TET2 lesions enhance the aggressiveness of CEBPA-mutant acute myeloid leukemia by rebalancing GATA2 expression

The myeloid transcription factor CEBPA is recurrently biallelically mutated (i.e., double mutated; CEBPADM) in acute myeloid leukemia (AML) with a combination of hypermorphic N-terminal mutations (CEBPANT), promoting expression of the leukemia-associated p30 isoform, and amorphic C-terminal mutations. The most frequently co-mutated genes in CEBPADM AML are GATA2 and TET2, however the molecular mechanisms underlying this co-mutational spectrum are incomplete. By combining transcriptomic and epigenomic analyses of CEBPA-TET2 co-mutated patients with models thereof, we identify GATA2 as a conserved target of the CEBPA-TET2 mutational axis, providing a rationale for the mutational spectra in CEBPADM AML. Elevated CEBPA levels, driven by CEBPANT, mediate recruitment of TET2 to the Gata2 distal hematopoietic enhancer thereby increasing Gata2 expression. Concurrent loss of TET2 in CEBPADM AML induces a competitive advantage by increasing Gata2 promoter methylation, thereby rebalancing GATA2 levels. Of clinical relevance, demethylating treatment of Cebpa-Tet2 co-mutated AML restores Gata2 levels and prolongs disease latency.

The impact of SWI/SNF and NuRD inactivation on gene expression is tightly coupled with levels of RNA polymerase II occupancy at promoters

SWI/SNF and NuRD are protein complexes that antagonistically regulate DNA accessibility. However, repression of their activities often leads to unanticipated changes in target gene expression (paradoxical), highlighting our incomplete understanding of their activities. Here we show that SWI/SNF and NuRD are in a tug-of-war to regulate PRC2 occupancy at lowly expressed and bivalent genes in mouse embryonic stem cells (mESCs). In contrast, at promoters of average or highly expressed genes, SWI/SNF and NuRD antagonistically modulate RNA polymerase II (Pol II) release kinetics, arguably owing to accompanying alterations in H3.3 and H2A.Z levels at promoter-flanking nucleosomes, leading to paradoxical changes in gene expression. Owing to this mechanism, the relative activities of the two remodelers potentiate gene promoters toward Pol II-dependent open or PRC2-dependent closed chromatin states. Our results highlight RNA Pol II occupancy as the key parameter in determining the direction of gene expression changes in response to SWI/SNF and NuRD inactivation at gene promoters in mESCs.

Transcription factor-driven coordination of cell cycle exit and lineage-specification in vivo during granulocytic differentiation : In memoriam Professor Niels Borregaard

Differentiation of multipotent stem cells into mature cells is fundamental for development and homeostasis of mammalian tissues, and requires the coordinated induction of lineage-specific transcriptional programs and cell cycle withdrawal. To understand the underlying regulatory mechanisms of this fundamental process, we investigated how the tissue-specific transcription factors, CEBPA and CEBPE, coordinate cell cycle exit and lineage-specification in vivo during granulocytic differentiation. We demonstrate that CEBPA promotes lineage-specification by launching an enhancer-primed differentiation program and direct activation of CEBPE expression. Subsequently, CEBPE confers promoter-driven cell cycle exit by sequential repression of MYC target gene expression at the G1/S transition and E2F-meditated G2/M gene expression, as well as by the up-regulation of Cdk1/2/4 inhibitors. Following cell cycle exit, CEBPE unleashes the CEBPA-primed differentiation program to generate mature granulocytes. These findings highlight how tissue-specific transcription factors coordinate cell cycle exit with differentiation through the use of distinct gene regulatory elements.

Here the authors show that differentiation of haematopoietic stem cells into mature blood cells is primed by cell type-specific transcription factors at the enhancer level during early differentiation, before they confere promoter-driven growth arrest, and activate post-mitotic terminal differentiation.

PTBP1 promotes hematopoietic stem cell maintenance and red blood cell development by ensuring sufficient availability of ribosomal constituents

Ribosomopathies constitute a range of disorders associated with defective protein synthesis mainly affecting hematopoietic stem cells (HSCs) and erythroid development. Here, we demonstrate that deletion of poly-pyrimidine-tract-binding protein 1 (PTBP1) in the hematopoietic compartment leads to the development of a ribosomopathy-like condition. Specifically, loss of PTBP1 is associated with decreases in HSC self-renewal, erythroid differentiation, and protein synthesis. Consistent with its function as a splicing regulator, PTBP1 deficiency results in splicing defects in hundreds of genes, and we demonstrate that the up-regulation of a specific isoform of CDC42 partly mimics the protein-synthesis defect associated with loss of PTBP1. Furthermore, PTBP1 deficiency is associated with a marked defect in ribosome biogenesis and a selective reduction in the translation of mRNAs encoding ribosomal proteins. Collectively, this work identifies PTBP1 as a key integrator of ribosomal functions and highlights the broad functional repertoire of RNA-binding proteins.

H3K9 dimethylation safeguards cancer cells against activation of the interferon pathway

Activation of interferon genes constitutes an important anticancer pathway able to restrict proliferation of cancer cells. Here, we demonstrate that the H3K9me3 histone methyltransferase (HMT) suppressor of variegation 3-9 homolog 1 (SUV39H1) is required for the proliferation of acute myeloid leukemia (AML) and find that its loss leads to activation of the interferon pathway. Mechanistically, we show that this occurs via destabilization of a complex composed of SUV39H1 and the two H3K9me2 HMTs, G9A and GLP. Indeed, loss of H3K9me2 correlated with the activation of key interferon pathway genes, and interference with the activities of G9A/GLP largely phenocopied loss of SUV39H1. Last, we demonstrate that inhibition of G9A/GLP synergized with DNA demethylating agents and that SUV39H1 constitutes a potential biomarker for the response to hypomethylation treatment. Collectively, we uncovered a clinically relevant role for H3K9me2 in safeguarding cancer cells against activation of the interferon pathway.

The ASXL1-G643W variant accelerates the development of CEBPA mutant acute myeloid leukemia

ASXL1 is one of the most commonly mutated genes in myeloid malignancies, including myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). In order to further our understanding of the role of ASXL1 lesions in malignant hematopoiesis, we generated a novel knockin mouse model carrying the most frequent ASXL1 mutation identified in MDS patients, ASXL1 p.G643WfsX12. Mutant mice neither displayed any major hematopoietic defects nor developed any apparent hematological disease. In AML patients, ASXL1 mutations co-occur with mutations in CEBPA and we therefore generated compound Cebpa and Asxl1 mutated mice. Using a transplantation model, we found that the mutated Asxl1 allele significantly accelerated disease development in a CEBPA mutant context. Importantly, we demonstrated that, similar to the human setting, Asxl1 mutated mice responded poorly to chemotherapy. This model therefore constitutes an excellent experimental system for further studies into the clinically important question of chemotherapy resistance mediated by mutant ASXL1.

Epigenetic and Transcriptomic Characterization of Pure Adipocyte Fractions From Obese Pigs Identifies Candidate Pathways Controlling Metabolism

Reprogramming of adipocyte function in obesity is implicated in metabolic disorders like type 2 diabetes. Here, we used the pig, an animal model sharing many physiological and pathophysiological similarities with humans, to perform in-depth epigenomic and transcriptomic characterization of pure adipocyte fractions. Using a combined DNA methylation capture sequencing and Reduced Representation bisulfite sequencing (RRBS) strategy in 11 lean and 12 obese pigs, we identified in 3529 differentially methylated regions (DMRs) located at close proximity to-, or within genes in the adipocytes. By sequencing of the transcriptome from the same fraction of isolated adipocytes, we identified 276 differentially expressed transcripts with at least one or more DMR. These transcripts were over-represented in gene pathways related to MAPK, metabolic and insulin signaling. Using a candidate gene approach, we further characterized 13 genes potentially regulated by DNA methylation and identified putative transcription factor binding sites that could be affected by the differential methylation in obesity. Our data constitute a valuable resource for further investigations aiming to delineate the epigenetic etiology of metabolic disorders.

Differences in Cell Cycle Status Underlie Transcriptional Heterogeneity in the HSC Compartment

Hematopoietic stem cells (HSCs) are considered a heterogeneous cell population. To further resolve the HSC compartment, we characterized a retinoic acid (RA) reporter mouse line. Sub-fractionation of the HSC compartment in RA-CFP reporter mice demonstrated that RA-CFP-dim HSCs were largely non-proliferative and displayed superior engraftment potential in comparison with RA-CFP-bright HSCs. Gene expression analysis demonstrated higher expression of RA-target genes in RA-CFP-dim HSCs, in contrast to the RA-CFP reporter expression, but both RA-CFP-dim and RA-CFP-bright HSCs responded efficiently to RA in vitro. Single-cell RNA sequencing (RNA-seq) of >1,200 HSCs showed that differences in cell cycle activity constituted the main driver of transcriptional heterogeneity in HSCs. Moreover, further analysis of the single-cell RNA-seq data revealed that stochastic low-level expression of distinct lineage-affiliated transcriptional programs is a common feature of HSCs. Collectively, this work demonstrates the utility of the RA-CFP reporter line as a tool for the isolation of superior HSCs.

Enhancer and Transcription Factor Dynamics during Myeloid Differentiation Reveal an Early Differentiation Block in Cebpa null Progenitors

Transcription factors PU.1 and CEBPA are required for the proper coordination of enhancer activity during granulocytic-monocytic (GM) lineage differentiation to form myeloid cells. However, precisely how these factors control the chronology of enhancer establishment during differentiation is not known. Through integrated analyses of enhancer dynamics, transcription factor binding, and proximal gene expression during successive stages of murine GM-lineage differentiation, we unravel the distinct kinetics by which PU.1 and CEBPA coordinate GM enhancer activity. We find no evidence of a pioneering function of PU.1 during late GM-lineage differentiation. Instead, we delineate a set of enhancers that gain accessibility in a CEBPA-dependent manner, suggesting a pioneering function of CEBPA. Analyses of Cebpa null bone marrow demonstrate that CEBPA controls PU.1 levels and, unexpectedly, that the loss of CEBPA results in an early differentiation block. Taken together, our data provide insights into how PU.1 and CEBPA functionally interact to drive GM-lineage differentiation.

Mutant CEBPA directly drives the expression of the targetable tumor-promoting factor CD73 in AML

The key myeloid transcription factor (TF), CEBPA, is frequently mutated in acute myeloid leukemia (AML), but the direct molecular effects of this leukemic driver mutation remain elusive. To investigate CEBPA mutant AML, we performed microscale, in vivo chromatin immunoprecipitation sequencing and identified a set of aberrantly activated enhancers, exclusively occupied by the leukemia-associated CEBPA-p30 isoform. Comparing gene expression changes in human CEBPA mutant AML and the corresponding Cebpa ^Lp30 mouse model, we identified Nt5e, encoding CD73, as a cross-species AML gene with an upstream leukemic enhancer physically and functionally linked to the gene. Increased expression of CD73, mediated by the CEBPA-p30 isoform, sustained leukemic growth via the CD73/A2AR axis. Notably, targeting of this pathway enhanced survival of AML-transplanted mice. Our data thus indicate a first-in-class link between a cancer driver mutation in a TF and a druggable, direct transcriptional target.

The splicing factor RBM25 controls MYC activity in acute myeloid leukemia

Cancer sequencing studies have implicated regulators of pre-mRNA splicing as important disease determinants in acute myeloid leukemia (AML), but the underlying mechanisms have remained elusive. We hypothesized that "non-mutated" splicing regulators may also play a role in AML biology and therefore conducted an in vivo shRNA screen in a mouse model of CEBPA mutant AML. This has led to the identification of the splicing regulator RBM25 as a novel tumor suppressor. In multiple human leukemic cell lines, knockdown of RBM25 promotes proliferation and decreases apoptosis. Mechanistically, we show that RBM25 controls the splicing of key genes, including those encoding the apoptotic regulator BCL-X and the MYC inhibitor BIN1. This mechanism is also operative in human AML patients where low RBM25 levels are associated with high MYC activity and poor outcome. Thus, we demonstrate that RBM25 acts as a regulator of MYC activity and sensitizes cells to increased MYC levels.

Peak-valley-peak pattern of histone modifications delineates active regulatory elements and their directionality

Formation of nucleosome free region (NFR) accompanied by specific histone modifications at flanking nucleosomes is an important prerequisite for enhancer and promoter activity. Due to this process, active regulatory elements often exhibit a distinct shape of histone signal in the form of a peak-valley-peak (PVP) pattern. However, different features of PVP patterns and their robustness in predicting active regulatory elements have never been systematically analyzed. Here, we present PARE, a novel computational method that systematically analyzes the H3K4me1 or H3K4me3 PVP patterns to predict NFRs. We show that NFRs predicted by H3K4me1 and me3 patterns are associated with active enhancers and promoters, respectively. Furthermore, asymmetry in the height of peaks flanking the central valley can predict the directionality of stable transcription at promoters. Using PARE on ChIP-seq histone modifications from four ENCODE cell lines and four hematopoietic differentiation stages, we identified several enhancers whose regulatory activity is stage specific and correlates positively with the expression of proximal genes in a particular stage. In conclusion, our results demonstrate that PVP patterns delineate both the histone modification landscape and the transcriptional activities governed by active enhancers and promoters, and therefore can be used for their prediction. PARE is freely available at http://servers.binf.ku.dk/pare.

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan–Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space.

Differential and coherent processing patterns from small RNAs

Post-transcriptional processing events related to short RNAs are often reflected in their read profile patterns emerging from high-throughput sequencing data. MicroRNA arm switching across different tissues is a well-known example of what we define as differential processing. Here, short RNAs from the nine cell lines of the ENCODE project, irrespective of their annotation status, were analyzed for genomic loci representing differential or coherent processing. We observed differential processing predominantly in RNAs annotated as miRNA, snoRNA or tRNA. Four out of five known cases of differentially processed miRNAs that were in the input dataset were recovered and several novel cases were discovered. In contrast to differential processing, coherent processing is observed widespread in both annotated and unannotated regions. While the annotated loci predominantly consist of ~24 nt short RNAs, the unannotated loci comparatively consist of ~17 nt short RNAs. Furthermore, these ~17 nt short RNAs are significantly enriched for overlap to transcription start sites and DNase I hypersensitive sites (p-value < 0.01) that are characteristic features of transcription initiation RNAs. We discuss how the computational pipeline developed in this study has the potential to be applied to other forms of RNA-seq data for further transcriptome-wide studies of differential and coherent processing.

Emerging applications of read profiles towards the functional annotation of the genome

Functional annotation of the genome is important to understand the phenotypic complexity of various species. The road toward functional annotation involves several challenges ranging from experiments on individual molecules to large-scale analysis of high-throughput sequencing (HTS) data. HTS data is typically a result of the protocol designed to address specific research questions. The sequencing results in reads, which when mapped to a reference genome often leads to the formation of distinct patterns (read profiles). Interpretation of these read profiles is essential for their analysis in relation to the research question addressed. Several strategies have been employed at varying levels of abstraction ranging from a somewhat ad hoc to a more systematic analysis of read profiles. These include methods which can compare read profiles, e.g., from direct (non-sequence based) alignments to classification of patterns into functional groups. In this review, we highlight the emerging applications of read profiles for the annotation of non-coding RNA and cis-regulatory elements (CREs) such as enhancers and promoters. We also discuss the biological rationale behind their formation.

EssOilDB: a database of essential oils reflecting terpene composition and variability in the plant kingdom

Plant essential oils are complex mixtures of volatile organic compounds, which play indispensable roles in the environment, for the plant itself, as well as for humans. The potential biological information stored in essential oil composition data can provide an insight into the silent language of plants, and the roles of these chemical emissions in defense, communication and pollinator attraction. In order to decipher volatile profile patterns from a global perspective, we have developed the ESSential OIL DataBase (EssOilDB), a continually updated, freely available electronic database designed to provide knowledge resource for plant essential oils, that enables one to address a multitude of queries on volatile profiles of native, invasive, normal or stressed plants, across taxonomic clades, geographical locations and several other biotic and abiotic influences. To our knowledge, EssOilDB is the only database in the public domain providing an opportunity for context based scientific research on volatile patterns in plants. EssOilDB presently contains 123 041 essential oil records spanning a century of published reports on volatile profiles, with data from 92 plant taxonomic families, spread across diverse geographical locations all over the globe. We hope that this huge repository of VOCs will facilitate unraveling of the true significance of volatiles in plants, along with creating potential avenues for industrial applications of essential oils. We also illustrate the use of this database in terpene biology and show how EssOilDB can be used to complement data from computational genomics to gain insights into the diversity and variability of terpenoids in the plant kingdom. EssOilDB would serve as a valuable information resource, for students and researchers in plant biology, in the design and discovery of new odor profiles, as well as for entrepreneurs—the potential for generating consumer specific scents being one of the most attractive and interesting topics in the cosmetic industry.

Database URL: http://nipgr.res.in/Essoildb/

Structured RNAs and synteny regions in the pig genome

Background

Annotating mammalian genomes for noncoding RNAs (ncRNAs) is nontrivial since far from all ncRNAs are known and the computational models are resource demanding. Currently, the human genome holds the best mammalian ncRNA annotation, a result of numerous efforts by several groups. However, a more direct strategy is desired for the increasing number of sequenced mammalian genomes of which some, such as the pig, are relevant as disease models and production animals.

Results

We present a comprehensive annotation of structured RNAs in the pig genome. Combining sequence and structure similarity search as well as class specific methods, we obtained a conservative set with a total of 3,391 structured RNA loci of which 1,011 and 2,314, respectively, hold strong sequence and structure similarity to structured RNAs in existing databases. The RNA loci cover 139 cis-regulatory element loci, 58 lncRNA loci, 11 conflicts of annotation, and 3,183 ncRNA genes. The ncRNA genes comprise 359 miRNAs, 8 ribozymes, 185 rRNAs, 638 snoRNAs, 1,030 snRNAs, 810 tRNAs and 153 ncRNA genes not belonging to the here fore mentioned classes. When running the pipeline on a local shuffled version of the genome, we obtained no matches at the highest confidence level. Additional analysis of RNA-seq data from a pooled library from 10 different pig tissues added another 165 miRNA loci, yielding an overall annotation of 3,556 structured RNA loci. This annotation represents our best effort at making an automated annotation. To further enhance the reliability, 571 of the 3,556 structured RNAs were manually curated by methods depending on the RNA class while 1,581 were declared as pseudogenes. We further created a multiple alignment of pig against 20 representative vertebrates, from which RNAz predicted 83,859 de novo RNA loci with conserved RNA structures. 528 of the RNAz predictions overlapped with the homology based annotation or novel miRNAs. We further present a substantial synteny analysis which includes 1,004 lineage specific de novo RNA loci and 4 ncRNA loci in the known annotation specific for Laurasiatheria (pig, cow, dolphin, horse, cat, dog, hedgehog).

Conclusions

We have obtained one of the most comprehensive annotations for structured ncRNAs of a mammalian genome, which is likely to play central roles in both health modelling and production. The core annotation is available in Ensembl 70 and the complete annotation is available at http://rth.dk/resources/rnannotator/susscr102/version1.02.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-459) contains supplementary material, which is available to authorized users.

Spatially conserved regulatory elements identified within human and mouse Cd247 gene using high-throughput sequencing data from the ENCODE project

The Cd247 gene encodes for a transmembrane protein important for the expression and assembly of TCR/CD3 complex on the surface of T lymphocytes. Down-regulation of CD247 has functional consequences in systemic autoimmunity and has been shown to be associated with Type 1 Diabetes in NOD mouse. In this study, we have utilized the wealth of high-throughput sequencing data produced during the Encyclopedia of DNA Elements (ENCODE) project to identify spatially conserved regulatory elements within the Cd247 gene from human and mouse. We show the presence of two transcription factor binding sites, supported by histone marks and ChIP-seq data, that specifically have features of an enhancer and a promoter, respectively. We also identified a putative long non-coding RNA from the characteristically long first intron of the Cd247 gene. The long non-coding RNA annotation is supported by manual annotations from the GENCODE project in human and our expression quantification analysis performed in NOD and B6 mice using qRT-PCR. Furthermore, 17 of the 23 SNPs already known to be implicated with T1D were observed within the long non-coding RNA region in mouse. The spatially conserved regulatory elements identified in this study have the potential to enrich our understanding of the role of Cd247 gene in autoimmune diabetes.

MicroRNA discovery by similarity search to a database of RNA-seq profiles

In silico generated search for microRNAs (miRNAs) has been driven by methods compiling structural features of the miRNA precursor hairpin, as well as to some degree combining this with the analysis of RNA-seq profiles for which the miRNA typically leave the drosha/dicer fingerprint of 1-2 ~22 nt blocks of reads corresponding to the mature and star miRNA. In complement to the previous methods, we present a study where we systematically exploit these patterns of read profiles. We created two datasets comprised of 2540 and 4795 read profiles obtained after preprocessing short RNA-seq data from miRBase and ENCODE, respectively. Out of 4795 ENCODE read profiles, 1361 are annotated as non-coding RNAs (ncRNAs) and of which 285 are further annotated as miRNAs. Using deepBlockAlign (dba), we align ncRNA read profiles from ENCODE against the miRBase read profiles (cleaned for "self-matches") and are able to separate ENCODE miRNAs from the other ncRNAs by a Matthews Correlation Coefficient (MCC) of 0.8 and obtain an area under the curve of 0.93. Based on the dba score cut-off of 0.7 at which we observed the maximum MCC of 0.8, we predict 523 novel miRNA candidates. An additional RNA secondary structure analysis reveal that 42 of the candidates overlap with predicted conserved secondary structure. Further analysis reveal that the 523 miRNA candidates are located in genomic regions with MAF block (UCSC) fragmentation and poor sequence conservation, which in part might explain why they have been overlooked in previous efforts. We further analyzed known human and mouse miRNA read profiles and found two distinct classes; the first containing two blocks and the second containing >2 blocks of reads. Also the latter class holds read profiles that have less well defined arrangement of reads in comparison to the former class. On comparison of miRNA read profiles from plants and animals, we observed kingdom specific read profiles that are distinct in terms of both length and distribution of reads within the read profiles to each other. All the data, as well as a server to search miRBase read profiles by uploading a BED file, is available at http://rth.dk/resources/mirdba.

deepBlockAlign: a tool for aligning RNA-seq profiles of read block patterns

MOTIVATION

High-throughput sequencing methods allow whole transcriptomes to be sequenced fast and cost-effectively. Short RNA sequencing provides not only quantitative expression data but also an opportunity to identify novel coding and non-coding RNAs. Many long transcripts undergo post-transcriptional processing that generates short RNA sequence fragments. Mapped back to a reference genome, they form distinctive patterns that convey information on both the structure of the parent transcript and the modalities of its processing. The miR-miR* pattern from microRNA precursors is the best-known, but by no means singular, example.

RESULTS

deepBlockAlign introduces a two-step approach to align RNA-seq read patterns with the aim of quickly identifying RNAs that share similar processing footprints. Overlapping mapped reads are first merged to blocks and then closely spaced blocks are combined to block groups, each representing a locus of expression. In order to compare block groups, the constituent blocks are first compared using a modified sequence alignment algorithm to determine similarity scores for pairs of blocks. In the second stage, block patterns are compared by means of a modified Sankoff algorithm that takes both block similarities and similarities of pattern of distances within the block groups into account. Hierarchical clustering of block groups clearly separates most miRNA and tRNA, and also identifies about a dozen tRNAs clustering together with miRNA. Most of these putative Dicer-processed tRNAs, including eight cases reported to generate products with miRNA-like features in literature, exhibit read blocks distinguished by precise start position of reads.

AVAILABILITY

The program deepBlockAlign is available as source code from http://rth.dk/resources/dba/.

CONTACT

gorodkin@rth.dk; studla@bioinf.uni-leipzig.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

SSPred: A prediction server based on SVM for the identification and classification of proteins involved in bacterial secretion systems

Protein secretion systems used by almost all bacteria are highly significant for the normal existence and interaction of bacteria with their host. The accumulation of genome sequence data in past few years has provided great insights into the distribution and function of these secretion systems. In this study, a support vector machine (SVM)- based method, SSPred was developed for the automated functional annotation of proteins involved in secretion systems further classifying them into five major sub-types (Type-I, Type-II, Type-III, Type-IV and Sec systems). The dataset used in this study for training and testing was obtained from KEGG and SwissProt database and was curated in order to avoid redundancy. To overcome the problem of imbalance in positive and negative dataset, an ensemble of SVM modules, each trained on a balanced subset of the training data were used. Firstly, protein sequence features like amino-acid composition (AAC), dipeptide composition (DPC) and physico-chemical composition (PCC) were used to develop the SVM-based modules that achieved an average accuracy of 84%, 85.17% and 82.59%, respectively. Secondly, a hybrid module (hybrid-I) integrating all the previously used features was developed that achieved an average accuracy of 86.12%. Another hybrid module (hybrid-II) developed using evolutionary information of a protein sequence extracted from position-specific scoring matrix and amino-acid composition achieved a maximum average accuracy of 89.73%. On unbiased evaluation using an independent data set, SSPred showed good prediction performance in identification and classification of secretion systems. SSPred is a freely available World Wide Web server at http//www.bioinformatics.org/sspred.

PredictBias: a server for the identification of genomic and pathogenicity islands in prokaryotes

Pathogenicity Islands (PAIs) are the sub-sets of Genomic Islands (GIs) that are acquired by horizontal gene transfer (HGT) and are generally shown to have a significant deviation in G+C, dinucleotide or codon frequency from core genome. Major approaches used for PAI identification are based on composition bias and/or similarity with known PAIs. These approaches either limit the search to GIs or to regions similar to previously annotated PAIs. PredictBias is a web application for the identification of genomic and pathogenicity islands in prokaryotes based on composition bias, presence of insertion elements, proximity with virulence-associated genes and absence in related non-pathogenic species. A profile database of virulence factors (VFPD) has been developed using 213 protein families associated to virulence retrieved from Pfam and PRINTS database. PredictBias performs a RPSBLAST search for regions with significant composition bias against VFPD. If a region encodes for at least one protein related to virulence then it is marked as potential PAI (biased-composition) otherwise as GI. Regions involved in virulence but having unsuspicious composition bias due to ancient HGT are identified by scanning genome segments (8 ORFs) with more than four significant hits to VFPD and are marked as potential PAI (unbiased-composition). The relative absence of potential PAIs in related non-pathogenic species can be investigated using 'compare genome feature' of PredictBias that further aids in validating the results and defining boundaries for PAIs. Performance measure analysis showed that the output of PredictBias is in agreement with the known findings. PredictBias is available at www.davvbiotech.res.in/PredictBias.