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EST and EST-SSR marker resources for Iris.

ABSTRACT: BACKGROUND:Limited DNA sequence and DNA marker resources have been developed for Iris (Iridaceae), a monocot genus of 200-300 species in the Asparagales, several of which are horticulturally important. We mined an I. brevicaulis-I. fulva EST database for simple sequence repeats (SSRs) and developed ortholog-specific EST-SSR markers for genetic mapping and other genotyping applications in Iris. Here, we describe the abundance and other characteristics of SSRs identified in the transcript assembly (EST database) and the cross-species utility and polymorphisms of I. brevicaulis-I. fulva EST-SSR markers among wild collected ecotypes and horticulturally important cultivars. RESULTS:Collectively, 6,530 ESTs were produced from normalized leaf and root cDNA libraries of I. brevicaulis (IB72) and I. fulva (IF174), and assembled into 4,917 unigenes (1,066 contigs and 3,851 singletons). We identified 1,447 SSRs in 1,162 unigenes and developed 526 EST-SSR markers, each tracing a different unigene. Three-fourths of the EST-SSR markers (399/526) amplified alleles from IB72 and IF174 and 84% (335/399) were polymorphic between IB25 and IF174, the parents of I. brevicaulis x I. fulva mapping populations. Forty EST-SSR markers were screened for polymorphisms among 39 ecotypes or cultivars of seven species - 100% amplified alleles from wild collected ecotypes of Louisiana Iris (I.brevicaulis, I.fulva, I. nelsonii, and I. hexagona), whereas 42-52% amplified alleles from cultivars of three horticulturally important species (I. pseudacorus, I. germanica, and I. sibirica). Ecotypes and cultivars were genetically diverse - the number of alleles/locus ranged from two to 18 and mean heterozygosity was 0.76. CONCLUSION:Nearly 400 ortholog-specific EST-SSR markers were developed for comparative genetic mapping and other genotyping applications in Iris, were highly polymorphic among ecotypes and cultivars, and have broad utility for genotyping applications within the genus.

SUBMITTER: Tang S

PROVIDER: S-EPMC2703627 | biostudies-literature | 2009 Jun

REPOSITORIES: biostudies-literature

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EST and EST-SSR marker resources for Iris.

Tang Shunxue S Okashah Rebecca A RA Cordonnier-Pratt Marie-Michele MM Pratt Lee H LH Ed Johnson Virgil V Taylor Christopher A CA Arnold Michael L ML Knapp Steven J SJ

BMC plant biology 20090610

<h4>Background</h4>Limited DNA sequence and DNA marker resources have been developed for Iris (Iridaceae), a monocot genus of 200-300 species in the Asparagales, several of which are horticulturally important. We mined an I. brevicaulis-I. fulva EST database for simple sequence repeats (SSRs) and developed ortholog-specific EST-SSR markers for genetic mapping and other genotyping applications in Iris. Here, we describe the abundance and other characteristics of SSRs identified in the transcript ...[more]

PMID: 19515254

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Project description:BackgroundSimple sequence repeats (SSRs) have become widely used as molecular markers in plant genetic studies due to their abundance, high allelic variation at each locus and simplicity to analyze using conventional PCR amplification. To study plants with unknown genome sequence, SSR markers from Expressed Sequence Tags (ESTs), which can be obtained from the plant mRNA (converted to cDNA), must be utilized. With the advent of high-throughput sequencing technology, huge EST sequence data have been generated and are now accessible from many public databases. However, SSR marker identification from a large in-house or public EST collection requires a computational pipeline that makes use of several standard bioinformatic tools to design high quality EST-SSR primers. Some of these computational tools are not users friendly and must be tightly integrated with reference genomic databases.ResultsA web-based bioinformatic pipeline, called EST Analysis Pipeline Plus (ESAP Plus), was constructed for assisting researchers to develop SSR markers from a large EST collection. ESAP Plus incorporates several bioinformatic scripts and some useful standard software tools necessary for the four main procedures of EST-SSR marker development, namely 1) pre-processing, 2) clustering and assembly, 3) SSR mining and 4) SSR primer design. The proposed pipeline also provides two alternative steps for reducing EST redundancy and identifying SSR loci. Using public sugarcane ESTs, ESAP Plus automatically executed the aforementioned computational pipeline via a simple web user interface, which was implemented using standard PHP, HTML, CSS and Java scripts. With ESAP Plus, users can upload raw EST data and choose various filtering options and parameters to analyze each of the four main procedures through this web interface. All input EST data and their predicted SSR results will be stored in the ESAP Plus MySQL database. Users will be notified via e-mail when the automatic process is completed and they can download all the results through the web interface.ConclusionsESAP Plus is a comprehensive and convenient web-based bioinformatic tool for SSR marker development. ESAP Plus offers all necessary EST-SSR development processes with various adjustable options that users can easily use to identify SSR markers from a large EST collection. With familiar web interface, users can upload the raw EST using the data submission page and visualize/download the corresponding EST-SSR information from within ESAP Plus. ESAP Plus can handle considerably large EST datasets. This EST-SSR discovery tool can be accessed directly from: http://gbp.kku.ac.th/esap_plus/ .

Project description:BackgroundThe medicinal legume Mucuna pruriens (L.) DC. has attracted attention worldwide as a source of the anti-Parkinson's drug L-Dopa. It is also a popular green manure cover crop that offers many agronomic benefits including high protein content, nitrogen fixation and soil nutrients. The plant currently lacks genomic resources and there is limited knowledge on gene expression, metabolic pathways, and genetics of secondary metabolite production. Here, we present transcriptomic resources for M. pruriens, including a de novo transcriptome assembly and annotation, as well as differential transcript expression analyses between root, leaf, and pod tissues. We also develop microsatellite markers and analyze genetic diversity and population structure within a set of Indian germplasm accessions.ResultsOne-hundred ninety-one million two hundred thirty-three thousand two hundred forty-two bp cleaned reads were assembled into 67,561 transcripts with mean length of 626 bp and N50 of 987 bp. Assembled sequences were annotated using BLASTX against public databases with over 80% of transcripts annotated. We identified 7,493 simple sequence repeat (SSR) motifs, including 787 polymorphic repeats between the parents of a mapping population. 134 SSRs from expressed sequenced tags (ESTs) were screened against 23?M. pruriens accessions from India, with 52 EST-SSRs retained after quality control. Population structure analysis using a Bayesian framework implemented in fastSTRUCTURE showed nearly similar groupings as with distance-based (neighbor-joining) and principal component analyses, with most of the accessions clustering per geographical origins. Pair-wise comparison of transcript expression in leaves, roots and pods identified 4,387 differentially expressed transcripts with the highest number occurring between roots and leaves. Differentially expressed transcripts were enriched with transcription factors and transcripts annotated as belonging to secondary metabolite pathways.ConclusionsThe M. pruriens transcriptomic resources generated in this study provide foundational resources for gene discovery and development of molecular markers. Polymorphic SSRs identified can be used for genetic diversity, marker-trait analyses, and development of functional markers for crop improvement. The results of differential expression studies can be used to investigate genes involved in L-Dopa synthesis and other key metabolic pathways in M. pruriens.

Project description:BackgroundPrairie grass (Bromus catharticus) is a typical cool-season forage crop with high biomass production and fast growth rate during winter and spring. However, its genetic research and breeding has remained stagnant due to limited available genomic resources. The aim of this study was to generate large-scale genomic data using high-throughput transcriptome sequencing, and perform a preliminary validation of EST-SSR markers of B. catharticus.ResultsEleven tissue samples including seeds, leaves, and stems were collected from a new high-yield strain of prairie grass BCS1103. A total of 257,773 unigenes were obtained, of which 193,082 (74.90%) were annotated. Comparison analysis between tissues identified 1803, 3030, and 1570 genes specifically and highly expressed in seed, leaf, and stem, respectively. A total of 37,288 EST-SSRs were identified from unigene sequences, and more than 80,000 primer pairs were designed. We synthesized 420 primer pairs and selected 52 ones with high polymorphisms to estimate genetic diversity and population structure in 24 B. catharticus accessions worldwide. Despite low diversity indicated by an average genetic distance of 0.364, the accessions from South America and Asia and wild accessions showed higher genetic diversity. Moreover, South American accessions showed a pure ancestry, while Asian accessions demonstrated mixed internal relationships, which indicated a different probability of gene flow. Phylogenetic analysis clustered the studied accessions into four clades, being consistent with phenotypic clustering results. Finally, Mantel analysis suggested the total phenotypic variation was mostly contributed by genetic component. Stem diameter, plant height, leaf width, and biomass yield were significantly correlated with genetic data (r > 0.6, P < 0.001), and might be used in the future selection and breeding.ConclusionA genomic resource was generated that could benefit genetic and taxonomic studies, as well as molecular breeding for B. catharticus and its relatives in the future.

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EST and EST-SSR marker resources for Iris.

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EST and EST-SSR marker resources for Iris.

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