Transcriptome map of mouse isochores

<p>Abstract</p> <p>Background</p> <p>The availability of fully sequenced genomes and the implementation of transcriptome technologies have increased the studies investigating the expression profiles for a variety of tissues, conditions, and species. In this study, using RNA-seq data for three distinct tissues (brain, liver, and muscle), we investigate how base composition affects mammalian gene expression, an issue of prime practical and evolutionary interest.</p> <p>Results</p> <p>We present the transcriptome map of the mouse isochores (DNA segments with a fairly homogeneous base composition) for the three different tissues and the effects of isochores' base composition on their expression activity. Our analyses also cover the relations between the genes' expression activity and their localization in the isochore families.</p> <p>Conclusions</p> <p>This study is the first where next-generation sequencing data are used to associate the effects of both genomic and genic compositional properties to their corresponding expression activity. Our findings confirm previous results, and further support the existence of a relationship between isochores and gene expression. This relationship corroborates that isochores are primarily a product of evolutionary adaptation rather than a simple by-product of neutral evolutionary processes.</p

IsoXpressor: A Tool to Assess Transcriptional Activity within Isochores

Genomes are characterized by large regions of homogeneous base compositions known as isochores. The latter are divided into GC-poor and GC-rich classes linked to distinct functional and structural properties. Several studies have addressed how isochores shape function and structure. To aid in this important subject, we present IsoXpressor, a tool designed for the analysis of the functional property of transcription within isochores. IsoXpressor allows users to process RNA-Seq data in relation to the isochores, and it can be employed to investigate any biological question of interest for any species. The results presented herein as proof of concept are focused on the preimplantation process in Homo sapiens (human) and Macaca mulatta (rhesus monkey)

Compositional Genome Contexts Affect Gene Expression Control in Sea Urchin Embryo

Gene expression is widely perceived as exclusively controlled by the information contained in cis-regulatory regions. These are built in a modular way, each module being a cluster of binding sites for the transcription factors that control the level, the location and the time at which gene transcription takes place. On the other hand, results from our laboratory have shown that gene expression is affected by the compositional properties (GC levels) of the isochores in which genes are embedded, i.e. the genome context. To clarify how compositional genomic properties affect the way cis-regulatory information is utilized, we have changed the genome context of a GFP-reporter gene containing the complete cis-regulatory region of the gene spdeadringer (spdri), expressed during sea urchin embryogenesis. We have observed that GC levels higher or lower than those found in the natural genome context can alter the reporter expression pattern. We explain this as the result of an interference with the functionality of specific modules in the gene's cis-regulatory region. From these observations we derive the notion that the compositional properties of the genome context can affect cis-regulatory control of gene expression. Therefore although the way a gene works depends on the information contained in its cis-regulatory region, availability of such information depends on the compositional properties of the genomic context

Differential Selective Constraints Shaping Codon Usage Pattern of Housekeeping and Tissue-specific Homologous Genes of Rice and Arabidopsis

Intra-genomic variation between housekeeping and tissue-specific genes has always been a study of interest in higher eukaryotes. To-date, however, no such investigation has been done in plants. Availability of whole genome expression data for both rice and Arabidopsis has made it possible to examine the evolutionary forces in shaping codon usage pattern in both housekeeping and tissue-specific genes in plants. In the present work, we have taken 4065 rice–Arabidopsis homologous gene pairs to study evolutionary forces responsible for codon usage divergence between housekeeping and tissue-specific genes. In both rice and Arabidopsis, it is mutational bias that regulates error minimization in highly expressed genes of both housekeeping and tissue-specific genes. Our results show that, in comparison to tissue-specific genes, housekeeping genes are under strong selective constraint in plants. However, in tissue-specific genes, lowly expressed genes are under stronger selective constraint compared with highly expressed genes. We demonstrated that constraint acting on mRNA secondary structure is responsible for modulating codon usage variations in rice tissue-specific genes. Thus, different evolutionary forces must underline the evolution of synonymous codon usage of highly expressed genes of housekeeping and tissue-specific genes in rice and Arabidopsis

Exploring the gonad transcriptome of two extreme male pigs with RNA-seq

Background: Although RNA-seq greatly advances our understanding of complex transcriptome landscapes, such as those found in mammals, complete RNA-seq studies in livestock and in particular in the pig are still lacking. Here, we used high-throughput RNA sequencing to gain insight into the characterization of the poly-A RNA fraction expressed in pig male gonads. An expression analysis comparing different mapping approaches and detection of allele specific expression is also discussed in this study. Results: By sequencing testicle mRNA of two phenotypically extreme pigs, one Iberian and one Large White, we identified hundreds of unannotated protein-coding genes (PcGs) in intergenic regions, some of them presenting orthology with closely related species. Interestingly, we also detected 2047 putative long non-coding RNA (lncRNA), including 469 with human homologues. Two methods, DEGseq and Cufflinks, were used for analyzing expression. DEGseq identified 15% less expressed genes than Cufflinks, because DEGseq utilizes only unambiguously mapped reads. Moreover, a large fraction of the transcriptome is made up of transposable elements (14500 elements encountered), as has been reported in previous studies. Gene expression results between microarray and RNA-seq technologies were relatively well correlated (r = 0.71 across individuals). Differentially expressed genes between Large White and Iberian showed a significant overrepresentation of gamete production and lipid metabolism gene ontology categories. Finally, allelic imbalance was detected in ~ 4% of heterozygous sites. Conclusions: RNA-seq is a powerful tool to gain insight into complex transcriptomes. In addition to uncovering many unnanotated genes, our study allowed us to determine that a considerable fraction is made up of long non-coding transcripts and transposable elements. Their biological roles remain to be determined in future studies. In terms of differences in expression between Large White and Iberian pigs, these were largest for genes involved in spermatogenesis and lipid metabolism, which is consistent with phenotypic extreme differences in prolificacy and fat deposition between these two breeds

Transcriptome map of mouse isochores in embryonic and neonatal cortex

AbstractSeveral studies on adult tissues agree on the presence of a positive effect of the genomic and genic base composition on mammalian gene expression. Recent literature supports the idea that during developmental processes GC-poor genomic regions are preferentially implicated. We investigate the relationship between the compositional properties of the isochores and of the genes with their respective expression activity during developmental processes. Using RNA-seq data from two distinct developmental stages of the mouse cortex, embryonic day 18 (E18) and postnatal day 7 (P7), we established for the first time a developmental-related transcriptome map of the mouse isochores. Additionally, for each stage we estimated the correlation between isochores' GC level and their expression activity, and the genes' expression patterns for each isochore family. Our analyses add evidence supporting the idea that during development GC-poor isochores are preferentially implicated, and confirm the positive effect of genes' GC level on their expression activity

The Use of EST Expression Matrixes for the Quality Control of Gene Expression Data

EST expression profiling provides an attractive tool for studying differential gene expression, but cDNA libraries' origins and EST data quality are not always known or reported. Libraries may originate from pooled or mixed tissues; EST clustering, EST counts, library annotations and analysis algorithms may contain errors. Traditional data analysis methods, including research into tissue-specific gene expression, assume EST counts to be correct and libraries to be correctly annotated, which is not always the case. Therefore, a method capable of assessing the quality of expression data based on that data alone would be invaluable for assessing the quality of EST data and determining their suitability for mRNA expression analysis. Here we report an approach to the selection of a small generic subset of 244 UniGene clusters suitable for identification of the tissue of origin for EST libraries and quality control of the expression data using EST expression information alone. We created a small expression matrix of UniGene IDs using two rounds of selection followed by two rounds of optimisation. Our selection procedures differ from traditional approaches to finding "tissue-specific" genes and our matrix yields consistency high positive correlation values for libraries with confirmed tissues of origin and can be applied for tissue typing and quality control of libraries as small as just a few hundred total ESTs. Furthermore, we can pick up tissue correlations between related tissues e.g. brain and peripheral nervous tissue, heart and muscle tissues and identify tissue origins for a few libraries of uncharacterised tissue identity. It was possible to confirm tissue identity for some libraries which have been derived from cancer tissues or have been normalised. Tissue matching is affected strongly by cancer progression or library normalisation and our approach may potentially be applied for elucidating the stage of normalisation in normalised libraries or for cancer staging