Kaitao Lai

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.

Sequencing wheat chromosome arm 7BS delimits the 7BS/4AL translocation and reveals homoeologous gene conservation

Complex Triticeae genomes pose a challenge to genome sequencing efforts due to their size and repetitive nature. Genome sequencing can reveal details of conservation and rearrangements between related genomes. We have applied Illumina second generation sequencing technology to sequence and assemble the low copy and unique regions of Triticum aestivum chromosome arm 7BS, followed by the construction of a syntenic build based on gene order in Brachypodium. We have delimited the position of a previously reported translocation between 7BS and 4AL with a resolution of one or a few genes and report approximately 13% genes from 7BS having been translocated to 4AL. An additional 13 genes are found on 7BS which appear to have originated from 4AL. The gene content of the 7DS and 7BS syntenic builds indicate a total of ~77,000 genes in wheat. Within wheat syntenic regions, 7BS and 7DS share 740 genes and a common gene conservation rate of ~39% of the genes from the corresponding regions in Brachypodium, as well as a common rate of colinearity with Brachypodium of ~60%. Comparison of wheat homoeologues revealed ~84% of genes previously identified in 7DS have a homoeologue on 7BS or 4AL. The conservation rates we have identified among wheat homoeologues and with Brachypodium provide a benchmark of homoeologous gene conservation levels for future comparative genomic analysis. The syntenic build of 7BS is publicly available at http://www.wheatgenome.info.

Next-generation sequencing applications for wheat crop improvement

Bread wheat (Triticum aestivum; Poaceae) is a crop plant of great importance. It provides nearly 20% of the worlds daily food supply measured by calorie intake, similar to that provided by rice. The yield of wheat has doubled over the last 40 years due to a combination of advanced agronomic practice and improved germplasm through selective breeding. More recently, yield growth has been less dramatic, and a significant improvement in wheat production will be required if demand from the growing human population is to be met. Next-generation sequencing (NGS) technologies are revolutionizing biology and can be applied to address critical issues in plant biology. Technologies can produce draft sequences of genomes with a significant reduction to the cost and timeframe of traditional technologies. In addition, NGS technologies can be used to assess gene structure and expression, and importantly, to identify heritable genome variation underlying important agronomic traits. This review provides an overview of the wheat genome and NGS technologies, details some of the problems in applying NGS technology to wheat, and describes how NGS technologies are starting to impact wheat crop improvement.

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.

Dispersion and domestication shaped the genome of bread wheat

Despite the international significance of wheat, its large and complex genome hinders genome sequencing efforts. To assess the impact of selection on this genome, we have assembled genomic regions representing genes for chromosomes 7A, 7B and 7D. We demonstrate that the dispersion of wheat to new environments has shaped the modern wheat genome. Most genes are conserved between the three homoeologous chromosomes. We found differential gene loss that supports current theories on the evolution of wheat, with greater loss observed in the A and B genomes compared with the D. Analysis of intervarietal polymorphisms identified fewer polymorphisms in the D genome, supporting the hypothesis of early gene flow between the tetraploid and hexaploid. The enrichment for genes on the D genome that confer environmental adaptation may be associated with dispersion following wheat domestication. Our results demonstrate the value of applying next-generation sequencing technologies to assemble gene-rich regions of complex genomes and investigate polyploid genome evolution. We anticipate the genome-wide application of this reduced-complexity syntenic assembly approach will accelerate crop improvement efforts not only in wheat, but also in other polyploid crops of significance.

WheatGenome.info: An Integrated Database and Portal for Wheat Genome Information

Bread wheat (Triticum aestivum) is one of the most important crop plants, globally providing staple food for a large proportion of the human population. However, improvement of this crop has been limited due to its large and complex genome. Advances in genomics are supporting wheat crop improvement. We provide a variety of web-based systems hosting wheat genome and genomic data to support wheat research and crop improvement. WheatGenome.info is an integrated database resource which includes multiple web-based applications. These include a GBrowse2-based wheat genome viewer with BLAST search portal, TAGdb for searching wheat second-generation genome sequence data, wheat autoSNPdb, links to wheat genetic maps using CMap and CMap3D, and a wheat genome Wiki to allow interaction between diverse wheat genome sequencing activities. This system includes links to a variety of wheat genome resources hosted at other research organizations. This integrated database aims to accelerate wheat genome research and is freely accessible via the web interface at http://www.wheatgenome.info/.

Targeted identification of genomic regions using TAGdb

BackgroundThe introduction of second generation sequencing technology has enabled the cost effective sequencing of genomes and the identification of large numbers of genes and gene promoters. However, the assembly of DNA sequences to create a representation of the complete genome sequence remains costly, especially for the larger and more complex plant genomes.ResultsWe have developed an online database, TAGdb, that enables researchers to identify paired read sequences that share identity with a submitted query sequence. These tags can be used to design oligonucleotide primers for the PCR amplification of the region in the target genome.ConclusionsThe ability to produce large numbers of paired read genome tags using second generation sequencing provides a cost effective method for the identification of genes and promoters in large, complex or orphan species without the need for whole genome assembly.

Identification and characterization of more than 4 million intervarietal SNPs across the group 7 chromosomes of bread wheat

Despite being a major international crop, our understanding of the wheat genome is relatively poor due to its large size and complexity. To gain a greater understanding of wheat genome diversity, we have identified single nucleotide polymorphisms between 16 Australian bread wheat varieties. Whole-genome shotgun Illumina paired read sequence data were mapped to the draft assemblies of chromosomes 7A, 7B and 7D to identify more than 4 million intervarietal SNPs. SNP density varied between the three genomes, with much greater density observed on the A and B genomes than the D genome. This variation may be a result of substantial gene flow from the tetraploid Triticum turgidum, which possesses A and B genomes, during early co-cultivation of tetraploid and hexaploid wheat. In addition, we examined SNP density variation along the chromosome syntenic builds and identified genes in low-density regions which may have been selected during domestication and breeding. This study highlights the impact of evolution and breeding on the bread wheat genome and provides a substantial resource for trait association and crop improvement. All SNP data are publically available on a generic genome browser GBrowse at www.wheatgenome.info.

Wheatgenome.info: a resource for wheat genomics resource

An integrated database with a variety of Web-based systems named WheatGenome.info hosting wheat genome and genomic data has been developed to support wheat research and crop improvement. The resource includes multiple Web-based applications, which are implemented as a variety of Web-based systems. These include a GBrowse2-based wheat genome viewer with BLAST search portal, TAGdb for searching wheat second generation genome sequence data, wheat autoSNPdb, links to wheat genetic maps using CMap and CMap3D, and a wheat genome Wiki to allow interaction between diverse wheat genome sequencing activities. This portal provides links to a variety of wheat genome resources hosted at other research organizations. This integrated database aims to accelerate wheat genome research and is freely accessible via the web interface at http://www.wheatgenome.info/ .

Molecular Marker Databases

The detection and analysis of genetic variation plays an important role in plant breeding and this role is increasing with the continued development of genome sequencing technologies. Molecular genetic markers are important tools to characterize genetic variation and assist with genomic breeding. Processing and storing the growing abundance of molecular marker data being produced requires the development of specific bioinformatics tools and advanced databases. Molecular marker databases range from species specific through to organism wide and often host a variety of additional related genetic, genomic, or phenotypic information. In this chapter, we will present some of the features of plant molecular genetic marker databases, highlight the various types of marker resources, and predict the potential future direction of crop marker databases.