new dominant markers distributed over all nine sugar beet linkage groups and calculated genetic maps. Besides the method´s transferability to other species, the obtained genetic markers will be an asset for ordering of sequence contigs in the context of the ongoing sugar beet genome sequencing project. In addition, possible linkage of physical and genetic maps was provided, since genetic markers were based on source sequences, which were also used for construction of a BAC based physical map utilising a hybridisation approach. An example of the hybridisation based approach for physical map construction and its application for synteny studies was demonstrated. Since little is known about synteny between rosids and Caryophyllales so far, we analysed the extent of synteny between the genomic sequences of two BAC clones derived from two different Beta vulgaris haplotypes and rosid genomes. For selection of the two BAC clones we hybridised 30 oligonucleotide probes based on ESTs corresponding to Arabidopsis orthologs on chromosomes 1 and 4 that were presumably co-localised in the reconstructed Arabidopsis pseudo ancestral genome (Blanc et al. 2003) on sugar beet BAC macroarrays comprising two different sugar beet libraries. A total of 27,648 clones were screened per sugar beet library, corresponding to 4.4-fold and 5.5-fold, respectively, sugar beet genome coverage. We obtained four and five positive clones for the probes on average. Two clones, one from each haplotype that were positive with the same five EST probes, were selected and their genomic sequences were determined, annotated and exploited for synteny studies. Furthermore, I constructed and characterised a sugar beet fosmid library from the doubled haploid accession KWS2320 encompassing 115,200 independent clones. The insert size of the fosmid library was determined by pulsed field gel electrophoresis to be 39 kbp on average, thus representing 5.9-fold coverage of the sugar beet genome. Fosmids bear the advantage of narrowly defined size of the clone inserts, thus fosmid end sequences will essentially contribute to the future assembly and ordering of sequence contigs. Since repeats are a major obstacle for successful assembly of plant genome sequences, frequently causing gaps and misassembled contigs, I generated a genomic short-insert library. The short-insert library facilitated repeat identification within the sugar beet genome, which was exemplarily shown for three miniature inverted-repeat transposable element (MITE) families. Altogether this work contributed substantially to a deeper understanding of the genome structure of sugar beet and provided the basis for successful sequencing of the sugar beet genome