RNA sequencing: advances, challenges and opportunities

Analysis of the Asian seabass transcriptome based on expressed sequence tags

Analysis of transcriptomes is of great importance in genomic studies. Asian seabass is an important fish species. A number of genomic tools in it were developed, while large expressed sequence tag (EST) data are lacking. We sequenced ESTs from nine normalized cDNA libraries and obtained 11 431 high-quality ESTs. We retrieved 8524 ESTs from dbEST database and analyzed all 19 975 ESTs using bioinformatics tools. After clustering, we obtained 8837 unique sequences (2838 contigs and 5999 singletons). The average contig length was 574 bp. Annotation of these unique sequences revealed that 48.9% of them showed significant homology to RNA sequences in GenBank. Functional classification of the unique ESTs identified a broad range of genes involved in different functions. We identified 6114 putative single-nucleotide polymorphisms and 634 microsatellites in ESTs. We discovered different temporal and spatial expression patterns of some immune-related genes in the Asian seabass after challenging with a pathogen Vibrio harveyi. The unique EST sequences are being used in developing a cDNA microarray to examine global gene expression and will also facilitate future whole-genome sequence assembly and annotation of Asian seabass and comparative genomics.

The physiology and pathobiology of human kallikrein-related peptidase 6 (KLK6)

The human kallikrein-related peptidase 6 (KLK6) gene belongs to the 15-member kallikrein (KLK) gene family mapping to chromosome 19q13.3-13.4. Encoding for an enzyme with trypsin-like properties, KLK6 can degrade components of the extracellular matrix. The successful utilisation of another KLK member (KLK3/PSA) for prostate cancer diagnosis has led many to evaluate KLK6 as a potential biomarker for other cancer and diseased states. The observed dysregulated expression in cancers, neurodegenerative diseases and skin conditions has led to the discovery that KLK6 participates in other cellular pathways including inflammation, receptor activation and regulation of apoptosis. Moreover, the improvements in high-throughput genomics have not only enabled the identification of sequence polymorphisms, but of transcript variants, whose functional significances have yet to be realised. This comprehensive review will summarise the current findings of KLK6 pathophysiology and discuss its potential as a viable biomarker.

Evaluation of Normalization Methods for RNA-Seq Gene Expression Estimation

Statistical inferences on RNA-Seq data, e.g., detecting differential gene expression, are meaningful only after proper normalization. However, there is no consensus for choosing a normalization procedure from among the many existing procedures. We evaluated several RNA-Seq normalization procedures by (1) correlating estimated RNA-Seq expression values to those of microarrays, (2) examining the concordance of stable and differential gene detection between the platforms, and (3) applying the procedures to simulated RNA-Seq data. Results suggested that RNA-Seq normalization procedures have little effect on both inter-platform gene expression correlation as well as inter-platform concordance of genes detected as stably or differentially expressed. However, the results of simulated analysis suggested that some normalization procedures are more robust to changes in distribution of differentially expressed genes. These results may provide guidance for selecting RNA-Seq normalization procedures.

Sequencing technologies and genome sequencing

The high-throughput - next generation sequencing (HT-NGS) technologies are currently the hottest topic in the field of human and animals genomics researches, which can produce over 100 times more data compared to the most sophisticated capillary sequencers based on the Sanger method. With the ongoing developments of high throughput sequencing machines and advancement of modern bioinformatics tools at unprecedented pace, the target goal of sequencing individual genomes of living organism at a cost of $1,000 each is seemed to be realistically feasible in the near future. In the relatively short time frame since 2005, the HT-NGS technologies are revolutionizing the human and animal genome researches by analysis of chromatin immunoprecipitation coupled to DNA microarray (ChIP-chip) or sequencing (ChIP-seq), RNA sequencing (RNA-seq), whole genome genotyping, genome wide structural variation, de novo assembling and re-assembling of genome, mutation detection and carrier screening, detection of inherited disorders and complex human diseases, DNA library preparation, paired ends and genomic captures, sequencing of mitochondrial genome and personal genomics. In this review, we addressed the important features of HT-NGS like, first generation DNA sequencers, birth of HT-NGS, second generation HT-NGS platforms, third generation HT-NGS platforms: including single molecule Heliscope™, SMRT™ and RNAP sequencers, Nanopore, Archon Genomics X PRIZE foundation, comparison of second and third HT-NGS platforms, applications, advances and future perspectives of sequencing technologies on human and animal genome research.

A systems biology approach to nutritional immunology - focus on innate immunity

Innate immunity and nutrient metabolism are complex biological systems that must work in concert to sustain and preserve life. The effector cells of the innate immune system rely on essential nutrients to generate energy, produce metabolic precursors for macromolecule biosynthesis and tune their responses to infectious agents. Thus disruptions to nutritional status have a substantial impact on immune competence and can result in increased susceptibility to infection in the case of nutrient deficiency, or chronic inflammation in the case of over-nutrition. The traditional, reductionist methods used in the study of nutritional immunology are incapable of exploring the extremely complex interactions between nutrient metabolism and innate immunity. Here, we review a relatively new analytical approach, systems biology, and highlight how it can be applied to nutritional immunology to provide a comprehensive view of the mechanisms behind nutritional regulation of the innate immune system.

PhyloCSF: a comparative genomics method to distinguish protein coding and non-coding regions

Motivation: As high-throughput transcriptome sequencing provides evidence for novel transcripts in many species, there is a renewed need for accurate methods to classify small genomic regions as protein coding or non-coding. We present PhyloCSF, a novel comparative genomics method that analyzes a multispecies nucleotide sequence alignment to determine whether it is likely to represent a conserved protein-coding region, based on a formal statistical comparison of phylogenetic codon models.

Results: We show that PhyloCSF's classification performance in 12-species Drosophila genome alignments exceeds all other methods we compared in a previous study. We anticipate that this method will be widely applicable as the transcriptomes of many additional species, tissues and subcellular compartments are sequenced, particularly in the context of ENCODE and modENCODE, and as interest grows in long non-coding RNAs, often initially recognized by their lack of protein coding potential rather than conserved RNA secondary structures.

Availability and Implementation: The Objective Caml source code and executables for GNU/Linux and Mac OS X are freely available at http://compbio.mit.edu/PhyloCSF

Contact:mlin@mit.edu; manoli@mit.edu

A low-cost library construction protocol and data analysis pipeline for Illumina-based strand-specific multiplex RNA-seq

The emergence of NextGen sequencing technology has generated much interest in the exploration of transcriptomes. Currently, Illumina Inc. (San Diego, CA) provides one of the most widely utilized sequencing platforms for gene expression analysis. While Illumina reagents and protocols perform adequately in RNA-sequencing (RNA-seq), alternative reagents and protocols promise a higher throughput at a much lower cost. We have developed a low-cost and robust protocol to produce Illumina-compatible (GAIIx and HiSeq2000 platforms) RNA-seq libraries by combining several recent improvements. First, we designed balanced adapter sequences for multiplexing of samples; second, dUTP incorporation in 2^nd strand synthesis was used to enforce strand-specificity; third, we simplified RNA purification, fragmentation and library size-selection steps thus drastically reducing the time and increasing throughput of library construction; fourth, we included an RNA spike-in control for validation and normalization purposes. To streamline informatics analysis for the community, we established a pipeline within the iPlant Collaborative. These scripts are easily customized to meet specific research needs and improve on existing informatics and statistical treatments of RNA-seq data. In particular, we apply significance tests for determining differential gene expression and intron retention events. To demonstrate the potential of both the library-construction protocol and data-analysis pipeline, we characterized the transcriptome of the rice leaf. Our data supports novel gene models and can be used to improve current rice genome annotation. Additionally, using the rice transcriptome data, we compared different methods of calculating gene expression and discuss the advantages of a strand-specific approach to detect bona-fide anti-sense transcripts and to detect intron retention events. Our results demonstrate the potential of this low cost and robust method for RNA-seq library construction and data analysis.

Transcriptome map of mouse isochores

Background

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.

Results

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.

Conclusions

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.

Genome-wide transcriptome analysis in murine neural retina using high-throughput RNA sequencing

Genome-wide characterization of the retinal transcriptome is central to understanding development, physiology and disorders of the visual system. Massively parallel, short-read sequencing of mRNA libraries was used to generate an extensive map of the transcriptome of the adult, murine neural retina. RNA-seq data strongly corroborates prior transcriptome studies by microarray and SAGE. However, several novel features of the retinal transcriptome were discovered. For example, retinal disease genes were discovered to be among the most highly expressed in the transcriptome. We also demonstrate other interesting features of the retinal transcriptome, for example, that the retina appears to employ a very specific and restricted set of synaptic vesicle genes, and also that there is persistence of expression of a majority of "neurodevelopmental" genes into adulthood. Retina transcriptome studies utilizing novel sequencing methods have been highly informative and these data may also serve as a resource for the community of researchers.

Transcriptional profiling of endocrine cerebro-osteodysplasia using microarray and next-generation sequencing

Background

Transcriptome profiling of patterns of RNA expression is a powerful approach to identify networks of genes that play a role in disease. To date, most mRNA profiling of tissues has been accomplished using microarrays, but next-generation sequencing can offer a richer and more comprehensive picture.

Methodology/Principal Findings

ECO is a rare multi-system developmental disorder caused by a homozygous mutation in ICK encoding intestinal cell kinase. We performed gene expression profiling using both cDNA microarrays and next-generation mRNA sequencing (mRNA-seq) of skin fibroblasts from ECO-affected subjects. We then validated a subset of differentially expressed transcripts identified by each method using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Finally, we used gene ontology (GO) to identify critical pathways and processes that were abnormal according to each technical platform. Methodologically, mRNA-seq identifies a much larger number of differentially expressed genes with much better correlation to qRT-PCR results than the microarray (r² = 0.794 and 0.137, respectively). Biologically, cDNA microarray identified functional pathways focused on anatomical structure and development, while the mRNA-seq platform identified a higher proportion of genes involved in cell division and DNA replication pathways.

Conclusions/Significance

Transcriptome profiling with mRNA-seq had greater sensitivity, range and accuracy than the microarray. The two platforms generated different but complementary hypotheses for further evaluation.

The genetics of kidney transplantation

Over the last decade, the search for gene variants with the potential to influence transplant outcomes or predispose individuals to host-recipient-related phenotypes has generated a considerable number of studies with conflicting results. Thousands of genotypes have been associated with complex traits related to transplant medicine, including acute rejection, immunosuppressive drug metabolism and side effects, infections, long-term outcomes, and cardiovascular complications. However, these efforts have given disappointing results, both in terms of gaining understanding of the biological basis of disease and in patient management. The methodological weaknesses that constitute the major limitations of most of these studies have been discussed widely. A new generation of approaches is needed to understand the relationship between gene variants and complex kidney transplantation traits. These approaches should be global, to generate original pathophysiological hypotheses, and should rely on advanced genomic tools, including Genome Wide Association studies and Whole Genome Sequencing technologies. Such enterprises will only be successful with the creation of international consortiums that connect partners in clinical, industrial, and academic transplant medicine.

An integrated proteomics/transcriptomics approach points to oxygen as the main electron sink for methanol metabolism in Methylotenera mobilis

Methylotenera species, unlike their close relatives in the genera Methylophilus, Methylobacillus, and Methylovorus, neither exhibit the activity of methanol dehydrogenase nor possess mxaFI genes encoding this enzyme, yet they are able to grow on methanol. In this work, we integrated a genome-wide proteomics approach, shotgun proteomics, and a genome-wide transcriptomics approach, shotgun transcriptome sequencing (RNA-seq), of Methylotenera mobilis JLW8 to identify genes and enzymes potentially involved in methanol oxidation, with special attention to alternative nitrogen sources, to address the question of whether nitrate could play a role as an electron acceptor in place of oxygen. Both proteomics and transcriptomics identified a limited number of genes and enzymes specifically responding to methanol. This set includes genes involved in oxidative stress response systems, a number of oxidoreductases, including XoxF-type alcohol dehydrogenases, a type II secretion system, and proteins without a predicted function. Nitrate stimulated expression of some genes in assimilatory nitrate reduction and denitrification pathways, while ammonium downregulated some of the nitrogen metabolism genes. However, none of these genes appeared to respond to methanol, which suggests that oxygen may be the main electron sink during growth on methanol. This study identifies initial targets for future focused physiological studies, including mutant analysis, which will provide further details into this novel process.

Evaluation of two commercial global miRNA expression profiling platforms for detection of less abundant miRNAs

Background

microRNAs (miRNA) are short, endogenous transcripts that negatively regulate the expression of specific mRNA targets. miRNAs are found both in tissues and body fluids such as plasma. A major perspective for the use of miRNAs in the clinical setting is as diagnostic plasma markers for neoplasia. While miRNAs are abundant in tissues, they are often scarce in plasma. For quantification of miRNA in plasma it is therefore of importance to use a platform with high sensitivity and linear performance in the low concentration range. This motivated us to evaluate the performance of three commonly used commercial miRNA quantification platforms: GeneChip miRNA 2.0 Array, miRCURY Ready-to-Use PCR, Human panel I+II V1.M, and TaqMan Human MicroRNA Array v3.0.

Results

Using synthetic miRNA samples and plasma RNA samples spiked with different ratios of 174 synthetic miRNAs we assessed the performance characteristics reproducibility, recovery, specificity, sensitivity and linearity. It was found that while the qRT-PCR based platforms were sufficiently sensitive to reproducibly detect miRNAs at the abundance levels found in human plasma, the array based platform was not. At high miRNA levels both qRT-PCR based platforms performed well in terms of specificity, reproducibility and recovery. At low miRNA levels, as in plasma, the miRCURY platform showed better sensitivity and linearity than the TaqMan platform.

Conclusion

For profiling clinical samples with low miRNA abundance, such as plasma samples, the miRCURY platform with its better sensitivity and linearity would probably be superior.

Genome-Wide Gene Expression Profiling of Nucleus Accumbens Neurons Projecting to Ventral Pallidum Using both Microarray and Transcriptome Sequencing

The cellular heterogeneity of brain poses a particularly thorny issue in genome-wide gene expression studies. Because laser capture microdissection (LCM) enables the precise extraction of a small area of tissue, we combined LCM with neuronal track tracing to collect nucleus accumbens shell neurons that project to ventral pallidum, which are of particular interest in the study of reward and addiction. Four independent biological samples of accumbens projection neurons were obtained. Approximately 500 pg of total RNA from each sample was then amplified linearly and subjected to Affymetrix microarray and Applied Biosystems sequencing by oligonucleotide ligation and detection (SOLiD) transcriptome sequencing (RNA-seq). A total of 375 million 50-bp reads were obtained from RNA-seq. Approximately 57% of these reads were mapped to the rat reference genome (Baylor 3.4/rn4). Approximately 11,000 unique RefSeq genes and 100,000 unique exons were identified from each sample. Of the unmapped reads, the quality scores were 4.74 ± 0.42 lower than the mapped reads. When RNA-seq and microarray data from the same samples were compared, Pearson correlations were between 0.764 and 0.798. The variances in data obtained for the four samples by microarray and RNA-seq were similar for medium to high abundance genes, but less among low abundance genes detected by microarray. Analysis of 34 genes by real-time polymerase chain reaction showed higher correlation with RNA-seq (0.66) than with microarray (0.46). Further analysis showed 20–30 million 50-bp reads are sufficient to provide estimates of gene expression levels comparable to those produced by microarray. In summary, this study showed that picogram quantities of total RNA obtained by LCM of ∼700 individual neurons is sufficient to take advantage of the benefits provided by the transcriptome sequencing technology, such as low background noise, high dynamic range, and high precision.

Green systems biology - From single genomes, proteomes and metabolomes to ecosystems research and biotechnology

Plants have shaped our human life form from the outset. With the emerging recognition of world population feeding, global climate change and limited energy resources with fossil fuels, the relevance of plant biology and biotechnology is becoming dramatically important. One key issue is to improve plant productivity and abiotic/biotic stress resistance in agriculture due to restricted land area and increasing environmental pressures. Another aspect is the development of CO(2)-neutral plant resources for fiber/biomass and biofuels: a transition from first generation plants like sugar cane, maize and other important nutritional crops to second and third generation energy crops such as Miscanthus and trees for lignocellulose and algae for biomass and feed, hydrogen and lipid production. At the same time we have to conserve and protect natural diversity and species richness as a foundation of our life on earth. Here, biodiversity banks are discussed as a foundation of current and future plant breeding research. Consequently, it can be anticipated that plant biology and ecology will have more indispensable future roles in all socio-economic aspects of our life than ever before. We therefore need an in-depth understanding of the physiology of single plant species for practical applications as well as the translation of this knowledge into complex natural as well as anthropogenic ecosystems. Latest developments in biological and bioanalytical research will lead into a paradigm shift towards trying to understand organisms at a systems level and in their ecosystemic context: (i) shotgun and next-generation genome sequencing, gene reconstruction and annotation, (ii) genome-scale molecular analysis using OMICS technologies and (iii) computer-assisted analysis, modeling and interpretation of biological data. Systems biology combines these molecular data, genetic evolution, environmental cues and species interaction with the understanding, modeling and prediction of active biochemical networks up to whole species populations. This process relies on the development of new technologies for the analysis of molecular data, especially genomics, metabolomics and proteomics data. The ambitious aim of these non-targeted 'omic' technologies is to extend our understanding beyond the analysis of separated parts of the system, in contrast to traditional reductionistic hypothesis-driven approaches. The consequent integration of genotyping, pheno/morphotyping and the analysis of the molecular phenotype using metabolomics, proteomics and transcriptomics will reveal a novel understanding of plant metabolism and its interaction with the environment. The analysis of single model systems - plants, fungi, animals and bacteria - will finally emerge in the analysis of populations of plants and other organisms and their adaptation to the ecological niche. In parallel, this novel understanding of ecophysiology will translate into knowledge-based approaches in crop plant biotechnology and marker- or genome-assisted breeding approaches. In this review the foundations of green systems biology are described and applications in ecosystems research are presented. Knowledge exchange of ecosystems research and green biotechnology merging into green systems biology is anticipated based on the principles of natural variation, biodiversity and the genotype-phenotype environment relationship as the fundamental drivers of ecology and evolution.

A hormone sends instant messages to the genome

Bridging a gap between transcriptomics and the study of cis-acting elements (cistromics), Hah et al. (2011) apply a next-generation sequencing technique to gain an unprecedented view of the changes in RNA synthesis that occur following estrogen receptor activation in human breast cancer cells.

Advances in bacterial transcriptome and transposon insertion-site profiling using second-generation sequencing

The arrival of second-generation sequencing has revolutionized the study of bacteria within a short period. The sequence information generated from these platforms has helped in our understanding of bacterial development, adaptation and diversity and how bacteria cause disease. Furthermore, these technologies have quickly been adapted for high-throughput studies that were previously performed using DNA cloning or microarray-based applications. This has facilitated a more comprehensive study of bacterial transcriptomes through RNA sequencing (RNA-Seq) and the systematic determination of gene function by 'transposon monitoring'. In this review, we provide an outline of these powerful tools and the in silico analyses used in their application, and also highlight the biological questions being addressed in these approaches.

Analysis of muscle and ovary transcriptome of Sus scrofa: assembly, annotation and marker discovery

Pig (Sus scrofa) is an important organism for both agricultural and medical purpose. This study aims to investigate the S. scrofa transcriptome by the use of Roche 454 pyrosequencing. We obtained a total of 558 743 and 528 260 reads for the back-leg muscle and ovary tissue each. The overall 1 087 003 reads give rise to 421 767 341 bp total residues averaging 388 bp per read. The de novo assemblies yielded 11 057 contigs and 60 270 singletons for the back-leg muscle, 12 204 contigs and 70 192 singletons for the ovary and 18 938 contigs and 102 361 singletons for combined tissues. The overall GC content of S. scrofa transcriptome is 42.3% for assembled contigs. Alternative splicing was found within 4394 contigs, giving rise to 1267 isogroups or genes. A total of 56 589 transcripts are involved in molecular function (40 916), biological process (38 563), cellular component (35 787) by further gene ontology analyses. Comparison analyses showed that 336 and 553 genes had significant higher expression in the back-leg muscle and ovary each. In addition, we obtained a total of 24 214 single-nucleotide polymorphisms and 11 928 simple sequence repeats. These results contribute to the understanding of the genetic makeup of S. scrofa transcriptome and provide useful information for functional genomic research in future.

Directional RNA deep sequencing sheds new light on the transcriptional response of Anabaena sp. strain PCC 7120 to combined-nitrogen deprivation

Background

Cyanobacteria are potential sources of renewable chemicals and biofuels and serve as model organisms for bacterial photosynthesis, nitrogen fixation, and responses to environmental changes. Anabaena (Nostoc) sp. strain PCC 7120 (hereafter Anabaena) is a multicellular filamentous cyanobacterium that can "fix" atmospheric nitrogen into ammonia when grown in the absence of a source of combined nitrogen. Because the nitrogenase enzyme is oxygen sensitive, Anabaena forms specialized cells called heterocysts that create a microoxic environment for nitrogen fixation. We have employed directional RNA-seq to map the Anabaena transcriptome during vegetative cell growth and in response to combined-nitrogen deprivation, which induces filaments to undergo heterocyst development. Our data provide an unprecedented view of transcriptional changes in Anabaena filaments during the induction of heterocyst development and transition to diazotrophic growth.

Results

Using the Illumina short read platform and a directional RNA-seq protocol, we obtained deep sequencing data for RNA extracted from filaments at 0, 6, 12, and 21 hours after the removal of combined nitrogen. The RNA-seq data provided information on transcript abundance and boundaries for the entire transcriptome. From these data, we detected novel antisense transcripts within the UTRs (untranslated regions) and coding regions of key genes involved in heterocyst development, suggesting that antisense RNAs may be important regulators of the nitrogen response. In addition, many 5' UTRs were longer than anticipated, sometimes extending into upstream open reading frames (ORFs), and operons often showed complex structure and regulation. Finally, many genes that had not been previously identified as being involved in heterocyst development showed regulation, providing new candidates for future studies in this model organism.

Conclusions

Directional RNA-seq data were obtained that provide comprehensive mapping of transcript boundaries and abundance for all transcribed RNAs in Anabaena filaments during the response to nitrogen deprivation. We have identified genes and noncoding RNAs that are transcriptionally regulated during heterocyst development. These data provide detailed information on the Anabaena transcriptome as filaments undergo heterocyst development and begin nitrogen fixation.

Genome-wide genetic marker discovery and genotyping using next-generation sequencing

The advent of next-generation sequencing (NGS) has revolutionized genomic and transcriptomic approaches to biology. These new sequencing tools are also valuable for the discovery, validation and assessment of genetic markers in populations. Here we review and discuss best practices for several NGS methods for genome-wide genetic marker development and genotyping that use restriction enzyme digestion of target genomes to reduce the complexity of the target. These new methods -- which include reduced-representation sequencing using reduced-representation libraries (RRLs) or complexity reduction of polymorphic sequences (CRoPS), restriction-site-associated DNA sequencing (RAD-seq) and low coverage genotyping -- are applicable to both model organisms with high-quality reference genome sequences and, excitingly, to non-model species with no existing genomic data.

Dark matter: are mice the solution to missing heritability?

Genome-wide association studies (GWAS) in humans have identified hundreds of single nucleotide polymorphisms associated with complex traits, yet for most traits studied, the sum total of all these identified variants fail to explain a significant portion of the heritable variation. Reasons for this “missing heritability” are thought to include the existence of rare causative variants not captured by current genotyping arrays, structural variants that go undetected by existing technology, insufficient power to identify multi-gene interactions, small sample sizes, and the influence of environmental and epigenetic effects. As genotyping technologies have evolved it has become inexpensive and relatively straightforward to perform GWAS in mice. Mice offer a powerful tool for elucidating the genetic architecture of behavioral and physiological traits, and are complementary to human studies. Unlike F₂ crosses of inbred strains, advanced intercross lines, heterogeneous stocks, outbred, and wild-caught mice have more rapid breakdown of linkage disequilibrium which allow for increasingly high resolution mapping. Because some of these populations are created using a small number of founder chromosomes they are not expected to harbor rare alleles. We discuss the differences between these mouse populations and examine their potential to overcome some of the pitfalls that have plagued human GWAS studies.

Characterisation of unclassified variants in the BRCA1/2 genes with a putative effect on splicing

A subset of the unclassified variants (UVs) identified during genetic screening of BRCA1/2 genes may affect splicing. We assessed at RNA level the effect of four BRCA1 and ten BRCA2 UVs with a putative splice effect, as predicted in silico. The variants selected for this study were beyond the positions -1, -2 or +1, +2 from the exon, and were not previously described (n = 8) or their effect on splicing was not assessed previously (n = 6). Lymphocytes from UV carriers and healthy controls were cultured and treated with puromycin to prevent nonsense-mediated mRNA decay. The relative contribution of each allele to the various transcripts was assessed using combinations of allele-specific and transcript-specific primers. BRCA2 c.425G>T, c.7976+3_7976+4del and c.8754+3G>C give rise to aberrant transcripts BRCA2Δ4, BRCA2Δ17 and retention of 46nt of intron 21, respectively, and were considered pathogenic. BRCA1 c.4987-3C>G gives rise to BRCA1Δ17 that is likely pathogenic; however, residual expression of the full-length transcript from the variant allele could not be excluded. BRCA1 c.692C>T, c.693G>A and BRCA2 c.6935A>T, besides expressing the full-length transcript, increased expression of BRCA1Δ11 and BRCA2Δ12, respectively. As these are naturally occurring isoforms, also observed in controls, the clinical relevance is unclear. The seven remaining UVs did not affect splicing and three intronic variants were therefore classified as neutral. In conclusion, the RNA analysis results clarified the clinical relevance of 6 of the 14 studied UVs and thereby greatly improve the genetic counselling of high-risk breast/ovarian cancer patients carrying these classified variants.

Looking ultra deep: short identical sequences and transcriptional slippage

Studying transcriptomes by ultra deep sequencing provides an in-depth picture of transcriptional regulation and it facilitates the detection of rare transcriptional events. Using ultra deep sequencing of amplicons we identified known isoforms and also various new low frequency variants. Most of these variants likely involve the splicing machinery except for two events that we named variations affecting multiple exons, which are mainly deletions affecting parts of adjacent exons and intra-exonic deletions. Both events involve short identical sequences of 1 to 8 nucleotides at the junction and canonical splice sites are missing. They were identified in different genes and species at very low frequencies. We excluded that they are an artifact of PCR, sequencing, or reverse transcription. We propose that these variants represent intramolecular slippage events that require short identical sequences for reannealing of dissociated transcripts.

High throughput nano-liter RT-qPCR to classify soil contamination using a soil arthropod

Background

To incorporate genomics data into environmental assessments a mechanistic perspective of interactions between chemicals and induced biological processes needs to be developed. Since chemical compounds with structural similarity often induce comparable biological responses in exposed animals, gene expression signatures can serve as a starting point for the assessment of chemicals and their toxicity, but only when relevant and stable gene panels are available. To design such a panel, we isolated differentially expressed gene fragments from the soil arthropod Folsomia candida, a species often used for ecotoxicological testing. Animals were exposed to two chemically distinct compounds, being a metal (cadmium) and a polycyclic aromatic hydrocarbon (phenanthrene). We investigated the affected molecular responses resulting from either treatment and developed and validated 44 qPCR assays for their responses using a high throughput nano-liter RT-qPCR platform for the analysis of the samples.

Results

Suppressive subtractive hybridization (SSH) was used to retrieve stress-related gene fragments. SSH libraries revealed pathways involved in mitochondrial dysfunction and protein degradation for cadmium and biotransformation for phenanthrene to be overrepresented. Amongst a small cluster of SSH-derived cadmium responsive markers were an inflammatory response protein and an endo-glucanase. Conversely, cytochrome P450 family 6 or 9 was specifically induced by phenanthrene. Differential expressions of these candidate biomarkers were also highly significant in the independently generated test sample set. Toxicity levels in different training samples were not reflected by any of the markers' intensity of expressions. Though, a model based on partial least squares differential analysis (PLS-DA) (with RMSEPs between 9 and 22% and R²s between 0.82 and 0.97) using gene expressions of 25 important qPCR assays correctly predicted the nature of exposures of test samples.

Conclusions

For the application of molecular bio-indication in environmental assessments, multivariate analyses obviously have an added value over univariate methods. Our results suggest that compound discrimination can be achieved by PLS-DA, based on a hard classification of the within-class rankings of samples from a test set. This study clearly shows that the use of high throughput RT-qPCR could be a valuable tool in ecotoxicology combining high throughput with analytical sensitivity.

Comparative Genomics in Perennial Ryegrass (Lolium perenne L.): Identification and Characterisation of an Orthologue for the Rice Plant Architecture-Controlling Gene OsABCG5

Perennial ryegrass is an important pasture grass in temperate regions. As a forage biomass-generating species, plant architecture-related characters provide key objectives for breeding improvement. In silico comparative genomics analysis predicted colocation between a previously identified QTL for plant type (erect versus prostrate growth) and the ortholocus of the rice OsABCG5 gene (LpABCG5), as well as related QTLs in other Poaceae species. Sequencing of an LpABCG5-containing BAC clone identified presence of a paralogue (LpABCG6) in the vicinity of the LpABCG5 locus, in addition to three other gene-like sequences. Comparative genomics involving five other 5 grass species (rice, Brachypodium, sorghum, maize, and foxtail millet) revealed conserved microsynteny in the ABCG5 ortholocus-flanking region. Gene expression profiling and phylogenetic analysis suggested that the two paralogues are functionally distinct. Fourteen additional ABCG5 gene family members, which may interact with the LpABCG5 gene, were identified through sequencing of transcriptomes from perennial ryegrass leaf, anther, and pistils. A larger-scale phylogenetic analysis of the ABCG gene family suggested conservation between major branches of the Poaceae family. This study identified the LpABCG5 gene as a candidate for the plant type determinant, suggesting that manipulation of gene expression may provide valuable phenotypes for perennial ryegrass breeding.