Single cell transcriptome analysis using next generation sequencing.

The heterogeneity of tissues, especially in cancer research, is a central issue in transcriptome analysis. In recent years, research has primarily focused on the development of methods for single cell analysis. Single cell analysis aims at gaining (novel) insights into biological processes of healthy and diseased cells. Some of the challenges in transcriptome analysis concern low abundance of sample starting material, necessary sample amplification steps and subsequent analysis. In this study, two fundamentally different approaches to amplification were compared using next-generation sequencing analysis: I. exponential amplification using polymerase-chain-reaction (PCR) and II. linear amplification. For both approaches, protocols for single cell extraction, cell lysis, cDNA synthesis, cDNA amplification and preparation of next-generation sequencing libraries were developed. We could successfully show that transcriptome analysis of low numbers of cells is feasible with both exponential and linear amplification. Using exponential amplification, the highest amplification rates up to 106 were possible. The reproducibility of results is a strength of the linear amplification method. The analysis of next generation sequencing data in single cell samples showed detectable expression in at least 16.000 genes. The variance between samples results in a need to work with a greater amount of biological replicates. In summary it can be said that single cell transcriptome analysis with next generation sequencing is possible but improvements leading to a higher yield of transcriptome reads is required. In the near future by comparing single cancer cells with healthy ones for example, a basis for improved prognosis and diagnosis can be realised

Tissue resolved, gene structure refined equine transcriptome.

BackgroundTranscriptome interpretation relies on a good-quality reference transcriptome for accurate quantification of gene expression as well as functional analysis of genetic variants. The current annotation of the horse genome lacks the specificity and sensitivity necessary to assess gene expression especially at the isoform level, and suffers from insufficient annotation of untranslated regions (UTR) usage. We built an annotation pipeline for horse and used it to integrate 1.9 billion reads from multiple RNA-seq data sets into a new refined transcriptome.ResultsThis equine transcriptome integrates eight different tissues from 59 individuals and improves gene structure and isoform resolution, while providing considerable tissue-specific information. We utilized four levels of transcript filtration in our pipeline, aimed at producing several transcriptome versions that are suitable for different downstream analyses. Our most refined transcriptome includes 36,876 genes and 76,125 isoforms, with 6474 candidate transcriptional loci novel to the equine transcriptome.ConclusionsWe have employed a variety of descriptive statistics and figures that demonstrate the quality and content of the transcriptome. The equine transcriptomes that are provided by this pipeline show the best tissue-specific resolution of any equine transcriptome to date and are flexible for several downstream analyses. We encourage the integration of further equine transcriptomes with our annotation pipeline to continue and improve the equine transcriptome

Analysis of wheat SAGE tags reveals evidence for widespread antisense transcription

BACKGROUND: Serial Analysis of Gene Expression (SAGE) is a powerful tool for genome-wide transcription studies. Unlike microarrays, it has the ability to detect novel forms of RNA such as alternatively spliced and antisense transcripts, without the need for prior knowledge of their existence. One limitation of using SAGE on an organism with a complex genome and lacking detailed sequence information, such as the hexaploid bread wheat Triticum aestivum, is accurate annotation of the tags generated. Without accurate annotation it is impossible to fully understand the dynamic processes involved in such complex polyploid organisms. Hence we have developed and utilised novel procedures to characterise, in detail, SAGE tags generated from the whole grain transcriptome of hexaploid wheat. RESULTS: Examination of 71,930 Long SAGE tags generated from six libraries derived from two wheat genotypes grown under two different conditions suggested that SAGE is a reliable and reproducible technique for use in studying the hexaploid wheat transcriptome. However, our results also showed that in poorly annotated and/or poorly sequenced genomes, such as hexaploid wheat, considerably more information can be extracted from SAGE data by carrying out a systematic analysis of both perfect and "fuzzy" (partially matched) tags. This detailed analysis of the SAGE data shows first that while there is evidence of alternative polyadenylation this appears to occur exclusively within the 3' untranslated regions. Secondly, we found no strong evidence for widespread alternative splicing in the developing wheat grain transcriptome. However, analysis of our SAGE data shows that antisense transcripts are probably widespread within the transcriptome and appear to be derived from numerous locations within the genome. Examination of antisense transcripts showing sequence similarity to the Puroindoline a and Puroindoline b genes suggests that such antisense transcripts might have a role in the regulation of gene expression. CONCLUSION: Our results indicate that the detailed analysis of transcriptome data, such as SAGE tags, is essential to understand fully the factors that regulate gene expression and that such analysis of the wheat grain transcriptome reveals that antisense transcripts maybe widespread and hence probably play a significant role in the regulation of gene expression during grain development

Perturbations in neuroinflammatory pathways are associated with paclitaxel-induced peripheral neuropathy in breast cancer survivors.

Paclitaxel is a common chemotherapy drug associated with the development of chronic paclitaxel-induced peripheral neuropathy (PIPN). PIPN is associated with neuroinflammatory mechanisms in pre-clinical studies. Here, we evaluated for differential gene expression (DGE) in peripheral blood between breast cancer survivors with and without PIPN and for neuroinflammatory (NI) related signaling pathways and whole-transcriptome profiles from other experiments. Pathway impact analysis identified 8 perturbed NI related pathways. Expression profile analysis found 15 experiments having similar whole-transcriptome profiles of DGE related to neuroinflammation and PIPN. These findings suggest that perturbations in pathways associated with neuroinflammation are found in cancer survivors with PIPN

FUS mutant human motoneurons display altered transcriptome and microRNA pathways with implications for ALS pathogenesis

The FUS gene has been linked to amyotrophic lateral sclerosis (ALS). FUS is a ubiquitous RNA-binding protein, and the mechanisms leading to selective motoneuron loss downstream of ALS-linked mutations are largely unknown. We report the transcriptome analysis of human purified motoneurons, obtained from FUS wild-type or mutant isogenic induced pluripotent stem cells (iPSCs). Gene ontology analysis of differentially expressed genes identified significant enrichment of pathways previously associated to sporadic ALS and other neurological diseases. Several microRNAs (miRNAs) were also deregulated in FUS mutant motoneurons, including miR-375, involved in motoneuron survival. We report that relevant targets of miR-375, including the neural RNA-binding protein ELAVL4 and apoptotic factors, are aberrantly increased in FUS mutant motoneurons. Characterization of transcriptome changes in the cell type primarily affected by the disease contributes to the definition of the pathogenic mechanisms of FUS-linked ALS

Transcriptome analysis of Azospirillum lipoferum during its interaction with rice

The associative symbiosis between Plant Growth Promoting Rhizobacteria of the genus Azospirillum and cereals have mainly been studied from an agronomic and economic point of view, and several studies showed that plant morphological and metabolic changes depend on both bacterial and plant genotypes. However, if the specificity in the Rhizobium-legume symbiosis has been well characterized, the question of whether specificity occurs in the Azospirillum-plant associative symbiosis remains controversial. In this context, the overall gene expression of A. lipoferum 4B during its interaction with roots of two rice varieties (cv. Cigalon, cv. Nipponbare) was analyzed in order to characterize (i) genes differentially regulated in response to plant regardless of the variety and (ii) genes displaying a varietydependent regulation. Results of the transcriptomic analysis show that presence of the host plant triggers stress response systems, a large number of putative transcriptional regulators, signal transduction pathways, and many proteins of unknown function. This indicates a reprogramming of bacterial gene expression, due to adaptation to host plant. Genes specifically expressed during the interaction with one of the two varieties could be identified, suggesting the existence of specificity in the associative symbiosis between Azospirillum and cereals. (Texte intégral

The Sorghum bicolor reference genome: improved assembly, gene annotations, a transcriptome atlas, and signatures of genome organization.

Sorghum bicolor is a drought tolerant C4 grass used for the production of grain, forage, sugar, and lignocellulosic biomass and a genetic model for C4 grasses due to its relatively small genome (approximately 800 Mbp), diploid genetics, diverse germplasm, and colinearity with other C4 grass genomes. In this study, deep sequencing, genetic linkage analysis, and transcriptome data were used to produce and annotate a high-quality reference genome sequence. Reference genome sequence order was improved, 29.6 Mbp of additional sequence was incorporated, the number of genes annotated increased 24% to 34 211, average gene length and N50 increased, and error frequency was reduced 10-fold to 1 per 100 kbp. Subtelomeric repeats with characteristics of Tandem Repeats in Miniature (TRIM) elements were identified at the termini of most chromosomes. Nucleosome occupancy predictions identified nucleosomes positioned immediately downstream of transcription start sites and at different densities across chromosomes. Alignment of more than 50 resequenced genomes from diverse sorghum genotypes to the reference genome identified approximately 7.4 M single nucleotide polymorphisms (SNPs) and 1.9 M indels. Large-scale variant features in euchromatin were identified with periodicities of approximately 25 kbp. A transcriptome atlas of gene expression was constructed from 47 RNA-seq profiles of growing and developed tissues of the major plant organs (roots, leaves, stems, panicles, and seed) collected during the juvenile, vegetative and reproductive phases. Analysis of the transcriptome data indicated that tissue type and protein kinase expression had large influences on transcriptional profile clustering. The updated assembly, annotation, and transcriptome data represent a resource for C4 grass research and crop improvement

SERpredict: Detection of tissue- or tumor-specific isoforms generated through exonization of transposable elements

Background: Transposed elements (TEs) are known to affect transcriptomes, because either new exons are generated from intronic transposed elements (this is called exonization), or the element inserts into the exon, leading to a new transcript. Several examples in the literature show that isoforms generated by an exonization are specific to a certain tissue (for example the heart muscle) or inflict a disease. Thus, exonizations can have negative effects for the transcriptome of an organism. Results: As we aimed at detecting other tissue- or tumor-specific isoforms in human and mouse genomes which were generated through exonization of a transposed element, we designed the automated analysis pipeline SERpredict (SER = Specific Exonized Retroelement) making use of Bayesian Statistics. With this pipeline, we found several genes in which a transposed element formed a tissue- or tumor-specific isoform. Conclusion: Our results show that SERpredict produces relevant results, demonstrating the importance of transposed elements in shaping both the human and the mouse transcriptomes. The effect of transposed elements on the human transcriptome is several times higher than the effect on the mouse transcriptome, due to the contribution of the primate-specific Alu element