Next-generation sequencing applications for wheat crop improvement

Development of chromosome-arm-specific microsatellite markers in Triticum aestivum (Poaceae) using NGS technology

PREMISE OF THE STUDY

The aim of this study was to assess the feasibility of developing chromosome-arm-specific microsatellite markers in wheat on a large scale based on chromosome survey sequences obtained with next-generation sequencing (NGS) technology.

METHODS AND RESULTS

The Illumina Hi Seq2000 sequencing platform was used to sequence DNA of isolated wheat chromosome-arm 7DL. The data were assembled and microsatellite loci were identified computationally. In total, 16315 microsatellites were identified from 161061 assembled contigs. Thirty-three markers were randomly selected for validation across 20 diverse wheat cultivars. Two nulli-tetrasomic stocks were also screened to validate the specificity of the newly developed markers.

CONCLUSIONS

This is the first study on identification of chromosome-arm-specific microsatellite markers using NGS technology. These new chromosome-arm-specific markers will facilitate saturation of the 7DL genetic map, and their availability will support genetic mapping and positional cloning in wheat.

Discovery of Single Nucleotide Polymorphisms in Complex Genomes Using SGSautoSNP

Single nucleotide polymorphisms (SNPs) are becoming the dominant form of molecular marker for genetic and genomic analysis. The advances in second generation DNA sequencing provide opportunities to identify very large numbers of SNPs in a range of species. However, SNP identification remains a challenge for large and polyploid genomes due to their size and complexity. We have developed a pipeline for the robust identification of SNPs in large and complex genomes using Illumina second generation DNA sequence data and demonstrated this by the discovery of SNPs in the hexaploid wheat genome. We have developed a SNP discovery pipeline called SGSautoSNP (Second-Generation Sequencing AutoSNP) and applied this to discover more than 800,000 SNPs between four hexaploid wheat cultivars across chromosomes 7A, 7B and 7D. All SNPs are presented for download and viewing within a public GBrowse database. Validation suggests an accuracy of greater than 93% of SNPs represent polymorphisms between wheat cultivars and hence are valuable for detailed diversity analysis, marker assisted selection and genotyping by sequencing. The pipeline produces output in GFF3, VCF, Flapjack or Illumina Infinium design format for further genotyping diverse populations. As well as providing an unprecedented resource for wheat diversity analysis, the method establishes a foundation for high resolution SNP discovery in other large and complex genomes.

Evidence of cryptic introgression in tomato (Solanum lycopersicum L.) based on wild tomato species alleles

BACKGROUND

Many highly beneficial traits (e.g. disease or abiotic stress resistance) have been transferred into crops through crosses with their wild relatives. The 13 recognized species of tomato (Solanum section Lycopersicon) are closely related to each other and wild species genes have been extensively used for improvement of the crop, Solanum lycopersicum L. In addition, the lack of geographical barriers has permitted natural hybridization between S. lycopersicum and its closest wild relative Solanum pimpinellifolium in Ecuador, Peru and northern Chile. In order to better understand patterns of S. lycopersicum diversity, we sequenced 47 markers ranging in length from 130 to 1200 bp (total of 24 kb) in genotypes of S. lycopersicum and wild tomato species S. pimpinellifolium, Solanum arcanum, Solanum peruvianum, Solanum pennellii and Solanum habrochaites. Between six and twelve genotypes were comparatively analyzed per marker. Several of the markers had previously been hypothesized as carrying wild species alleles within S. lycopersicum, i.e., cryptic introgressions.

RESULTS

Each marker was mapped with high confidence (e<1 x 10-30) to a single genomic location using BLASTN against tomato whole genome shotgun chromosomes (SL2.40) database. Neighbor-joining trees showed high mean bootstrap support (86.8 ± 2.34%) for distinguishing red-fruited from green-fruited taxa for 38 of the markers. Hybridization and parsimony splits networks, genomic map positions of markers relative to documented introgressions, and historical origins of accessions were used to interpret evolutionary patterns at nine markers with putatively introgressed alleles.

CONCLUSION

Of the 47 genetic markers surveyed in this study, four were involved in linkage drag on chromosome 9 during introgression breeding, while alleles at five markers apparently originated from natural hybridization with S. pimpinellifolium and were associated with primitive genotypes of S. lycopersicum. The positive identification of introgressed genes within crop species such as S. lycopersicum will help inform conservation and utilization of crop germplasm diversity, for example, facilitating the purging of undesirable linkage drag or the exploitation of novel, favorable alleles.

Single nucleotide polymorphism discovery from wheat next-generation sequence data

Single nucleotide polymorphisms (SNPs) are the most abundant type of molecular genetic marker and can be used for producing high-resolution genetic maps, marker-trait association studies and marker-assisted breeding. Large polyploid genomes such as wheat present a challenge for SNP discovery because of the potential presence of multiple homoeologs for each gene. AutoSNPdb has been successfully applied to identify SNPs from Sanger sequence data for several species, including barley, rice and Brassica, but the volume of data required to accurately call SNPs in the complex genome of wheat has prevented its application to this important crop. DNA sequencing technology has been revolutionized by the introduction of next-generation sequencing, and it is now possible to generate several million sequence reads in a timely and cost-effective manner. We have produced wheat transcriptome sequence data using 454 sequencing technology and applied this for SNP discovery using a modified autoSNPdb method, which integrates SNP and gene annotation information with a graphical viewer. A total of 4,694,141 sequence reads from three bread wheat varieties were assembled to identify a total of 38 928 candidate SNPs. Each SNP is within an assembly complete with annotation, enabling the selection of polymorphism within genes of interest.

Bread matters: a national initiative to profile the genetic diversity of Australian wheat

The large and complex genome of wheat makes genetic and genomic analysis in this important species both expensive and resource intensive. The application of next-generation sequencing technologies is particularly resource intensive, with at least 17 Gbp of sequence data required to obtain minimal (1×) coverage of the genome. A similar volume of data would represent almost 40× coverage of the rice genome. Progress can be made through the establishment of consortia to produce shared genomic resources. Australian wheat genome researchers, working with Bioplatforms Australia, have collaborated in a national initiative to establish a genetic diversity dataset representing Australian wheat germplasm based on whole genome next-generation sequencing data. Here, we describe the establishment and validation of this resource which can provide a model for broader international initiatives for the analysis of large and complex genomes.

Applications of next-generation sequencing in plant biology

The last several years have seen revolutionary advances in DNA sequencing technologies with the advent of next-generation sequencing (NGS) techniques. NGS methods now allow millions of bases to be sequenced in one round, at a fraction of the cost relative to traditional Sanger sequencing. As costs and capabilities of these technologies continue to improve, we are only beginning to see the possibilities of NGS platforms, which are developing in parallel with online availability of a wide range of biological data sets and scientific publications and allowing us to address a variety of questions not possible before. As techniques and data sets continue to improve and grow, we are rapidly moving to the point where every organism, not just select "model organisms", is open to the power of NGS. This volume presents a brief synopsis of NGS technologies and the development of exemplary applications of such methods in the fields of molecular marker development, hybridization and introgression, transcriptome investigations, phylogenetic and ecological studies, polyploid genetics, and applications for large genebank collections.