An evaluation of potential candidate genes involved in salinity tolerance in striped catfish (Pangasianodon hypopthalmus) using an RNA-SEQ approach

The project investigated the molecular response of Tra catfish (Pangasianodon hypophthalmus) to elevated salinity conditions. We employed Next generation sequencing platform to evaluate differential gene expression profiles of key genes under two salinity conditions. Results of the current project can form the basis for further studies to confirm the functional roles of specific genes that influence salinity tolerance in the target species and more broadly in other freshwater teleost fishes. Ultimately, the approach can contribute to developing superior culture stocks of the target species.

Evaluation of potential candidate genes involved in salinity tolerance in striped catfish (Pangasianodon hypophthalmus) using an RNA-Seq approach

Increasing salinity levels in freshwater and coastal environments caused by sea level rise linked to climate change is now recognized to be a major factor that can impact fish growth negatively, especially for freshwater teleost species. Striped catfish (Pangasianodon hypophthalmus) is an important freshwater teleost that is now widely farmed across the Mekong River Delta in Vietnam. Understanding the basis for tolerance and adaptation to raised environmental salinity conditions can assist the regional culture industry to mitigate predicted impacts of climate change across this region. Attempt of next generation sequencing using the ion proton platform results in more than 174 million raw reads from three tissue libraries (gill, kidney and intestine). Reads were filtered and de novo assembled using a variety of assemblers and then clustered together to generate a combined reference transcriptome. Downstream analysis resulted in a final reference transcriptome that contained 60,585 transcripts with an N50 of 683 bp. This resource was further annotated using a variety of bioinformatics databases, followed by differential gene expression analysis that resulted in 3062 transcripts that were differentially expressed in catfish samples raised under two experimental conditions (0 and 15 ppt). A number of transcripts with a potential role in salinity tolerance were then classified into six different functional gene categories based on their gene ontology assignments. These included; energy metabolism, ion transportation, detoxification, signal transduction, structural organization and detoxification. Finally, we combined the data on functional salinity tolerance genes into a hypothetical schematic model that attempted to describe potential relationships and interactions among target genes to explain the molecular pathways that control adaptive salinity responses in P. hypophthalmus. Our results indicate that P. hypophthalmus exhibit predictable plastic regulatory responses to elevated salinity by means of characteristic gene expression patterns, providing numerous candidate genes for future investigations.

Quantitative RNA-seq analysis of the campylobacter jejuni transcriptome

Campylobacter jejuni is the most common bacterial cause of foodborne disease in the developed world. Its general physiology and biochemistry, as well as the mechanisms enabling it to colonize and cause disease in various hosts, are not well understood, and new approaches are required to understand its basic biology. High-throughput sequencing technologies provide unprecedented opportunities for functional genomic research. Recent studies have shown that direct Illumina sequencing of cDNA (RNA-seq) is a useful technique for the quantitative and qualitative examination of transcriptomes. In this study we report RNA-seq analyses of the transcriptomes of C. jejuni (NCTC11168) and its rpoN mutant. This has allowed the identification of hitherto unknown transcriptional units, and further defines the regulon that is dependent on rpoN for expression. The analysis of the NCTC11168 transcriptome was supplemented by additional proteomic analysis using liquid chromatography-MS. The transcriptomic and proteomic datasets represent an important resource for the Campylobacter research community. © 2011 SGM.

Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses

BACKGROUND:

We have recently identified a number of Quantitative Trait Loci (QTL) contributing to the 2-fold muscle weight difference between the LG/J and SM/J mouse strains and refined their confidence intervals. To facilitate nomination of the candidate genes responsible for these differences we examined the transcriptome of the tibialis anterior (TA) muscle of each strain by RNA-Seq.

13,726 genes were expressed in mouse skeletal muscle. Intersection of a set of 1061 differentially expressed transcripts with a mouse muscle Bayesian Network identified a coherent set of differentially expressed genes that we term the LG/J and SM/J Regulatory Network (LSRN). The integration of the QTL, transcriptome and the network analyses identified eight key drivers of the LSRN (Kdr, Plbd1, Mgp, Fah, Prss23, 2310014F06Rik, Grtp1, Stk10) residing within five QTL regions, which were either polymorphic or differentially expressed between the two strains and are strong candidates for quantitative trait genes (QTGs) underlying muscle mass. The insight gained from network analysis including the ability to make testable predictions is illustrated by annotating the LSRN with knowledge-based signatures and showing that the SM/J state of the network corresponds to a more oxidative state. We validated this prediction by NADH tetrazolium reductase staining in the TA muscle revealing higher oxidative potential of the SM/J compared to the LG/J strain (p<0.03).

Thus, integration of fine resolution QTL mapping, RNA-Seq transcriptome information and mouse muscle Bayesian Network analysis provides a novel and unbiased strategy for nomination of muscle QTGs.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. © 2013 McArt et al.

Analysis of RNA-seq data from the interaction of Coffea spp. - Colletotrichum kahawae

Tese de mestrado em Bioinformática e Biologia Computacional (Bioinformática), apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2014

Cell walls of developing wheat starchy endosperm: comparison of composition and RNA-Seq transcriptome

The transcriptome of the developing starchy endosperm of hexaploid wheat (Triticum aestivum) was determined using RNA-Seq isolated at five stages during grain fill. This resource represents an excellent way to identify candidate genes responsible for the starchy endosperm cell wall, which is dominated by arabinoxylan (AX), accounting for 70% of the cell wall polysaccharides, with 20% (1,3; 1,4)-beta-D-glucan, 7% glucomannan, and 4% cellulose. A complete inventory of transcripts of 124 glycosyltransferase (GT) and 72 glycosylhydrolase (GH) genes associated with cell walls is presented. The most highly expressed GT transcript (excluding those known to be involved in starch synthesis) was a GT47 family transcript similar to Arabidopsis (Arabidopsis thaliana) IRX10 involved in xylan extension, and the second most abundant was a GT61. Profiles for GT43 IRX9 and IRX14 putative orthologs were consistent with roles in AX synthesis. Low abundances were found for transcripts from genes in the acyl-coA transferase BAHD family, for which a role in AX feruloylation has been postulated. The relative expression of these was much greater in whole grain compared with starchy endosperm, correlating with the levels of bound ferulate. Transcripts associated with callose (GSL), cellulose (CESA), pectin (GAUT), and glucomannan (CSLA) synthesis were also abundant in starchy endosperm, while the corresponding cell wall polysaccharides were confirmed as low abundance (glucomannan and callose) or undetectable (pectin) in these samples. Abundant transcripts from GH families associated with the hydrolysis of these polysaccharides were also present, suggesting that they may be rapidly turned over. Abundant transcripts in the GT31 family may be responsible for the addition of Gal residues to arabinogalactan peptide.

Transcriptomics-based analysis using RNA-Seq of the coconut (Cocos nucifera) leaf in response to yellow decline phytoplasma infection

Invasive phytoplasmas wreak havoc on coconut palms worldwide, leading to high loss of income, food insecurity and extreme poverty of farmers in producing countries. Phytoplasmas as strictly biotrophic insect-transmitted bacterial pathogens instigate distinct changes in developmental processes and defence responses of the infected plants and manipulate plants to their own advantage; however, little is known about the cellular and molecular mechanisms underlying host–phytoplasma interactions. Further, phytoplasma-mediated transcriptional alterations in coconut palm genes have not yet been identified. This study evaluated the whole transcriptome profiles of naturally infected leaves of Cocos nucifera ecotype Malayan Red Dwarf in response to yellow decline phytoplasma from group 16SrXIV, using RNA-Seq technique. Transcriptomics-based analysis reported here identified genes involved in coconut innate immunity. The number of down-regulated genes in response to phytoplasma infection exceeded the number of genes up-regulated. Of the 39,873 differentially expressed unigenes, 21,860 unigenes were suppressed and 18,013 were induced following infection. Comparative analysis revealed that genes associated with defence signalling against biotic stimuli were significantly overexpressed in phytoplasma-infected leaves versus healthy coconut leaves. Genes involving cell rescue and defence, cellular transport, oxidative stress, hormone stimulus and metabolism, photosynthesis reduction, transcription and biosynthesis of secondary metabolites were differentially represented. Our transcriptome analysis unveiled a core set of genes associated with defence of coconut in response to phytoplasma attack, although several novel defence response candidate genes with unknown function have also been identified. This study constitutes valuable sequence resource for uncovering the resistance genes and/or susceptibility genes which can be used as genetic tools in disease resistance breeding.

Transcriptoma (RNA-seq) de laranja doce Valência (Citrus sinensis L. Osbeck) e Kumquat (Fortunella spp.) infectadas por Xanthomonas citri subsp. citri

Pós-graduação em Biociências e Biotecnologia Aplicadas à Farmácia - FCFAR

Análise funcional das proteínas desacopladas mitocondriais de plantas utilizando RNA-seq e mutantes de inserção

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise do método suvrel na expressão diferencial a partir da matriz de contagens gerada com dados de RNA-SEQ

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise do transcriptoma de folhas de cana-de-açúcar submetidas à prolongada limitação hídrica usando RNA-Seq

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Exploring the Schistosoma mansoni adult male transcriptome using RNA-seq

Schistosoma mansoni is one of the agents of schistosomiasis, a chronic and debilitating disease. Here we, present a transcriptome-wide characterization of adult S. mansoni males by high-throughput RNA-sequencing. We obtained 1,620,432 high-quality ESTs from a directional strand-specific cDNA library, resulting in a 26% higher coverage of genome bases than that of the public ESTs available at NCBI. With a 15 x-deep coverage of transcribed genomic regions, our data were able to (i) confirm for the first time 990 predictions without previous evidence of transcription; (ii) correct gene predictions; (iii) discover 989 and 1196 RNA-seq contigs that map to intergenic and intronic genomic regions, respectively, where no gene had been predicted before. These contigs could represent new protein-coding genes or non-coding RNAs (ncRNAs). Interestingly, we identified 11 novel Micro-exon genes (MEGs). These data reveal new features of the S. mansoni transcriptional landscape and significantly advance our understanding of the parasite transcriptome. (c) 2011 Elsevier Inc. All rights reserved.