DNA methylation and histone H3 lysine 9 trimethylation (H3K9me3) play important roles in silencing of genes and retroelements. However, a comprehensive comparison of genes and repetitive elements repressed by these pathways has not been reported. Here we show that in mouse embryonic stem cells (mESCs), the genes up-regulated following deletion of the H3K9 methyltransferase Setdb1 are distinct from those de-repressed in mESC deficient in the DNA methyltransferases Dnmt1, Dnmt3a and Dnmt3b, with the exception of a small number of primarily germline-specific genes. Numerous endogenous retroviruses (ERVs) lose H3K9me3 and are concomitantly de-repressed exclusively in SETDB1 knockout mESCs. Strikingly, ~15% of up-regulated genes are induced in association with de-repression of promoter proximal ERVs, half in the context of “chimaeric” transcripts that initiate within these retroelements and splice to genic exons. Thus, SETDB1 plays a previously unappreciated yet critical role in inhibiting aberrant gene transcription by suppressing the expression of proximal ERVs.
PMID: 21624812 CAMSID: cams3765
Next-generation sequencing is making sequence-based molecular pathology and personalized oncology viable. We selected an individual initially diagnosed with conventional but aggressive prostate adenocarcinoma and sequenced the genome and transcriptome from primary and metastatic tissues collected prior to hormone therapy. The histology-pathology and copy number profiles were remarkably homogeneous, yet it was possible to propose the quadrant of the prostate tumour that likely seeded the metastatic diaspora. Despite a homogeneous cell type, our transcriptome analysis revealed signatures of both luminal and neuroendocrine cell types. Remarkably, the repertoire of expressed but apparently private gene fusions, including C15orf21:MYC, recapitulated this biology. We hypothesize that the amplification and over-expression of the stem cell gene MSI2 may have contributed to the stable hybrid cellular identity. This hybrid luminal-neuroendocrine tumour appears to represent a novel and highly aggressive case of prostate cancer with unique biological features and, conceivably, a propensity for rapid progression to castrate-resistance. Overall, this work highlights the importance of integrated analyses of genome, exome and transcriptome sequences for basic tumour biology, sequence-based molecular pathology and personalized oncology.
RNA sequencing; DNA sequencing; prostate cancer; fusion genes; neuroendocrine; personalized medicine; cancer genetics
Neuroblastoma is a malignancy of the developing sympathetic nervous system that often presents with widespread metastatic disease, resulting in survival rates of less than 50%1. To determine the spectrum of somatic mutation in high-risk neuroblastoma, we studied 240 cases using a combination of whole exome, genome and transcriptome sequencing as part of the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiative. Here we report a low median exonic mutation frequency of 0.60 per megabase (0.48 non-silent), and remarkably few recurrently mutated genes in these tumors. Genes with significant somatic mutation frequencies included ALK (9.2% of cases), PTPN11 (2.9%), ATRX (2.5%, an additional 7.1% had focal deletions), MYCN (1.7%, a recurrent p.Pro44Leu alteration), and NRAS (0.83%). Rare, potentially pathogenic germline variants were significantly enriched in ALK, CHEK2, PINK1, and BARD1. The relative paucity of recurrent somatic mutations in neuroblastoma challenges current therapeutic strategies reliant upon frequently altered oncogenic drivers.
Genomic profiling has identified a subtype of high-risk B-progenitor acute lymphoblastic leukemia (B-ALL) with alteration of IKZF1, a gene expression profile similar to BCR-ABL1-positive ALL and poor outcome (Ph-like ALL). The genetic alterations that activate kinase signaling in Ph-like ALL are poorly understood. We performed transcriptome and whole genome sequencing on 15 cases of Ph-like ALL, and identified rearrangements involving ABL1, JAK2, PDGFRB, CRLF2 and EPOR, activating mutations of IL7R and FLT3, and deletion of SH2B3, which encodes the JAK2 negative regulator LNK. Importantly, several of these alterations induce transformation that is attenuated with tyrosine kinase inhibitors, suggesting the treatment outcome of these patients may be improved with targeted therapy.
Castrate resistant prostate cancer (CRPC) and neuroendocrine carcinoma of the prostate are invariably fatal diseases for which only palliative therapies exist. As part of a prostate tumour sequencing program, a patient tumour was analyzed using Illumina genome sequencing and a matched renal capsule tumour xenograft was generated. Both tumour and xenograft had a homozygous 9p21 deletion spanning the MTAP, CDKN2 and ARF genes. It is rare for this deletion to occur in primary prostate tumours yet approximately 10% express decreased levels of MTAP mRNA. Decreased MTAP expression is a prognosticator for poor outcome. Moreover, it appears that this deletion is more common in CRPC than in primary prostate cancer. We show for the first time that treatment with methylthioadenosine and high dose 6-thioguanine causes marked inhibition of a patient derived neuroendocrine xenograft growth while protecting the host from 6-thioguanine toxicity. This therapeutic approach can be applied to other MTAP-deficient human cancers since deletion or hypermethylation of the MTAP gene occurs in a broad spectrum of tumours at high frequency. The combination of genome sequencing and patient-derived xenografts can identify candidate therapeutic agents and evaluate them for personalized oncology.
massively parallel sequencing; MTAP; patient-derived xenograft; genitourinary cancers: prostate; animal models of cancer; gene expression profiling; functional genomics; xenograft models
DNA rearrangements such as sister chromatid exchanges (SCEs) are sensitive indicators of genomic stress and instability, but they are typically masked by single-cell sequencing techniques. We developed Strand-seq to independently sequence parental DNA template strands from single cells, making it possible to map SCEs at orders-of-magnitude greater resolution than was previously possible. On average, murine embryonic stem (mES) cells exhibit eight SCEs, which are detected at a resolution of up to 23 bp. Strikingly, Strand-seq of 62 single mES cells predicts that the mm9 mouse reference genome assembly contains at least 17 incorrectly oriented segments totaling nearly 1% of the genome. These misoriented contigs and fragments have persisted through several iterations of the mouse reference genome and have been difficult to detect using conventional sequencing techniques. The ability to map SCE events at high resolution and fine-tune reference genomes by Strand-seq dramatically expands the scope of single-cell sequencing.
Oligodendroglioma is characterized by unique clinical, pathological, and genetic features. Recurrent losses of chromosomes 1p and 19q are strongly associated with this brain cancer but knowledge of the identity and function of the genes affected by these alterations is limited. We performed exome sequencing on a discovery set of 16 oligodendrogliomas with 1p/19q co-deletion to identify new molecular features at base-pair resolution. As anticipated, there was a high rate of IDH mutations: all cases had mutations in either IDH1 (14/16) or IDH2 (2/16). In addition, we discovered somatic mutations and insertions/deletions in the CIC gene on chromosome 19q13.2 in 13/16 tumours. These discovery set mutations were validated by deep sequencing of 13 additional tumours, which revealed 7 others with CIC mutations, thus bringing the overall mutation rate in oligodendrogliomas in this study to 20/29 (69%). In contrast, deep sequencing of astrocytomas and oligoastrocytomas without 1p/19q loss revealed that CIC alterations were otherwise rare (1/60; 2%). Of the 21 non-synonymous somatic mutations in 20 CIC-mutant oligodendrogliomas, 9 were in exon 5 within an annotated DNA interacting domain and 3 were in exon 20 within an annotated protein interacting domain. The remaining 9 were found in other exons and frequently included truncations. CIC mutations were highly associated with oligodendroglioma histology, 1p/19q co-deletion and IDH1/2 mutation (p<0.001). Although we observed no differences in the clinical outcomes of CIC mutant versus wild-type tumors, in a background of 1p/19q co-deletion, hemizygous CIC mutations are likely important. We hypothesize that the mutant CIC on the single retained 19q allele is linked to the pathogenesis of oligodendrogliomas with IDH mutation. Our detailed study of genetic aberrations in oligodendroglioma suggests a functional interaction between CIC mutation, IDH1/2 mutation and 1p/19q co-deletion.
Glioma; Oligodendroglioma; Next Generation Sequencing; Capicua; IDH1
Next generation sequencing has now enabled a cost-effective enumeration of the full mutational complement of a tumor genome—in particular single nucleotide variants (SNVs). Most current computational and statistical models for analyzing next generation sequencing data, however, do not account for cancer-specific biological properties, including somatic segmental copy number alterations (CNAs)—which require special treatment of the data. Here we present CoNAn-SNV (Copy Number Annotated SNV): a novel algorithm for the inference of single nucleotide variants (SNVs) that overlap copy number alterations. The method is based on modelling the notion that genomic regions of segmental duplication and amplification induce an extended genotype space where a subset of genotypes will exhibit heavily skewed allelic distributions in SNVs (and therefore render them undetectable by methods that assume diploidy). We introduce the concept of modelling allelic counts from sequencing data using a panel of Binomial mixture models where the number of mixtures for a given locus in the genome is informed by a discrete copy number state given as input. We applied CoNAn-SNV to a previously published whole genome shotgun data set obtained from a lobular breast cancer and show that it is able to discover 21 experimentally revalidated somatic non-synonymous mutations in a lobular breast cancer genome that were not detected using copy number insensitive SNV detection algorithms. Importantly, ROC analysis shows that the increased sensitivity of CoNAn-SNV does not result in disproportionate loss of specificity. This was also supported by analysis of a recently published lymphoma genome with a relatively quiescent karyotype, where CoNAn-SNV showed similar results to other callers except in regions of copy number gain where increased sensitivity was conferred. Our results indicate that in genomically unstable tumors, copy number annotation for SNV detection will be critical to fully characterize the mutational landscape of cancer genomes.
Motivation: Identification of somatic single nucleotide variants (SNVs) in tumour genomes is a necessary step in defining the mutational landscapes of cancers. Experimental designs for genome-wide ascertainment of somatic mutations now routinely include next-generation sequencing (NGS) of tumour DNA and matched constitutional DNA from the same individual. This allows investigators to control for germline polymorphisms and distinguish somatic mutations that are unique to the tumour, thus reducing the burden of labour-intensive and expensive downstream experiments needed to verify initial predictions. In order to make full use of such paired datasets, computational tools for simultaneous analysis of tumour–normal paired sequence data are required, but are currently under-developed and under-represented in the bioinformatics literature.
Results: In this contribution, we introduce two novel probabilistic graphical models called JointSNVMix1 and JointSNVMix2 for jointly analysing paired tumour–normal digital allelic count data from NGS experiments. In contrast to independent analysis of the tumour and normal data, our method allows statistical strength to be borrowed across the samples and therefore amplifies the statistical power to identify and distinguish both germline and somatic events in a unified probabilistic framework.
Availability: The JointSNVMix models and four other models discussed in the article are part of the JointSNVMix software package available for download at http://compbio.bccrc.ca
Supplementary information:Supplementary data are available at Bioinformatics online.
Next generation sequencing has brought epigenomic studies to the forefront of current research. The power of massively parallel sequencing coupled to innovative molecular and computational techniques has allowed researchers to profile the epigenome at resolutions that were unimaginable only a few years ago. With early proof of concept studies published, the field is now moving into the next phase where the importance of method standardization and rigorous quality control are becoming paramount. In this review we will describe methodologies that have been developed to profile the epigenome using next generation sequencing platforms. We will discuss these in terms of library preparation, sequence platforms and analysis techniques.
epigenomics; next generation sequencing
Motivation: The study of cancer genomes now routinely involves using next-generation sequencing technology (NGS) to profile tumours for single nucleotide variant (SNV) somatic mutations. However, surprisingly few published bioinformatics methods exist for the specific purpose of identifying somatic mutations from NGS data and existing tools are often inaccurate, yielding intolerably high false prediction rates. As such, the computational problem of accurately inferring somatic mutations from paired tumour/normal NGS data remains an unsolved challenge.
Results: We present the comparison of four standard supervised machine learning algorithms for the purpose of somatic SNV prediction in tumour/normal NGS experiments. To evaluate these approaches (random forest, Bayesian additive regression tree, support vector machine and logistic regression), we constructed 106 features representing 3369 candidate somatic SNVs from 48 breast cancer genomes, originally predicted with naive methods and subsequently revalidated to establish ground truth labels. We trained the classifiers on this data (consisting of 1015 true somatic mutations and 2354 non-somatic mutation positions) and conducted a rigorous evaluation of these methods using a cross-validation framework and hold-out test NGS data from both exome capture and whole genome shotgun platforms. All learning algorithms employing predictive discriminative approaches with feature selection improved the predictive accuracy over standard approaches by statistically significant margins. In addition, using unsupervised clustering of the ground truth ‘false positive’ predictions, we noted several distinct classes and present evidence suggesting non-overlapping sources of technical artefacts illuminating important directions for future study.
Availability: Software called MutationSeq and datasets are available from http://compbio.bccrc.ca.
Supplementary information: Supplementary data are available at Bioinformatics online.
The “arms race” relationship between transposable elements (TEs) and their host has promoted a series of epigenetic silencing mechanisms directed against TEs. Retrotransposons, a class of TEs, are often located in repressed regions and are thought to induce heterochromatin formation and spreading. However, direct evidence for TE–induced local heterochromatin in mammals is surprisingly scarce. To examine this phenomenon, we chose two mouse embryonic stem (ES) cell lines that possess insertionally polymorphic retrotransposons (IAP, ETn/MusD, and LINE elements) at specific loci in one cell line but not the other. Employing ChIP-seq data for these cell lines, we show that IAP elements robustly induce H3K9me3 and H4K20me3 marks in flanking genomic DNA. In contrast, such heterochromatin is not induced by LINE copies and only by a minority of polymorphic ETn/MusD copies. DNA methylation is independent of the presence of IAP copies, since it is present in flanking regions of both full and empty sites. Finally, such spreading into genes appears to be rare, since the transcriptional start sites of very few genes are less than one Kb from an IAP. However, the B3galtl gene is subject to transcriptional silencing via IAP-induced heterochromatin. Hence, although rare, IAP-induced local heterochromatin spreading into nearby genes may influence expression and, in turn, host fitness.
Transposable elements (TEs) are often thought to be harmful because of their potential to spread heterochromatin (repressive chromatin) into nearby sequences. However, there are few examples of spreading of heterochromatin caused by TEs, even though they are often found within repressive chromatin. We exploited natural variation in TE integrations to study heterochromatin induction. Specifically, we compared chromatin states of two mouse embryonic stem cell lines harboring polymorphic retrotransposons of three families, such that one line possesses a particular TE copy (full site) while the other does not (empty site). Nearly all IAP copies, a family of retroviral-like elements, are able to strongly induce repressive chromatin surrounding their insertion sites, with repressive histone modifications extending at least one kb from the IAP. This heterochromatin induction was not observed for the LINE family of non-viral retrotransposons and for only a minority of copies of the ETn/MusD retroviral-like family. We found only one gene that was partly silenced by IAP-induced chromatin. Therefore, while induction of repressive chromatin occurs after IAP insertion, measurable impacts on host gene expression are rare. Nonetheless, this phenomenon may play a role in rapid change in gene expression and therefore in host adaptive potential.
Gene fusions created by somatic genomic rearrangements are known to play an important role in the onset and development of some cancers, such as lymphomas and sarcomas. RNA-Seq (whole transcriptome shotgun sequencing) is proving to be a useful tool for the discovery of novel gene fusions in cancer transcriptomes. However, algorithmic methods for the discovery of gene fusions using RNA-Seq data remain underdeveloped. We have developed deFuse, a novel computational method for fusion discovery in tumor RNA-Seq data. Unlike existing methods that use only unique best-hit alignments and consider only fusion boundaries at the ends of known exons, deFuse considers all alignments and all possible locations for fusion boundaries. As a result, deFuse is able to identify fusion sequences with demonstrably better sensitivity than previous approaches. To increase the specificity of our approach, we curated a list of 60 true positive and 61 true negative fusion sequences (as confirmed by RT-PCR), and have trained an adaboost classifier on 11 novel features of the sequence data. The resulting classifier has an estimated value of 0.91 for the area under the ROC curve. We have used deFuse to discover gene fusions in 40 ovarian tumor samples, one ovarian cancer cell line, and three sarcoma samples. We report herein the first gene fusions discovered in ovarian cancer. We conclude that gene fusions are not infrequent events in ovarian cancer and that these events have the potential to substantially alter the expression patterns of the genes involved; gene fusions should therefore be considered in efforts to comprehensively characterize the mutational profiles of ovarian cancer transcriptomes.
Genome rearrangements and associated gene fusions are known to be important oncogenic events in some cancers. We have developed a novel computational method called deFuse for detecting gene fusions in RNA-Seq data and have applied it to the discovery of novel gene fusions in sarcoma and ovarian tumors. We assessed the accuracy of our method and found that deFuse produces substantially better sensitivity and specificity than two other published methods. We have also developed a set of 60 positive and 61 negative examples that will be useful for accurate identification of gene fusions in future RNA-Seq datasets. We have trained a classifier on 11 novel features of the 121 examples, and show that the classifier is able to accurately identify real gene fusions. The 45 gene fusions reported in this study represent the first ovarian cancer fusions reported, as well as novel sarcoma fusions. By examining the expression patterns of the affected genes, we find that many fusions are predicted to have functional consequences and thus merit experimental followup to determine their clinical relevance.
Ovarian clear-cell and endometrioid carcinomas may arise from endometriosis, but the molecular events involved in this transformation have not been described.
We sequenced the whole transcriptomes of 18 ovarian clear-cell carcinomas and 1 ovarian clear-cell carcinoma cell line and found somatic mutations in ARID1A (the AT-rich interactive domain 1A [SWI-like] gene) in 6 of the samples. ARID1A encodes BAF250a, a key component of the SWI–SNF chromatin remodeling complex. We sequenced ARID1A in an additional 210 ovarian carcinomas and a second ovarian clear-cell carcinoma cell line and measured BAF250a expression by means of immunohistochemical analysis in an additional 455 ovarian carcinomas.
ARID1A mutations were seen in 55 of 119 ovarian clear-cell carcinomas (46%), 10 of 33 endometrioid carcinomas (30%), and none of the 76 high-grade serous ovarian carcinomas. Seventeen carcinomas had two somatic mutations each. Loss of the BAF250a protein correlated strongly with the ovarian clear-cell carcinoma and endometrioid carcinoma subtypes and the presence of ARID1A mutations. In two patients, ARID1A mutations and loss of BAF250a expression were evident in the tumor and contiguous atypical endometriosis but not in distant endometriotic lesions.
These data implicate ARID1A as a tumor-suppressor gene frequently disrupted in ovarian clear-cell and endometrioid carcinomas. Since ARID1A mutation and loss of BAF250a can be seen in the preneoplastic lesions, we speculate that this is an early event in the transformation of endometriosis into cancer. (Funded by the British Columbia Cancer Foundation and the Vancouver General Hospital–University of British Columbia Hospital Foundation.)
Sequencing-based DNA methylation profiling methods are comprehensive and, as accuracy and affordability improve, will increasingly supplant microarrays for genome-scale analyses. Here, four sequencing-based methodologies were applied to biological replicates of human embryonic stem cells to compare their CpG coverage genome-wide and in transposons, resolution, cost, concordance and its relationship with CpG density and genomic context. The two bisulfite methods reached concordance of 82% for CpG methylation levels and 99% for non-CpG cytosine methylation levels. Using binary methylation calls, two enrichment methods were 99% concordant, while regions assessed by all four methods were 97% concordant. To achieve comprehensive methylome coverage while reducing cost, an approach integrating two complementary methods was examined. The integrative methylome profile along with histone methylation, RNA, and SNP profiles derived from the sequence reads allowed genome-wide assessment of allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression.
DNA methylation; Sequencing; Bisulfite
The H3K9me3 histone modification is often found at promoter regions, where it functions to repress transcription. However, we have previously shown that 3′ exons of zinc finger genes (ZNFs) are marked by high levels of H3K9me3. We have now further investigated this unusual location for H3K9me3 in ZNF genes. Neither bioinformatic nor experimental approaches support the hypothesis that the 3′ exons of ZNFs are promoters. We further characterized the histone modifications at the 3′ ZNF exons and found that these regions also contain H3K36me3, a mark of transcriptional elongation. A genome-wide analysis of ChIP-seq data revealed that ZNFs constitute the majority of genes that have high levels of both H3K9me3 and H3K36me3. These results suggested the possibility that the ZNF genes may be imprinted, with one allele transcribed and one allele repressed. To test the hypothesis that the contradictory modifications are due to imprinting, we used a SNP analysis of RNA-seq data to demonstrate that both alleles of certain ZNF genes having H3K9me3 and H3K36me3 are transcribed. We next analyzed isolated ZNF 3′ exons using stably integrated episomes. We found that although the H3K36me3 mark was lost when the 3′ ZNF exon was removed from its natural genomic location, the isolated ZNF 3′ exons retained the H3K9me3 mark. Thus, the H3K9me3 mark at ZNF 3′ exons does not impede transcription and it is regulated independently of the H3K36me3 mark. Finally, we demonstrate a strong relationship between the number of tandemly repeated domains in the 3′ exons and the H3K9me3 mark. We suggest that the H3K9me3 at ZNF 3′ exons may function to protect the genome from inappropriate recombination rather than to regulate transcription.
B cell lymphoma 6 (BCL6), which encodes a transcriptional repressor, is a critical oncogene in diffuse large B cell lymphomas (DLBCLs). Although a retro-inverted BCL6 peptide inhibitor (RI-BPI) was recently shown to potently kill DLBCL cells, the underlying mechanisms remain unclear. Here, we show that RI-BPI induces a particular gene expression signature in human DLBCL cell lines that included genes associated with the actions of histone deacetylase (HDAC) and Hsp90 inhibitors. BCL6 directly repressed the expression of p300 lysine acetyltransferase (EP300) and its cofactor HLA-B–associated transcript 3 (BAT3). RI-BPI induced expression of p300 and BAT3, resulting in acetylation of p300 targets including p53 and Hsp90. Induction of p300 and BAT3 was required for the antilymphoma effects of RI-BPI, since specific blockade of either protein rescued human DLBCL cell lines from the BCL6 inhibitor. Consistent with this, combination of RI-BPI with either an HDAC inhibitor (HDI) or an Hsp90 inhibitor potently suppressed or even eradicated established human DLBCL xenografts in mice. Furthermore, HDAC and Hsp90 inhibitors independently enhanced RI-BPI killing of primary human DLBCL cells in vitro. We also show that p300-inactivating mutations occur naturally in human DLBCL patients and may confer resistance to BCL6 inhibitors. Thus, BCL6 repression of EP300 provides a basis for rational targeted combinatorial therapy for patients with DLBCL.
Adenocarcinomas of the tongue are rare and represent the minority (20 to 25%) of salivary gland tumors affecting the tongue. We investigated the utility of massively parallel sequencing to characterize an adenocarcinoma of the tongue, before and after treatment.
In the pre-treatment tumor we identified 7,629 genes within regions of copy number gain. There were 1,078 genes that exhibited increased expression relative to the blood and unrelated tumors and four genes contained somatic protein-coding mutations. Our analysis suggested the tumor cells were driven by the RET oncogene. Genes whose protein products are targeted by the RET inhibitors sunitinib and sorafenib correlated with being amplified and or highly expressed. Consistent with our observations, administration of sunitinib was associated with stable disease lasting 4 months, after which the lung lesions began to grow. Administration of sorafenib and sulindac provided disease stabilization for an additional 3 months after which the cancer progressed and new lesions appeared. A recurring metastasis possessed 7,288 genes within copy number amplicons, 385 genes exhibiting increased expression relative to other tumors and 9 new somatic protein coding mutations. The observed mutations and amplifications were consistent with therapeutic resistance arising through activation of the MAPK and AKT pathways.
We conclude that complete genomic characterization of a rare tumor has the potential to aid in clinical decision making and identifying therapeutic approaches where no established treatment protocols exist. These results also provide direct in vivo genomic evidence for mutational evolution within a tumor under drug selection and potential mechanisms of drug resistance accrual.
RNA-seq; WTSS; PRC2; genome; transcriptome; epigenetic
Starting with SAGE-libraries prepared from C. elegans FAC-sorted embryonic intestine cells (8E-16E cell stage), from total embryos and from purified oocytes, and taking advantage of the NextDB in situ hybridization data base, we define sets of genes highly expressed from the zygotic genome, and expressed either exclusively or preferentially in the embryonic intestine or in the intestine of newly hatched larvae; we had previously defined a similarly expressed set of genes from the adult intestine. We show that an extended TGATAA-like sequence is essentially the only candidate for a cis-acting regulatory motif common to intestine genes expressed at all stages. This sequence is a strong ELT-2 binding site and matches the sequence of GATA-like sites found to be important for the expression of every intestinal gene so far analyzed experimentally. We show that the majority of these three sets of highly expressed intestinal-specific/intestinal-enriched genes respond strongly to ectopic expression of ELT-2 within the embryo. By flow-sorting elt-2(null) larvae from elt-2(+) larvae and then preparing Solexa/Illumina-SAGE libraries, we show that the majority of these genes also respond strongly to loss-of-function of ELT-2. To test the consequences of loss of other transcription factors identified in the embryonic intestine, we develop a strain of worms that is RNAi-sensitive only in the intestine; however, we are unable (with one possible exception) to identify any other transcription factor whose intestinal loss-of-function causes a phenotype of comparable severity to the phenotype caused by loss of ELT-2. Overall, our results support a model in which ELT-2 is the predominant transcription factor in the post-specification C. elegans intestine and participates directly in the transcriptional regulation of the majority (> 80%) of intestinal genes. We present evidence that ELT-2 plays a central role in most aspects of C. elegans intestinal physiology: establishing the structure of the enterocyte, regulating enzymes and transporters involved in digestion and nutrition, responding to environmental toxins and pathogenic infections, and regulating the downstream intestinal components of the daf-2/daf-16 pathway influencing aging and longevity.
Motivation: Next-generation sequencing (NGS) has enabled whole genome and transcriptome single nucleotide variant (SNV) discovery in cancer. NGS produces millions of short sequence reads that, once aligned to a reference genome sequence, can be interpreted for the presence of SNVs. Although tools exist for SNV discovery from NGS data, none are specifically suited to work with data from tumors, where altered ploidy and tumor cellularity impact the statistical expectations of SNV discovery.
Results: We developed three implementations of a probabilistic Binomial mixture model, called SNVMix, designed to infer SNVs from NGS data from tumors to address this problem. The first models allelic counts as observations and infers SNVs and model parameters using an expectation maximization (EM) algorithm and is therefore capable of adjusting to deviation of allelic frequencies inherent in genomically unstable tumor genomes. The second models nucleotide and mapping qualities of the reads by probabilistically weighting the contribution of a read/nucleotide to the inference of a SNV based on the confidence we have in the base call and the read alignment. The third combines filtering out low-quality data in addition to probabilistic weighting of the qualities. We quantitatively evaluated these approaches on 16 ovarian cancer RNASeq datasets with matched genotyping arrays and a human breast cancer genome sequenced to >40× (haploid) coverage with ground truth data and show systematically that the SNVMix models outperform competing approaches.
Availability: Software and data are available at http://compbio.bccrc.ca
Supplemantary information: Supplementary data are available at Bioinformatics online.