Genome-scale de novo assembly using ALGA.

MOTIVATION: There are very few methods for de novo genome assembly based on the overlap graph approach. It is considered as giving more exact results than the so-called de Bruijn graph approach but in much greater time and of much higher memory usage. It is not uncommon that assembly methods involving the overlap graph model are not able to successfully compute greater datasets, mainly due to memory limitation of a computer. This was the reason for developing in last decades mainly de Bruijn-based assembly methods, fast and fairly accurate. However, the latter methods can fail for longer or more repetitive genomes, as they decompose reads to shorter fragments and lose a part of information. An efficient assembler for processing big datasets and using the overlap graph model is still looked out. RESULTS: We propose a new genome-scale de novo assembler based on the overlap graph approach, designed for short-read sequencing data. The method, ALGA, incorporates several new ideas resulting in more exact contigs produced in short time. Among these ideas, we have creation of a sparse but quite informative graph, reduction of the graph including a procedure referring to the problem of minimum spanning tree of a local subgraph, and graph traversal connected with simultaneous analysis of contigs stored so far. What is rare in genome assembly, the algorithm is almost parameter-free, with only one optional parameter to be set by a user. ALGA was compared with nine state-of-the-art assemblers in tests on genome-scale sequencing data obtained from real experiments on six organisms, differing in size, coverage, GC content and repetition rate. ALGA produced best results in the sense of overall quality of genome reconstruction, understood as a good balance between genome coverage, accuracy and length of resulting sequences. The algorithm is one of tools involved in processing data in currently realized national project Genomic Map of Poland. AVAILABILITY AND IMPLEMENTATION: ALGA is available at http://alga.put.poznan.pl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcriptome Remodeling in Gradual Development of Inverse Resistance between Paclitaxel and Cisplatin in Ovarian Cancer Cells.

Resistance to anti-cancer drugs is the main challenge in oncology. In pre-clinical studies, established cancer cell lines are primary tools in deciphering molecular mechanisms of this phenomenon. In this study, we proposed a new, transcriptome-focused approach, utilizing a model of isogenic cancer cell lines with gradually changing resistance. We analyzed trends in gene expression in the aim to find out a scaffold of resistance development process. The ovarian cancer cell line A2780 was treated with stepwise increased concentrations of paclitaxel (PTX) to generate a series of drug resistant sublines. To monitor transcriptome changes we submitted them to mRNA-sequencing, followed by the identification of differentially expressed genes (DEGs), principal component analysis (PCA), and hierarchical clustering. Functional interactions of proteins, encoded by DEGs, were analyzed by building protein-protein interaction (PPI) networks. We obtained human ovarian cancer cell lines with gradually developed resistance to PTX and collateral sensitivity to cisplatin (CDDP) (inverse resistance). In their transcriptomes, we identified two groups of DEGs: (1) With fluctuations in expression in the course of resistance acquiring; and (2) with a consistently changed expression at each stage of resistance development, constituting a scaffold of the process. In the scaffold PPI network, the cell cycle regulator-polo-like kinase 2 (PLK2); proteins belonging to the tumor necrosis factor (TNF) ligand and receptor family, as well as to the ephrin receptor family were found, and moreover, proteins linked to osteo- and chondrogenesis and the nervous system development. Our cellular model of drug resistance allowed for keeping track of trends in gene expression and studying this phenomenon as a process of evolution, reflected by global transcriptome remodeling. This approach enabled us to explore novel candidate genes and surmise that abrogation of the osteomimic phenotype in ovarian cancer cells might occur during the development of inverse resistance between PTX and CDDP.

Antifungal Agent 4-AN Changes the Genome-Wide Expression Profile, Downregulates Virulence-Associated Genes and Induces Necrosis in Candida albicans Cells.

In the light of the increasing occurrence of antifungal resistance, there is an urgent need to search for new therapeutic strategies to overcome this phenomenon. One of the applied approaches is the synthesis of small-molecule compounds showing antifungal properties. Here we present a continuation of the research on the recently discovered anti-Candida albicans agent 4-AN. Using next generation sequencing and transcriptional analysis, we revealed that the treatment of C. albicans with 4-AN can change the expression profile of a large number of genes. The highest upregulation was observed in the case of genes involved in cell stress, while the highest downregulation was shown for genes coding sugar transporters. Real-time PCR analysis revealed 4-AN mediated reduction of the relative expression of genes engaged in fungal virulence (ALS1, ALS3, BCR1, CPH1, ECE1, EFG1, HWP1, HYR1 and SAP1). The determination of the fractional inhibitory concentration index (FICI) showed that the combination of 4-AN with amphotericin B is synergistic. Finally, flow cytometry analysis revealed that the compound induces mainly necrosis in C. albicans cells.

Characterization of RNP Networks of PUM1 and PUM2 Post-Transcriptional Regulators in TCam-2 Cells, a Human Male Germ Cell Model.

Mammalian Pumilio (PUM) proteins are sequence-specific, RNA-binding proteins (RBPs) with wide-ranging roles. They are involved in germ cell development, which has functional implications in development and fertility. Although human PUM1 and PUM2 are closely related to each other and recognize the same RNA binding motif, there is some evidence for functional diversity. To address that problem, first we used RIP-Seq and RNA-Seq approaches, and identified mRNA pools regulated by PUM1 and PUM2 proteins in the TCam-2 cell line, a human male germ cell model. Second, applying global mass spectrometry-based profiling, we identified distinct PUM1- and PUM2-interacting putative protein cofactors, most of them involved in RNA processing. Third, combinatorial analysis of RIP and RNA-Seq, mass spectrometry, and RNA motif enrichment analysis revealed that PUM1 and PUM2 form partially varied RNP-regulatory networks (RNA regulons), which indicate different roles in human reproduction and testicular tumorigenesis. Altogether, this work proposes that protein paralogues with very similar and evolutionary highly conserved functional domains may play divergent roles in the cell by combining with different sets of protein cofactors. Our findings highlight the versatility of PUM paralogue-based post-transcriptional regulation, offering insight into the mechanisms underlying their diverse biological roles and diseases resulting from their dysfunction.

GRASShopPER-An algorithm for de novo assembly based on GPU alignments.

Next generation sequencers produce billions of short DNA sequences in a massively parallel manner, which causes a great computational challenge in accurately reconstructing a genome sequence de novo using these short sequences. Here, we propose the GRASShopPER assembler, which follows an approach of overlap-layout-consensus. It uses an efficient GPU implementation for the sequence alignment during the graph construction stage and a greedy hyper-heuristic algorithm at the fork detection stage. A two-part fork detection method allows us to identify repeated fragments of a genome and to reconstruct them without misassemblies. The assemblies of data sets of bacteria Candidatus Microthrix, nematode Caenorhabditis elegans, and human chromosome 14 were evaluated with the golden standard tool QUAST. In comparison with other assemblers, GRASShopPER provided contigs that covered the largest part of the genomes and, at the same time, kept good values of other metrics, e.g., NG50 and misassembly rate.

Coexisting psoriasis affects the clinical course of type 1 diabetes in children.

INTRODUCTION: Literature reports link psoriasis with insulin resistance characteristic for type 2 diabetes. However, this condition may also affect the clinical course of type 1 diabetes (T1D). AIM: To investigate whether children with type 1 diabetes mellitus (T1D) and psoriasis have a different course of diabetes. METHODS: We evaluated patients diagnosed with T1D in the years 2002-2011 for the presence of psoriasis and matched them 1:10 with T1D-only patients by sex and duration of diabetes using propensity score. We collected T1D-onset parameters and metabolic control surrogates from six months after T1D diagnosis. RESULTS: We identified 14 patients with psoriasis and matched 140 controls, of whom 129 (68 boys) were eligible for the analysis. At onset T1D+psoriasis patients showed higher concentration of C-peptide than controls (median: 0.38ng/ml vs 0.15ng/ml, p=0.02). Six months later, they had non-significantly lower HbA1c (6.0 vs 6.6%, p=0.11), TC (143mg/dl vs 159mg/dl, p=0.14) HDL (54.5mg/dl vs 59mg/dl, p=0.11). CONCLUSIONS: Patients with T1D and psoriasis present higher endogenous insulin secretion at T1D onset and a tendency for better glycemic control during the first 6 months.

Dealing with repetitions in sequencing by hybridization.

DNA sequencing by hybridization (SBH) induces errors in the biochemical experiment. Some of them are random and disappear when the experiment is repeated. Others are systematic, involving repetitions in the probes of the target sequence. A good method for solving SBH problems must deal with both types of errors. In this work we propose a new hybrid genetic algorithm for isothermic and standard sequencing that incorporates the concept of structured combinations. The algorithm is then compared with other methods designed for handling errors that arise in standard and isothermic SBH approaches. DNA sequences used for testing are taken from GenBank. The set of instances for testing was divided into two groups. The first group consisted of sequences containing positive and negative errors in the spectrum, at a rate of up to 20%, excluding errors coming from repetitions. The second group consisted of sequences containing repeated oligonucleotides, and containing additional errors up to 5% added into the spectra. Our new method outperforms the best alternative procedures for both data sets. Moreover, the method produces solutions exhibiting extremely high degree of similarity to the target sequences in the cases without repetitions, which is an important outcome for biologists. The spectra prepared from the sequences taken from GenBank are available on our website http://bio.cs.put.poznan.pl/.

MTTE: an innovative strategy for the evaluation of targeted/exome enrichment efficiency.

Although currently available strategies for the preparation of exome-enriched libraries are well established, a final validation of the libraries in terms of exome enrichment efficiency prior to the sequencing step is of considerable importance. Here, we present a strategy for the evaluation of exome enrichment, i.e., the Multipoint Test for Targeted-enrichment Efficiency (MTTE), PCR-based approach utilizing multiplex ligation-dependent probe amplification with capillary electrophoresis separation. We used MTTE for the analysis of subsequent steps of the Illumina TruSeq Exome Enrichment procedure. The calculated values of enrichment-associated parameters (i.e., relative enrichment, relative clearance, overall clearance, and fold enrichment) and the comparison of MTTE results with the actual enrichment revealed the high reliability of our assay. Additionally, the MTTE assay enabled the determination of the sequence-associated features that may confer bias in the enrichment of different targets. Importantly, the MTTE is low cost method that can be easily adapted to the region of interest important for a particular project. Thus, the MTTE strategy is attractive for post-capture validation in a variety of targeted/exome enrichment NGS projects.

A gene expression microarray for Nicotiana benthamiana based on de novo transcriptome sequence assembly.

BACKGROUND: Nicotiana benthamiana has been widely used in laboratories around the world for studying plant-pathogen interactions and posttranscriptional gene expression silencing. Yet the exploration of its transcriptome has lagged behind due to the lack of both adequate sequence information and genome-wide analysis tools, such as DNA microarrays. Despite the increasing use of high-throughput sequencing technologies, the DNA microarrays still remain a popular gene expression tool, because they are cheaper and less demanding regarding bioinformatics skills and computational effort. RESULTS: We designed a gene expression microarray with 103,747 60-mer probes, based on two recently published versions of N. benthamiana transcriptome (v.3 and v.5). Both versions were reconstructed from RNA-Seq data of non-strand-specific pooled-tissue libraries, so we defined the sense strand of the contigs prior to designing the probe. To accomplish this, we combined a homology search against Arabidopsis thaliana proteins and hybridization to a test 244k microarray containing pairs of probes, which represented individual contigs. We identified the sense strand in 106,684 transcriptome contigs and used this information to design an Nb-105k microarray on an Agilent eArray platform. Following hybridization of RNA samples from N. benthamiana roots and leaves we demonstrated that the new microarray had high specificity and sensitivity for detection of differentially expressed transcripts. We also showed that the data generated with the Nb-105k microarray may be used to identify incorrectly assembled contigs in the v.5 transcriptome, by detecting inconsistency in the gene expression profiles, which is indicated using multiple microarray probes that match the same v.5 primary transcripts. CONCLUSIONS: We provided a complete design of an oligonucleotide microarray that may be applied to the research of N. benthamiana transcriptome. This, in turn, will allow the N. benthamiana research community to take full advantage of microarray capabilities for studying gene expression in this plant. Additionally, by defining the sense orientation of over 106,000 contigs, we substantially improved the functional information on the N. benthamiana transcriptome. The simple hybridization-based approach for detecting the sense orientation of computationally assembled sequences can be used for updating the transcriptomes of other non-model organisms, including cases where no significant homology to known proteins exists.

Tabu search algorithm for DNA sequencing by hybridization with isothermic libraries.

In this paper, a problem of isothermic DNA sequencing by hybridization (SBH) is considered. In isothermic SBH a new type of oligonucleotide libraries is used. The library consists of oligonucleotides of different lengths depending on an oligonucleotide content. It is assumed that every oligonucleotide in such a library has an equal melting temperature. Each nucleotide adds its increment to the oligonucleotide temperature and it is assumed that A and T add 2 degrees C and C and G add 4 degrees C. The hybridization experiment using isothermic libraries should provide data with a lower number of errors due to an expected similarity of melting temperatures. From the computational point of view the problem of isothermic DNA sequencing with errors is hard, similarly like its classical counterpart. Hence, there is a need for developing heuristic algorithms that construct good suboptimal solutions. The aim of the paper is to propose a heuristic algorithm based on tabu search approach. The algorithm solves the problem with both positive and negative errors. Results of an extensive computational experiment are presented, which prove the high quality of the proposed method.

Characterization of Sus scrofa small non-coding RNAs present in both female and male gonads.

Small non-coding RNAs (sncRNAs) are indispensable for proper germ cell development, emphasizing the need for greater elucidation of the mechanisms of germline development and regulation of this process by sncRNAs. We used deep sequencing to characterize three families of small non-coding RNAs (piRNAs, miRNAs, and tRFs) present in Sus scrofa gonads and focused on the small RNA fraction present in both male and female gonads. Although similar numbers of reads were obtained from both types of gonads, the number of unique RNA sequences in the ovaries was several times lower. Of the sequences detected in the testes, 2.6% of piRNAs, 9% of miRNAs, and 10% of tRFs were also present in the ovaries. Notably, the majority of the shared piRNAs mapped to ribosomal RNAs and were derived from clustered loci. In addition, the most abundant miRNAs present in the ovaries and testes are conserved and are involved in many biological processes such as the regulation of homeobox genes, the control of cell proliferation, and carcinogenesis. Unexpectedly, we detected a novel sncRNA type, the tRFs, which are 30-36-nt RNA fragments derived from tRNA molecules, in gonads. Analysis of S. scrofa piRNAs show that testes specific piRNAs are biased for 5' uracil but both testes and ovaries specific piRNAs are not biased for adenine at the 10th nucleotide position. These observations indicate that adult porcine piRNAs are predominantly produced by a primary processing pathway or other mechanisms and secondary piRNAs generated by ping-pong mechanism are absent.

An integrated approach (CLuster Analysis Integration Method) to combine expression data and protein-protein interaction networks in agrigenomics: application on Arabidopsis thaliana.

Experimental co-expression data and protein-protein interaction networks are frequently used to analyze the interactions among genes or proteins. Recent studies have investigated methods to integrate these two sources of information. We propose a new method to integrate co-expression data obtained through DNA microarray analysis (MA) and protein-protein interaction (PPI) network data, and apply it to Arabidopsis thaliana. The proposed method identifies small subsets of highly interacting proteins. Based on the analysis of the basis of co-localization and mRNA developmental expression, we show that these groups provide important biological insights; additionally, these subsets are significantly enriched with respect to KEGG Pathways and can be used to predict successfully whether proteins belong to known pathways. Thus, the method is able to provide relevant biological information and support the functional identification of complex genetic traits of economic value in plant agrigenomics research. The method has been implemented in a prototype software tool named CLAIM (CLuster Analysis Integration Method) and can be downloaded from http://bio.cs.put.poznan.pl/research_fields . CLAIM is based on the separate clustering of MA and PPI data; the clusters are merged in a special graph; cliques of this graph are subsets of strongly connected proteins. The proposed method was successfully compared with existing methods. CLAIM appears to be a useful semi-automated tool for protein functional analysis and warrants further evaluation in agrigenomics research.

Whole genome assembly from 454 sequencing output via modified DNA graph concept.

Recently, 454 Life Sciences Corporation proposed a new biochemical approach to DNA sequencing (the 454 sequencing). It is based on the pyrosequencing protocol. The 454 sequencing aims to give reliable output at a low cost and in a short time. The produced sequences are shorter than reads produced by classical methods. Our paper proposes a new DNA assembly algorithm which deals well with such data and outperforms other assembly algorithms used in practice. The constructed SR-ASM algorithm is a heuristic method based on a graph model, the graph being a modified DNA graph proposed for DNA sequencing by hybridization procedure. Other new features of the assembly algorithm are, among others, temporary compression of input sequences, and a new and fast multiple alignment heuristics taking advantage of the way the output data for the 454 sequencing are presented and coded. The usefulness of the algorithm has been proved in tests on raw data generated during sequencing of the whole 1.84Mbp genome of Prochlorococcus marinus bacteria and also on a part of chromosome 15 of Homo sapiens. The source code of SR-ASM can be downloaded from http://bio.cs.put.poznan.pl/ in the section 'Current research'--> 'DNA Assembly'. Among publicly available assemblers our algorithm appeared to generate the best results, especially in the number of produced contigs and in the lengths of the contigs with high similarity to the genome sequence.