Novel loss-of-function variant in DENND5A impedes melanosomal cargo transport and predisposes to familial cutaneous melanoma.

PURPOSE: More than half of the familial cutaneous melanomas have unknown genetic predisposition. This study aims at characterizing a novel melanoma susceptibility gene. METHODS: We performed exome and targeted sequencing in melanoma-prone families without any known melanoma susceptibility genes. We analyzed the expression of candidate gene DENND5A in melanoma samples in relation to pigmentation and UV signature. Functional studies were carried out using microscopic approaches and zebrafish model. RESULTS: We identified a novel DENND5A truncating variant that segregated with melanoma in a Swedish family and 2 additional rare DENND5A variants, 1 of which segregated with the disease in an American family. We found that DENND5A is significantly enriched in pigmented melanoma tissue. Our functional studies show that loss of DENND5A function leads to decrease in melanin content in vitro and pigmentation defects in vivo. Mechanistically, harboring the truncating variant or being suppressed leads to DENND5A losing its interaction with SNX1 and its ability to transport the SNX1-associated vesicles from melanosomes. Consequently, untethered SNX1-premelanosome protein and redundant tyrosinase are redirected to lysosomal degradation by default, causing decrease in melanin content. CONCLUSION: Our findings provide evidence of a physiological role of DENND5A in the skin context and link its variants to melanoma susceptibility.

Interaction of Sox2 with RNA binding proteins in mouse embryonic stem cells.

Sox2 is a master transcriptional regulator of embryonic development. In this study, we determined the protein interactome of Sox2 in the chromatin and nucleoplasm of mouse embryonic stem (mES) cells. Apart from canonical interactions with pluripotency-regulating transcription factors, we identified interactions with several chromatin modulators, including members of the heterochromatin protein 1 (HP1) family, suggesting a role for Sox2 in chromatin-mediated transcriptional repression. Sox2 was also found to interact with RNA binding proteins (RBPs), including proteins involved in RNA processing. RNA immunoprecipitation followed by sequencing revealed that Sox2 associates with different messenger RNAs, as well as small nucleolar RNA Snord34 and the non-coding RNA 7SK. 7SK has been shown to regulate transcription at gene regulatory regions, which could suggest a functional interaction with Sox2 for chromatin recruitment. Nevertheless, we found no evidence of Sox2 modulating recruitment of 7SK to chromatin when examining 7SK chromatin occupancy by Chromatin Isolation by RNA Purification (ChIRP) in Sox2 depleted mES cells. In addition, knockdown of 7SK in mES cells did not lead to any change in Sox2 occupancy at 7SK-regulated genes. Thus, our results show that Sox2 extensively interacts with RBPs, and suggest that Sox2 and 7SK co-exist in a ribonucleoprotein complex whose function is not to regulate chromatin recruitment, but could rather regulate other processes in the nucleoplasm.

Proteogenomics produces comprehensive and highly accurate protein-coding gene annotation in a complete genome assembly of Malassezia sympodialis.

Complete and accurate genome assembly and annotation is a crucial foundation for comparative and functional genomics. Despite this, few complete eukaryotic genomes are available, and genome annotation remains a major challenge. Here, we present a complete genome assembly of the skin commensal yeast Malassezia sympodialis and demonstrate how proteogenomics can substantially improve gene annotation. Through long-read DNA sequencing, we obtained a gap-free genome assembly for M. sympodialis (ATCC 42132), comprising eight nuclear and one mitochondrial chromosome. We also sequenced and assembled four M. sympodialis clinical isolates, and showed their value for understanding Malassezia reproduction by confirming four alternative allele combinations at the two mating-type loci. Importantly, we demonstrated how proteomics data could be readily integrated with transcriptomics data in standard annotation tools. This increased the number of annotated protein-coding genes by 14% (from 3612 to 4113), compared to using transcriptomics evidence alone. Manual curation further increased the number of protein-coding genes by 9% (to 4493). All of these genes have RNA-seq evidence and 87% were confirmed by proteomics. The M. sympodialis genome assembly and annotation presented here is at a quality yet achieved only for a few eukaryotic organisms, and constitutes an important reference for future host-microbe interaction studies.

Massive parallel sequencing questions the pathogenic role of missense variants in dilated cardiomyopathy.

BACKGROUND: Germline genetic variants are an important cause of dilated cardiomyopathy (DCM). However, recent sequencing studies have revealed rare variants in DCM-associated genes also in individuals without known heart disease. In this study, we investigate variant prevalence and genotype-phenotype correlations in Swedish DCM patients, and compare their genetic variants to those detected in reference cohorts. METHODS AND RESULTS: We sequenced the coding regions of 41 DCM-associated genes in 176 unrelated patients with idiopathic DCM and found 102 protein-altering variants with an allele frequency of <0.04% in reference cohorts; the majority were missense variants not previously described in DCM. Fifty-five (31%) patients had one variant, and 24 (14%) patients had two or more variants in the analysed genes. Detection of genetic variants in any gene, and in LMNA, MYH7 or TTN alone, was associated with early onset disease and reduced transplant-free survival. As expected, nonsense and frameshift variants were more common in DCM patients than in healthy individuals of the reference cohort 1000 Genomes Europeans. Surprisingly however, the prevalence, conservation and pathogenicity scores, and localization of missense variants were similar in DCM patients and healthy reference individuals. CONCLUSION: To our knowledge, this is the first study to identify correlations between genotype and prognosis when sequencing a large number of genes in unselected DCM patients. The similar distribution of missense variants in DCM patients and healthy reference individuals questions the pathogenic role of many variants, and suggests that results from genetic testing of DCM patients should be interpreted with caution.

The role of germline alterations in the DNA damage response genes BRIP1 and BRCA2 in melanoma susceptibility.

We applied a targeted sequencing approach to identify germline mutations conferring a moderately to highly increased risk of cutaneous and uveal melanoma. Ninety-two high-risk melanoma patients were screened for inherited variation in 120 melanoma candidate genes. Observed gene variants were filtered based on frequency in reference populations, cosegregation with melanoma in families and predicted functional effect. Several novel or rare genetic variants in genes involved in DNA damage response, cell-cycle regulation and transcriptional control were identified in melanoma patients. Among identified genetic alterations was an extremely rare variant (minor allele frequency of 0.00008) in the BRIP1 gene that was found to cosegregate with the melanoma phenotype. We also found a rare nonsense variant in the BRCA2 gene (rs11571833), previously associated with cancer susceptibility but not with melanoma, which showed weak association with melanoma susceptibility in the Swedish population. Our results add to the growing knowledge about genetic factors associated with melanoma susceptibility and also emphasize the role of DNA damage response as an important factor in melanoma etiology. © 2016 Wiley Periodicals, Inc.

Systematic evaluation of spliced alignment programs for RNA-seq data.

High-throughput RNA sequencing is an increasingly accessible method for studying gene structure and activity on a genome-wide scale. A critical step in RNA-seq data analysis is the alignment of partial transcript reads to a reference genome sequence. To assess the performance of current mapping software, we invited developers of RNA-seq aligners to process four large human and mouse RNA-seq data sets. In total, we compared 26 mapping protocols based on 11 programs and pipelines and found major performance differences between methods on numerous benchmarks, including alignment yield, basewise accuracy, mismatch and gap placement, exon junction discovery and suitability of alignments for transcript reconstruction. We observed concordant results on real and simulated RNA-seq data, confirming the relevance of the metrics employed. Future developments in RNA-seq alignment methods would benefit from improved placement of multimapped reads, balanced utilization of existing gene annotation and a reduced false discovery rate for splice junctions.

Assessment of transcript reconstruction methods for RNA-seq.

We evaluated 25 protocol variants of 14 independent computational methods for exon identification, transcript reconstruction and expression-level quantification from RNA-seq data. Our results show that most algorithms are able to identify discrete transcript components with high success rates but that assembly of complete isoform structures poses a major challenge even when all constituent elements are identified. Expression-level estimates also varied widely across methods, even when based on similar transcript models. Consequently, the complexity of higher eukaryotic genomes imposes severe limitations on transcript recall and splice product discrimination that are likely to remain limiting factors for the analysis of current-generation RNA-seq data.

A high-content small molecule screen identifies sensitivity of glioblastoma stem cells to inhibition of polo-like kinase 1.

Glioblastoma multiforme (GBM) is the most common primary brain cancer in adults and there are few effective treatments. GBMs contain cells with molecular and cellular characteristics of neural stem cells that drive tumour growth. Here we compare responses of human glioblastoma-derived neural stem (GNS) cells and genetically normal neural stem (NS) cells to a panel of 160 small molecule kinase inhibitors. We used live-cell imaging and high content image analysis tools and identified JNJ-10198409 (J101) as an agent that induces mitotic arrest at prometaphase in GNS cells but not NS cells. Antibody microarrays and kinase profiling suggested that J101 responses are triggered by suppression of the active phosphorylated form of polo-like kinase 1 (Plk1) (phospho T210), with resultant spindle defects and arrest at prometaphase. We found that potent and specific Plk1 inhibitors already in clinical development (BI 2536, BI 6727 and GSK 461364) phenocopied J101 and were selective against GNS cells. Using a porcine brain endothelial cell blood-brain barrier model we also observed that these compounds exhibited greater blood-brain barrier permeability in vitro than J101. Our analysis of mouse mutant NS cells (INK4a/ARF(-/-), or p53(-/-)), as well as the acute genetic deletion of p53 from a conditional p53 floxed NS cell line, suggests that the sensitivity of GNS cells to BI 2536 or J101 may be explained by the lack of a p53-mediated compensatory pathway. Together these data indicate that GBM stem cells are acutely susceptible to proliferative disruption by Plk1 inhibitors and that such agents may have immediate therapeutic value.

The non-coding snRNA 7SK controls transcriptional termination, poising, and bidirectionality in embryonic stem cells.

BACKGROUND: Pluripotency is characterized by a unique transcriptional state, in which lineage-specification genes are poised for transcription upon exposure to appropriate stimuli, via a bivalency mechanism involving the simultaneous presence of activating and repressive methylation marks at promoter-associated histones. Recent evidence suggests that other mechanisms, such as RNA polymerase II pausing, might be operational in this process, but their regulation remains poorly understood. RESULTS: Here we identify the non-coding snRNA 7SK as a multifaceted regulator of transcription in embryonic stem cells. We find that 7SK represses a specific cohort of transcriptionally poised genes with bivalent or activating chromatin marks in these cells, suggesting a novel poising mechanism independent of Polycomb activity. Genome-wide analysis shows that 7SK also prevents transcription downstream of polyadenylation sites at several active genes, indicating that 7SK is required for normal transcriptional termination or control of 3'-UTR length. In addition, 7SK suppresses divergent upstream antisense transcription at more than 2,600 loci, including many that encode divergent long non-coding RNAs, a finding that implicates the 7SK snRNA in the control of transcriptional bidirectionality. CONCLUSIONS: Our study indicates that a single non-coding RNA, the snRNA 7SK, is a gatekeeper of transcriptional termination and bidirectional transcription in embryonic stem cells and mediates transcriptional poising through a mechanism independent of chromatin bivalency.

Widespread resetting of DNA methylation in glioblastoma-initiating cells suppresses malignant cellular behavior in a lineage-dependent manner.

Epigenetic changes are frequently observed in cancer. However, their role in establishing or sustaining the malignant state has been difficult to determine due to the lack of experimental tools that enable resetting of epigenetic abnormalities. To address this, we applied induced pluripotent stem cell (iPSC) reprogramming techniques to invoke widespread epigenetic resetting of glioblastoma (GBM)-derived neural stem (GNS) cells. GBM iPSCs (GiPSCs) were subsequently redifferentiated to the neural lineage to assess the impact of cancer-specific epigenetic abnormalities on tumorigenicity. GiPSCs and their differentiating derivatives display widespread resetting of common GBM-associated changes, such as DNA hypermethylation of promoter regions of the cell motility regulator TES (testis-derived transcript), the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C; p57KIP2), and many polycomb-repressive complex 2 (PRC2) target genes (e.g., SFRP2). Surprisingly, despite such global epigenetic reconfiguration, GiPSC-derived neural progenitors remained highly malignant upon xenotransplantation. Only when GiPSCs were directed to nonneural cell types did we observe sustained expression of reactivated tumor suppressors and reduced infiltrative behavior. These data suggest that imposing an epigenome associated with an alternative developmental lineage can suppress malignant behavior. However, in the context of the neural lineage, widespread resetting of GBM-associated epigenetic abnormalities is not sufficient to override the cancer genome.

Digital transcriptome profiling of normal and glioblastoma-derived neural stem cells identifies genes associated with patient survival.

BACKGROUND: Glioblastoma multiforme, the most common type of primary brain tumor in adults, is driven by cells with neural stem (NS) cell characteristics. Using derivation methods developed for NS cells, it is possible to expand tumorigenic stem cells continuously in vitro. Although these glioblastoma-derived neural stem (GNS) cells are highly similar to normal NS cells, they harbor mutations typical of gliomas and initiate authentic tumors following orthotopic xenotransplantation. Here, we analyzed GNS and NS cell transcriptomes to identify gene expression alterations underlying the disease phenotype. METHODS: Sensitive measurements of gene expression were obtained by high-throughput sequencing of transcript tags (Tag-seq) on adherent GNS cell lines from three glioblastoma cases and two normal NS cell lines. Validation by quantitative real-time PCR was performed on 82 differentially expressed genes across a panel of 16 GNS and 6 NS cell lines. The molecular basis and prognostic relevance of expression differences were investigated by genetic characterization of GNS cells and comparison with public data for 867 glioma biopsies. RESULTS: Transcriptome analysis revealed major differences correlated with glioma histological grade, and identified misregulated genes of known significance in glioblastoma as well as novel candidates, including genes associated with other malignancies or glioma-related pathways. This analysis further detected several long non-coding RNAs with expression profiles similar to neighboring genes implicated in cancer. Quantitative PCR validation showed excellent agreement with Tag-seq data (median Pearson r = 0.91) and discerned a gene set robustly distinguishing GNS from NS cells across the 22 lines. These expression alterations include oncogene and tumor suppressor changes not detected by microarray profiling of tumor tissue samples, and facilitated the identification of a GNS expression signature strongly associated with patient survival (P = 1e-6, Cox model). CONCLUSIONS: These results support the utility of GNS cell cultures as a model system for studying the molecular processes driving glioblastoma and the use of NS cells as reference controls. The association between a GNS expression signature and survival is consistent with the hypothesis that a cancer stem cell component drives tumor growth. We anticipate that analysis of normal and malignant stem cells will be an important complement to large-scale profiling of primary tumors.

RNAi screen indicates widespread biological function for human natural antisense transcripts.

Natural antisense transcripts represent a class of regulatory RNA molecules, which are characterized by their complementary sequence to another RNA transcript. Extensive sequencing efforts suggest that natural antisense transcripts are prevalent throughout the mammalian genome; however, their biological significance has not been well defined. We performed a loss-of-function RNA interference (RNAi) screen, which targeted 797 evolutionary conserved antisense transcripts, and found evidence for a regulatory role for a number of natural antisense transcripts. Specifically, we found that natural antisense transcripts for CCPG1 and RAPGEF3 may functionally disrupt signaling pathways and corresponding biological phenotypes, such as cell viability, either independently or in parallel with the corresponding sense transcript. Our results show that the large-scale siRNA screen can be applied to evaluate natural antisense transcript modulation of fundamental cellular events.

Long-range gene regulation links genomic type 2 diabetes and obesity risk regions to HHEX, SOX4, and IRX3.

Genome-wide association studies identified noncoding SNPs associated with type 2 diabetes and obesity in linkage disequilibrium (LD) blocks encompassing HHEX-IDE and introns of CDKAL1 and FTO [Sladek R, et al. (2007) Nature 445:881-885; Steinthorsdottir V, et al. (2007) Nat. Genet 39:770-775; Frayling TM, et al. (2007) Science 316:889-894]. We show that these LD blocks contain highly conserved noncoding elements and overlap with the genomic regulatory blocks of the transcription factor genes HHEX, SOX4, and IRX3. We report that human highly conserved noncoding elements in LD with the risk SNPs drive expression in endoderm or pancreas in transgenic mice and zebrafish. Both HHEX and SOX4 have recently been implicated in pancreas development and the regulation of insulin secretion, but IRX3 had no prior association with pancreatic function or development. Knockdown of its orthologue in zebrafish, irx3a, increased the number of pancreatic ghrelin-producing epsilon cells and decreased the number of insulin-producing beta-cells and glucagon-producing alpha-cells, thereby suggesting a direct link of pancreatic IRX3 function to both obesity and type 2 diabetes.

Web-based tools and approaches to study long-range gene regulation in Metazoa.

Regulatory elements can affect specific genes from megabase distances, often from within or beyond unrelated neighbouring genes. The task of computational charting of regulatory inputs in the genome can be approached from several directions. Typically, computational identification of putative regulatory elements for a gene of interest requires tools that will aid in estimating the extent of the (potentially vast) genomic region around the gene that is likely to contain regulatory elements, as well as tools for the identification and characterization of individual elements. Conversely, starting from a putative regulatory element or a regulatory variation in a non-coding region, one often wants to associate the regulatory element with the correct target gene(s). The design of tools for these purposes relies on the remarkably high level of sequence conservation of thousands of regulatory enhancers, their strong tendency to cluster around their target genes, as well as a constrained range of functional categories of the corresponding target genes, many of which are developmental regulators. Additional evolutionary information, such as conservation of synteny, and a growing body of functional genomic and epigenomic data are being rapidly added to established and emerging tools for studying developmental regulation and cross-species conservation to provide new functional insights into the roles of these regions. In this article, we give an overview of the functionality available in general purpose and new/specialized web tools for the above tasks, and discuss current and future developments in the field.

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

Ancora: a web resource for exploring highly conserved noncoding elements and their association with developmental regulatory genes.

Metazoan genomes contain arrays of highly conserved noncoding elements (HCNEs) that span developmental regulatory genes and define regulatory domains. We describe Ancora http://ancora.genereg.net, a web resource that provides data and tools for exploring genomic organization of HCNEs for multiple genomes. Ancora includes a genome browser that shows HCNE locations and features novel HCNE density plots as a powerful tool to discover developmental regulatory genes and distinguish their regulatory elements and domains.

In silico detection of sequence variations modifying transcriptional regulation.

Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN (regulatory analysis of variation in enhancers). The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation.

Genomic regulatory blocks underlie extensive microsynteny conservation in insects.

Insect genomes contain larger blocks of conserved gene order (microsynteny) than would be expected under a random breakage model of chromosome evolution. We present evidence that microsynteny has been retained to keep large arrays of highly conserved noncoding elements (HCNEs) intact. These arrays span key developmental regulatory genes, forming genomic regulatory blocks (GRBs). We recently described GRBs in vertebrates, where most HCNEs function as enhancers and HCNE arrays specify complex expression programs of their target genes. Here we present a comparison of five Drosophila genomes showing that HCNE density peaks centrally in large synteny blocks containing multiple genes. Besides developmental regulators that are likely targets of HCNE enhancers, HCNE arrays often span unrelated neighboring genes. We describe differences in core promoters between the target genes and the unrelated genes that offer an explanation for the differences in their responsiveness to enhancers. We show examples of a striking correspondence between boundaries of synteny blocks, HCNE arrays, and Polycomb binding regions, confirming that the synteny blocks correspond to regulatory domains. Although few noncoding elements are highly conserved between Drosophila and the malaria mosquito Anopheles gambiae, we find that A. gambiae regions orthologous to Drosophila GRBs contain an equivalent distribution of noncoding elements highly conserved in the yellow fever mosquito Aëdes aegypti and coincide with regions of ancient microsynteny between Drosophila and mosquitoes. The structural and functional equivalence between insect and vertebrate GRBs marks them as an ancient feature of metazoan genomes and as a key to future studies of development and gene regulation.

Mammalian microRNA prediction through a support vector machine model of sequence and structure.

BACKGROUND: MicroRNAs (miRNAs) are endogenous small noncoding RNA gene products, on average 22 nt long, found in a wide variety of organisms. They play important regulatory roles by targeting mRNAs for degradation or translational repression. There are 377 known mouse miRNAs and 475 known human miRNAs in the May 2007 release of the miRBase database, the majority of which are conserved between the two species. A number of recent reports imply that it is likely that many mammalian miRNAs remain to be discovered. The possibility that there are more of them expressed at lower levels or in more specialized expression contexts calls for the exploitation of genome sequence information to accelerate their discovery. METHODOLOGY/PRINCIPAL FINDINGS: In this article, we describe a computational method-mirCoS-that uses three support vector machine models sequentially to discover new miRNA candidates in mammalian genomes based on sequence, secondary structure, and conservation. mirCoS can efficiently detect the majority of known miRNAs and predicts an extensive set of hairpin structures based on human-mouse comparisons. In total, 3476 mouse candidates and 3441 human candidates were found. These hairpins are more similar to known miRNAs than to negative controls in several aspects not considered by the prediction algorithm. A significant fraction of predictions is supported by existing expression evidence. CONCLUSIONS/SIGNIFICANCE: Using a novel approach, mirCoS performs comparably to or better than existing miRNA prediction methods, and contributes a significant number of new candidate miRNAs for experimental verification.

Genomic regulatory blocks encompass multiple neighboring genes and maintain conserved synteny in vertebrates.

We report evidence for a mechanism for the maintenance of long-range conserved synteny across vertebrate genomes. We found the largest mammal-teleost conserved chromosomal segments to be spanned by highly conserved noncoding elements (HCNEs), their developmental regulatory target genes, and phylogenetically and functionally unrelated "bystander" genes. Bystander genes are not specifically under the control of the regulatory elements that drive the target genes and are expressed in patterns that are different from those of the target genes. Reporter insertions distal to zebrafish developmental regulatory genes pax6.1/2, rx3, id1, and fgf8 and miRNA genes mirn9-1 and mirn9-5 recapitulate the expression patterns of these genes even if located inside or beyond bystander genes, suggesting that the regulatory domain of a developmental regulatory gene can extend into and beyond adjacent transcriptional units. We termed these chromosomal segments genomic regulatory blocks (GRBs). After whole genome duplication in teleosts, GRBs, including HCNEs and target genes, were often maintained in both copies, while bystander genes were typically lost from one GRB, strongly suggesting that evolutionary pressure acts to keep the single-copy GRBs of higher vertebrates intact. We show that loss of bystander genes and other mutational events suffered by duplicated GRBs in teleost genomes permits target gene identification and HCNE/target gene assignment. These findings explain the absence of evolutionary breakpoints from large vertebrate chromosomal segments and will aid in the recognition of position effect mutations within human GRBs.