340 research outputs found
Implementation of genomics and bioinformatics approaches for identification and characterization of tomato ripening-related genes
Initial activities were focused on isolation and characterization of fruit ripening-related genes from tomato. Screening of four tomato cDNA libraries at low stringency with 10 fruit development and ripening-related genes yielded ~3000 positives clones. Microarray expression analysis of half of these positives in mature green and breaker stage fruits resulted in eight ripening-induced genes. RNA gel-blot analysis and previously published data confirmed expression for seven of the eight. One novel gene, designated LeEREBP1, was chosen for further characterization. LeEREBP1 encodes an AP2/ERF-domain transcription factor and is ethylene inducible. The expression profiles of LeEREBP1 parallel previously characterized ripening-related genes from tomato. Transgenic plants with increased and decreased expression of LeEREBP1 were generated and are currently being characterized to define the function of LeEREBP1.
A large public tomato EST dataset was mined to gain insight into the tomato transcriptome. By clustering genes according to the respective expression profiles of individual tissues, tissue and developmental expression patterns were generated and genes with similar functions grouped together. Tissues effectively clustered for relatedness according to their profiles confirming the integrity of the approach used to calculate gene expression. Statistical analysis of EST prevalence in fruit and pathogenesis-related libraries resulted in 333 genes being classified as fruit ripening-induced, 185 as fruit ripening-repressed, and 169 as pathogenesis-related. We performed a parallel analysis on public EST data for grape and compared the results for ripening-induced genes to tomato to identify similar and distinct ripening factors in addition to candidates for conserved regulators of fruit ripening.
An online interactive database for tomato gene expression data - Tomato Expression Database (TED) was implemented. TED contains normalized expression data for approximately 12,000 ESTs over ten time points during fruit development. It also contains comprehensive annotation of each EST. Through TED, we provide multiple approaches to pursue analysis of specific genes of interest and/or access the larger microarray dataset to identify sets of genes that may behave in a pattern of interest. In addition, a set of useful data mining and data visualization tools were developed and are under continuing expansion
iAssembler: a package for de novo assembly of Roche-454/Sanger transcriptome sequences
<p>Abstract</p> <p>Background</p> <p>Expressed Sequence Tags (ESTs) have played significant roles in gene discovery and gene functional analysis, especially for non-model organisms. For organisms with no full genome sequences available, ESTs are normally assembled into longer consensus sequences for further downstream analysis. However current <it>de novo </it>EST assembly programs often generate large number of assembly errors that will negatively affect the downstream analysis. In order to generate more accurate consensus sequences from ESTs, tools are needed to reduce or eliminate errors from <it>de novo </it>assemblies.</p> <p>Results</p> <p>We present iAssembler, a pipeline that can assemble large-scale ESTs into consensus sequences with significantly higher accuracy than current existing assemblers. iAssembler employs MIRA and CAP3 assemblers to generate initial assemblies, followed by identifying and correcting two common types of transcriptome assembly errors: 1) ESTs from different transcripts (mainly alternatively spliced transcripts or paralogs) are incorrectly assembled into same contigs; and 2) ESTs from same transcripts fail to be assembled together. iAssembler can be used to assemble ESTs generated using the traditional Sanger method and/or the Roche-454 massive parallel pyrosequencing technology.</p> <p>Conclusion</p> <p>We compared performances of iAssembler and several other <it>de novo </it>EST assembly programs using both Roche-454 and Sanger EST datasets. It demonstrated that iAssembler generated significantly more accurate consensus sequences than other assembly programs.</p
Tomato Expression Database (TED): a suite of data presentation and analysis tools
The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150 000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at
Transcriptome analysis of ectopic chloroplast development in green curd cauliflower (Brassica oleracea L. var. botrytis)
<p>Abstract</p> <p>Background</p> <p>Chloroplasts are the green plastids where photosynthesis takes place. The biogenesis of chloroplasts requires the coordinate expression of both nuclear and chloroplast genes and is regulated by developmental and environmental signals. Despite extensive studies of this process, the genetic basis and the regulatory control of chloroplast biogenesis and development remain to be elucidated.</p> <p>Results</p> <p>Green cauliflower mutant causes ectopic development of chloroplasts in the curd tissue of the plant, turning the otherwise white curd green. To investigate the transcriptional control of chloroplast development, we compared gene expression between green and white curds using the RNA-seq approach. Deep sequencing produced over 15 million reads with lengths of 86 base pairs from each cDNA library. A total of 7,155 genes were found to exhibit at least 3-fold changes in expression between green and white curds. These included light-regulated genes, genes encoding chloroplast constituents, and genes involved in chlorophyll biosynthesis. Moreover, we discovered that the cauliflower <it>ELONGATED HYPOCOTYL5 </it>(<it>BoHY5</it>) was expressed higher in green curds than white curds and that 2616 HY5-targeted genes, including 1600 up-regulated genes and 1016 down-regulated genes, were differently expressed in green in comparison to white curd tissue. All these 1600 up-regulated genes were HY5-targeted genes in the light.</p> <p>Conclusions</p> <p>The genome-wide profiling of gene expression by RNA-seq in green curds led to the identification of large numbers of genes associated with chloroplast development, and suggested the role of regulatory genes in the high hierarchy of light signaling pathways in mediating the ectopic chloroplast development in the green curd cauliflower mutant.</p
Use of RNA-seq data to identify and validate RT-qPCR reference genes for studying the tomato-<i>Pseudomonas pathosystem</i>
The agronomical relevant tomato-Pseudomonas syringae pv. tomato pathosystem is widely used to explore and understand the underlying mechanisms of the plant immune response. Transcript abundance estimation, mainly through reverse transcription-quantitative PCR (RT-qPCR), is a common approach employed to investigate the possible role of a candidate gene in certain biological process under study. The accuracy of this technique relies heavily on the selection of adequate reference genes. Initially, genes derived from other techniques (such as Northern blots) were used as reference genes in RT-qPCR experiments, but recent studies in different systems suggest that many of these genes are not stably expressed. The development of high throughput transcriptomic techniques, such as RNA-seq, provides an opportunity for the identification of transcriptionally stable genes that can be adopted as novel and robust reference genes. Here we take advantage of a large set of RNA-seq data originating from tomato leaves infiltrated with different immunity inducers and bacterial strains. We assessed and validated 9 genes that are much more stable than two traditional reference genes. Specifically, ARD2 and VIN3 were the most stably expressed genes and consequently we propose they be adopted for RT-qPCR experiments involving this pathosystem.Instituto de FisiologÃa Vegeta
Development of a EST dataset and characterization of EST-SSRs in a traditional Chinese medicinal plant, Epimedium sagittatum (Sieb. Et Zucc.) Maxim
<p>Abstract</p> <p>Background</p> <p><it>Epimedium sagittatum </it>(Sieb. Et Zucc.) Maxim, a traditional Chinese medicinal plant species, has been used extensively as genuine medicinal materials. Certain <it>Epimedium </it>species are endangered due to commercial overexploition, while sustainable application studies, conservation genetics, systematics, and marker-assisted selection (MAS) of <it>Epimedium </it>is less-studied due to the lack of molecular markers. Here, we report a set of expressed sequence tags (ESTs) and simple sequence repeats (SSRs) identified in these ESTs for <it>E. sagittatum</it>.</p> <p>Results</p> <p>cDNAs of <it>E. sagittatum </it>are sequenced using 454 GS-FLX pyrosequencing technology. The raw reads are cleaned and assembled into a total of 76,459 consensus sequences comprising of 17,231 contigs and 59,228 singlets. About 38.5% (29,466) of the consensus sequences significantly match to the non-redundant protein database (E-value < 1e-10), 22,295 of which are further annotated using Gene Ontology (GO) terms. A total of 2,810 EST-SSRs is identified from the <it>Epimedium </it>EST dataset. Trinucleotide SSR is the dominant repeat type (55.2%) followed by dinucleotide (30.4%), tetranuleotide (7.3%), hexanucleotide (4.9%), and pentanucleotide (2.2%) SSR. The dominant repeat motif is AAG/CTT (23.6%) followed by AG/CT (19.3%), ACC/GGT (11.1%), AT/AT (7.5%), and AAC/GTT (5.9%). Thirty-two SSR-ESTs are randomly selected and primer pairs are synthesized for testing the transferability across 52 <it>Epimedium </it>species. Eighteen primer pairs (85.7%) could be successfully transferred to <it>Epimedium </it>species and sixteen of those show high genetic diversity with 0.35 of observed heterozygosity (<it>Ho</it>) and 0.65 of expected heterozygosity (<it>He</it>) and high number of alleles per locus (11.9).</p> <p>Conclusion</p> <p>A large EST dataset with a total of 76,459 consensus sequences is generated, aiming to provide sequence information for deciphering secondary metabolism, especially for flavonoid pathway in <it>Epimedium</it>. A total of 2,810 EST-SSRs is identified from EST dataset and ~1580 EST-SSR markers are transferable. <it>E. sagittatum </it>EST-SSR transferability to the major <it>Epimedium </it>germplasm is up to 85.7%. Therefore, this EST dataset and EST-SSRs will be a powerful resource for further studies such as taxonomy, molecular breeding, genetics, genomics, and secondary metabolism in <it>Epimedium </it>species.</p
Transcriptome sequencing and whole genome expression profiling of chrysanthemum under dehydration stress
Use of RNA-seq data to identify and validate RT-qPCR reference genes for studying the tomato-<i>Pseudomonas pathosystem</i>
The agronomical relevant tomato-Pseudomonas syringae pv. tomato pathosystem is widely used to explore and understand the underlying mechanisms of the plant immune response. Transcript abundance estimation, mainly through reverse transcription-quantitative PCR (RT-qPCR), is a common approach employed to investigate the possible role of a candidate gene in certain biological process under study. The accuracy of this technique relies heavily on the selection of adequate reference genes. Initially, genes derived from other techniques (such as Northern blots) were used as reference genes in RT-qPCR experiments, but recent studies in different systems suggest that many of these genes are not stably expressed. The development of high throughput transcriptomic techniques, such as RNA-seq, provides an opportunity for the identification of transcriptionally stable genes that can be adopted as novel and robust reference genes. Here we take advantage of a large set of RNA-seq data originating from tomato leaves infiltrated with different immunity inducers and bacterial strains. We assessed and validated 9 genes that are much more stable than two traditional reference genes. Specifically, ARD2 and VIN3 were the most stably expressed genes and consequently we propose they be adopted for RT-qPCR experiments involving this pathosystem.Instituto de FisiologÃa Vegeta
Graph pangenome captures missing heritability and empowers tomato breeding
Missing heritability in genome-wide association studies defines a major problem in genetic analyses of complex biological traits(1,2). The solution to this problem is to identify all causal genetic variants and to measure their individual contributions(3,4). Here we report a graph pangenome of tomato constructed by precisely cataloguing more than 19 million variants from 838 genomes, including 32 new reference-level genome assemblies. This graph pangenome was used forgenome-wide association study analyses and heritability estimation of 20,323 gene-expression and metabolite traits. The average estimated trait heritability is 0.41 compared with 0.33 when using the single linear reference genome. This 24% increase in estimated heritability is largely due to resolving incomplete linkage disequilibrium through the inclusion of additional causal structural variants identified using the graph pangenome. Moreover, by resolving allelic and locus heterogeneity, structural variants improve the power to identify genetic factors underlying agronomically important traits leading to, for example, the identification of two new genes potentially contributing to soluble solid content. The newly identified structural variants will facilitate genetic improvement of tomato through both marker-assisted selection and genomic selection. Our study advances the understanding of the heritability of complex traits and demonstrates the power of the graph pangenome in crop breeding
The tomato kinase Pti1 contributes to production of reactive oxygen species in response to two flagellin-derived peptides and promotes resistance to pseudomonas syringae Infection
The Pti1 kinase was identified from a reverse genetic screen as contributing to pattern-triggered immunity (PTI) against Pseudomonas syringae pv. tomato (Pst). The tomato genome has two Pti1 genes, referred to as Pti1a and Pti1b. A hairpin-Pti1 (hpPti1) construct was developed and was used to generate two independent stable transgenic tomato lines that had reduced transcript abundance of both genes. In response to P. syringae pv. tomato inoculation, these hpPti1 plants developed more severe disease symptoms, supported higher bacterial populations, and had reduced transcript accumulation of PTI-associated genes, as compared with wild-type plants. In response to two flagellin-derived peptides, the hpPti1 plants produced lesser amounts of reactive oxygen species (ROS) but showed no difference in mitogen-activated protein kinase (MAPK). Synthetic Pti1a and Pti1b genes designed to avoid silencing were transiently expressed in the hpPti1 plants and restored the ability of the plants to produce wild-type levels of ROS. Our results identify a new component of PTI in tomato that, because it affects ROS production but not MAPK signaling, appears to act early in the immune response.Instituto de FisiologÃa Vegeta
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