Single nucleotide polymorphism discovery in barley using autoSNPdb

Bioinformatics approaches and big data analytics opportunities in improving fisheries and aquaculture

Aquaculture has witnessed an excellent growth rate during the last two decades and offers huge potential to provide nutritional as well as livelihood security. Genomic research has contributed significantly toward the development of beneficial technologies for aquaculture. The existing high throughput technologies like next-generation technologies generate oceanic data which requires extensive analysis using appropriate tools. Bioinformatics is a rapidly evolving science that involves integrating gene based information and computational technology to produce new knowledge for the benefit of aquaculture. Bioinformatics provides new opportunities as well as challenges for information and data processing in new generation aquaculture. Rapid technical advancements have opened up a world of possibilities for using current genomics to improve aquaculture performance. Understanding the genes that govern economically relevant characteristics, necessitates a significant amount of additional research. The various dimensions of data sources includes next-generation DNA sequencing, protein sequencing, RNA sequencing gene expression profiles, metabolic pathways, molecular markers, and so on. Appropriate bioinformatics tools are developed to mine the biologically relevant and commercially useful results. The purpose of this scoping review is to present various arms of diverse bioinformatics tools with special emphasis on practical translation to the aquaculture industry.

Tracking Changes in the Spring Barley Gene Pool in Poland during 120 Years of Breeding

This study was undertaken to investigate the diversity and population structure of 83 spring barley (Hordeum vulgare L.) cultivars, which corresponded to 120 years of this crop's breeding in Poland. The analysis was based on 11,655 DArTseq-derived SNPs evenly distributed across seven barley chromosomes. Five groups were assigned in the studied cultivars according to the period of their breeding. A decrease in observed heterozygosity within the groups was noted along with the progress in breeding, with a simultaneous increase in the inbreeding coefficient value. As a result of breeding, some of the unique allelic variation present in old cultivars was lost, but crosses with foreign materials also provided new alleles to the barley gene pool. It is important to mention that the above changes affected different chromosomes to varying degrees. The internal variability of the cultivars ranged from 0.011 to 0.236. Internal uniformity was lowest among the oldest cultivars, although some highly homogeneous ones were found among them. This is probably an effect of genetic drift or selection during their multiplications and regenerations in the period from breeding to the time of analysis. The population genetic structure of the studied group of cultivars appears to be quite complex. It was shown that their genetic makeup consists of as many as eleven distinct gene pools. The analysis also showed traces of directed selection on chromosomes 3H and 5H. Detailed data analysis confirmed the presence of duplicates for 11 cultivars. The performed research will allow both improvement of the management of barley genetic resources in the gene bank and the reuse of this rich and forgotten variability in breeding programs and research.

Discovery of Functional SNPs via Genome-Wide Exploration of Malaysian Pigmented Rice Varieties

Recently, rice breeding program has shown increased interests on the pigmented rice varieties due to their benefits to human health. However, the genetic variation of pigmented rice varieties is still scarce and remains unexplored. Hence, we performed genome-wide SNP analysis from the genome resequencing of four Malaysian pigmented rice varieties, representing two black and two red rice varieties. The genome of four pigmented varieties was mapped against Nipponbare reference genome sequences, and 1.9 million SNPs were discovered. Of these, 622 SNPs with polymorphic sites were identified in 258 protein-coding genes related to metabolism, stress response, and transporter. Comparative analysis of 622 SNPs with polymorphic sites against six rice SNP datasets from the Ensembl Plants variation database was performed, and 70 SNPs were identified as novel SNPs. Analysis of SNPs in the flavonoid biosynthetic genes revealed 40 nonsynonymous SNPs, which has potential as molecular markers for rice seed colour identification. The highlighted SNPs in this study show effort in producing valuable genomic resources for application in the rice breeding program, towards the genetic improvement of new and improved pigmented rice varieties.

Genetic variation of HvXYN1 associated with endoxylanase activity and TAX content in barley (Hordeum vulgare L.)

BACKGROUND

Endo-β-1,4-xylanase1 (EA), the key endoxylanase in plants, is involved in the degradation of arabinoxylan during grain germination. In barley (Hordeum vulgare L.), one gene (HvXYN-1) that encode a endo-beta-1,4-xylanase, has been cloned. However, the single nucleotide polymorphisms (SNPs) that affect the endoxylanase activity and total arabinoxylan (TAX) content have yet to be characterized. The investigation of genetic variation in HvXYN1 may facilitate a better understanding of the relationship between TAX content and EA activity in barley.

RESULTS

In the current study, 56 polymorphisms were detected in HvXYN1 among 210 barley accessions collected from 34 countries, with 10 distinct haplotypes identified. The SNPs at positions 110, 305, 1045, 1417, 1504, 1597, 1880 bp in the genomic region of HvXYN1 were significantly associated with EA activity (P < 0.0001), and the sites 110, 305, and 1045 were highly significantly associated with TAX content. The amount of phenotypic variation in a given trait explained by each associated polymorphism ranged from 6.96 to 9.85%. Most notably, we found two variants at positions 1504 bp and 1880 bp in the second exon that significantly (P < 0.0001) affected EA activity; this result could be used in breeding programs to improve beer quality. In addition, African accessions had the highest EA activity and TAX content, and the richest germplasm resources were from Asia, indicating the high potential value of Asian barley.

CONCLUSION

This study provided insight into understanding the relationship, EA activity, TAX content with the SNPs of HvXYN1 in barley. These SNPs can be applied as DNA markers in breeding programs to improve the quality of barley for beer brewing after further validation.

Genetic variations of HvP5CS1 and their association with drought tolerance related traits in barley (Hordeum vulgare L.)

Delta-1-pyrroline-5-carboxylate synthase gene1 (P5CS1) is the key gene involved in the biosynthesis of proline and is significantly induced by drought stress. The exploration of genetic variation in HvP5CS1 may facilitate a better understanding of the mechanism of drought adaptation in barley. In the current study, 41 polymorphisms including 16 single nucleotide polymorphisms (SNPs) and 25 insertions/deletions (indels) were detected in HvP5CS1 among 287 barley (Hordeum vulgare L.) accessions collected worldwide, with 13 distinct haplotypes identified in the barley collection. Five polymorphisms in HvP5CS1 were significantly (P < 0.001) associated with drought tolerance related traits in barley. The phenotypic variation of a given trait explained by each associated polymorphism ranged from 4.43% to 9.81%. Two sequence variations that were significantly (P < 0.0001) associated with grain yield had marginally significant positive Tajima’s D values in the sliding window, so they might have been selected for environmental adaptation. Meanwhile, two haplotypes HvP5CS1_H1 and HvP5CS1_H4, which contained desired alleles of the two variations mentioned above, were significantly (P < 0.001) associated with drought tolerance related traits, and explained 5.00~11.89% of the phenotypic variations. These variations associated with drought tolerance related traits can be used as potential markers for improving drought tolerance in barley.

Is a non-synonymous SNP in the HvAACT1 coding region associated with acidic soil tolerance in barley?

The barley HvAACT1 gene codes for a citrate transporter associated with tolerance to acidic soil. In this report, we describe a single nucleotide polymorphism (SNP) in the HvAACT1 coding region that was detected as T-1,198 (in genotypes with lower root growth on acidic soil) or G-1,198 (greater root growth) and resulted in a single amino acid change (L/V-172). Molecular dynamic analysis predicted that HvAACT1 proteins with L or V-172 were stable, although the substitution led to structural changes within the protein. To evaluate the effect of the SNP on tolerance to acidic soil, barley accessions were separated into haplotypes based on the presence of a 1 kb insertion in the HvAACT1 promoter and a 21 bp insertion/deletion. These markers and the SNP-1,198 allowed the identification of five haplotypes. Short-term soil experiments showed no difference in root growth for most of the accessions containing the 21 bp insertion and T or G-1,198. In contrast, genotypes showing both the 21 bp deletion and G-1,198, with one of them having the 1 kb insertion, showed greater root growth. These results indicate that the SNP was not advantageous or deleterious when genotypes from the same haplotype were compared. The occurrence of the SNP was highly correlated with the 21 bp insertion/deletion that, together with the 1 kb insertion, explained most of the barley tolerance to acidic soil.

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/ .

Comparison of SNP and CAPS markers application in genetic research in wheat and barley

BACKGROUND

Barley and bread wheat show large differences in frequencies of Single Nucleotide Polymorphism (SNP) as determined from genome-wide studies. These frequencies have been estimated as 2.4-3 times higher in the entire barley genome than within each diploid genomes of wheat (A, B or D). However, barley SNPs within individual genes occur significantly more frequently than quoted. Differences between wheat and barley are based on the origin and evolutionary history of the species. Bread wheat contains rarer SNPs due to the double genetic 'bottle-neck' created by natural hybridisation and spontaneous polyploidisation. Furthermore, wheat has the lowest level of useful SNP-derived markers while barley is estimated to have the highest level of polymorphism.

RESULTS

Different strategies are required for the development of suitable molecular markers in these cereal species. For example, SNP markers based on high-throughput technology (Infinium or KASP) are very effective and useful in both barley and bread wheat. In contrast, Cleaved Amplified Polymorphic Sequences (CAPS) are more widely and successfully employed in small-scale experiments with highly polymorphic genetic regions containing multiple SNPs in barley, but not in wheat. However, preliminary 'in silico' search databases for assessing the potential value of SNPs have yet to be developed.

CONCLUSIONS

This mini-review summarises results supporting the development of different strategies for the application of effective SNP and CAPS markers in wheat and barley.

CicArVarDB: SNP and InDel database for advancing genetics research and breeding applications in chickpea

Molecular markers are valuable tools for breeders to help accelerate crop improvement. High throughput sequencing technologies facilitate the discovery of large-scale variations such as single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs). Sequencing of chickpea genome along with re-sequencing of several chickpea lines has enabled the discovery of 4.4 million variations including SNPs and InDels. Here we report a repository of 1.9 million variations (SNPs and InDels) anchored on eight pseudomolecules in a custom database, referred as CicArVarDB that can be accessed at http://cicarvardb.icrisat.org/. It includes an easy interface for users to select variations around specific regions associated with quantitative trait loci, with embedded webBLAST search and JBrowse visualisation. We hope that this database will be immensely useful for the chickpea research community for both advancing genetics research as well as breeding applications for crop improvement.

Database URL:http://cicarvardb.icrisat.org.

Bioinformatics: identification of markers from next-generation sequence data

With the advent of sequencing technology, next-generation sequencing (NGS) technology has dramatically revolutionized plant genomics. NGS technology combined with new software tools enables the discovery, validation, and assessment of genetic markers on a large scale. Among different markers systems, simple sequence repeats (SSRs) and Single nucleotide polymorphisms (SNPs) are the markers of choice for genetics and plant breeding. SSR markers have been a choice for large-scale characterization of germplasm collections, construction of genetic maps, and QTL identification. Similarly, SNPs are the most abundant genetic variations with higher frequencies throughout the genome of plant species. This chapter discusses various tools available for genome assembly and widely focuses on SSR and SNP marker discovery.

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.

Transcriptome sequencing of two wild barley (Hordeum spontaneum L.) ecotypes differentially adapted to drought stress reveals ecotype-specific transcripts

BACKGROUND

Wild barley is adapted to highly diverse environments throughout its geographical distribution range. Transcriptome sequencing of differentially adapted wild barley ecotypes from contrasting environments contributes to the identification of genes and genetic variation involved in abiotic stress tolerance and adaptation.

RESULTS

Two differentially adapted wild barley ecotypes from desert (B1K2) and Mediterranean (B1K30) environments were analyzed for drought stress response under controlled conditions. The desert ecotype lost more water under both irrigation and drought, but exhibited higher relative water content (RWC) and better water use efficiency (WUE) than the coastal ecotype. We sequenced normalized cDNA libraries from drought-stressed leaves of both ecotypes with the 454 platform to identify drought-related transcripts. Over half million reads per ecotype were de novo assembled into 20,439 putative unique transcripts (PUTs) for B1K2, 21,494 for B1K30 and 28,720 for the joint assembly. Over 50% of PUTs of each ecotype were not shared with the other ecotype. Furthermore, 16% (3,245) of B1K2 and 17% (3,674) of B1K30 transcripts did not show orthologous sequence hits in the other wild barley ecotype and cultivated barley, and are candidates of ecotype-specific transcripts. Over 800 unique transcripts from each ecotype homologous to over 30 different stress-related genes were identified. We extracted 1,017 high quality SNPs that differentiated the two ecotypes. The genetic distance between the desert ecotype and cultivated barley was 1.9-fold higher than between the Mediterranean ecotype and cultivated barley. Moreover, the desert ecotype harbored a larger proportion of non-synonymous SNPs than the Mediterranean ecotype suggesting different demographic histories of these ecotypes.

CONCLUSIONS

The results indicate a strong physiological and genomic differentiation between the desert and Mediterranean wild barley ecotypes and a closer relationship of the Mediterranean to cultivated barley. A significant number of novel transcripts specific to wild barley were identified. The higher SNP density and larger proportion of SNPs with functional effects in the desert ecotype suggest different demographic histories and effects of natural selection in Mediterranean and desert wild barley. The data are a valuable genomic resource for an improved genome annotation, transcriptome studies of drought adaptation and a source of new genetic markers for future barley improvement.

A high-throughput SNP array in the amphidiploid species Brassica napus shows diversity in resistance genes

Single-nucleotide polymorphisms (SNPs)are molecular markers based on nucleotide variation and can be used for genotyping assays across populations and to track genomic inheritance. SNPs offer a comprehensive genotyping alternative to whole-genome sequencing for both agricultural and research purposes including molecular breeding and diagnostics, genome evolution and genetic diversity analyses, genetic mapping, and trait association studies. Here genomic SNPs were discovered between four cultivars of the important amphidiploid oilseed species Brassica napus and used to develop a B. napus Infinium™ array containing 5,306 SNPs randomly dispersed across the genome. Assay success was high, with >94 % of these producing a reproducible, polymorphic genotype in the 1,070 samples screened. Although the assay was designed to B. napus, successful SNP amplification was achieved in the B. napus progenitor species, Brassica rapa and Brassica oleracea, and to a lesser extent in the related species Brassica nigra. Phylogenetic analysis was consistent with the expected relationships between B. napus individuals. This study presents an efficient custom SNP assay development pipeline in the complex polyploid Brassica genome and demonstrates the utility of the array for high-throughput genotyping in a number of related Brassica species. It also demonstrates the utility of this assay in genotyping resistance genes on chromosome A7, which segregate amongst the 1,070 samples.

An integrated SNP mining and utilization (ISMU) pipeline for next generation sequencing data

Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.

New technologies for ultrahigh-throughput genotyping in plant taxonomy

Molecular genetic markers represent one of the most powerful tools for the analysis of variation between plant genomes. Molecular marker technology has developed rapidly over the last decade, with the introduction of new DNA sequencing methods and the development of high-throughput genotyping methods. Single nucleotide polymorphisms (SNPs) now dominate applications in modern plant genetic analysis. The reducing cost of DNA sequencing and increasing availability of large sequence data sets permit the mining of this data for large numbers of SNPs. These may then be used in applications such as genetic linkage analysis and trait mapping, diversity analysis, association studies, and marker-assisted selection. Here we describe automated methods for the discovery of SNP molecular markers and new technologies for high-throughput, low-cost molecular marker genotyping. Examples include SNP discovery using autoSNPdb and wheatgenome.info as well as SNP genotyping using Illumina's GoldenGate™ and Infinium™ methods.

Next generation characterisation of cereal genomes for marker discovery

Cereal crops form the bulk of the world’s food sources, and thus their importance cannot be understated. Crop breeding programs increasingly rely on high-resolution molecular genetic markers to accelerate the breeding process. The development of these markers is hampered by the complexity of some of the major cereal crop genomes, as well as the time and cost required. In this review, we address current and future methods available for the characterisation of cereal genomes, with an emphasis on faster and more cost effective approaches for genome sequencing and the development of markers for trait association and marker assisted selection (MAS) in crop breeding programs.

Genomics-based high-resolution mapping of the BaMMV/BaYMV resistance gene rym11 in barley (Hordeum vulgare L.)

Soil-borne barley yellow mosaic virus disease, caused by different strains of Barley yellow mosaic virus (BaYMV) and Barley mild mosaic virus (BaMMV), is one of the most important diseases of winter barley (Hordeum vulgare L.) in Europe and East Asia. The recessive resistance gene rym11 located in the centromeric region of chromosome 4HL is effective against all so far known strains of BaMMV and BaYMV in Germany. In order to isolate this gene, a high-resolution mapping population (10,204 meiotic events) has been constructed. F2 plants were screened with co-dominant flanking markers and segmental recombinant inbred lines (RILs) were tested for resistance to BaMMV under growth chamber and field conditions. Tightly linked markers were developed by exploiting (1) publicly available barley EST sequences, (2) employing barley synteny to rice, Brachypodium distachyon and sorghum and (3) using next-generation sequencing data of barley. Using this approach, the genetic interval was efficiently narrowed down from the initial 10.72 % recombination to 0.074 % recombination. A marker co-segregating with rym11 was developed providing the basis for gene isolation and efficient marker-assisted selection.

Single nucleotide polymorphisms in HSP17.8 and their association with agronomic traits in barley

Small heat shock protein 17.8 (HSP17.8) is produced abundantly in plant cells under heat and other stress conditions and may play an important role in plant tolerance to stress environments. However, HSP17.8 may be differentially expressed in different accessions of a crop species exposed to identical stress conditions. The ability of different genotypes to adapt to various stress conditions resides in their genetic diversity. Allelic variations are the most common forms of genetic variation in natural populations. In this study, single nucleotide polymorphisms (SNPs) of the HSP17.8 gene were investigated across 210 barley accessions collected from 30 countries using EcoTILLING technology. Eleven SNPs including 10 from the coding region of HSP17.8 were detected, which form nine distinguishable haplotypes in the barley collection. Among the 10 SNPs in the coding region, six are missense mutations and four are synonymous nucleotide changes. Five of the six missense changes are predicted to be deleterious to HSP17.8 function. The accessions from Middle East Asia showed the higher nucleotide diversity of HSP17.8 than those from other regions and wild barley (H. spontaneum) accessions exhibited greater diversity than the cultivated barley (H. vulgare) accessions. Four SNPs in HSP17.8 were found associated with at least one of the agronomic traits evaluated except for spike length, namely number of grains per spike, thousand kernel weight, plant height, flag leaf area and leaf color. The association between SNP and these agronomic traits may provide new insight for study of the gene's potential contribution to drought tolerance of barley.

Predicting polymorphic EST-SSRs in silico

The public availability of large quantities of gene sequence data provides a valuable resource of the mining of Simple Sequence Repeat (SSR) molecular genetic markers for genetic analysis. These markers are inexpensive, require minimal labour to produce and can frequently be associated with functionally annotated genes. This study presents the characterization of barley EST-SSRs and the identification of putative polymorphic SSRs from EST data. Polymorphic SSRs are distinguished from monomorphic SSRs by the representation of varying motif lengths within an alignment of sequence reads. Two measures of confidence are calculated, redundancy of a polymorphism and co-segregation with accessions. The utility of this method is demonstrated through the discovery of 597 candidate polymorphic SSRs, from a total of 452 642 consensus expressed sequences. PCR amplification primers were designed for the identified SSRs. Ten primer pairs were validated for polymorphism in barley and for transferability across species. Analysis of the polymorphisms in relation to SSR motif, length, position and annotation is discussed.

Accessing complex crop genomes with next-generation sequencing

Many important crop species have genomes originating from ancestral or recent polyploidisation events. Multiple homoeologous gene copies, chromosomal rearrangements and amplification of repetitive DNA within large and complex crop genomes can considerably complicate genome analysis and gene discovery by conventional, forward genetics approaches. On the other hand, ongoing technological advances in molecular genetics and genomics today offer unprecedented opportunities to analyse and access even more recalcitrant genomes. In this review, we describe next-generation sequencing and data analysis techniques that vastly improve our ability to dissect and mine genomes for causal genes underlying key traits and allelic variation of interest to breeders. We focus primarily on wheat and oilseed rape, two leading examples of major polyploid crop genomes whose size or complexity present different, significant challenges. In both cases, the latest DNA sequencing technologies, applied using quite different approaches, have enabled considerable progress towards unravelling the respective genomes. Our ability to discover the extent and distribution of genetic diversity in crop gene pools, and its relationship to yield and quality-related traits, is swiftly gathering momentum as DNA sequencing and the bioinformatic tools to deal with growing quantities of genomic data continue to develop. In the coming decade, genomic and transcriptomic sequencing, discovery and high-throughput screening of single nucleotide polymorphisms, presence-absence variations and other structural chromosomal variants in diverse germplasm collections will give detailed insight into the origins, domestication and available trait-relevant variation of polyploid crops, in the process facilitating novel approaches and possibilities for genomics-assisted breeding.

Comparative analysis of kabuli chickpea transcriptome with desi and wild chickpea provides a rich resource for development of functional markers

Chickpea (Cicer arietinum L.) is an important crop legume plant with high nutritional value. The transcriptomes of desi and wild chickpea have already been sequenced. In this study, we sequenced the transcriptome of kabuli chickpea, C. arietinum (genotype ICCV2), having higher commercial value, using GS-FLX Roche 454 and Illumina technologies. The assemblies of both Roche 454 and Illumina datasets were optimized using various assembly programs and parameters. The final optimized hybrid assembly generated 43,389 transcripts with an average length of 1065 bp and N50 length of 1653 bp representing 46.2 Mb of kabuli chickpea transcriptome. We identified a total of 5409 simple sequence repeats (SSRs) in these transcript sequences. Among these, at least 130 and 493 SSRs were polymorphic with desi (ICC4958) and wild (PI489777) chickpea, respectively. In addition, a total of 1986 and 37,954 single nucleotide polymorphisms (SNPs) were predicted in kabuli/desi and kabuli/wild genotypes, respectively. The SNP frequency was 0.043 SNP per kb for kabuli/desi and 0.821 SNP per kb for kabuli/wild, reflecting very low genetic diversity in chickpea. Further, SSRs and SNPs present in tissue-specific and transcription factor encoding transcripts have been identified. The experimental validation of a selected set of polymorphic SSRs and SNPs exhibited high intra-specific polymorphism potential between desi and kabuli chickpea, suggesting their utility in large-scale genotyping applications. The kabuli chickpea gene index assembled, and SSRs and SNPs identified in this study will serve as useful genomic resource for genetic improvement of chickpea.

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.

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.

Identification and characterization of candidate Rlm4 blackleg resistance genes in Brassica napus using next-generation sequencing

A thorough understanding of the relationships between plants and pathogens is essential if we are to continue to meet the agricultural needs of the world's growing population. The identification of genes underlying important quantitative trait loci is extremely challenging in complex genomes such as Brassica napus (canola, oilseed rape or rapeseed). However, recent advances in next-generation sequencing (NGS) enable much quicker identification of candidate genes for traits of interest. Here, we demonstrate this with the identification of candidate disease resistance genes from B. napus for its most devastating fungal pathogen, Leptosphaeria maculans (blackleg fungus). These two species are locked in an evolutionary arms race whereby a gene-for-gene interaction confers either resistance or susceptibility in the plant depending on the genotype of the plant and pathogen. Preliminary analysis of the complete genome sequence of Brassica rapa, the diploid progenitor of B. napus, identified numerous candidate genes with disease resistance characteristics, several of which were clustered around a region syntenic with a major locus (Rlm4) for blackleg resistance on A7 of B. napus. Molecular analyses of the candidate genes using B. napus NGS data are presented, and the difficulties associated with identifying functional gene copies within the highly duplicated Brassica genome are discussed.

Targeted re-sequencing of the allohexaploid wheat exome

Bread wheat, Triticum aestivum, is an allohexaploid composed of the three distinct ancestral genomes, A, B and D. The polyploid nature of the wheat genome together with its large size has limited our ability to generate the significant amount of sequence data required for whole genome studies. Even with the advent of next-generation sequencing technology, it is still relatively expensive to generate whole genome sequences for more than a few wheat genomes at any one time. To overcome this problem, we have developed a targeted-capture re-sequencing protocol based upon NimbleGen array technology to capture and characterize 56.5 Mb of genomic DNA with sequence similarity to over 100 000 transcripts from eight different UK allohexaploid wheat varieties. Using this procedure in conjunction with a carefully designed bioinformatic procedure, we have identified more than 500 000 putative single-nucleotide polymorphisms (SNPs). While 80% of these were variants between the homoeologous genomes, A, B and D, a significant number (20%) were putative varietal SNPs between the eight varieties studied. A small number of these latter polymorphisms were experimentally validated using KASPar technology and 94% proved to be genuine. The procedures described here to sequence a large proportion of the wheat genome, and the various SNPs identified should be of considerable use to the wider wheat community.

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/.

Coverage-based consensus calling (CbCC) of short sequence reads and comparison of CbCC results to identify SNPs in chickpea (Cicer arietinum; Fabaceae), a crop species without a reference genome

PREMISE OF THE STUDY

Next-generation sequencing (NGS) technologies are frequently used for resequencing and mining of single nucleotide polymorphisms (SNPs) by comparison to a reference genome. In crop species such as chickpea (Cicer arietinum) that lack a reference genome sequence, NGS-based SNP discovery is a challenge. Therefore, unlike probability-based statistical approaches for consensus calling and by comparison with a reference sequence, a coverage-based consensus calling (CbCC) approach was applied and two genotypes were compared for SNP identification.

METHODS

A CbCC approach is used in this study with four commonly used short read alignment tools (Maq, Bowtie, Novoalign, and SOAP2) and 15.7 and 22.1 million Illumina reads for chickpea genotypes ICC4958 and ICC1882, together with the chickpea trancriptome assembly (CaTA).

KEY RESULTS

A nonredundant set of 4543 SNPs was identified between two chickpea genotypes. Experimental validation of 224 randomly selected SNPs showed superiority of Maq among individual tools, as 50.0% of SNPs predicted by Maq were true SNPs. For combinations of two tools, greatest accuracy (55.7%) was reported for Maq and Bowtie, with a combination of Bowtie, Maq, and Novoalign identifying 61.5% true SNPs. SNP prediction accuracy generally increased with increasing reads depth.

CONCLUSIONS

This study provides a benchmark comparison of tools as well as read depths for four commonly used tools for NGS SNP discovery in a crop species without a reference genome sequence. In addition, a large number of SNPs have been identified in chickpea that would be useful for molecular breeding.

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 world's 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.

Future tools for association mapping in crop plants

Association mapping currently relies on the identification of genetic markers. Several technologies have been adopted for genetic marker analysis, with single nucleotide polymorphisms (SNPs) being the most popular where a reasonable quantity of genome sequence data are available. We describe several tools we have developed for the discovery, annotation, and visualization of molecular markers for association mapping. These include autoSNPdb for SNP discovery from assembled sequence data; TAGdb for the identification of gene specific paired read Illumina GAII data; CMap3D for the comparison of mapped genetic and physical markers; and BAC and Gene Annotator for the online annotation of genes and genomic sequences.

Plant genome sequencing: applications for crop improvement

DNA sequencing technology is undergoing a revolution with the commercialization of second generation technologies capable of sequencing thousands of millions of nucleotide bases in each run. The data explosion resulting from this technology is likely to continue to increase with the further development of second generation sequencing and the introduction of third generation single-molecule sequencing methods over the coming years. The question is no longer whether we can sequence crop genomes which are often large and complex, but how soon can we sequence them? Even cereal genomes such as wheat and barley which were once considered intractable are coming under the spotlight of the new sequencing technologies and an array of new projects and approaches are being established. The increasing availability of DNA sequence information enables the discovery of genes and molecular markers associated with diverse agronomic traits creating new opportunities for crop improvement. However, the challenge remains to convert this mass of data into knowledge that can be applied in crop breeding programs.