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BMC Plant Biology | Abstract | Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals.
Biswapriya Biswavas Misra's insight:
Abstract (provisional)Background

Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana.

Results

Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development.

Conclusion

The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process.

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BMC Genomics | Abstract | Transcriptome analysis at four developmental stages of grape berry (Vitis vinifera cv. Shiraz) provides insights into regulated and coordinated gene expression

Vitis vinifera berry development is characterised by an initial phase where the fruit is small, hard and acidic, followed by a lag phase known as veraison.
Biswapriya Biswavas Misra's insight:
Abstract (provisional)Background

Vitis vinifera berry development is characterised by an initial phase where the fruit is small, hard and acidic, followed by a lag phase known as veraison. In the final phase, berries become larger, softer and sweeter and accumulate an array of organoleptic compounds. Since the physiological and biochemical makeup of grape berries at harvest has a profound impact on the characteristics of wine, there is great interest in characterising the molecular and biophysical changes that occur from flowering through veraison and ripening, including the coordination and temporal regulation of metabolic gene pathways. Advances in deep-sequencing technologies, combined with the availability of increasingly accurate V. vinifera genomic and transcriptomic data, have enabled us to carry out RNA-transcript expression analysis on a global scale at key points during berry development.

Results

A total of 162 million 100-base pair reads were generated from pooled Vitis vinifera (cv. Shiraz) berries sampled at 3-weeks post-anthesis, 10- and 11-weeks post-anthesis (corresponding to early and late veraison) and at 17-weeks post-anthesis (harvest). Mapping reads from each developmental stage (36-45 million) onto the NCBI RefSeq transcriptome of 23,720 V. vinifera mRNAs revealed that at least 75% of these transcripts were detected in each sample. RNA-Seq analysis uncovered 4,185 transcripts that were significantly upregulated at a single developmental stage, including 161 transcription factors. Clustering transcripts according to distinct patterns of transcription revealed coordination in metabolic pathways such as organic acid, stilbene and terpenoid metabolism. From the phenylpropanoid/stilbene biosynthetic pathway at least 46 transcripts were upregulated in ripe berries when compared to veraison and immature berries, and 12 terpene synthases were predominantly detected only in a single sample. Quantitative real-time PCR was used to validate the expression pattern of 12 differentially expressed genes from primary and secondary metabolic pathways.

Conclusions

In this study we report the global transcriptional profile of Shiraz grapes at key stages of development. We have undertaken a comprehensive analysis of gene families contributing to commercially important berry characteristics and present examples of co-regulation and differential gene expression. The data reported here will provide an invaluable resource for the on-going molecular investigation of wine grapes.

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Tools for mapping high-throughput sequencing data

Tools for mapping high-throughput sequencing data | Plant Genomics | Scoop.it
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Abstract

Motivation: A ubiquitous and fundamental step in high-throughput sequencing analysis is the alignment (mapping) of the generated reads to a reference sequence. To accomplish this task, numerous software tools have been proposed. Determining the mappers that are most suitable for a specific application is not trivial.

Results: This survey focuses on classifying mappers through a wide number of characteristics. The goal is to allow practitioners to compare the mappers more easily and find those that are most suitable for their specific problem.

Availability: A regularly updated compendium of mappers can be found at http://wwwdev.ebi.ac.uk/fg/hts_mappers/.

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Progress in Ion Torrent semiconductor chip based sequencing - Merriman - 2012 - ELECTROPHORESIS - Wiley Online Library

Progress in Ion Torrent semiconductor chip based sequencing - Merriman - 2012 - ELECTROPHORESIS - Wiley Online Library | Plant Genomics | Scoop.it
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In order for next-generation sequencing to become widely used as a diagnostic in the healthcare industry, sequencing instrumentation will need to be mass produced with a high degree of quality and economy. One way to achieve this is to recast DNA sequencing in a format that fully leverages the manufacturing base created for computer chips, complementary metal-oxide semiconductor chip fabrication, which is the current pinnacle of large scale, high quality, low-cost manufacturing of high technology. To achieve this, ideally the entire sensory apparatus of the sequencer would be embodied in a standard semiconductor chip, manufactured in the same fab facilities used for logic and memory chips. Recently, such a sequencing chip, and the associated sequencing platform, has been developed and commercialized by Ion Torrent, a division of Life Technologies, Inc. Here we provide an overview of this semiconductor chip based sequencing technology, and summarize the progress made since its commercial introduction. We described in detail the progress in chip scaling, sequencing throughput, read length, and accuracy. We also summarize the enhancements in the associated platform, including sample preparation, data processing, and engagement of the broader development community through open source and crowdsourcing initiatives.

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Frontiers in Plant Systems Biology | Research Topics

Frontiers in Plant Systems Biology | Research Topics | Plant Genomics | Scoop.it
Biswapriya Biswavas Misra's insight:

Transcriptomes as assessed by either microarrays or next-generation sequencing have produced a hirtherto unprecedented data flood regarding transcript identity and levels in plant systems. Microarray data has been extensively used over the last 15 years or so and evaluation of the data they produced has progressed well beyond statistically quality evaluation and descriptive lists to a mature science whereby gene networks and cascades have been able to provide mechanistic insight. The development of sensitive quantitative PCR for lowly expressed genes such as transcription factors has additionally allowed another layer of complexity to be accessed and the modeling of transcription factor expression with that of target genes has met considerable success.
Yet more recently, data emanating from RNAseq studies have on one hand greatly improved the coverage of transcript profiling but on the other further compounded transcriptome analysis by adding the further complexity of it being facile to differentiate differentially spliced transcripts etc. In this research topic we would like to provide an “on the fly” portrait of the use of either microarray or RNAseq based datasets in contemporary Plant Systems Biology. In particular, we would like to cover (i) gene network models, (ii) novel ways of making these data accessible
(iii) RNA Seq data processing
(iv) mechanistic models

as well as providing a prospective view as to anticipated future developments in this rapidly expanding field. Because of the diversity of the field, we invite besides ‘Original Research’ and ‘Mini Reviews’ also ‘Hypothesis and Theory’, ‘Perspectives’, ‘Opinion’ and ‘Methods‘ papers. Manuscripts featuring computational elements would be strongly preferred but are by no means obligatory.

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BMC Genomics | Abstract | The transcriptomic fingerprint of glucoamylase over-expression in Aspergillus niger

Filamentous fungi such as Aspergillus niger are well known for their exceptionally high capacity for secretion of proteins, organic acids, and secondary metabolites and they are therefore used in biotechnology as versatile microbial production...
Biswapriya Biswavas Misra's insight:
Abstract (provisional)Background

Filamentous fungi such as Aspergillus niger are well known for their exceptionally high capacity for secretion of proteins, organic acids, and secondary metabolites and they are therefore used in biotechnology as versatile microbial production platforms. However, system-wide insights into their metabolic and secretory capacities are sparse and rational strain improvement approaches are therefore limited. In order to gain a genome-wide view on the transcriptional regulation of the protein secretory pathway of A. niger, we investigated the transcriptome of A. niger when it was forced to over-express the glaA gene (encoding glucoamylase, GlaA) and secrete GlaA to high level.

Results

An A. niger wild-type strain and a GlaA over-expressing strain, containing multiple copies of the glaA gene, were cultivated under maltose-limited chemostat conditions (specific growth rate 0.1 h-1). Elevated glaA mRNA and extracellular GlaA levels in the over-expressing strain were accompanied by elevated transcript levels from 772 genes and lowered transcript levels from 815 genes when compared to the wild-type strain. Using GO term enrichment analysis, four higher-order categories were identified in the up-regulated gene set: i) endoplasmic reticulum (ER) membrane translocation, ii) protein glycosylation, iii) vesicle transport, and iv) ion homeostasis. Among these, about 130 genes had predicted functions for the passage of proteins through the ER and those genes included target genes of the HacA transcription factor that mediates the unfolded protein response (UPR), e.g. bipA, clxA, prpA, tigA and pdiA.

In order to identify those genes that are important for high-level secretion of proteins by A. niger, we compared the transcriptome of the GlaA over-expression strain of A. niger with six other relevant transcriptomes of A. niger. Overall, 40 genes were found to have either elevated (from 36 genes) or lowered (from 4 genes) transcript levels under all conditions that were examined, thus defining the core set of genes important for ensuring high protein traffic through the secretory pathway.

Conclusion

We have defined the A. niger genes that respond to elevated secretion of GlaA and, furthermore, we have defined a core set of genes that appear to be involved more generally in the intensified traffic of proteins through the secretory pathway of A. niger. The consistent up-regulation of a gene encoding the acetyl-coenzyme A transporter suggests a possible role for transient acetylation to ensure correct folding of secreted proteins.

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BMC Biology | Full text | A spruce gene map infers ancient plant genome reshuffling and subsequent slow evolution in the gymnosperm lineage leading to extant conifers

Seed plants are composed of angiosperms and gymnosperms, which diverged from each other around 300 million years ago.
Biswapriya Biswavas Misra's insight:
AbstractBackground

Seed plants are composed of angiosperms and gymnosperms, which diverged from each other around 300 million years ago. While much light has been shed on the mechanisms and rate of genome evolution in flowering plants, such knowledge remains conspicuously meagre for the gymnosperms. Conifers are key representatives of gymnosperms and the sheer size of their genomes represents a significant challenge for characterization, sequencing and assembling.

Results

To gain insight into the macro-organisation and long-term evolution of the conifer genome, we developed a genetic map involving 1,801 spruce genes. We designed a statistical approach based on kernel density estimation to analyse gene density and identified seven gene-rich isochors. Groups of co-localizing genes were also found that were transcriptionally co-regulated, indicative of functional clusters. Phylogenetic analyses of 157 gene families for which at least two duplicates were mapped on the spruce genome indicated that ancient gene duplicates shared by angiosperms and gymnosperms outnumbered conifer-specific duplicates by a ratio of eight to one. Ancient duplicates were much more translocated within and among spruce chromosomes than conifer-specific duplicates, which were mostly organised in tandem arrays. Both high synteny and collinearity were also observed between the genomes of spruce and pine, two conifers that diverged more than 100 million years ago.

Conclusions

Taken together, these results indicate that much genomic evolution has occurred in the seed plant lineage before the split between gymnosperms and angiosperms, and that the pace of evolution of the genome macro-structure has been much slower in the gymnosperm lineage leading to extent conifers than that seen for the same period of time in flowering plants. This trend is largely congruent with the contrasted rates of diversification and morphological evolution observed between these two groups of seed plants.

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BioTechniques - Direct sequencing of small genomes on the Pacific Biosciences RS without library preparation

We have developed a sequencing method on the Pacific Biosciences RS sequencer (the PacBio) for small DNA molecules that avoids the need for a standard library preparation. To date this approach has been applied toward sequencing...
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Pacific Biosciences (Menlo Park, CA, USA) have developed a platform that will sequence a single molecule of DNA in real-time via the polymerization of that strand with a single polymerase (1-6). This technique has many benefits over multi-molecule (clonal) sequencing technologies (7, 8); one such potential advantage is that it may not be absolutely necessary to make a library (i.e., create SMRT bells (9)) to generate sequence data. The only input (molecular) requirements to enable sequencing are a primed piece of DNA; both single-stranded and double-stranded molecules will work. The polymerase is necessarily highly processive starting with a location on the DNA at which it can bind, i.e., a free 3′-OH group. We decided to test whether any primed DNA molecules, lacking any other features of a PacBio SMRT bell, could be used directly in a sequencing reaction. The bound complex (DNA-primer-polymerase), although lacking PacBio adapter sequences, can still be sequenced on the PacBio platform. The present efficiency of this process, in terms of the numbers of reads generated and Mb yield per SMRT cell, is considerably less than that using standard libraries. With standard methods a typical SMRT cell will yield 35,000–50,000 reads and 100–160 Mb of mapped bases. The direct sequencing method described here has generated up to 3000 reads per SMRT cell and therefore its utility is limited to small genomes. However, this approach enables one to acquire sequence data from comparatively low amounts of DNA, even less than 1 ng of input, and within eight hours from receiving the sample. There is a slight time saving, compared with the 12 h required for standard library prep. This is not the main advantage, though it does now offer a route from sample to sequence within an average working day. This protocol may be of benefit to the direct sequencing of plasmids, single-standed or double-stranded viruses, mitochondrial DNA, and microbial pathogens in a clinical setting.

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Science: The Tale of the TALEs (2012)

Science: The Tale of the TALEs (2012) | Plant Genomics | Scoop.it
Biologists have turned plant pest proteins into tools for studying and reshaping genomes of many species.

Some of biology's best technologies come from unexpected places. The green fluorescent protein that lit up biology with its ability to track proteins and gene expression in cells was borrowed from a jellyfish. A heat-stable enzyme from a bacterium often found in hot springs made the polymerase chain reaction method practical, facilitating the easy copying of DNA fragments needed for a myriad of applications, including the DNA fingerprinting used so widely to identify people. Now, thanks in part to inspiration that struck during a lunchtime discussion, proteins from a feared plant pest are poised to make genome engineering, the large-scale, directed manipulation of genes, routine for researchers studying a variety of organisms, including yeast and humans.
Via Kamoun Lab @ TSL
Biswapriya Biswavas Misra's insight:

Biologists have turned plant pest proteins into tools for studying and reshaping genomes of many species.

Some of biology's best technologies come from unexpected places. The green fluorescent protein that lit up biology with its ability to track proteins and gene expression in cells was borrowed from a jellyfish. A heat-stable enzyme from a bacterium often found in hot springs made the polymerase chain reaction method practical, facilitating the easy copying of DNA fragments needed for a myriad of applications, including the DNA fingerprinting used so widely to identify people. Now, thanks in part to inspiration that struck during a lunchtime discussion, proteins from a feared plant pest are poised to make genome engineering, the large-scale, directed manipulation of genes, routine for researchers studying a variety of organisms, including yeast and humans.

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Transcriptome analysis of intraspecific competition in Arabidopsis thaliana reveals organ-specific signatures related to nutrient acquisition and general stress respo...

Abstract (provisional)

Background

Plants are sessile and therefore have to perceive and adjust to changes in their environment. The presence of neighbours leads to a competitive situation where resources and space will be limited. Complex adaptive responses to such situation are poorly understood at the molecular level.

Results

Using microarrays, we analysed whole-genome expression changes in Arabidopsis thaliana plants subjected to intraspecific competition. The leaf and root transcriptome was strongly altered by competition. Differentially expressed genes were enriched in genes involved in nutrient deficiency (mainly N, P, K), perception of light quality, and responses to abiotic and biotic stresses. Interestingly, performance of the generalist insect Spodoptera littoralis on densely grown plants was significantly reduced, suggesting that plants under competition display enhanced resistance to herbivory.

Conclusions

This study provides a comprehensive list of genes whose expression is affected by intraspecific competition in Arabidopsis. The outcome is a unique response that involves genes related to light, nutrient deficiency, abiotic stress, and defence responses.

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An RNA-Seq Transcriptome Analysis of Pi Deficient White Lupin Reveals Novel Insights Into Phosphorus Acclimation in Plants

An RNA-Seq Transcriptome Analysis of Pi Deficient White Lupin Reveals Novel Insights Into Phosphorus Acclimation in Plants | Plant Genomics | Scoop.it

Abstract

Phosphorus, in its orthophosphate form (Pi), is one of the most limiting macronutrients in soils for plant growth and development. However, the whole genome molecular mechanisms contributing to plant acclimation to Pi deficiency remain largely unknown. White lupin (Lupinus albus L.) has evolved unique adaptations for growth in Pi deficient soils including the development of cluster roots to increase root surface area. In this study, we utilized RNA-Seq technology to assess global gene expression in white lupin cluster roots, normal roots, and leaves in response to Pi supply. We de novo assembled 277,224,180 Illumina reads from 12 cDNA libraries to build the first white lupin gene index (LAGI 1.0). This index contains 125,821 unique sequences with an average length of 1,155 bp. Of these sequences 50,734 were transcriptionally active (RPKM ≥ 3) representing approximately 7.8% of the Lupinus albus genome, using the predicted genome size of Lupinus angustifolius as a reference. We identified a total of 2,128 sequences differentially expressed in response to Pi deficiency with a ≥ 2-fold change and a p-value ≤ 0.05. Twelve sequences were consistently differentially expressed due to Pi deficiency stress in three species, making them ideal candidates to monitor the Pi status of plants. Additionally, classic physiological experiments were coupled with RNA-Seq data to examine the role of cytokinin and gibberellic acid in Pi deficiency-induced cluster root development. This global gene expression analysis provides new insights into the biochemical and molecular mechanisms involved in the acclimation to Pi deficiency.

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Cell - Deciphering and Prediction of Transcriptome Dynamics under Fluctuating Field Conditions

HighlightsDeciphering rice leaf transcriptome dynamics under complex field conditionsField transcriptome is primarily influenced by ambient temperature and circadian clockResponse thresholds to light were very low for many light-responsive genesModeling transcriptome fluctuations in changing environments yields predictive data

Summary

Determining the drivers of gene expression patterns is more straightforward in laboratory conditions than in the complex fluctuating environments where organisms typically live. We gathered transcriptome data from the leaves of rice plants in a paddy field along with the corresponding meteorological data and used them to develop statistical models for the endogenous and external influences on gene expression. Our results indicate that the transcriptome dynamics are predominantly governed by endogenous diurnal rhythms, ambient temperature, plant age, and solar radiation. The data revealed diurnal gates for environmental stimuli to influence transcription and pointed to relative influences exerted by circadian and environmental factors on different metabolic genes. The model also generated predictions for the influence of changing temperatures on transcriptome dynamics. We anticipate that our models will help translate the knowledge amassed in laboratories to problems in agriculture and that our approach to deciphering the transcriptome fluctuations in complex environments will be applicable to other organisms.

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PLOS Genetics: The Genomes of the Fungal Plant Pathogens Cladosporium fulvum and Dothistroma septosporum Reveal Adaptation to Different Hosts and Lifestyles But Also Signatures of Common Ancestry

PLOS Genetics: The Genomes of the Fungal Plant Pathogens Cladosporium fulvum and Dothistroma septosporum Reveal Adaptation to Different Hosts and Lifestyles But Also Signatures of Common Ancestry | Plant Genomics | Scoop.it

We sequenced and compared the genomes of the Dothideomycete fungal plant pathogens Cladosporium fulvum (Cfu) (syn. Passalora fulva) and Dothistroma septosporum (Dse) that are closely related phylogenetically, but have different lifestyles and hosts. Although both fungi grow extracellularly in close contact with host mesophyll cells, Cfu is a biotroph infecting tomato, while Dse is a hemibiotroph infecting pine. The genomes of these fungi have a similar set of genes (70% of gene content in both genomes are homologs), but differ significantly in size (Cfu >61.1-Mb; Dse 31.2-Mb), which is mainly due to the difference in repeat content (47.2% in Cfu versus 3.2% in Dse). Recent adaptation to different lifestyles and hosts is suggested by diverged sets of genes. Cfu contains an α-tomatinase gene that we predict might be required for detoxification of tomatine, while this gene is absent in Dse. Many genes encoding secreted proteins are unique to each species and the repeat-rich areas in Cfu are enriched for these species-specific genes. In contrast, conserved genes suggest common host ancestry. Homologs of Cfu effector genes, including Ecp2 and Avr4, are present in Dse and induce a Cf-Ecp2- and Cf-4-mediated hypersensitive response, respectively. Strikingly, genes involved in production of the toxin dothistromin, a likely virulence factor for Dse, are conserved in Cfu, but their expression differs markedly with essentially no expression by Cfu in planta. Likewise, Cfu has a carbohydrate-degrading enzyme catalog that is more similar to that of necrotrophs or hemibiotrophs and a larger pectinolytic gene arsenal than Dse, but many of these genes are not expressed in planta or are pseudogenized. Overall, comparison of their genomes suggests that these closely related plant pathogens had a common ancestral host but since adapted to different hosts and lifestyles by a combination of differentiated gene content, pseudogenization, and gene regulation.

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Repeated polyploidization of Gossypium genomes and the evolution of spinnable cotton fibres

Repeated polyploidization of Gossypium genomes and the evolution of spinnable cotton fibres | Plant Genomics | Scoop.it
Polyploidy often confers emergent properties, such as the higher fibre productivity and quality of tetraploid cottons than diploid cottons bred for the same environments.
Biswapriya Biswavas Misra's insight:

Polyploidy often confers emergent properties, such as the higher fibre productivity and quality of tetraploid cottons than diploid cottons bred for the same environments1. Here we show that an abrupt five- to sixfold ploidy increase approximately 60 million years (Myr) ago, and allopolyploidy reuniting divergent Gossypium genomes approximately 1–2 Myr ago2, conferred about 30–36-fold duplication of ancestral angiosperm (flowering plant) genes in elite cottons (Gossypium hirsutum and Gossypium barbadense), genetic complexity equalled only by Brassica3 among sequenced angiosperms. Nascent fibre evolution, before allopolyploidy, is elucidated by comparison of spinnable-fibred Gossypium herbaceum A and non-spinnable Gossypium longicalyx F genomes to one another and the outgroup D genome of non-spinnable Gossypium raimondii. The sequence of a G. hirsutum AtDt (in which ‘t’ indicates tetraploid) cultivar reveals many non-reciprocal DNA exchanges between subgenomes that may have contributed to phenotypic innovation and/or other emergent properties such as ecological adaptation by polyploids. Most DNA-level novelty in G. hirsutum recombines alleles from the D-genome progenitor native to its New World habitat and the Old World A-genome progenitor in which spinnable fibre evolved. Coordinated expression changes in proximal groups of functionally distinct genes, including a nuclear mitochondrial DNA block, may account for clusters of cotton-fibre quantitative trait loci affecting diverse traits. Opportunities abound for dissecting emergent properties of other polyploids, particularly angiosperms, by comparison to diploid progenitors and outgroups.

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Genome-Wide Transcriptome and Proteome Analysis on Different Developmental Stages of Cordyceps militaris

Genome-Wide Transcriptome and Proteome Analysis on Different Developmental Stages of Cordyceps militaris | Plant Genomics | Scoop.it
PLOS ONE: an inclusive, peer-reviewed, open-access resource from the PUBLIC LIBRARY OF SCIENCE. Reports of well-performed scientific studies from all disciplines freely available to the whole world.
Biswapriya Biswavas Misra's insight:
Abstract TopBackground

Cordyceps militaris, an ascomycete caterpillar fungus, has been used as a traditional Chinese medicine for many years owing to its anticancer and immunomodulatory activities. Currently, artificial culturing of this beneficial fungus has been widely used and can meet the market, but systematic molecular studies on the developmental stages of cultured C. militaris at transcriptional and translational levels have not been determined.

Methodology/Principal Findings

We utilized high-throughput Illumina sequencing to obtain the transcriptomes of C. militaris mycelium and fruiting body. All clean reads were mapped to C. militaris genome and most of the reads showed perfect coverage. Alternative splicing and novel transcripts were predicted to enrich the database. Gene expression analysis revealed that 2,113 genes were up-regulated in mycelium and 599 in fruiting body. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to analyze the genes with expression differences. Moreover, the putative cordycepin metabolism difference between different developmental stages was studied. In addition, the proteome data of mycelium and fruiting body were obtained by one-dimensional gel electrophoresis (1-DGE) coupled with nano-electrospray ionization liquid chromatography tandem mass spectrometry (nESI-LC-MS/MS). 359 and 214 proteins were detected from mycelium and fruiting body respectively. GO, KEGG and Cluster of Orthologous Groups (COG) analysis were further conducted to better understand their difference. We analyzed the amounts of some noteworthy proteins in these two samples including lectin, superoxide dismutase, glycoside hydrolase and proteins involved in cordycepin metabolism, providing important information for further protein studies.

Conclusions/Significance

The results reveal the difference in gene expression between the mycelium and fruiting body of artificially cultivated C. militaris by transcriptome and proteome analysis. Our study provides an effective resource for the further developmental and medicinal research of this promising fungus.

 

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BMC Genomics | Abstract | Evaluation method for the potential functionome harbored in the genome and metagenome

One of the main goals of genomic analysis is to elucidate the comprehensive functions (functionome) in individual organisms or a whole community in various environments.
Biswapriya Biswavas Misra's insight:
Abstract (provisional)Background

One of the main goals of genomic analysis is to elucidate the comprehensive functions (functionome) in individual organisms or a whole community in various environments. However, a standard evaluation method for discerning the functional potentials harbored within the genome or metagenome has not yet been established. We have developed a new evaluation method for the potential functionome, based on the completion ratio of Kyoto Encyclopedia of Genes and Genomes (KEGG) functional modules.

Results

Distribution of the completion ratio of the KEGG functional modules in 768 prokaryotic species varied greatly with the kind of module, and all modules primarily fell into 4 patterns (universal, restricted, diversified and non-prokaryotic modules), indicating the universal and unique nature of each module, and also the versatility of the KEGG Orthology (KO) identifiers mapped to each one. The module completion ratio in 8 phenotypically different bacilli revealed that some modules were shared only in phenotypically similar species. Metagenomes of human gut microbiomes from 13 healthy individuals previously determined by the Sanger method were analyzed based on the module completion ratio. Results led to new discoveries in the nutritional preferences of gut microbes, believed to be one of the mutualistic representations of gut microbiomes to avoid nutritional competition with the host.

Conclusions

The method developed in this study could characterize the functionome harbored in genomes and metagenomes. As this method also provided taxonomical information from KEGG modules as well as the gene hosts constructing the modules, interpretation of completion profiles was simplified and we could identify the complementarity between biochemical functions in human hosts and the nutritional preferences in human gut microbiomes. Thus, our method has the potential to be a powerful tool for comparative functional analysis in genomics and metagenomics, able to target unknown environments containing various uncultivable microbes within unidentified phyla.

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A computational pipeline for the development of multi-marker bio-signature panels and ensemble classifiers

Biomarker panels derived separately from genomic and proteomic data and with a variety of computational methods have demonstrated promising classification performance in various diseases.
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Abstract (provisional)Background

Biomarker panels derived separately from genomic and proteomic data and with a variety of computational methods have demonstrated promising classification performance in various diseases. An open question is how to create effective proteo-genomic panels. The framework of ensemble classifiers has been applied successfully in various analytical domains to combine classifiers so that the performance of the ensemble exceeds the performance of individual classifiers. Using blood-based diagnosis of acute renal allograft rejection as a case study, we address the following question in this paper: Can acute rejection classification performance be improved by combining individual genomic and proteomic classifiers in an ensemble?

Results

The first part of the paper presents a computational biomarker development pipeline for genomic and proteomic data. The pipeline begins with data acquisition (e.g., from bio-samples to microarray data), quality control, statistical analysis and mining of the data, and finally various forms of validation. The pipeline ensures that the various classifiers to be combined later in an ensemble are diverse and adequate for clinical use. Five mRNA genomic and five proteomic classifiers were developed independently using single time-point blood samples from 11 acute-rejection and 22 non-rejection renal transplant patients. The second part of the paper examines five ensembles ranging in size from two to 10 individual classifiers. Performance of ensembles is characterized by area under the curve (AUC), sensitivity, and specificity, as derived from the probability of acute rejection for individual classifiers in the ensemble in combination with one of two aggregation methods: (1) Average Probability or (2) Vote Threshold. One ensemble demonstrated superior performance and was able to improve sensitivity and AUC beyond the best values observed for any of the individual classifiers in the ensemble, while staying within the range of observed specificity. The Vote Threshold aggregation method achieved improved sensitivity for all 5 ensembles, but typically at the cost of decreased specificity.

Conclusion

Proteo-genomic biomarker ensemble classifiers show promise in the diagnosis of acute renal allograft rejection and can improve classification performance beyond that of individual genomic or proteomic classifiers alone. Validation of our results in an international multicenter study is currently underway.

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Improved transcriptome quantification and reconstruction from RNA-Seq reads using partial annotations - In Silico Biology - Volume 11, Number 5 / 2012 - IOS Press

Improved transcriptome quantification and reconstruction from RNA-Seq reads using partial annotations - In Silico Biology - Volume 11, Number 5 / 2012 - IOS Press | Plant Genomics | Scoop.it
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Abstract

The paper addresses the problem of how to use RNA-Seq data for transcriptome reconstruction and quantification, as well as novel transcript discovery in partially annotated genomes. We present a novel annotation-guided general framework for transcriptome discovery, reconstruction and quantification in partially annotated genomes and compare it with existing annotation-guided and genome-guided transcriptome assembly methods. Our method, referred as Discovery and Reconstruction of Unannotated Transcripts (DRUT), can be used to enhance existing transcriptome assemblers, such as Cufflinks [3], as well as to accurately estimate the transcript frequencies. Empirical analysis on synthetic datasets confirms that Cufflinks enhanced by DRUT has superior quality of reconstruction and frequency estimation of transcripts.

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BMC Plant Biology | Abstract | Transcriptome response analysis of Arabidopsis thaliana to leafminer (Liriomyza huidobrensis)

Plants have evolved a complicated resistance system and exhibit a variety of defense patterns in response to different attackers.
Biswapriya Biswavas Misra's insight:
Abstract (provisional)Background

Plants have evolved a complicated resistance system and exhibit a variety of defense patterns in response to different attackers. Previous studies have shown that responses of plants to chewing insects and phloem-feeding insects are significantly different. Less is known, however, regarding molecular responses to leafminer insects. To investigate plant transcriptome response to leafminers, we selected the leafminer Liriomyza huidobrensis, which has a special feeding pattern more similar to pathogen damage than that of chewing insects, as a model insect, and Arabidopsis thaliana as a response plant.

Results

We first investigated local and systemic responses of A. thaliana to leafminer feeding using an Affymetrix ATH1 genome array. Genes related to metabolic processes and stimulus responses were highly regulated. Most systemically-induced genes formed a subset of the local response genes. We then downloaded gene expression data from online databases and used hierarchical clustering to explore relationships among gene expression patterns in A. thaliana damaged by different attackers.

Conclusions

Our results demonstrate that plant response patterns are strongly coupled to damage patterns of attackers.

 
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A map of rice genome variation reveals the origin of cultivated rice : Nature : Nature Publishing Group

A map of rice genome variation reveals the origin of cultivated rice : Nature : Nature Publishing Group | Plant Genomics | Scoop.it

Crop domestications are long-term selection experiments that have greatly advanced human civilization. The domestication of cultivated rice (Oryza sativa L.) ranks as one of the most important developments in history. However, its origins and domestication processes are controversial and have long been debated. Here we generate genome sequences from 446 geographically diverse accessions of the wild rice species Oryza rufipogon, the immediate ancestral progenitor of cultivated rice, and from 1,083 cultivated indica and japonica varieties to construct a comprehensive map of rice genome variation. In the search for signatures of selection, we identify 55 selective sweeps that have occurred during domestication. In-depth analyses of the domestication sweeps and genome-wide patterns reveal that Oryza sativa japonica rice was first domesticated from a specific population of O. rufipogon around the middle area of the Pearl River in southern China, and that Oryza sativa indica rice was subsequently developed from crosses between japonica rice and local wild rice as the initial cultivars spread into South East and South Asia. The domestication-associated traits are analysed through high-resolution genetic mapping. This study provides an important resource for rice breeding and an effective genomics approach for crop domestication research.


Via Guogen Yang
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BioTechniques - cDNA normalization by hydroxyapatite chromatography to enrich transcriptome diversity in RNA-seq applications

Second-generation sequencing (SGS) has become the preferred method for RNA transcriptome profiling of organisms and single cells. However, SGS analysis of transcriptome diversity (including protein-coding transcripts and regulatory...
Biswapriya Biswavas Misra's insight:

Second-generation sequencing (SGS) has revolutionized whole genome sequencing and transcriptome analysis (1-5). In particular, sequencing of cDNA synthesized from intracellular total RNA (RNA-seq) enables RNA expression profiling with high dynamic range and genome coverage. RNA-seq has led to discoveries of novel alternative RNA splicing in various eukaryotic cells types and expanded our knowledge of regulatory non-coding RNA transcripts (6-8). The primary component of both eukaryotic and prokaryotic total RNA is ribosomal RNA (rRNA) with all other coding, noncoding, and small RNAs representing less than 15% of the total RNA population (9). The abundance of rRNA-derived sequences in cDNA libraries diminishes the utility of RNA-seq for functional genomics studies because only a small fraction of reads are from sequences of interest. In this context, RNA-seq library preparation techniques that efficiently remove highly abundant rRNA-derived sequence populations and enrich for non-ribosomal RNAs prior to SGS are highly desirable.

A common method for excluding rRNA is to capture RNA species that contain polyadenylated tails. This approach is highly effective in removing rRNA but also depletes all non-polyadenylated host transcripts, including non-coding RNAs that regulate eukaryotic cellular function, as well as both viral and prokaryotic microbial sequences present in many complex sample types (10). Another common method for excluding rRNA is to selectively remove the ribosomal RNA prior to generating a cDNA library for SGS. These rRNA depletion protocols utilize antisense rRNA probes specifically designed to capture human/mouse/rat or gram positive/gram negative bacterial rRNA transcripts from high-quality total RNA samples. This technique is a multi-step procedure that requires large amounts of starting material (250 ng to 10 µg of total RNA) and has been shown to be less effective on degraded RNA samples. Commercially available rRNA depletion kits such as RiboMinus, and Ribo-Zero are effective in removing highly abundant rRNA species from eukaryotic and prokaryotic total RNA, but are costly and the rRNA capture probes are species-specific (11-14).

An alternative to depleting rRNA sequences prior to cDNA library synthesis is to apply cDNA normalization (also called Cot filtration) approaches that remove highly abundant sequences from cDNA libraries (15, 16). In normalization, double-stranded DNA (dsDNA) populations are first denatured and then allowed to re-anneal at an elevated temperature. Highly abundant sequences hybridize at higher rates (proportional to the square of their concentration) and, if the re-annealing reaction is stopped at a suitable time point (e.g., 4–24 h), these will comprise the majority of double-stranded species (17). If double-stranded and single-stranded cDNA can then be separated, representation of the highest abundance species in the resulting ss fraction can be significantly reduced. The two common approaches for separating ss-cDNA and ds-cDNA populations include enzymatic digestion of ds-cDNA using a duplex specific nuclease (DSN) (18, 19) and physical separation of ds-cDNA from ss-cDNA through methods such as hydroxyapatite chromatography (HAC) (20-24).

Here we describe a micro-column based HAC approach for normalization using convenient re-packable cartridges that is rapid, reproducible, and amenable to future automated sample preparation platforms (25-27). We present a comparison of our microcolumn HAC-based method with a commercial rRNA-depletion kit, Ribo-Zero, and a DSN normalization kit for normalizing SGS libraries prepared from Escherichia coli K-12 or human peripheral blood mononuclear cell (PBMC) total RNA, respectively. Sequencing of RNA-seq cDNA libraries followed by alignment to either the E. coli K-12 or human (hg19) genome was used to measure rRNA abundance, non-rRNA transcript enrichment, and in the case of E. coli K-12, coverage across the entire bacterial transcriptome. Microcolumn HAC-based normalization proved to be an effective, cost saving alternative to commercial Ribo-Zero and DSN normalization kits, and the first step toward a fully automated system incorporating HAC normalization into RNA-seq cDNA library preparation workflows.

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Transcriptome data modeling for targeted plant metabolic engineering

Transcriptome data modeling for targeted plant metabolic engineering | Plant Genomics | Scoop.it

The massive data generated by omics technologies require the power of bioinformatics, especially network analysis, for data mining and doing data-driven biology. Gene coexpression analysis, a network approach based on comprehensive gene expression data using microarrays, is becoming a standard tool for predicting gene function and elucidating the relationship between metabolic pathways. Differential and comparative gene coexpression analyses suggest a change in coexpression relationships and regulators controlling common and/or specific biological processes. In conjunction with the newly emerging genome editing technology, network analysis integrated with other omics data should pave the way for robust and practical plant metabolic engineering.

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Transcriptome analysis of symptomatic and recovered ... [Virol J. 2012] - PubMed - NCBI

Abstract

ABSTRACT:

BACKGROUND: Geminiviruses are a large and important family of plant viruses that infect a wide range of crops throughout the world. The Begomovirus genus contains species that are transmitted by whiteflies and are distributed worldwide causing disease on an array of horticultural crops. Symptom remission, in which newly developed leaves of systemically infected plants exhibit a reduction in symptom severity (recovery), has been observed on pepper (Capsicum annuum) plants infected with Pepper golden mosaic virus (PepGMV). Previous studies have shown that transcriptional and post-transcriptional gene silencing mechanisms are involved in the reduction of viral nucleic acid concentration in recovered tissue. In this study, we employed deep transcriptome sequencing methods to assess transcriptional variation in healthy (mock), symptomatic, and recovered pepper leaves following PepGMV infection.

RESULTS:

Differential expression analyses of the pepper leaf transcriptome from symptomatic and recovered stages revealed a total of 309 differentially expressed genes between healthy (mock) and symptomatic or recovered tissues. Computational prediction of differential expression was validated using quantitative reverse-transcription PCR confirming the robustness of our bioinformatic methods. Within the set of differentially expressed genes associated with the recovery process were genes involved in defense responses including pathogenesis-related proteins, reactive oxygen species, systemic acquired resistance, jasmonic acid biosynthesis, and ethylene signaling. No major differences were found when compared the differentially expressed genes in symptomatic and recovered tissues. On the other hand, a set of genes with novel roles in defense responses was identified including genes involved in histone modification. This latter result suggested that post-transcriptional and transcriptional gene silencing may be one of the major mechanisms involved in the recovery process. Genes orthologous to the C. annuum proteins involved in the pepper-PepGMV recovery response were identified in both Solanum lycopersicum and Solanum tuberosum suggesting conservation of components of the viral recovery response in the Solanaceae.

CONCLUSION:

These data provide a valuable source of information for improving our understanding of the underlying molecular mechanisms by which pepper leaves become symptomless following infection with geminiviruses. The identification of orthologs for the majority of genes differentially expressed in recovered tissues in two major solanaceous crop species provides the basis for future comparative analyses of the viral recovery process across related taxa.

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Transcriptome walking: a laboratory-oriented GUI-based approach to mRNA identification from deep-sequenced data

Abstract (provisional)

Background

Deep sequencing technology provides efficient and economical production of large numbers of randomly positioned, relatively short, estimates of base identities in DNA molecules. Application of this technology to mRNA samples allows rapid examination of the molecular genetic environment in individual cells or tissues, the transcriptome. However, assembly of such short sequences into complete mRNA creates a challenge that limits the usefulness of the technology, particularly when no, or limited, genomic data is available. Several approaches to this problem have been developed, but there is still no general method to rapidly obtain an mRNA sequence from deep sequence data when a specific molecule, or family of molecules, are of interest. A frequent requirement is to identify specific mRNA molecules from tissues that are being investigated by methods such as electrophysiology, immunocytology and pharmacology. To be widely useful, any approach must be relatively simple to use in the laboratory by operators without extensive statistical or bioinformatics knowledge, and with readily available hardware.

Findings

An approach was developed that allows de novo assembly of individual mRNA sequences in two linked stages: sequence discovery and sequence completion. Both stages rely on computer assisted, Graphical User Interface (GUI)-guided, user interaction with the data, but proceed relatively efficiently once discovery is complete. The method grows a discovered sequence by repeated passes through the complete raw data in a series of steps, and is hence termed 'transcriptome walking'. All of the operations required for transcriptome analysis are combined in one program that presents a relatively simple user interface and runs on a standard desktop, or laptop computer, but takes advantage of multi-core processors, when available. Complete mRNA sequence identifications usually require less than 24 hours. This approach has already identified previously unknown mRNA sequences in two animal species that currently lack any significant genome or transcriptome data.

Conclusions

As deep sequencing data becomes more widely available, accessible methods for extracting useful sequence information in the biological or medical laboratory will be of increasing importance. The approach described here does not rely on detailed knowledge of bioinformatic algorithms, and allows users with basic knowledge of molecular biology and standard laboratory computing equipment, but limited software or bioinformatics experience, to extract complete gene sequences from deep-sequencing data.

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PLOS Biology: Rapid Evolution of Enormous, Multichromosomal Genomes in Flowering Plant Mitochondria with Exceptionally High Mutation Rates

PLOS Biology: Rapid Evolution of Enormous, Multichromosomal Genomes in Flowering Plant Mitochondria with Exceptionally High Mutation Rates | Plant Genomics | Scoop.it

Abstract Top

Genome size and complexity vary tremendously among eukaryotic species and their organelles. Comparisons across deeply divergent eukaryotic lineages have suggested that variation in mutation rates may explain this diversity, with increased mutational burdens favoring reduced genome size and complexity. The discovery that mitochondrial mutation rates can differ by orders of magnitude among closely related angiosperm species presents a unique opportunity to test this hypothesis. We sequenced the mitochondrial genomes from two species in the angiosperm genus Silene with recent and dramatic accelerations in their mitochondrial mutation rates. Contrary to theoretical predictions, these genomes have experienced a massive proliferation of noncoding content. At 6.7 and 11.3 Mb, they are by far the largest known mitochondrial genomes, larger than most bacterial genomes and even some nuclear genomes. In contrast, two slowly evolving Silene mitochondrial genomes are smaller than average for angiosperms. Consequently, this genus captures approximately 98% of known variation in organelle genome size. The expanded genomes reveal several architectural changes, including the evolution of complex multichromosomal structures (with 59 and 128 circular-mapping chromosomes, ranging in size from 44 to 192 kb). They also exhibit a substantial reduction in recombination and gene conversion activity as measured by the relative frequency of alternative genome conformations and the level of sequence divergence between repeat copies. The evolution of mutation rate, genome size, and chromosome structure can therefore be extremely rapid and interrelated in ways not predicted by current evolutionary theories. Our results raise the hypothesis that changes in recombinational processes, including gene conversion, may be a central force driving the evolution of both mutation rate and genome structure.

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