Sequence Alignment Tools Research Articles

Absence of GATA4 Mutations in Moroccan Patients with Atrial Septal Defect (ASD) Provides Further Evidence of Limited Involvement of GATA4 in Major Congenital Heart Defects.

Atrial septal defect (ASD) is one of the most common types of congenital heart disease (CHD). It is mainly caused by mutations of NK2 homeobox 5, GATA binding protein 4 (GATA4), and myosin heavy chain 6 in non-syndromic cases. This study aims to carry out, for the first time, the GATA4 mutation screening in a Moroccan population affected by ASD and compare the obtained mutation rate across populations. A total of 33 patients were enrolled in this study. DNAs were extracted from peripheral blood samples, and we performed PCR-sequencing for GATA4 coding regions. Sequences were analyzed by sequence alignment and functional impact prediction tools. Mutation rate comparisons were performed by R software using the appropriate statistical tests. We detected 7 variants, but no pathogenic mutation was revealed, except for Asn352= that was assessed by human splicing finder algorithms to have a potential impairing effect on the splicing mechanism. Until proven by in vitro functional studies, the current pathogenic mutation rate in our cohort seems to be 0%. Statistical comparison with previous studies from all over the world shows no significant difference. Seemingly, comparison of previous GATA4 mutation rates among tetralogy of Fallot (TOF) populations shows no significant difference. The low rates of GATA4 mutations observed throughout ASD and TOF international populations may suggest a limited causality of GATA4 mutations in the main CHDs, which further confirms the co-involvement of additional genetic and/or environmental factors in the manifestation of these phenotypes.

Abstract 2130: Human papillomavirus and hepatitis B virus in situ tumor oncoviral genotype and coinfection drive oncogenesis and patient clinical response in cross cancer analysis

Abstract Genotype of hepatitis B virus (HBV) and human papillomavirus (HPV) infection is well known as a significant risk factor in developing liver (HCC), cervical, and head and neck cancers. However, the effect of tumor viral genotype and single-virus coinfection in driving oncogenesis and striating patient survival is generally unclear, as previous studies have not exhaustively genotyped viral-cofactors or profiled viral gene expression in tumors. In this work, we develop and deploy a new scalable, high throughput dynamic sequence alignment tool that facilitates extremely sensitive and precise oncoviral genotype deconvolution using tumor RNA sequencing data from 536 virally infected liver, cervical, and head and neck tumors across several cohorts. Pairing these results with tumor gene expression and survival analyses, we find HBV genotype C (HBV-C) associated HCC patients (n=79) are significantly upregulated in cancer proliferation and decreased cancer survival (FDR<0.01) compared to HBV genotype B associated tumors (n=23). Across 3 liver cancer cohorts, oncogenes TERT, MLL4, and FN1 are found recurrently integrated in HBV-C but not HBV-B. HPV clade a9 infected cervical cancers (n=173) are associated with more aggressive tumor growth and worse survival than HPV clade a7 (n=39) infected tumors (FDR<0.01), and are enriched in COSMIC mutational signatures linked with defective DNA repair and hypermutation. Furthermore, we demonstrate that HPV coinfection may drive patient response as neoantigens from cervical tumors with multiple HPV infections (n=18) are more immunogenic on average than single-infection tumors (n=23), controlling for HPV genotype (p<0.001). Finally, we compare HPV gene expression in cervical and head and neck patients, demonstrating that HPV genotype drives viral gene expression over cancer type (p<0.0001), and indicating viral protein expression may be similar across episomal and integration-based infections. Our results illustrate that HBV and HPV genotype, and coinfection of tumor with multiple genotypes, serve as significant predictors of patient survival and tumor immune responsiveness, and should be considered alongside clinical covariates to improve survival and treatment models. Citation Format: Adrian P. Bubie, Barbara Testoni, Fabien Zoulim, Brett Miles, Marshall Posner, Augusto Villanueva, Bojan Losic. Human papillomavirus and hepatitis B virus in situ tumor oncoviral genotype and coinfection drive oncogenesis and patient clinical response in cross cancer analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2130.

Detection of Dengue Virus-Specific IgM and IgG Antibodies through Peptide Sequences of Envelope and NS1 Proteins for Serological Identification

Dengue is an acute febrile illness caused by positive-sense single-stranded RNA virus, belonging to the family Flaviviridae and genus Flavivirus. Transmission of virus among the individuals occurred by blood-feeding Aedes mosquitoes. This virus has four serotypes differentiated on the basis of antibody neutralization assay. At present, there is no particular treatment or vaccine candidate available for dengue infection. Approximately 3.9 billion human populations are at risk of dengue virus (DENV) infection. Thus, precise diagnosis of dengue at the early stage is very essential for disease control and effective therapy in order to treat or prevent severe complications. Indeed, the accurate diagnosis of DENV remains a problem because of low detection accuracy along with high testing price. Sensitivity and specificity of available kits vary from test to test, and cross-reactivity with other Flavivirus is a challenging issue for diagnosis. In this study, linear epitopes of envelope (E) and NS1 proteins were identified to diagnose the DENV. Whole protein sequences of E and NS1 of DENV were obtained from UniProtKB database. On the basis of algorithm prediction from DNASTAR, BCEPRED, and IEDB data resources, twelve peptides of E (EP1 to EP12) and eight peptides of NS1 (NS1-1 to NS1-8) were selected, which were common in all serotypes. Sequence homologies of peptides with other Flavivirus were checked by Multiple Sequence Alignment Tool ClustalX2. Peptide sequences were synthesized chemically by solid-phase peptide synthesis technique. Dengue-specific IgM and IgG (secondary response) antibodies in the patient's antisera were tested with the peptides using ELISA protocol. Peptides EP1, EP2, EP4, EP7, EP10, and EP12 of E protein and NS1-1, NS1-3, NS1-4, NS1-7, and NS1-8 of NS1 protein were considered the best immunoreactive peptides with the sensitivity (73.33-96.66%) and specificity (82.14-100%). Such peptides together can be used to construct the multiple antigen peptides (MAP) or multiplexed microbeads for designing a precise, cost-effective, and easy-to-make peptide-based immunodiagnostic kit for DENV detection.

Evolving geographic diversity in SARS-CoV2 and in silico analysis of replicating enzyme 3CLpro targeting repurposed drug candidates

BackgroundSevere acute respiratory syndrome (SARS) has been initiating pandemics since the beginning of the century. In December 2019, the world was hit again by a devastating SARS episode that has so far infected almost four million individuals worldwide, with over 200,000 fatalities having already occurred by mid-April 2020, and the infection rate continues to grow exponentially. SARS coronavirus 2 (SARS-CoV-2) is a single stranded RNA pathogen which is characterised by a high mutation rate. It is vital to explore the mutagenic capability of the viral genome that enables SARS-CoV-2 to rapidly jump from one host immunity to another and adapt to the genetic pool of local populations.MethodsFor this study, we analysed 2301 complete viral sequences reported from SARS-CoV-2 infected patients. SARS-CoV-2 host genomes were collected from The Global Initiative on Sharing All Influenza Data (GISAID) database containing 9 genomes from pangolin-CoV origin and 3 genomes from bat-CoV origin, Wuhan SARS-CoV2 reference genome was collected from GeneBank database. The Multiple sequence alignment tool, Clustal Omega was used for genomic sequence alignment. The viral replicating enzyme, 3-chymotrypsin-like cysteine protease (3CLpro) that plays a key role in its pathogenicity was used to assess its affinity with pharmacological inhibitors and repurposed drugs such as anti-viral flavones, biflavanoids, anti-malarial drugs and vitamin supplements.ResultsOur results demonstrate that bat-CoV shares > 96% similar identity, while pangolin-CoV shares 85.98% identity with Wuhan SARS-CoV-2 genome. This in-depth analysis has identified 12 novel recurrent mutations in South American and African viral genomes out of which 3 were unique in South America, 4 unique in Africa and 5 were present in-patient isolates from both populations. Using state of the art in silico approaches, this study further investigates the interaction of repurposed drugs with the SARS-CoV-2 3CLpro enzyme, which regulates viral replication machinery.ConclusionsOverall, this study provides insights into the evolving mutations, with implications to understand viral pathogenicity and possible new strategies for repurposing compounds to combat the nCovid-19 pandemic.

Memory-Optimized Wavefront Parallelism on GPUs

Wavefront parallelism is a well-known technique for exploiting the concurrency of applications that execute nested loops with uniform data dependencies. Recent research of such applications, which range from sequence alignment tools to partial differential equation solvers, has used GPUs to benefit from the massively parallel computing resources. To achieve optimal performance, tiling has been introduced as a popular solution to achieve a balanced workload. However, the use of hyperplane tiles increases the cost of synchronization and leads to poor data locality. In this paper, we present a highly optimized implementation of the wavefront parallelism technique that harnesses the GPU architecture. A balanced workload and maximum resource utilization are achieved with an extremely low synchronization overhead. We design the kernel configuration to significantly reduce the minimum number of synchronizations required and also introduce an inter-block lock to minimize the overhead of each synchronization. In addition, shared memory is used in place of the L1 cache. The well-tailored mapping of the operations to the shared memory improves both spatial and temporal locality. We evaluate the performance of our proposed technique for four different applications: sequence alignment, edit distance, summed-area table, and 2D-SOR. The performance results demonstrate that our method achieves speedups of up to six times compared to the previous best-known hyperplane tiling-based GPU implementation.

E-PROBCONS: Enhanced PROBCONS for Multiple Sequence Alignment

Abstract— the perfect alignment between three or more sequences of protein, RNA or DNA is a very difficult task in Bioinformatics. There are many techniques for alignment of multiple sequences. Many techniques enlarge speed and do not have a concern with the accuracy of the resulting alignment. However, other techniques heighten accuracy and do not have a concern with the speed. The vital goals of any technique are (a) reducing memory and execution time requirements, and (b) increasing the accuracy of multiple sequence alignment on large-scale datasets. PROBCONS is a multiple protein sequence alignment (MPSA) tool that achieves the most expected accuracy, but it has a time-consuming problem. To solve this problem and enlarging the accuracy of the MPSA, E-PROBCONS is proposed to enhance PROBCONS tool. E- PROBCONS cluster the large multiple protein sequences into structurally similar protein sequences. Then PROBCONS MPSA tool will be performed in parallel on the Amazon Elastic Cloud (EC2). The proposed approaches are more suitable for large-scale data sets and short sequences. Comparing with algorithms (e.g., PROBCONS, KALIGN, and HALIGN I), provided more than 50% improvement in terms of average sum of pairs alignment scores (SPscores) and reduce the execution time for producing the alignment result. The proposed approaches are implemented on big data framework Hadoop Map-Reduce platform in order to improve the scalability with different protein datasets.

Structural, glycosylation and antigenic variation between 2019 novel coronavirus (2019-nCoV) and SARS coronavirus (SARS-CoV).

The emergence of 2019 novel coronavirus (2019-nCoV) is of global concern and might have emerged from RNA recombination among existing coronaviruses. CoV spike (S) protein which is crucial for receptor binding, membrane fusion via conformational changes, internalization of the virus, host tissue tropism and comprises crucial targets for vaccine development, remain largely uncharacterized. Therefore, the present study has been planned to determine the sequence variation, structural and antigenic divergence of S glycoprotein which may be helpful for the management of 2019-nCoV infection. The sequences of spike glycoprotein of 2019-nCoV and SARS coronavirus (SARS-CoV) were used for the comparison. The sequence variations were determined using EMBOSS Needle pairwise sequence alignment tools. The variation in glycosylation sites was predicted by NetNGlyc 1.0 and validated by N-GlyDE server. Antigenicity was predicted by NetCTL 1.2 and validated by IEDB Analysis Resource server. The structural divergence was determined by using SuperPose Version 1.0 based on cryo-EM structure of the SARS coronavirus spike glycoprotein. Our data suggests that 2019-nCoV is newly spilled coronavirus into humans in China is closely related to SARS-CoV, which has only 12.8% of difference with SARS-CoV in S protein and has 83.9% similarity in minimal receptor-binding domain with SARS-CoV. Addition of a novel glycosylation sites were observed in 2019-nCoV. In addition, antigenic analysis proposes that great antigenic differences exist between both the viral strains, but some of the epitopes were found to be similar between both the S proteins. In spite of the variation in S protein amino acid composition, we found no significant difference in their structures. Collectively, for the first time our results exhibit the emergence of human 2019-nCoV is closely related to predecessor SARS-CoV and provide the evidence that 2019-nCoV uses various novel glycosylation sites as SARS-CoV and may have a potential to become pandemic owing its antigenic discrepancy. Further, demonstration of novel Cytotoxic T lymphocyte epitopes may impart opportunities for the development of peptide based vaccine for the prevention of 2019-nCoV.

GSAlign: an efficient sequence alignment tool for intra-species genomes

BackgroundPersonal genomics and comparative genomics are becoming more important in clinical practice and genome research. Both fields require sequence alignment to discover sequence conservation and variation. Though many methods have been developed, some are designed for small genome comparison while some are not efficient for large genome comparison. Moreover, most existing genome comparison tools have not been evaluated the correctness of sequence alignments systematically. A wrong sequence alignment would produce false sequence variants.ResultsIn this study, we present GSAlign that handles large genome sequence alignment efficiently and identifies sequence variants from the alignment result. GSAlign is an efficient sequence alignment tool for intra-species genomes. It identifies sequence variations from the sequence alignments. We estimate performance by measuring the correctness of predicted sequence variations. The experiment results demonstrated that GSAlign is not only faster than most existing state-of-the-art methods, but also identifies sequence variants with high accuracy.ConclusionsAs more genome sequences become available, the demand for genome comparison is increasing. Therefore an efficient and robust algorithm is most desirable. We believe GSAlign can be a useful tool. It exhibits the abilities of ultra-fast alignment as well as high accuracy and sensitivity for detecting sequence variations.

RNAconTest: comparing tools for noncoding RNA multiple sequence alignment based on structural consistency.

The importance of noncoding RNA sequences has become increasingly clear over the past decade. New RNA families are often detected and analyzed using comparative methods based on multiple sequence alignments. Accordingly, a number of programs have been developed for aligning and deriving secondary structures from sets of RNA sequences. Yet, the best tools for these tasks remain unclear because existing benchmarks contain too few sequences belonging to only a small number of RNA families. RNAconTest (RNA consistency test) is a new benchmarking approach relying on the observation that secondary structure is often conserved across highly divergent RNA sequences from the same family. RNAconTest scores multiple sequence alignments based on the level of consistency among known secondary structures belonging to reference sequences in their output alignment. Similarly, consensus secondary structure predictions are scored according to their agreement with one or more known structures in a family. Comparing the performance of 10 popular alignment programs using RNAconTest revealed that DAFS, DECIPHER, LocARNA, and MAFFT created the most structurally consistent alignments. The best consensus secondary structure predictions were generated by DAFS and LocARNA (via RNAalifold). Many of the methods specific to noncoding RNAs exhibited poor scalability as the number or length of input sequences increased, and several programs displayed substantial declines in score as more sequences were aligned. Overall, RNAconTest provides a means of testing and improving tools for comparative RNA analysis, as well as highlighting the best available approaches. RNAconTest is available from the DECIPHER website (http://DECIPHER.codes/Downloads.html).

The Emerging Role of Rhinoviruses in Lower Respiratory Tract Infections in Children - Clinical and Molecular Epidemiological Study From Croatia, 2017-2019.

Rhinoviruses (RVs) are increasingly implicated not only in mild upper respiratory tract infections, but also in more severe lower respiratory tract infections; however, little is known about species diversity and viral epidemiology of RVs among the infected children. Therefore, we investigated the rhinovirus (RV) infection prevalence over a 2-year period, compared it with prevalence patterns of other common respiratory viruses, and explored clinical and molecular epidemiology of RV infections among 590 children hospitalized with acute respiratory infection in north-western and central parts of Croatia. For respiratory virus detection, nasopharyngeal and pharyngeal flocked swabs were taken from each patient and subsequently analyzed with multiplex RT-PCR. To determine the RV species in a subset of positive children, 5′UTR in RV-positive samples has been sequenced. Nucleotide sequences of referent RV strains were retrieved by searching the database with Basic Local Alignment Tool, and used to construct alignments and phylogenetic trees using MAFFT multiple sequence alignment tool and the maximum likelihood method, respectively. In our study population RV was the most frequently detected virus, diagnosed in 197 patients (33.4%), of which 60.4% was detected as a monoinfection. Median age of RV-infected children was 2.25 years, and more than half of children infected with RV (55.8%) presented with lower respiratory tract infections. Most RV cases were detected from September to December, and all three species co-circulated during the analyzed period (2017–2019). Sequence analysis based on 5′UTR region yielded 69 distinct strains; the most prevalent was RV-C (47.4%) followed by RV-A (44.7%) and RV-B (7.9%). Most of RV-A sequences formed a distinct phylogenetic group; only strains RI/HR409-18 (along with a reference strain MF978777) clustered with RV-C strains. Strains belonging to the group C were the most diverse (41.6% identity among strains), while group B was the most conserved (71.5% identity among strains). Despite such differences in strain groups (hitherto undescribed in Croatia), clinical presentation of infected children was rather similar. Our results are consistent with newer studies that investigated the etiology of acute respiratory infections, especially those focused on children with lower respiratory tract infections, where RVs should always be considered as potentially serious pathogens.

Towards Exploring Toxin-Antitoxin Systems in Geobacillus: A Screen for Type II Toxin-Antitoxin System Families in a Thermophilic Genus.

The toxin-antitoxin (TA) systems have been attracting attention due to their role in regulating stress responses in prokaryotes and their biotechnological potential. Much recognition has been given to type II TA system of mesophiles, while thermophiles have received merely limited attention. Here, we are presenting the putative type II TA families encoded on the genomes of four Geobacillus strains. We employed the TA finder tool to mine for TA-coding genes and manually curated the results using protein domain analysis tools. We also used the NCBI BLAST, Operon Mapper, ProOpDB, and sequence alignment tools to reveal the geobacilli TA features. We identified 28 putative TA pairs, distributed over eight TA families. Among the identified TAs, 15 represent putative novel toxins and antitoxins, belonging to the MazEF, MNT-HEPN, ParDE, RelBE, and XRE-COG2856 TA families. We also identified a potentially new TA composite, AbrB-ParE. Furthermore, we are suggesting the Geobacillus acetyltransferase TA (GacTA) family, which potentially represents one of the unique TA families with a reverse gene order. Moreover, we are proposing a hypothesis on the xre-cog2856 gene expression regulation, which seems to involve the c-di-AMP. This study aims for highlighting the significance of studying TAs in Geobacillus and facilitating future experimental research.

Modeling Transient Myeloproliferative Disorder Using Induced Pluripotent Stem Cells and CRISPR/Cas9 Technology

Down syndrome (DS) is recognized as one of the most important leukemia-predisposing syndromes. Specifically, 1-2% of DS children develop acute myeloid leukemia (AML) prior to age 5. AML in DS children (DS-AML) is characterized by the pathognomonic mutation in the gene encoding the essential hematopoietic transcription factor GATA1, resulting in N-terminally truncated mutant GATA1 (GATA1s). Trisomy 21 and GATA1s together induce a transient myeloproliferative disorder (TMD) exhibiting pre-leukemic characteristics. Approximately thirty percent of these cases progress into DS-AML by acquisition of additional somatic mutations in a step-wise manner. We employed disease modeling in vitro by the use of customizable induced pluripotent stem cells (iPSCs) (7, 8) to generate a TMD model. Isogenic iPSC lines derived from the fibroblasts of a DS patient with trisomy 21 and with disomy 21 were used. We also obtained DS2-iPS10 (iPSCs derived from DS patient fibroblast) from Prof. George Daley, Children's Hospital, Harvard University (Boston, MA). CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas9 system with the indicated guide sequence (Fig. 1A) was used to introduce clinically relevant GATA1 mutation in both disomic and trisomic iPSC lines. A representative plot of TIDE (Tracking of Indels by Decomposition) analysis showing 98% allelic mutation frequency of a clone with 2 bp deletion at chromosomal level (Fig. 1B) correlated with sequence analysis using Basic Local Sequence Alignment Tool (BLAST) and Sanger sequencing chromatogram (Fig. 1C). This mutation resulted in the disruption of first initiation codon and thus prevented the production of full length GATA1 protein, while allowing the usage of second initiation codon at 84th position to generate GATA1s. GATA1 and GATA1s are not expressed in iPSCs. To determine the expression of GATA1s, we differentiated these mutant iPSC lines into hematopoietic stem cell progenitors (HSPCs) using hematopoietic differentiation kit (StemCell Technologies) following a protocol depicted in Fig. 1D. The HSPCs derived from two distinct clones of trisomic iPSCs showed expression of full-length GATA1 protein and GATA1 mutant HSPCs lacked the expression of full-length GATA1 as expected (Fig. 1E). These HSPCs expressed GATA1s. Given that trisomy 21 promotes hematopoietic differentiation, an increase in the percentage of erythroid, megakaryoid and myeloid population was observed in trisomy 21 HSPCs with full length GATA1 (Fig. 1F, compare bars 1 and 3 in each category). The expression of GATA1s reduced erythroid lineage cells whereas it augmented megakaryoid and myeloid lineages in both disomy 21 (compare red and blue bars 1 and 2) and trisomy 21 backgrounds (compare bars 3 and 4). HSPCs derived from trisomy 21 iPSCs with GATA1s exhibited more megakaryoid expansion compared to the GATA1s in disomy 21 background (Fig. 1F, compare bars 2 and 4), in agreement with the synergistic function of trisomy 21 and GATA1s in promoting TMD. Transplantation of HSPCs derived from GATA1 mutated trisomic iPSCS into NSG-SGM3 mice showed the presence of human CD45+ cells in peripheral blood at 12 weeks post cell injection (Fig. 1G). In conclusion, we have developed a model system representing TMD, which can be used for step-wise modeling of Down-syndrome AML by introducing additional mutations. Figure 1 Disclosures No relevant conflicts of interest to declare.

GenGraph: a python module for the simple generation and manipulation of genome graphs

BackgroundAs sequencing technology improves, the concept of a single reference genome is becoming increasingly restricting. In the case of Mycobacterium tuberculosis, one must often choose between using a genome that is closely related to the isolate, or one that is annotated in detail. One promising solution to this problem is through the graph based representation of collections of genomes as a single genome graph. Though there are currently a handful of tools that can create genome graphs and have demonstrated the advantages of this new paradigm, there still exists a need for flexible tools that can be used by researchers to overcome challenges in genomics studies.ResultsWe present GenGraph, a Python toolkit and accompanying modules that use existing multiple sequence alignment tools to create genome graphs. Python is one of the most popular coding languages for the biological sciences, and by providing these tools, GenGraph makes it easier to experiment and develop new tools that utilise genome graphs. The conceptual model used is highly intuitive, and as much as possible the graph structure represents the biological relationship between the genomes. This design means that users will quickly be able to start creating genome graphs and using them in their own projects. We outline the methods used in the generation of the graphs, and give some examples of how the created graphs may be used. GenGraph utilises existing file formats and methods in the generation of these graphs, allowing graphs to be visualised and imported with widely used applications, including Cytoscape, R, and Java Script.ConclusionsGenGraph provides a set of tools for generating graph based representations of sets of sequences with a simple conceptual model, written in the widely used coding language Python, and publicly available on Github.

CCM1 and CCM2 variants in patients with cerebral cavernous malformation in an ethnically Chinese population in Taiwan

Cerebral cavernous malformation (CCM) is a vascular malformation characterized by clustered enlarged capillary-like channels in the central nervous system. The genes harboring variants in patients with CCM include CCM1/Krev interaction trapped-1, CCM2/MGC4607, and CCM3/programmed cell death protein 10. We aimed to identify pathogenic variants in an ethnic Chinese population in Taiwan. We recruited 95 patients with multiple CCMs or a single lesion with a relevant family history. Sanger sequencing was performed for 41 patients. Variants were identified using sequence alignment tools, and the clinical significance of these variants was determined using American College of Medical Genetics and Genomics standards and guidelines. Several pathogenic variants were found in six patients, including three unrelated patients and three affected members of one family. Two novel pathogenic variants leading to early truncation comprised a deletion variant in exon 18 of CCM1 (c.1846delA; p.Glu617LysfsTer44) and an insertion variant in exon 4 of CCM2 (c.401_402insGCCC; p.Ile136AlafsTer4). One novel pathogenic splice site variant was c.485 + 1G > C at the beginning of intron 8 of CCM1. In this study, we identified novel variants related to CCM in an ethnically Chinese population in Taiwan.

Exploring efficient data parallelism for genome read mapping on multicore and manycore architectures

Nowadays heterogeneous architectures formed by multicore and manycore systems have become attractive solutions to cope with the data booming in genomic-based studies. Our work explores the efficient usage of heterogeneous architectures in such area. In particular, we have studied the use of manycore components like the Xeon Phi accelerator, which has proved to be a convenient choice because it allows an easy migration of applications developed for multicore servers based on the × 86 architecture. Our study also focuses on the problem of sequence alignment, which is one of the fundamental and most costly computational stages in most genome variant studies. We concentrate our attention on BWA, one of the most popular sequence aligners, and we have focused our attention on three types of heterogeneous systems, one containing Intel multi-core CPUs and accelerators, one that are made up of several multi-core servers, and one large-scale system. Each with different characteristics in terms of number of CPUs, number of cores and system organization memory. Although the problem of alignment of sequences fits in the embarrassingly parallel pattern, achieving good performance and good scalability in heterogeneous environments can be complex. We have analyzed different strategies based on the distribution of data and the replication of certain data structures and we found that MDPR (Multi-level Data Parallelization and Replication) strategy has shown the best results in all the heterogeneous platforms tested. Its results have surpassed other strategies proposed in the literature and have shown its malleability to be used in different heterogeneous environments without the need to apply specific adjustments according to the underlying architecture. In the design of MDPR, different static and dynamic data distribution strategies have also been evaluated. The best results were obtained by the static strategy, which has a significant preprocessing cost. However, the dynamic strategy of data distribution using a round-robin mechanism obtained similar times without the need for the preprocessing stage. Although our proposal was applied to BWA using human genome data samples, this strategy can be easily applied to other sequence datasets and alignment tools that have similar operating principles with those of BWA aligner.

MAFFT-DASH: integrated protein sequence and structural alignment.

Here, we describe a web server that integrates structural alignments with the MAFFT multiple sequence alignment (MSA) tool. For this purpose, we have prepared a web-based Database of Aligned Structural Homologs (DASH), which provides structural alignments at the domain and chain levels for all proteins in the Protein Data Bank (PDB), and can be queried interactively or by a simple REST-like API. MAFFT-DASH integration can be invoked with a single flag on either the web (https://mafft.cbrc.jp/alignment/server/) or command-line versions of MAFFT. In our benchmarks using 878 cases from the BAliBase, HomFam, OXFam, Mattbench and SISYPHUS datasets, MAFFT-DASH showed 10–20% improvement over standard MAFFT for MSA problems with weak similarity, in terms of Sum-of-Pairs (SP), a measure of how well a program succeeds at aligning input sequences in comparison to a reference alignment. When MAFFT alignments were supplemented with homologous sequences, further improvement was observed. Potential applications of DASH beyond MSA enrichment include functional annotation through detection of remote homology and assembly of template libraries for homology modeling.

Pblat: a multithread blat algorithm speeding up aligning sequences to genomes

BackgroundThe blat is a widely used sequence alignment tool. It is especially useful for aligning long sequences and gapped mapping, which cannot be performed properly by other fast sequence mappers designed for short reads. However, the blat tool is single threaded and when used to map whole genome or whole transcriptome sequences to reference genomes this program can take days to finish, making it unsuitable for large scale sequencing projects and iterative analysis. Here, we present pblat (parallel blat), a parallelized blat algorithm with multithread and cluster computing support, which functions to rapidly fine map large scale DNA/RNA sequences against genomes.ResultsThe pblat algorithm takes advantage of modern multicore processors and significantly reduces the run time with the number of threads used. pblat utilizes almost equal amount of memory as when running blat. The results generated by pblat are identical with those generated by blat. The pblat tool is easy to install and can run on Linux and Mac OS systems. In addition, we provide a cluster version of pblat (pblat-cluster) running on computing clusters with MPI support.Conclusionpblat is open source and free available for non-commercial users. It is easy to install and easy to use. pblat and pblat-cluster would facilitate the high-throughput mapping of large scale genomic and transcript sequences to reference genomes with both high speed and high precision.

PMBD: a Comprehensive Plastics Microbial Biodegradation Database.

Since the invention over a hundred years ago, plastics have been used in many applications, and they are involved in every aspect of our lives. The extensive usage of plastics results in a tremendous amount of waste, which has become a severe burden on the environment. Several degradation approaches exist in nature to cope with ever-increasing plastic waste. Among these approaches, biodegradation by microorganisms has emerged as a natural way, which is favored by many environmentally conscious societies. To facilitate the study on biodegradation of plastics, we developed an online resource, Plastics Microbial Biodegradation Database (PMBD), to gather and present the information about microbial biodegradation of plastics. In this database, 949 microorganisms–plastics relationships and 79 genes involved in the biodegradation of plastics were manually collected and confirmed through literature searching. In addition, more than 8000 automatically annotated enzyme sequences, which were predicted to be involved in the plastics biodegradation, were extracted from the TrEMBL section of the UniProt database. The PMBD database is presented with a website at http://pmbd.genome-mining.cn/home. Data may be accessed through browsing or searching. Also included on the website are a sequence alignment tool and a function prediction tool.

Using Rosetta for RNA homology modeling.

The three-dimensional structures of RNA molecules provide rich and often critical information for understanding their functions, including how they recognize small molecule and protein partners. Computational modeling of RNA 3D structure is becoming increasingly accurate, particularly with the availability of growing numbers of template structures already solved experimentally and the development of sequence alignment and 3D modeling tools to take advantage of this database. For several recent "RNA puzzle" blind modeling challenges, we have successfully identified useful template structures and achieved accurate structure predictions through homology modeling tools developed in the Rosetta software suite. We describe our semi-automated methodology here and walk through two illustrative examples: an adenine riboswitch aptamer, modeled from a template guanine riboswitch structure, and a SAM I/IV riboswitch aptamer, modeled from a template SAM I riboswitch structure.

SAliBASE: A Database of Simulated Protein Alignments.

Simulated alignments are alternatives to manually constructed multiple sequence alignments for evaluating performance of multiple sequence alignment tools. The importance of simulated sequences is recognized because their true evolutionary history is known, which is very helpful for reconstructing accurate phylogenetic trees and alignments. However, generating simulated alignments require expertise to use bioinformatics tools and consume several hours for reconstructing even a few hundreds of simulated sequences. It becomes a tedious job for an end user who needs a few datasets of variety of simulated sequences. Currently, there is no databank available which may help researchers to download simulated sequences/alignments for their study. Major focus of our study was to develop a database of simulated protein sequences (SAliBASE) based on different varying parameters such as insertion rate, deletion rate, sequence length, number of sequences, and indel size. Each dataset has corresponding alignment as well. This repository is very useful for evaluating multiple alignment methods.