Snipping polymorphisms from large EST collections in barley (Hordeum vulgare L.)

QTL mapping of shoot and seed traits impacted by Drought in Barley using a recombinant inbred line Population

BACKGROUND

With ongoing climate change, drought events are severely limiting barley production worldwide and pose a significant risk to the malting, brewing and food industry. The genetic diversity inherent in the barley germplasm offers an important resource to develop stress resiliency. The purpose of this study was to identify novel, stable, and adaptive Quantitative Trait Loci (QTL), and candidate genes associated with drought tolerance. A recombinant inbred line (RIL) population (n = 192) developed from a cross between the drought tolerant 'Otis' barley variety, and susceptible 'Golden Promise'(GP) was subjected to short-term progressive drought during heading in the biotron. This population was also evaluated under irrigated and rainfed conditions in the field for yields and seed protein content.

RESULTS

Barley 50k iSelect SNP Array was used to genotype the RIL population to elucidate drought-adaptive QTL. Twenty-three QTL (eleven for seed weight, eight for shoot dry weight and four for protein content) were identified across several barley chromosomes. QTL analysis identified genomic regions on chromosome 2 and 5 H that appear to be stable across both environments and accounted for nearly 60% variation in shoot weight and 17.6% variation in seed protein content. QTL at approximately 29 Mbp on chromosome 2 H and 488 Mbp on chromosome 5 H are in very close proximity to ascorbate peroxidase (APX) and in the coding sequence of the Dirigent (DIR) gene, respectively. Both APX and DIR are well-known key players in abiotic stress tolerance in several plants. In the quest to identify key recombinants with improved tolerance to drought (like Otis) and good malting profiles (like GP), five drought tolerant RILs were selected for malt quality analysis. The selected drought tolerant RILs exhibited one or more traits that were outside the realms of the suggested limits for acceptable commercial malting quality.

CONCLUSIONS

The candidate genes can be used for marker assisted selection and/or genetic manipulation to develop barley cultivars with improved tolerance to drought. RILs with genetic network reshuffling necessary to generate drought tolerance of Otis and favorable malting quality attributes of GP may be realized by screening a larger population.

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.

Comparative Transcriptome Analysis and Expression of Genes Reveal the Biosynthesis and Accumulation Patterns of Key Flavonoids in Different Varieties of Zanthoxylum bungeanum Leaves

Zanthoxylum bungeanum (Rutaceae), a popular food flavoring and traditional Chinese medicine ingredient, is an important cash crop. Its leaves are rich in flavonoids with multiple bioactivities. However, the transcriptional sequencing has not been investigated, and the molecular basis for the flavonoid biosynthesis remains unclear in this plant. This paper, the key flavonoids (epicatechin, rutin, hyperoside, trifolin, quercitrin, and afzelin) contents were determined in the leaves of 10 Z. bungeanum varieties from a common garden. Results show the leaves of Z. bungeanum mainly contained hyperoside (11.410-21.721 mg/g) and quercitrin (9.401-18.016 mg/g). The total content of these key components was the highest in Fengxian Dahongpao (66.012 mg/g) and the lowest in Fugu (32.223 mg/g). Three varieties (Hancheng stingless, Fugu, and Fengxian Dahongpao) with significant differences in the total content of key flavonoids were selected for transcriptome analysis to obtain flavonoid biosynthesis-related genes. In total, 83 522 unigenes were obtained, 40 668 (48.69%) unigenes were annotated, and 6656 differentially expressed genes (DEGs) were identified. Comparison of the other two varieties, Fugu had many differentially expressed genes indicating the particularity of its variety. Flavonoid-related DEGs of 22 structural genes, including three PALs, one CYP73A, three 4CLs, six CHSs, one CHI, one F3H, one DFR, two ANSs, one ANR, one FLS, and two CYP75B1s, as well as nine MYBs were obtained. These structural genes had different expression patterns in different Z. bungeanum varieties. It is worth noting that the genes expressing the flavonoid 3'5' hydroxylase are absent in Z. bungeanum. Furthermore, quantitative real-time PCR experiment showed consistent results in transcriptome analysis. The RNA-Seq data set of this study sheds lights on the molecular mechanism of flavonoid biosynthesis in Z. bungeanum, provides valuable information for the metabolic regulation of flavonoids, and may serve as a guide for future breeding programs.

High Resolution Mapping of Rph MBR1012 Conferring Resistance to Puccinia hordei in Barley (Hordeum vulgare L.)

Isolation of disease resistance genes in barley was hampered by the large genome size, but has become easy due to the availability of the reference genome sequence. During the last years, many genomic resources, e.g., the Illumina 9K iSelect, the 50K Infinium arrays, the Barley Genome Zipper, POPSEQ, and genotyping by sequencing (GBS), were developed that enable enhanced gene isolation in combination with the barley genome sequence. In the present study, we developed a fine map of the barley leaf rust resistance gene Rph MBR1012. 537 segmental homozygous recombinant inbred lines (RILs) derived from 4775 F2-plants were used to construct a high-resolution mapping population (HRMP). The Barley Genome Zipper, the 9K iSelect chip, the 50K Infinium chip and GBS were used to develop 56 molecular markers located in the target interval of 8 cM. This interval was narrowed down to about 0.07 cM corresponding to 0.44 Mb of the barley reference genome. Eleven low-confidence and 18 high-confidence genes were identified in this interval. Five of these are putative disease resistance genes and were subjected to allele-specific sequencing. In addition, comparison of the genetic map and the reference genome revealed an inversion of 1.34 Mb located distally to the resistance locus. In conclusion, the barley reference sequence and the respective gene annotation delivered detailed information about the physical size of the target interval, the genes located in the target interval and facilitated the efficient development of molecular markers for marker-assisted selection for RphMBR1012.

Comparative transcriptome among Euscaphis konishii Hayata tissues and analysis of genes involved in flavonoid biosynthesis and accumulation

BACHGROUND

Euscaphis konishii Hayata, a member of the Staphyleaceae Family, is a plant that has been widely used in Traditional Chinese Medicine and it has been the source for several types of flavonoids. To identify candidate genes involved in flavonoid biosynthesis and accumulation, we analyzed transcriptome data from three E. konishii tissues (leaf, branch and capsule) using Illumina Hiseq 2000 platform.

RESULTS

A total of 91.7, 100.3 and 100.1million clean reads were acquired for the leaf, branch and capsule, respectively; and 85,342 unigenes with a mean length of 893.60 bp and N50 length of 1307 nt were assembled using Trinity program. BLASTx analysis allowed to annotate 40,218 unigenes using public protein databases, including NR, KOG/COG/eggNOG, Swiss-Prot, KEGG and GO. A total of 14,291 (16.75%) unigenes were assigned to 128 KEGG pathways, and 900 unigenes were annotated into 22 KEGG secondary metabolites, including flavonoid biosynthesis. The structure enzymes involved in flavonoid biosynthesis, such as phenylalanine ammonia lyase, cinnamate 4-hydroxylase, 4-coumarate CoA ligase, shikimate O-hydroxycinnamoyltransferase, coumaroylquinate 3'-monooxygenase, caffeoyl-CoA O-methyltransferase, chalcone synthase, chalcone isomerase, flavanone 3-hydroxylase, flavonoid 3'-hydroxylase, flavonoid 3',5'-hydroxylase, flavonolsynthese, dihydroflavonol 4-reductase, anthocyanidinreductase, leucoanthocyanidin dioxygenase, leucoanthocyanidin reductase, were identified in the transcriptome data, 40 UDP-glycosyltransferase (UGT), 122 Cytochrome P450 (CYP) and 25 O-methyltransferase (OMT) unigenes were also found. A total of 295 unigenes involved in flavonoid transport and 220 transcription factors (97 MYB, 84 bHLH and 39 WD40) were identified. Furthermore, their expression patterns among different tissues were analyzed by DESeq, the differentially expressed genes may play important roles in tissues-specific synthesis, accumulation and modification of flavonoids.

CONCLUSION

We present here the de novo transcriptome analysis of E. konishii and the identification of candidate genes involved in biosynthesis and accumulation of flavonoid. In general, these results are an important resource for further research on gene expression, genomic and functional genomics in E. konishii and other related species.

Single nucleotide polymorphism in sugar pathway and disease resistance genes in sugarcane

Single nucleotide polymorphism in sugar pathway and disease resistance genes showing genetic association with sugar content and red rot resistance would be useful in marker-assisted genetic improvement of sugarcane. Validation and genotyping of potential sequence variants in candidate genes are necessary to understand their functional significance and trait association potential. We discovered, characterized, validated and genotyped SNPs and InDels in sugar pathway and disease resistance genes of Saccharum complex and sugarcane varieties using amplicon sequencing and CAPS assays. The SNPs were abundant in the non-coding 3'UTRs than 5'UTRs and coding sequences depicting a strong bias toward C to T transition substitutions than transversions. Sequencing of cloned amplicons validated 61.6 and 45.2 % SNPs detected in silico in 21 sugar pathway and 16 disease resistance genes, respectively. Sixteen SNPs in four sugar pathway genes and 10 SNPs in nine disease resistance genes were validated through cost-effective CAPS assay. Functional and adaptive significance of SNP and protein haplotypes identified in sugar pathway and disease resistance genes was assessed by correlating their allelic variation with missense amino acid substitutions in the functional domains, alteration in protein structure models and possible modulation of catalytic enzyme activity in contrasting high and low sugar and moderately red rot resistant and highly susceptible sugarcane genotypes. A strong genetic association of five SNPs in the sugar pathway and disease resistance genes, and an InDel marker in the promoter sequence of sucrose synthase-2 gene, with sugar content and red rot resistance, was evident. The functionally relevant SNPs and InDels, detected and validated in sugar pathway and disease resistance genes, and genic CAPS markers designed, would be of immense use in marker-assisted genetic improvement of sugarcane for sugar content and disease resistance.

Quantitative Trait Loci for Yield and Yield-Related Traits in Spring Barley Populations Derived from Crosses between European and Syrian Cultivars

In response to climatic changes, breeding programmes should be aimed at creating new cultivars with improved resistance to water scarcity. The objective of this study was to examine the yield potential of barley recombinant inbred lines (RILs) derived from three cross-combinations of European and Syrian spring cultivars, and to identify quantitative trait loci (QTLs) for yield-related traits in these populations. RILs were evaluated in field experiments over a period of three years (2011 to 2013) and genotyped with simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers; a genetic map for each population was constructed and then one consensus map was developed. Biological interpretation of identified QTLs was achieved by reference to Ensembl Plants barley gene space. Twelve regions in the genomes of studied RILs were distinguished after QTL analysis. Most of the QTLs were identified on the 2H chromosome, which was the hotspot region in all three populations. Syrian parental cultivars contributed alleles decreasing traits' values at majority of QTLs for grain weight, grain number, spike length and time to heading, and numerous alleles increasing stem length. The phenomic and molecular approaches distinguished the lines with an acceptable grain yield potential combining desirable features or alleles from their parents, that is, early heading from the Syrian breeding line (Cam/B1/CI08887//CI05761) and short plant stature from the European semidwarf cultivar (Maresi).

SNP-Based QTL Mapping of 15 Complex Traits in Barley under Rain-Fed and Well-Watered Conditions by a Mixed Modeling Approach

This study identified single nucleotide polymorphism (SNP) markers associated with 15 complex traits in a breeding population of barley (Hordeum vulgare L.) consisting of 137 recombinant chromosome substitution lines (RCSL), evaluated under contrasting water availability conditions in the Mediterranean climatic region of central Chile. Given that markers showed a very strong segregation distortion, a quantitative trait locus/loci (QTL) mapping mixed model was used to account for the heterogeneity in genetic relatedness between genotypes. Fifty-seven QTL were detected under rain-fed conditions, which accounted for 5-22% of the phenotypic variation. In full irrigation conditions, 84 SNPs were significantly associated with the traits studied, explaining 5-35% of phenotypic variation. Most of the QTL were co-localized on chromosomes 2H and 3H. Environment-specific genomic regions were detected for 12 of the 15 traits scored. Although most QTL-trait associations were environment and trait specific, some important and stable associations were also detected. In full irrigation conditions, a relatively major genomic region was found underlying hectoliter weight (HW), on chromosome 1H, which explained between 27% (SNP 2711-234) and 35% (SNP 1923-265) of the phenotypic variation. Interestingly, the locus 1923-265 was also detected for grain yield at both environmental conditions, accounting for 9 and 18%, in the rain-fed and irrigation conditions, respectively. Analysis of QTL in this breeding population identified significant genomic regions that can be used for marker-assisted selection (MAS) of barley in areas where drought is a significant constraint.

Molecular marker development from transcript sequences and germplasm evaluation for cultivated peanut (Arachis hypogaea L.)

Molecular markers are important tools for genotyping in genetic studies and molecular breeding. The SSR and SNP are two commonly used marker systems developed from genomic or transcript sequences. The objectives of this study were to: (1) assemble and annotate the publicly available ESTs in Arachis and the in-house short reads, (2) develop and validate SSR and SNP markers, and (3) investigate the genetic diversity and population structure of the peanut breeding lines and the U.S. peanut mini core collection using developed SSR markers. An NCBI EST dataset with 252,951 sequences and an in-house 454 RNAseq dataset with 288,701 sequences were assembled separately after trimming. Transcript sequence comparison and phylogenetic analysis suggested that peanut is closer to cowpea and scarlet bean than to soybean, common bean and Medicago. From these two datasets, 6455 novel SSRs and 11,902 SNPs were identified. Of the discovered SSRs, 380 representing various SSR types were selected for PCR validation. The amplification rate was 89.2 %. Twenty-two (6.5 %) SSRs were polymorphic between at least one pair of four genotypes. Sanger sequencing of PCR products targeting 110 SNPs revealed 13 true SNPs between tetraploid genotypes and 193 homoeologous SNPs within genotypes. Eight out of the 22 polymorphic SSR markers were selected to evaluate the genetic diversity of Florida peanut breeding lines and the U.S. peanut mini core collection. This marker set demonstrated high discrimination power by displaying an average polymorphism information content value of 0.783, a combined probability of identity of 10(-11), and a combined power of exclusion of 0.99991. The structure analysis revealed four sub-populations among the peanut accessions and lines evaluated. The results of this study enriched the peanut genomic resources, provided over 6000 novel SSR markers and the credentials for true peanut SNP marker development, and demonstrated the power of newly developed SSR markers in genotyping peanut germplasm and breeding materials.

Sequence diversity and differential expression of major phenylpropanoid-flavonoid biosynthetic genes among three mango varieties

BACKGROUND

Mango fruits contain a broad spectrum of phenolic compounds which impart potential health benefits; their biosynthesis is catalysed by enzymes in the phenylpropanoid-flavonoid (PF) pathway. The aim of this study was to reveal the variability in genes involved in the PF pathway in three different mango varieties Mangifera indica L., a member of the family Anacardiaceae: Kensington Pride (KP), Irwin (IW) and Nam Doc Mai (NDM) and to determine associations with gene expression and mango flavonoid profiles.

RESULTS

A close evolutionary relationship between mango genes and those from the woody species poplar of the Salicaceae family (Populus trichocarpa) and grape of the Vitaceae family (Vitis vinifera), was revealed through phylogenetic analysis of PF pathway genes. We discovered 145 SNPs in total within coding sequences with an average frequency of one SNP every 316 bp. Variety IW had the highest SNP frequency (one SNP every 258 bp) while KP and NDM had similar frequencies (one SNP every 369 bp and 360 bp, respectively). The position in the PF pathway appeared to influence the extent of genetic diversity of the encoded enzymes. The entry point enzymes phenylalanine lyase (PAL), cinnamate 4-mono-oxygenase (C4H) and chalcone synthase (CHS) had low levels of SNP diversity in their coding sequences, whereas anthocyanidin reductase (ANR) showed the highest SNP frequency followed by flavonoid 3'-hydroxylase (F3'H). Quantitative PCR revealed characteristic patterns of gene expression that differed between mango peel and flesh, and between varieties.

CONCLUSIONS

The combination of mango expressed sequence tags and availability of well-established reference PF biosynthetic genes from other plant species allowed the identification of coding sequences of genes that may lead to the formation of important flavonoid compounds in mango fruits and facilitated characterisation of single nucleotide polymorphisms between varieties. We discovered an association between the extent of sequence variation and position in the pathway for up-stream genes. The high expression of PAL, C4H and CHS genes in mango peel compared to flesh is associated with high amounts of total phenolic contents in peels, which suggest that these genes have an influence on total flavonoid levels in mango fruit peel and flesh. In addition, the particularly high expression levels of ANR in KP and NDM peels compared to IW peel and the significant accumulation of its product epicatechin gallate (ECG) in those extracts reflects the rate-limiting role of ANR on ECG biosynthesis in mango.

Current knowledge in lentil genomics and its application for crop improvement

Most of the lentil growing countries face a certain set of abiotic and biotic stresses causing substantial reduction in crop growth, yield, and production. Until-to date, lentil breeders have used conventional plant breeding techniques of selection-recombination-selection cycle to develop improved cultivars.These techniques have been successful in mainstreaming some of the easy-to-manage monogenic traits. However, in case of complex quantitative traits, these conventional techniques are less precise. As most of the economic traits are complex, quantitative, and often influenced by environments and genotype-environment interaction, the genetic improvement of these traits becomes difficult. Genomics assisted breeding is relatively powerful and fast approach to develop high yielding varieties more suitable to adverse environmental conditions. New tools such as molecular markers and bioinformatics are expected to generate new knowledge and improve our understanding on the genetics of complex traits. In the past, the limited availability of genomic resources in lentil could not allow breeders to employ these tools in mainstream breeding program.The recent application of the next generation sequencing and genotyping by sequencing technologies has facilitated to speed up the lentil genome sequencing project and large discovery of genome-wide single nucleotide polymorphism (SNP) markers. Currently, several linkage maps have been developed in lentil through the use of expressed sequenced tag (EST) derived simple sequence repeat (SSR) and SNP markers.These maps have emerged as useful genomic resources to identify quantitative trait loci imparting tolerance to biotic and abiotic stresses in lentil. In this review, the current knowledge on available genomic resources and its application in lentil breeding program are discussed.

Development of EST-based SNP and InDel markers and their utilization in tetraploid cotton genetic mapping

Background

Availability of molecular markers has proven to be an efficient tool in facilitating progress in plant breeding, which is particularly important in the case of less researched crops such as cotton. Considering the obvious advantages of single nucleotide polymorphisms (SNPs) and insertion-deletion polymorphisms (InDels), expressed sequence tags (ESTs) were analyzed in silico to identify SNPs and InDels in this study, aiming to develop more molecular markers in cotton.

Results

A total of 1,349 EST-based SNP and InDel markers were developed by comparing ESTs between Gossypium hirsutum and G. barbadense, mining G. hirsutum unigenes, and analyzing 3′ untranslated region (3′UTR) sequences. The marker polymorphisms were investigated using the two parents of the mapping population based on the single-strand conformation polymorphism (SSCP) analysis. Of all the markers, 137 (10.16%) were polymorphic, and revealed 142 loci. Linkage analysis using a BC₁ population mapped 133 loci on the 26 chromosomes. Statistical analysis of base variations in SNPs showed that base transitions accounted for 55.78% of the total base variations and gene ontology indicated that cotton genes varied greatly in harboring SNPs ranging from 1.00 to 24.00 SNPs per gene. Sanger sequencing of three randomly selected SNP markers revealed discrepancy between the in silico predicted sequences and the actual sequencing results.

Conclusions

In silico analysis is a double-edged blade to develop EST-SNP/InDel markers. On the one hand, the designed markers can be well used in tetraploid cotton genetic mapping. And it plays a certain role in revealing transition preference and SNP frequency of cotton genes. On the other hand, the developmental efficiency of markers and polymorphism of designed primers are comparatively low.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1046) contains supplementary material, which is available to authorized users.

Barley genetic variation: implications for crop improvement

Genetic variation is crucial for successful barley improvement. Genomic technologies are improving dramatically and are providing access to the genetic diversity within this important crop species. Diverse collections of barley germplasm are being assembled and mined via genome-wide association studies and the identified variation can be linked to the barley sequence assembly. Introgression of favorable alleles via marker-assisted selection is now faster and more efficient due to the availability of single nucleotide polymorphism platforms. High-throughput genotyping is also making genomic selection an essential tool in modern barley breeding. Contemporary plant breeders now benefit from publicly available user-friendly databases providing genotypic and phenotypic information on large numbers of barley accessions. These resources facilitate access to allelic variation. In this review we explore how the most recent genomics and molecular breeding advances are changing breeding practices. The Coordinated Agricultural Projects (CAPs), Barley CAP and Triticeae CAP coupled with international collaborations, are discussed in detail as examples of a collaborative approach to exploit diverse germplasm resources for barley improvement.

QTL scanning for rice yield using a whole genome SNP array

High-throughput SNP genotyping is widely used for plant genetic studies. Recently, a RICE6K SNP array has been developed based on the Illumina Bead Array platform and Infinium SNP assay technology for genome-wide evaluation of allelic variations and breeding applications. In this study, the RICE6K SNP array was used to genotype a recombinant inbred line (RIL) population derived from the cross between the indica variety, Zhenshan 97, and the japonica variety, Xizang 2. A total of 3324 SNP markers of high quality were identified and were grouped into 1495 recombination bins in the RIL population. A high-density linkage map, consisting of the 1495 bins, was developed, covering 1591.2 cM and with average length of 1.1 cM per bin. Segregation distortions were observed in 24 regions of the 11 chromosomes in the RILs. One half of the distorted regions contained fertility genes that had been previously reported. A total of 23 QTLs were identified for yield. Seven QTLs were firstly detected in this study. The positive alleles from about half of the identified QTLs came from Zhenshan 97 and they had lower phenotypic values than Xizang 2. This indicated that favorable alleles for breeding were dispersed in both parents and pyramiding favorable alleles could develop elite lines. The size of the mapping population for QTL analysis using high throughput SNP genotyping platform is also discussed.

Application of single nucleotide polymorphisms to non-model species: a technical review

Single nucleotide polymorphisms (SNPs) have gained wide use in humans and model species and are becoming the marker of choice for applications in other species. Technology that was developed for work in model species may provide useful tools for SNP discovery and genotyping in non-model organisms. However, SNP discovery can be expensive, labour intensive, and introduce ascertainment bias. In addition, the most efficient approaches to SNP discovery will depend on the research questions that the markers are to resolve as well as the focal species. We discuss advantages and disadvantages of several past and recent technologies for SNP discovery and genotyping and summarize a variety of SNP discovery and genotyping studies in ecology and evolution.

Single nucleotide polymorphism isolated from a novel EST dataset in garden asparagus (Asparagus officinalis L.)

Single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSR) are abundant and evenly distributed co-dominant molecular markers in plant genomes. SSRs are valuable for marker assisted breeding and positional cloning of genes associated traits of interest. Although several high throughput platforms have been developed to identify SNP and SSR markers for analysis of segregant plant populations, breeding in garden asparagus (Asparagus officinalis L.) has been limited by a low content of such markers. In this study massively parallel GS-FLX pyro-sequencing technology (454 Life Sciences) has been used to sequence and compare transcriptome from two genotypes: a rust tolerant male (1770) and a susceptible female (G190). A total of 122,963 and 99,368 sequence reads, with an average length of 245.7bp, have been recovered from accessions 1770 and 190 respectively. A computational pipeline has been used to predict and visually inspect putative SNPs and SSR sequences. Analysis of Gene Ontology (GO) slim annotation assignments for all assembled uniscripts indicated that the 24,403 assemblies represent genes from a broad array of functions. Further, over 1800 putative SNPs and 1000 SSRs were detected. One hundred forty-four SNPs together with 60 selected SSRs were validated and used to develop a preliminary genetic map by using a large BC(1) population, derived from 1770 and G190. The abundance of SNPs and SSRs provides a foundation for the development of saturated genetic maps and their utilization in assisted asparagus breeding programs.

A transcriptome map of perennial ryegrass (Lolium perenne L.)

Background

Single nucleotide polymorphisms (SNPs) are increasingly becoming the DNA marker system of choice due to their prevalence in the genome and their ability to be used in highly multiplexed genotyping assays. Although needed in high numbers for genome-wide marker profiles and genomics-assisted breeding, a surprisingly low number of validated SNPs are currently available for perennial ryegrass.

Results

A perennial ryegrass unigene set representing 9,399 genes was used as a reference for the assembly of 802,156 high quality reads generated by 454 transcriptome sequencing and for in silico SNP discovery. Out of more than 15,433 SNPs in 1,778 unigenes fulfilling highly stringent assembly and detection parameters, a total of 768 SNP markers were selected for GoldenGate genotyping in 184 individuals of the perennial ryegrass mapping population VrnA, a population being previously evaluated for important agronomic traits. A total of 592 (77%) of the SNPs tested were successfully called with a cluster separation above 0.9. Of these, 509 (86%) genic SNP markers segregated in the VrnA mapping population, out of which 495 were assigned to map positions. The genetic linkage map presented here comprises a total of 838 DNA markers (767 gene-derived markers) and spans 750 centi Mogan (cM) with an average marker interval distance of less than 0.9 cM. Moreover, it locates 732 expressed genes involved in a broad range of molecular functions of different biological processes in the perennial ryegrass genome.

Conclusions

Here, we present an efficient approach of using next generation sequencing (NGS) data for SNP discovery, and the successful design of a 768-plex Illumina GoldenGate genotyping assay in a complex genome. The ryegrass SNPs along with the corresponding transcribed sequences represent a milestone in the establishment of genetic and genomics resources available for this species and constitute a further step towards molecular breeding strategies. Moreover, the high density genetic linkage map predominantly based on gene-associated DNA markers provides an important tool for the assignment of candidate genes to quantitative trait loci (QTL), functional genomics and the integration of genetic and physical maps in perennial ryegrass, one of the most important temperate grassland species.

SNP discovery by transcriptome pyrosequencing

Single nucleotide polymorphisms (SNPs) are single base differences between haplotypes. SNPs are abundant in many species and valuable as markers for genetic map construction, modern molecular breeding programs, and quantitative genetic studies. SNPs are readily mined from genomic DNA or cDNA sequence obtained from individuals having two or more distinct genotypes. While automated Sanger sequencing has become less expensive over time, it is still costly to acquire deep Sanger sequence from several genotypes. "Next-generation" DNA sequencing technologies that utilize new chemistries and massively parallel approaches have enabled DNA sequences to be acquired at extremely high depths of coverage faster and for less cost than traditional sequencing. One such method is represented by the Roche/454 Life Sciences GS-FLX Titanium Series, which currently uses pyrosequencing to produce up to 400-600 million bases of DNA sequence/run (>1 million reads, ~400 bp/read). This chapter discusses the use of high-throughput pyrosequencing for SNP discovery by focusing on 454 sequencing of maize cDNA, the development of a computational pipeline for polymorphism detection, and the subsequent identification of over 7,000 putative SNPs between Mo17 and B73 maize. In addition, alternative alignment and polymorphism detection strategies that implement Illumina short reads, data processing and visualization tools, and reduced representation techniques that reduce the sequencing of repeat DNA, thus enabling efficient analysis of genome sequence, are discussed.

An integrated pipeline of open source software adapted for multi-CPU architectures: use in the large-scale identification of single nucleotide polymorphisms

The large amounts of EST sequence data available from a single species of an organism as well as for several species within a genus provide an easy source of identification of intra- and interspecies single nucleotide polymorphisms (SNPs). In the case of model organisms, the data available are numerous, given the degree of redundancy in the deposited EST data. There are several available bioinformatics tools that can be used to mine this data; however, using them requires a certain level of expertise: the tools have to be used sequentially with accompanying format conversion and steps like clustering and assembly of sequences become time-intensive jobs even for moderately sized datasets. We report here a pipeline of open source software extended to run on multiple CPU architectures that can be used to mine large EST datasets for SNPs and identify restriction sites for assaying the SNPs so that cost-effective CAPS assays can be developed for SNP genotyping in genetics and breeding applications. At the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), the pipeline has been implemented to run on a Paracel high-performance system consisting of four dual AMD Opteron processors running Linux with MPICH. The pipeline can be accessed through user-friendly web interfaces at http://hpc.icrisat.cgiar.org/PBSWeb and is available on request for academic use. We have validated the developed pipeline by mining chickpea ESTs for interspecies SNPs, development of CAPS assays for SNP genotyping, and confirmation of restriction digestion pattern at the sequence level.

Genomics and bioinformatics resources for crop improvement

Recent remarkable innovations in platforms for omics-based research and application development provide crucial resources to promote research in model and applied plant species. A combinatorial approach using multiple omics platforms and integration of their outcomes is now an effective strategy for clarifying molecular systems integral to improving plant productivity. Furthermore, promotion of comparative genomics among model and applied plants allows us to grasp the biological properties of each species and to accelerate gene discovery and functional analyses of genes. Bioinformatics platforms and their associated databases are also essential for the effective design of approaches making the best use of genomic resources, including resource integration. We review recent advances in research platforms and resources in plant omics together with related databases and advances in technology.

Conversion of barley SNPs into PCR-based markers using dCAPS method

Molecular genetic research relies heavily on the ability to detect polymorphisms in DNA. Single nucleotide polymorphisms (SNPs) are the most frequent form of DNA variation in the genome. In combination with a PCR assay, the corresponding SNP can be analyzed as a derived cleaved amplified polymorphic sequence (dCAPS) marker. The dCAPS method exploits the well-known specificity of a restriction endonuclease for its recognition site and can be used to virtually detect any SNP. Here, we describe the use of the dCAPS method for detecting single-nucleotide changes by means of a barley EST, CK569932, PCR-based marker.

Development and assessment of simple PCR markers for SNP genotyping in barley

Simple molecular marker assays underpin routine plant breeding and research activities in many laboratories worldwide. With the rapid growth of single nucleotide polymorphism (SNP) resources for many important crop plants, the availability of routine, low-tech marker assays for genotyping SNPs is of increased importance. In this study, we demonstrate that temperature-switch PCR (TSP) supports the rapid development of robust, allele-specific PCR markers for codominant SNP genotyping on agarose gel. A total of 87 TSP markers for assessing gene diversity in barley were developed and used to investigate the efficacy for marker development, assay reliably and genotyping accuracy. The TSP markers described provide good coverage of the barley genome, are simple to use, easy to interpret and score, and are amenable to assay automation. They provide a resource of informative SNP markers for assessing genetic relationships among individuals, populations and gene pools of cultivated barley (Hordeum vulgare L.) and its wild relative H. spontaneum K. Koch. TSP markers provide opportunities to use available SNP resources for marker-assisted breeding and plant genetic research, and to generate information that can be integrated with SNP data from different sources and studies. TSP markers are expected to provide similar advantages for any animal or plant species.

Perl module and PISE wrappers for the integrated analysis of sequence data and SNP features

Background

There is a need for software scripts and modules for format parsing, data manipulation, statistical analysis and annotation especially for tasks related to marker identification from sequence data and sequence diversity analysis.

Results

Here we present several new Perl scripts and a module for sequence data diversity analysis. To enable the use of these software with other public domain tools, we also make available PISE (Pasteur Institute Software Environment) wrappers for these Perl scripts and module. This enables the user to generate pipelines for automated analysis, since PISE is a web interface generator for bioinformatics programmes.

Conclusion

A new set of modules and scripts for diversity statistic calculation, format parsing and data manipulation are available with PISE wrappers that enable pipelining of these scripts with commonly used contig assembly and sequence feature prediction software, to answer specific sequence diversity related questions.

SNP identification in crop plants

In many plants, single nucleotide polymorphism (SNP) markers are increasingly becoming the marker system of choice. However, for many crop plants there are surprisingly low numbers of validated SNP markers available although they are needed in large numbers for studies regarding genetic variation, linkage mapping, population structure analysis, association genetics, map-based gene isolation, and plant breeding. This review summarizes the current status of SNP marker development technologies for major crop plants. It will also provide an outlook into the future regarding possible SNP identification approaches in crop plants on the basis of current development in model systems such as Arabidopsis which will become available with the full sequencing of more plant genomes, genome resequencing, and in conjunction with the next-generation sequencing technologies.

Meiotic genes and proteins in cereals

We review the current status of our understanding and knowledge of the genes and proteins controlling meiosis in five major cereals, rye, wheat, barley, rice and maize. For each crop, we describe the genetic and genomic infrastructure available to investigators, before considering the inventory of genes and proteins that have roles to play in this process. Emphasis is given throughout as to how translational genomic and proteomic approaches have enabled us to circumvent some of the intractable features of this important group of plants.

Identification of single nucleotide polymorphisms and analysis of linkage disequilibrium in sunflower elite inbred lines using the candidate gene approach

BACKGROUND

Association analysis is a powerful tool to identify gene loci that may contribute to phenotypic variation. This includes the estimation of nucleotide diversity, the assessment of linkage disequilibrium structure (LD) and the evaluation of selection processes. Trait mapping by allele association requires a high-density map, which could be obtained by the addition of Single Nucleotide Polymorphisms (SNPs) and short insertion and/or deletions (indels) to SSR and AFLP genetic maps. Nucleotide diversity analysis of randomly selected candidate regions is a promising approach for the success of association analysis and fine mapping in the sunflower genome. Moreover, knowledge of the distance over which LD persists, in agronomically meaningful sunflower accessions, is important to establish the density of markers and the experimental design for association analysis.

RESULTS

A set of 28 candidate genes related to biotic and abiotic stresses were studied in 19 sunflower inbred lines. A total of 14,348 bp of sequence alignment was analyzed per individual. In average, 1 SNP was found per 69 nucleotides and 38 indels were identified in the complete data set. The mean nucleotide polymorphism was moderate (theta = 0.0056), as expected for inbred materials. The number of haplotypes per region ranged from 1 to 9 (mean = 3.54 +/- 1.88). Model-based population structure analysis allowed detection of admixed individuals within the set of accessions examined. Two putative gene pools were identified (G1 and G2), with a large proportion of the inbred lines being assigned to one of them (G1). Consistent with the absence of population sub-structuring, LD for G1 decayed more rapidly (r2 = 0.48 at 643 bp; trend line, pooled data) than the LD trend line for the entire set of 19 individuals (r2 = 0.64 for the same distance).

CONCLUSION

Knowledge about the patterns of diversity and the genetic relationships between breeding materials could be an invaluable aid in crop improvement strategies. The relatively high frequency of SNPs within the elite inbred lines studied here, along with the predicted extent of LD over distances of 100 kbp (r2 approximately 0.1) suggest that high resolution association mapping in sunflower could be achieved with marker densities lower than those usually reported in the literature.

Identification of single nucleotide polymorphisms and analysis of linkage disequilibrium in sunflower elite inbred lines using the candidate gene approach

BACKGROUND

Association analysis is a powerful tool to identify gene loci that may contribute to phenotypic variation. This includes the estimation of nucleotide diversity, the assessment of linkage disequilibrium structure (LD) and the evaluation of selection processes. Trait mapping by allele association requires a high-density map, which could be obtained by the addition of Single Nucleotide Polymorphisms (SNPs) and short insertion and/or deletions (indels) to SSR and AFLP genetic maps. Nucleotide diversity analysis of randomly selected candidate regions is a promising approach for the success of association analysis and fine mapping in the sunflower genome. Moreover, knowledge of the distance over which LD persists, in agronomically meaningful sunflower accessions, is important to establish the density of markers and the experimental design for association analysis.

RESULTS

A set of 28 candidate genes related to biotic and abiotic stresses were studied in 19 sunflower inbred lines. A total of 14,348 bp of sequence alignment was analyzed per individual. In average, 1 SNP was found per 69 nucleotides and 38 indels were identified in the complete data set. The mean nucleotide polymorphism was moderate (theta = 0.0056), as expected for inbred materials. The number of haplotypes per region ranged from 1 to 9 (mean = 3.54 +/- 1.88). Model-based population structure analysis allowed detection of admixed individuals within the set of accessions examined. Two putative gene pools were identified (G1 and G2), with a large proportion of the inbred lines being assigned to one of them (G1). Consistent with the absence of population sub-structuring, LD for G1 decayed more rapidly (r2 = 0.48 at 643 bp; trend line, pooled data) than the LD trend line for the entire set of 19 individuals (r2 = 0.64 for the same distance).

CONCLUSION

Knowledge about the patterns of diversity and the genetic relationships between breeding materials could be an invaluable aid in crop improvement strategies. The relatively high frequency of SNPs within the elite inbred lines studied here, along with the predicted extent of LD over distances of 100 kbp (r2 approximately 0.1) suggest that high resolution association mapping in sunflower could be achieved with marker densities lower than those usually reported in the literature.

EST-derived single nucleotide polymorphism markers for assembling genetic and physical maps of the barley genome

In a panel of seven genotypes, 437 expressed sequence tag (EST)-derived DNA fragments were sequenced. Single nucleotide polymorphisms (SNPs) that were polymorphic between the parents of three mapping populations were mapped by heteroduplex analysis and a genome-wide consensus map comprising 216 EST-derived SNPs and 4 InDel (insertion/deletion) markers was constructed. The average frequency of SNPs amounted to 1/130 bp and 1/107.8 bp for a set of randomly selected and a set of mapped ESTs, respectively. The calculated nucleotide diversities (pi) ranged from 0 to 40.0 x 10(-3) (average 3.1 x 10(-3)) and 0.52 x 10(-3) to 39.51 x 10(-3) (average 4.37 x 10(-3)) for random and mapped ESTs, respectively. The polymorphism information content value for mapped SNPs ranged from 0.24 to 0.50 with an average of 0.34. As expected, combination of SNPs present in an amplicon (haplotype) exhibited a higher information content ranging from 0.24 to 0.85 with an average of 0.50. Cleaved amplified polymorphic sequence assays (including InDels) were designed for a total of 87 (39.5%) SNP markers. The high abundance of SNPs in the barley genome provides avenues for the systematic development of saturated genetic maps and their integration with physical maps.

SNP discovery via 454 transcriptome sequencing

A massively parallel pyro-sequencing technology commercialized by 454 Life Sciences Corporation was used to sequence the transcriptomes of shoot apical meristems isolated from two inbred lines of maize using laser capture microdissection (LCM). A computational pipeline that uses the POLYBAYES polymorphism detection system was adapted for 454 ESTs and used to detect SNPs (single nucleotide polymorphisms) between the two inbred lines. Putative SNPs were computationally identified using 260,000 and 280,000 454 ESTs from the B73 and Mo17 inbred lines, respectively. Over 36,000 putative SNPs were detected within 9980 unique B73 genomic anchor sequences (MAGIs). Stringent post-processing reduced this number to > 7000 putative SNPs. Over 85% (94/110) of a sample of these putative SNPs were successfully validated by Sanger sequencing. Based on this validation rate, this pilot experiment conservatively identified > 4900 valid SNPs within > 2400 maize genes. These results demonstrate that 454-based transcriptome sequencing is an excellent method for the high-throughput acquisition of gene-associated SNPs.

Characterization of an 18,166 EST dataset for cassava (Manihot esculenta Crantz) enriched for drought-responsive genes

Cassava (Manihot esculenta Crantz) is a staple food for over 600 million people in the tropics and subtropics and is increasingly used as an industrial crop for starch production. Cassava has a high growth rate under optimal conditions but also performs well in drought-prone areas and on marginal soils. To increase the tools for understanding and manipulating drought tolerance in cassava, we generated expressed sequence tags (ESTs) from normalized cDNA libraries prepared from dehydration-stressed and control well-watered tissues. Analysis of a total of 18,166 ESTs resulted in the identification of 8,577 unique gene clusters (5,383 singletons and 3,194 clusters). Functional categories could be assigned to 63% of the unigenes, while another approximately 11% were homologous to hypothetical genes with unclear functions. The remaining approximately 26% were not significantly homologous to sequences in public databases suggesting that some may be novel and putatively specific to cassava. The dehydration-stressed library uncovered numerous ESTs with recognized roles in drought-responses, including those that encode late-embryogenesis-abundant proteins thought to confer osmoprotective functions during water stress, transcription factors, heat-shock proteins as well as proteins involved in signal transduction and oxidative stress. The unigene clusters were screened for short tandem repeats for further development as microsatellite markers. A total of 592 clusters contained 646 repeats, representing 3.3% of the ESTs queried. The ESTs presented here are the first dehydration stress transcriptome of cassava and can be utilized for the development of microarrays and gene-derived molecular markers to further dissect the molecular basis of drought tolerance in cassava.

Single nucleotide polymorphisms in rye (Secale cereale L.): discovery, frequency, and applications for genome mapping and diversity studies

To elucidate the potential of single nucleotide polymorphism (SNP) markers in rye, a set of 48 barley EST (expressed sequence tag) primer pairs was employed to amplify from DNA prepared from five rye inbred lines. A total of 96 SNPs and 26 indels (insertion-deletions) were defined from the sequences of 14 of the resulting amplicons, giving an estimated frequency of 1 SNP per 58 bp and 1 indel per 214 bp in the rye transcriptome. A mean of 3.4 haplotypes per marker with a mean expected heterozygosity of 0.66 were observed. The nucleotide diversity index (pi) was estimated to be in the range 0.0059-0.0530. To improve assay cost-effectiveness, 12 of the 14 SNPs were converted to a cleaved amplified polymorphic sequence (CAPS) format. The resulting 12 SNP loci mapped to chromosomes 1R, 3R, 4R, 5R, 6R, and 7R, at locations consistent with their known map positions in barley. SNP genotypic data were compared with genomic simple sequence repeat (SSR) and EST-derived SSR genotypic data collected from the same templates. This showed a broad equivalence with respect to genetic diversity between these different data types.

A 1,000-loci transcript map of the barley genome: new anchoring points for integrative grass genomics

An integrated barley transcript map (consensus map) comprising 1,032 expressed sequence tag (EST)-based markers (total 1,055 loci: 607 RFLP, 190 SSR, and 258 SNP), and 200 anchor markers from previously published data, has been generated by mapping in three doubled haploid (DH) populations. Between 107 and 179 EST-based markers were allocated to the seven individual barley linkage groups. The map covers 1118.3 cM with individual linkage groups ranging from 130 cM (chromosome 4H) to 199 cM (chromosome 3H), yielding an average marker interval distance of 0.9 cM. 475 EST-based markers showed a syntenic organisation to known colinear linkage groups of the rice genome, providing an extended insight into the status of barley/rice genome colinearity as well as ancient genome duplications predating the divergence of rice and barley. The presented barley transcript map is a valuable resource for targeted marker saturation and identification of candidate genes at agronomically important loci. It provides new anchor points for detailed studies in comparative grass genomics and will support future attempts towards the integration of genetic and physical mapping information.

Validation of in silico-predicted genic SNPs in white clover (Trifolium repens L.), an outbreeding allopolyploid species

White clover (Trifolium repens L.) is an obligate outbreeding allotetraploid forage legume. Gene-associated SNPs provide the optimum genetic system for improvement of such crop species. An EST resource obtained from multiple cDNA libraries constructed from numerous genotypes of a single cultivar has been used for in silico SNP discovery and validation. A total of 58 from 236 selected sequence clusters (24.5%) were fully validated as containing polymorphic SNPs by genotypic analysis across the parents and progeny of several two-way pseudo-testcross mapping families. The clusters include genes belonging to a broad range of predicted functional categories. Polymorphic SNP-containing ESTs have also been used for comparative genomic analysis by comparison with whole genome data from model legume species, as well as Arabidopsis thaliana. A total of 29 (50%) of the 58 clusters detected putative ortholoci with known chromosomal locations in Medicago truncatula, which is closely related to white clover within the Trifolieae tribe of the Fabaceae. This analysis provides access to translational data from model species. The efficiency of in silico SNP discovery in white clover is limited by paralogous and homoeologous gene duplication effects, which are resolved unambiguously by the transmission test. This approach will also be applicable to other agronomically important cross-pollinating allopolyploid plant species.

Application of Genomics to Molecular Breeding of Wheat and Barley

In wheat and barley, several generations of selectable molecular markers have been included in the genetic maps; and a large number of qualitative and quantitative traits were located in the genomes, some of which are being routinely selected in marker-assisted breeding programs. In recent years, a large number of expressed sequence tags (ESTs) have been generated for wheat and barley that have been used for development of functional molecular markers, preparation of transcript maps, and construction of cDNA arrays. These functional genomic resources combined together with new approaches such as expression genetics, association mapping, allele mining, and informatics (bioinformatic tools) possess potential to identify genes responsible for a trait and their deployment in practical plant breeding. High costs currently limit the implementation of functional genomics in breeding programs. The potential applications together with some examples as well as challenges for applying genomics research in breeding activities are discussed. Genomics research will continue to enhance the efficiency and precision for crop improvement but will not replace conventional breeding and evaluation methods.

The molecular ecologist's guide to expressed sequence tags

Genomics and bioinformatics have great potential to help address numerous topics in ecology and evolution. Expressed sequence tags (ESTs) can bridge genomics and molecular ecology because they can provide a means of accessing the gene space of almost any organism. We review how ESTs have been used in molecular ecology research in the last several years by providing sequence data for the design of molecular markers, genome-wide studies of gene expression and selection, the identification of candidate genes underlying adaptation, and the basis for studies of gene family and genome evolution. Given the tremendous recent advances in inexpensive sequencing technologies, we predict that molecular ecologists will increasingly be developing and using EST collections in the years to come. With this in mind, we close our review by discussing aspects of EST resource development of particular relevance for molecular ecologists.

QualitySNP: a pipeline for detecting single nucleotide polymorphisms and insertions/deletions in EST data from diploid and polyploid species

Background

Single nucleotide polymorphisms (SNPs) are important tools in studying complex genetic traits and genome evolution. Computational strategies for SNP discovery make use of the large number of sequences present in public databases (in most cases as expressed sequence tags (ESTs)) and are considered to be faster and more cost-effective than experimental procedures. A major challenge in computational SNP discovery is distinguishing allelic variation from sequence variation between paralogous sequences, in addition to recognizing sequencing errors. For the majority of the public EST sequences, trace or quality files are lacking which makes detection of reliable SNPs even more difficult because it has to rely on sequence comparisons only.

Results

We have developed a new algorithm to detect reliable SNPs and insertions/deletions (indels) in EST data, both with and without quality files. Implemented in a pipeline called QualitySNP, it uses three filters for the identification of reliable SNPs. Filter 1 screens for all potential SNPs and identifies variation between or within genotypes. Filter 2 is the core filter that uses a haplotype-based strategy to detect reliable SNPs. Clusters with potential paralogs as well as false SNPs caused by sequencing errors are identified. Filter 3 screens SNPs by calculating a confidence score, based upon sequence redundancy and quality. Non-synonymous SNPs are subsequently identified by detecting open reading frames of consensus sequences (contigs) with SNPs. The pipeline includes a data storage and retrieval system for haplotypes, SNPs and alignments. QualitySNP's versatility is demonstrated by the identification of SNPs in EST datasets from potato, chicken and humans.

Conclusion

QualitySNP is an efficient tool for SNP detection, storage and retrieval in diploid as well as polyploid species. It is available for running on Linux or UNIX systems. The program, test data, and user manual are available at and as Additional files.

Mapped Ds/T-DNA launch pads for functional genomics in barley

A system for targeted gene tagging and local saturation mutagenesis based on maize transposable elements (Ac/Ds) was developed in barley (Hordeum vulgare L.). We generated large numbers of transgenic barley lines carrying a single copy of the non-autonomous maize Ds element at defined positions in the genome. Independent Ds lines were either generated by activating Ds elements in existing single-copy lines after crossing with AcTPase-expressing plants or by Agrobacterium-mediated transformation. Genomic DNA flanking Ds and T-DNA insertion sites from over 200 independent lines was isolated and sequenced, and was used for a sequence based mapping strategy in a barley reference population. More than 100 independent Ds insertion sites were mapped and can be used as launch pads for future targeted tagging of genes in the vicinity of the insertion sites. Sequence analysis of Ds and T-DNA flanking regions revealed a sevenfold preference of both mutagens for insertion into non-redundant, gene-containing regions of the barley genome. However, whilst transposed Ds elements preferentially inserted adjacent to regions with a high number of predicted and experimentally validated matrix attachment regions (nuclear MARs), this was not the case for T-DNA integration sites. These findings and an observed high transposition frequency from mapped launch pads demonstrate the future potential of gene tagging for functional genomics and gene discovery in barley.

Prospecting for pig single nucleotide polymorphisms in the human genome: have we struck gold?

Gene-to-gene variation in the frequency of single nucleotide polymorphisms (SNPs) has been observed in humans, mice, rats, primates and pigs, but a relationship across species in this variation has not been described. Here, the frequency of porcine coding SNPs (cSNPs) identified by in silico methods, and the frequency of murine cSNPs, were compared with the frequency of human cSNPs across homologous genes. From 150,000 porcine expressed sequence tag (EST) sequences, a total of 452 SNP-containing sequence clusters were found, totalling 1394 putative SNPs. All the clustered porcine EST annotations and SNP data have been made publicly available at http://sputnik.btk.fi/project?name=swine. Human and murine cSNPs were identified from dbSNP and were characterized as either validated or total number of cSNPs (validated plus non-validated) for comparison purposes. The correlation between in silico pig cSNP and validated human cSNP densities was found to be 0.77 (p < 0.00001) for a set of 25 homologous genes, while a correlation of 0.48 (p < 0.0005) was found for a primarily random sample of 50 homologous human and mouse genes. This is the first evidence of conserved gene-to-gene variability in cSNP frequency across species and indicates that site-directed screening of porcine genes that are homologous to cSNP-rich human genes may rapidly advance cSNP discovery in pigs.

Gene-associated single nucleotide polymorphism discovery in perennial ryegrass (Lolium perenne L.)

Molecular genetic marker development in perennial ryegrass has largely been dependent on anonymous sequence variation. The availability of a large-scale EST resource permits the development of functionally-associated genetic markers based on SNP variation in candidate genes. Genic SNP loci and associated haplotypes are suitable for implementation in molecular breeding of outbreeding forage species. Strategies for in vitro SNP discovery through amplicon cloning and sequencing have been designed and implemented. Putative SNPs were identified within and between the parents of the F(1)(NA(6) x AU(6)) genetic mapping family and were validated among progeny individuals. Proof-of-concept for the process was obtained using the drought tolerance-associated LpASRa2 gene. SNP haplotype structures were determined and correlated with predicted amino acid changes. Gene-length LD was evaluated across diverse germplasm collections. A survey of SNP variation across 100 candidate genes revealed a high frequency of SNP incidence (c. 1 per 54 bp), with similar proportions in exons and introns. A proportion (c. 50%) of the validated genic SNPs were assigned to the F(1)(NA(6) x AU(6)) genetic map, showing high levels of coincidence with previously mapped RFLP loci. The perennial ryegrass SNP resource will enable genetic map integration, detailed LD studies and selection of superior allele content during varietal development.

Robust allele-specific polymerase chain reaction markers developed for single nucleotide polymorphisms in expressed barley sequences

Many methods have been developed to assay for single nucleotide polymorphisms (SNPs), but generally these depend on access to specialised equipment. Allele-specific polymerase chain reaction (AS-PCR) is a method that does not require specialised equipment (other than a thermocycler), but there is a common perception that AS-PCR markers can be unreliable. We have utilised a three primer AS-PCR method comprising of two flanking-primers combined with an internal allele-specific primer. We show here that this method produces a high proportion of robust markers (from candidate allele specific primers). Forty-nine inter-varietal SNP sites in 31 barley (Hordeum vulgare L.) genes were targeted for the development of AS-PCR assays. The SNP sites were found by aligning barley expressed sequence tags from public databases. The targeted genes correspond to cDNAs that have been used as restriction fragment length polymorphic probes for linkage mapping in barley. Two approaches were adopted in developing the markers. In the first approach, designed to maximise the successful development of markers to a SNP site, markers were developed for 18 sites from 19 targeted (95% success rate). With the second approach, designed to maximise the number of markers developed per primer synthesised, markers were developed for 18 SNP sites from 30 that were targeted (a 60% success rate). The robustness of markers was assessed from the range of annealing temperatures over which the PCR assay was allele-specific. The results indicate that this form of AS-PCR is highly successful for the development of robust SNP markers.

Genome-wide SNP discovery and linkage analysis in barley based on genes responsive to abiotic stress

More than 2,000 genome-wide barley single nucleotide polymorphisms (SNPs) were developed by resequencing unigene fragments from eight diverse accessions. The average genome-wide SNP frequency observed in 877 unigenes was 1 SNP per 200 bp. However, SNP frequency was highly variable with the least number of SNP and SNP haplotypes observed within European cultivated germplasm reflecting effects of breeding history on genetic diversity. More than 300 SNP loci were mapped genetically in three experimental mapping populations which allowed the construction of an integrated SNP map incorporating a large number of RFLP, AFLP and SSR markers (1,237 loci in total). The genes used for SNP discovery were selected based on their transcriptional response to a variety of abiotic stresses. A set of known barley abiotic stress QTL was positioned on the linkage map, while the available sequence and gene expression information facilitated the identification of genes potentially associated with these traits. Comparison of the sequenced SNP loci to the rice genome sequence identified several regions of highly conserved gene order providing a framework for marker saturation in barley genomic regions of interest. The integration of genome-wide SNP and expression data with available genetic and phenotypic information will facilitate the identification of gene function in barley and other non-model organisms.

Genome-wide SNP discovery and linkage analysis in barley based on genes responsive to abiotic stress

More than 2,000 genome-wide barley single nucleotide polymorphisms (SNPs) were developed by resequencing unigene fragments from eight diverse accessions. The average genome-wide SNP frequency observed in 877 unigenes was 1 SNP per 200 bp. However, SNP frequency was highly variable with the least number of SNP and SNP haplotypes observed within European cultivated germplasm reflecting effects of breeding history on genetic diversity. More than 300 SNP loci were mapped genetically in three experimental mapping populations which allowed the construction of an integrated SNP map incorporating a large number of RFLP, AFLP and SSR markers (1,237 loci in total). The genes used for SNP discovery were selected based on their transcriptional response to a variety of abiotic stresses. A set of known barley abiotic stress QTL was positioned on the linkage map, while the available sequence and gene expression information facilitated the identification of genes potentially associated with these traits. Comparison of the sequenced SNP loci to the rice genome sequence identified several regions of highly conserved gene order providing a framework for marker saturation in barley genomic regions of interest. The integration of genome-wide SNP and expression data with available genetic and phenotypic information will facilitate the identification of gene function in barley and other non-model organisms.

Expressed sequence tags from the laboratory-grown miniature tomato (Lycopersicon esculentum) cultivar Micro-Tom and mining for single nucleotide polymorphisms and insertions/deletions in tomato cultivars

Laboratory-grown miniature tomato (Lycopersicon esculentum) cultivar Micro-Tom has attracted attention as a host for functional genomics research. In this study, we generated 35,824 expressed sequence tags (ESTs) from leaves and fruits of Micro-Tom. The ESTs comprised 10,287 unigenes (5007 contigs and 5280 singletons), including 1858 novel tomato unigenes. Of the 18 unigenes that shared strong homology with tobacco chloroplast genome sequences, one unigene was likely derived from polyadenylated transcripts of the atpH gene. Interestingly, ESTs for vacuolar invertase, pectate lyase and alcohol acyl transferase were underrepresented in the Micro-Tom data set. From all of the ESTs, we mined 2039 candidate single nucleotide polymorphisms (SNPs) and 121 candidate insertions and deletions (indels) based on homology with four tomato inbred lines, E6203, R11-13, Rio Grande PtoR and R11-12, and a wild relative, L. pennellii TA56, for which sequence data was publicly available with more than 5000 entries. Direct genome sequencing of several SNP or indel sites in Micro-Tom and L. esculentum E6203 suggested that more than 69% of the candidate sites were truly polymorphic, making them useful for the preparation of DNA markers.

XenDB: full length cDNA prediction and cross species mapping in Xenopus laevis

Background

Research using the model system Xenopus laevis has provided critical insights into the mechanisms of early vertebrate development and cell biology. Large scale sequencing efforts have provided an increasingly important resource for researchers. To provide full advantage of the available sequence, we have analyzed 350,468 Xenopus laevis Expressed Sequence Tags (ESTs) both to identify full length protein encoding sequences and to develop a unique database system to support comparative approaches between X. laevis and other model systems.

Description

Using a suffix array based clustering approach, we have identified 25,971 clusters and 40,877 singleton sequences. Generation of a consensus sequence for each cluster resulted in 31,353 tentative contig and 4,801 singleton sequences. Using both BLASTX and FASTY comparison to five model organisms and the NR protein database, more than 15,000 sequences are predicted to encode full length proteins and these have been matched to publicly available IMAGE clones when available. Each sequence has been compared to the KOG database and ~67% of the sequences have been assigned a putative functional category. Based on sequence homology to mouse and human, putative GO annotations have been determined.

Conclusion

The results of the analysis have been stored in a publicly available database XenDB . A unique capability of the database is the ability to batch upload cross species queries to identify potential Xenopus homologues and their associated full length clones. Examples are provided including mapping of microarray results and application of 'in silico' analysis. The ability to quickly translate the results of various species into 'Xenopus-centric' information should greatly enhance comparative embryological approaches.

Supplementary material can be found at .

Discovery of SNPs in soybean genotypes frequently used as the parents of mapping populations in the United States and Korea

Single nucleotide polymorphisms (SNPs) including insertion/deletions (indels) serve as useful and informative genetic markers. The availability of high-throughput and inexpensive SNP typing systems has increased interest in the development of SNP markers. After fragments of genes were amplified with primers derived from 110 soybean GenBank ESTs, sequencing data of PCR products from 15 soybean genotypes from Korea and the United States were analyzed by SeqScape software to find SNPs. Among 35 gene fragments with at least one SNP among the 15 genotypes, SNPs occurred at a frequency of 1 per 2,038 bp in 16,302 bp of coding sequence and 1 per 191 bp in 16,960 bp of noncoding regions. This corresponds to a nucleotide diversity (theta) of 0.00017 and 0.00186, respectively. Of the 97 SNPs discovered, 78 or 80.4% were present in the six North American soybean mapping parents. The addition of "Hwaeomputkong," which originated from Japan, increased the number to 92, or 94.8% of the total number of SNPs present among the 15 genotypes. Thus, Hwaeomputkong and the six North American mapping parents provide a diverse set of soybean genotypes that can be successfully used for SNP discovery in coding DNA and closely associated introns and untranslated regions.

Single-feature polymorphism discovery in the barley transcriptome

A probe-level model for analysis of GeneChip gene-expression data is presented which identified more than 10,000 single-feature polymorphisms (SFP) between two barley genotypes. The method has good sensitivity, as 67% of known single-nucleotide polymorphisms (SNP) were called as SFPs. This method is applicable to all oligonucleotide microarray data, accounts for SNP effects in gene-expression data and represents an efficient and versatile approach for highly parallel marker identification in large genomes.

Single-feature polymorphism discovery in the barley transcriptome

A probe level model for analysis of GeneChip gene expression data is presented which identified more than 10,000 single-feature polymorphisms between two barley genotypes, with a high sensitivity. This method is applicable to all oligonucleotide microarray data.

A probe-level model for analysis of GeneChip gene-expression data is presented which identified more than 10,000 single-feature polymorphisms (SFP) between two barley genotypes. The method has good sensitivity, as 67% of known single-nucleotide polymorphisms (SNP) were called as SFPs. This method is applicable to all oligonucleotide microarray data, accounts for SNP effects in gene-expression data and represents an efficient and versatile approach for highly parallel marker identification in large genomes.