RiboTagger: fast and unbiased 16S/18S profiling using whole community shotgun metagenomic or metatranscriptome surveys.

BACKGROUND: Taxonomic profiling of microbial communities is often performed using small subunit ribosomal RNA (SSU) amplicon sequencing (16S or 18S), while environmental shotgun sequencing is often focused on functional analysis. Large shotgun datasets contain a significant number of SSU sequences and these can be exploited to perform an unbiased SSU--based taxonomic analysis. RESULTS: Here we present a new program called RiboTagger that identifies and extracts taxonomically informative ribotags located in a specified variable region of the SSU gene in a high-throughput fashion. CONCLUSIONS: RiboTagger permits fast recovery of SSU-RNA sequences from shotgun nucleic acid surveys of complex microbial communities. The program targets all three domains of life, exhibits high sensitivity and specificity and is substantially faster than comparable programs.

Inter-individual variation in expression: a missing link in biomarker biology?

The past decade has seen an explosion of variation data demonstrating that diversity of both protein-coding sequences and of regulatory elements of protein-coding genes is common and of functional importance. In this article, we argue that genetic diversity can no longer be ignored in studies of human biology, even research projects without explicit genetic experimental design, and that this knowledge can, and must, inform research. By way of illustration, we focus on the potential role of genetic data in case-control studies to identify and validate cancer protein biomarkers. We argue that a consideration of genetics, in conjunction with proteomic biomarker discovery projects, should improve the proportion of biomarkers that can accurately classify patients.

Intra- and inter-individual genetic differences in gene expression.

Genetic variation is known to influence the amount of mRNA produced by a gene. Because molecular machines control mRNA levels of multiple genes, we expect genetic variation in components of these machines would influence multiple genes in a similar fashion. We show that this assumption is correct by using correlation of mRNA levels measured from multiple tissues in mouse strain panels to detect shared genetic influences. These correlating groups of genes (CGGs) have collective properties that on average account for 52-79% of the variability of their constituent genes and can contain genes that encode functionally related proteins. We show that the genetic influences are essentially tissue-specific and, consequently, the same genetic variations in one animal may upregulate a CGG in one tissue but downregulate the CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. Thus, this class of genetic variation can result in complex inter- and intraindividual differences. This will create substantial challenges in humans, where multiple tissues are not readily available.

Primer-free FISH probes from metagenomics/metatranscriptomics data permit the study of uncharacterised taxa in complex microbial communities.

Methods for the study of member species in complex microbial communities remain a high priority, particularly for rare and/or novel member species that might play an important ecological role. Specifically, methods that link genomic information of member species with its spatial structure are lacking. This study adopts an integrative workflow that permits the characterisation of previously unclassified bacterial taxa from microbiomes through: (1) imaging of the spatial structure; (2) taxonomic classification and (3) genome recovery. Our study attempts to bridge the gaps between metagenomics/metatranscriptomics and high-resolution biomass imaging methods by developing new fluorescence in situ hybridisation (FISH) probes-termed as R-Probes-from shotgun reads that harbour hypervariable regions of the 16S rRNA gene. The sample-centric design of R-Probes means that probes can directly hybridise to OTUs as detected in shotgun sequencing surveys. The primer-free probe design captures larger microbial diversity as compared to canonical probes. R-Probes were designed from deep-sequenced RNA-Seq datasets for both FISH imaging and FISH-Fluorescence activated cell sorting (FISH-FACS). FISH-FACS was used for target enrichment of previously unclassified bacterial taxa prior to downstream multiple displacement amplification (MDA), genomic sequencing and genome recovery. After validation of the workflow on an axenic isolate of Thauera species, the techniques were applied to investigate two previously uncharacterised taxa from a tropical full-scale activated sludge community. In some instances, probe design on the hypervariable region allowed differentiation to the species level. Collectively, the workflow can be readily applied to microbiomes for which shotgun nucleic acid survey data is available.

The influence of genetic variation on gene expression.

The view that changes to the control of gene expression rather than alterations to protein sequence are central to the evolution of organisms has become something of a truism in molecular biology. In reality, the direct evidence for this is limited, and only recently have we had the ability to look more globally at how genetic variation influences gene expression, focusing upon inter-individual variation in gene expression and using microarrays to test for differences in mRNA levels. Here, we review the scope of these experimental analyses, what they are designed to tell us about genetic variation, and what are their limitations from both a technical and a conceptual viewpoint. We conclude that while we are starting to understand the impact of this class of genetic variation upon steady-state mRNA levels, we are still far from identifying the potential phenotypic and evolutionary outcomes.

Genetic dissection of gene regulation in multiple mouse tissues.

The analysis of the influence of genetic variation on regulation of gene expression at a near-genome-wide level has become the focus of much recent interest. It is widely appreciated that many genes are expressed in a tissue-specific manner and that others are more ubiquitously expressed but relatively little is known about how genetic variation might influence these tissue patterns of gene expression. In this review we discuss what is known about the tissue specificity of the influence of genetic variation and review the challenges that we face in combining hugely parallel, microarray-based gene analysis with equally expensive genetic analysis. We conclude that the available data suggest that genetic variation is essentially tissue specific in its effects upon gene expression and this has important implications for experimental analysis.

Structure and function of the human genome.

The human genome project has had an impact on both biological research and its political organization; this review focuses primarily on the scientific novelty that has emerged from the project but also touches on its political dimensions. The project has generated both anticipated and novel information; in the later category are the description of the unusual distribution of genes, the prevalence of non-protein-coding genes, and the extraordinary evolutionary conservation of some regions of the genome. The applications of the sequence data are just starting to be felt in basic, rather than therapeutic, biomedical research and in the vibrant human origins and variation debates. The political impact of the project is in the unprecedented extent to which directed funding programs have emerged as drivers of basic research and the organization of the multidisciplinary groups that are needed to utilize the human DNA sequence.