Matthew J. Wakefield

Gene ontology analysis for RNA-seq: accounting for selection bias

We present GOseq, an application for performing Gene Ontology (GO) analysis on RNA-seq data. GO analysis is widely used to reduce complexity and highlight biological processes in genome-wide expression studies, but standard methods give biased results on RNA-seq data due to over-detection of differential expression for long and highly expressed transcripts. Application of GOseq to a prostate cancer data set shows that GOseq dramatically changes the results, highlighting categories more consistent with the known biology.

PyEvolve: a toolkit for statistical modelling of molecular evolution.

BackgroundExamining the distribution of variation has proven an extremely profitable technique in the effort to identify sequences of biological significance. Most approaches in the field, however, evaluate only the conserved portions of sequences – ignoring the biological significance of sequence differences. A suite of sophisticated likelihood based statistical models from the field of molecular evolution provides the basis for extracting the information from the full distribution of sequence variation. The number of different problems to which phylogeny-based maximum likelihood calculations can be applied is extensive. Available software packages that can perform likelihood calculations suffer from a lack of flexibility and scalability, or employ error-prone approaches to model parameterisation.ResultsHere we describe the implementation of PyEvolve, a toolkit for the application of existing, and development of new, statistical methods for molecular evolution. We present the object architecture and design schema of PyEvolve, which includes an adaptable multi-level parallelisation schema. The approach for defining new methods is illustrated by implementing a novel dinucleotide model of substitution that includes a parameter for mutation of methylated CpGs, which required 8 lines of standard Python code to define. Benchmarking was performed using either a dinucleotide or codon substitution model applied to an alignment of BRCA1 sequences from 20 mammals, or a 10 species subset. Up to five-fold parallel performance gains over serial were recorded. Compared to leading alternative software, PyEvolve exhibited significantly better real world performance for parameter rich models with a large data set, reducing the time required for optimisation from ~10 days to ~6 hours.ConclusionPyEvolve provides flexible functionality that can be used either for statistical modelling of molecular evolution, or the development of new methods in the field. The toolkit can be used interactively or by writing and executing scripts. The toolkit uses efficient processes for specifying the parameterisation of statistical models, and implements numerous optimisations that make highly parameter rich likelihood functions solvable within hours on multi-cpu hardware. PyEvolve can be readily adapted in response to changing computational demands and hardware configurations to maximise performance. PyEvolve is released under the GPL and can be downloaded from http://cbis.anu.edu.au/software.

Transcript length bias in RNA-seq data confounds systems biology

BackgroundSeveral recent studies have demonstrated the effectiveness of deep sequencing for transcriptome analysis (RNA-seq) in mammals. As RNA-seq becomes more affordable, whole genome transcriptional profiling is likely to become the platform of choice for species with good genomic sequences. As yet, a rigorous analysis methodology has not been developed and we are still in the stages of exploring the features of the data.ResultsWe investigated the effect of transcript length bias in RNA-seq data using three different published data sets. For standard analyses using aggregated tag counts for each gene, the ability to call differentially expressed genes between samples is strongly associated with the length of the transcript.ConclusionTranscript length bias for calling differentially expressed genes is a general feature of current protocols for RNA-seq technology. This has implications for the ranking of differentially expressed genes, and in particular may introduce bias in gene set testing for pathway analysis and other multi-gene systems biology analyses.ReviewersThis article was reviewed by Rohan Williams (nominated by Gavin Huttley), Nicole Cloonan (nominated by Mark Ragan) and James Bullard (nominated by Sandrine Dudoit).

ChIP-seq analysis reveals distinct H3K27me3 profiles that correlate with transcriptional activity

Transcriptional control is dependent on a vast network of epigenetic modifications. One epigenetic mark of particular interest is tri-methylation of lysine 27 on histone H3 (H3K27me3), which is catalysed and maintained by Polycomb Repressive Complex 2 (PRC2). Although this histone mark is studied widely, the precise relationship between its local pattern of enrichment and regulation of gene expression is currently unclear. We have used ChIP-seq to generate genome-wide maps of H3K27me3 enrichment, and have identified three enrichment profiles with distinct regulatory consequences. First, a broad domain of H3K27me3 enrichment across the body of genes corresponds to the canonical view of H3K27me3 as inhibitory to transcription. Second, a peak of enrichment around the transcription start site (TSS) is commonly associated with ‘bivalent’ genes, where H3K4me3 also marks the TSS. Finally and most surprisingly, we identified an enrichment profile with a peak in the promoter of genes that is associated with active transcription. Genes with each of these three profiles were found in different proportions in each of the cell types studied. The data analysis techniques developed here will be useful for the identification of common enrichment profiles for other histone modifications that have important consequences for transcriptional regulation.

PyCogent: a toolkit for making sense from sequence

We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in generalized probabilistic techniques for working with biological sequences, and controllers for third-party applications. The toolkit takes advantage of parallel architectures and runs on a range of hardware and operating systems, and is available under the general public license from http://sourceforge.net/projects/pycogent.

Reconstructing an Ancestral Mammalian Immune Supercomplex from a Marsupial Major Histocompatibility Complex

The first sequenced marsupial genome promises to reveal unparalleled insights into mammalian evolution. We have used theMonodelphis domestica (gray short-tailed opossum) sequence to construct the first map of a marsupial major histocompatibility complex (MHC). The MHC is the most gene-dense region of the mammalian genome and is critical to immunity and reproductive success. The marsupial MHC bridges the phylogenetic gap between the complex MHC of eutherian mammals and the minimal essential MHC of birds. Here we show that the opossum MHC is gene dense and complex, as in humans, but shares more organizational features with non-mammals. The Class I genes have amplified within the Class II region, resulting in a unique Class I/II region. We present a model of the organization of the MHC in ancestral mammals and its elaboration during mammalian evolution. The opossum genome, together with other extant genomes, reveals the existence of an ancestral “immune supercomplex” that contained genes of both types of natural killer receptors together with antigen processing genes and MHC genes.

The region homologous to the X-chromosome inactivation centre has been disrupted in marsupial and monotreme mammals

SummaryMarsupial, as well as eutherian, mammals are subject to X chromosome inactivation in the somatic cells of females, although the phenotype and the molecular mechanism differ in important respects. Monotreme mammals appear to subscribe at least to a form of dosage compensation of X-borne genes. An important question is whether inactivation in these non-eutherian mammals involves co-ordination by a control locus homologous to the XIST gene and neighbouring genes, which play a key regulatory role in human and mouse X inactivation. We mapped BACs containing several orthologues of protein-coding genes that flank human and mouse XIST and genes that lie in the homologous region in chicken and frog. We found that these genes map to two distant locations on the opossum X, and also to different locations on a platypus autosome. We failed to find any trace of an XIST orthologue in any marsupial or monotreme or on any flanking BAC, confirming the conclusion from recent work that non-eutherian mammals lack XIST. We propose the region homologous to the human and mouse X-inactivation centre expanded in early mammals, and this unstable region was disrupted independently in marsupial and monotreme lineages. In the eutherian lineage, inserted and existing sequences provided the starting material for the non-translated RNAs of the X-inactivation centre, including XIST.

Molecular correlates of platinum response in human high-grade serous ovarian cancer patient-derived xenografts

Improvement in the ability to target underlying drivers and vulnerabilities of high‐grade serous ovarian cancer (HG‐SOC) requires the development of molecularly annotated pre‐clinical models reflective of clinical responses.

Smchd1 regulates a subset of autosomal genes subject to monoallelic expression in addition to being critical for X inactivation

BackgroundSmchd1 is an epigenetic modifier essential for X chromosome inactivation: female embryos lacking Smchd1 fail during midgestational development. Male mice are less affected by Smchd1-loss, with some (but not all) surviving to become fertile adults on the FVB/n genetic background. On other genetic backgrounds, all males lacking Smchd1 die perinatally. This suggests that, in addition to being critical for X inactivation, Smchd1 functions to control the expression of essential autosomal genes.ResultsUsing genome-wide microarray expression profiling and RNA-seq, we have identified additional genes that fail X inactivation in female Smchd1 mutants and have identified autosomal genes in male mice where the normal expression pattern depends upon Smchd1. A subset of genes in the Snrpn imprinted gene cluster show an epigenetic signature and biallelic expression consistent with loss of imprinting in the absence of Smchd1. In addition, single nucleotide polymorphism analysis of expressed genes in the placenta shows that the Igf2r imprinted gene cluster is also disrupted, with Slc22a3 showing biallelic expression in the absence of Smchd1. In both cases, the disruption was not due to loss of the differential methylation that marks the imprint control region, but affected genes remote from this primary imprint controlling element. The clustered protocadherins (Pcdhα, Pcdhβ, and Pcdhγ) also show altered expression levels, suggesting that their unique pattern of random combinatorial monoallelic expression might also be disrupted.ConclusionsSmchd1 has a role in the expression of several autosomal gene clusters that are subject to monoallelic expression, rather than being restricted to functioning uniquely in X inactivation. Our findings, combined with the recent report implicating heterozygous mutations of SMCHD1 as a causal factor in the digenically inherited muscular weakness syndrome facioscapulohumeral muscular dystrophy-2, highlight the potential importance of Smchd1 in the etiology of diverse human diseases.

RegA, an AraC-Like Protein, Is a Global Transcriptional Regulator That Controls Virulence Gene Expression in Citrobacter rodentium

ABSTRACT Citrobacter rodentium is an attaching and effacing pathogen which causes transmissible colonic hyperplasia in mice. Infection with C. rodentium serves as a model for infection of humans with enteropathogenic and enterohemorrhagic Escherichia coli. To identify novel colonization factors of C. rodentium, we screened a signature-tagged mutant library of C. rodentium in mice. One noncolonizing mutant had a single transposon insertion in an open reading frame (ORF) which we designated regA because of its homology to genes encoding members of the AraC family of transcriptional regulators. Deletion of regA in C. rodentium resulted in markedly reduced colonization of the mouse intestine. Examination of lacZ transcriptional fusions using promoter regions of known and putative virulence-associated genes of C. rodentium revealed that RegA strongly stimulated transcription of two newly identified genes located close to regA, which we designated adcA and kfcC. The cloned adcA gene conferred autoaggregation and adherence to mammalian cells to E. coli strain DH5α, and a kfc mutation led to a reduction in the duration of intestinal colonization, but the kfc mutant was far less attenuated than the regA mutant. These results indicated that other genes of C. rodentium whose expression required activation by RegA were required for colonization. Microarray analysis revealed a number of RegA-regulated ORFs encoding proteins homologous to known colonization factors. Transcription of these putative virulence determinants was activated by RegA only in the presence of sodium bicarbonate. Taken together, these results show that RegA is a global regulator of virulence in C. rodentium which activates factors that are required for intestinal colonization.