Sequencing Data Analysis Pipeline Research Articles

Virome characterization and identification of a putative parvovirus and poxvirus in bat ectoparasites of Yunnan Province, China

Ectoparasites found on bats are known to contain important microbes. However, the viruses hosted by these obligate parasites are understudied. This has led to the near oversight of the potential role of these ectoparasites in virus maintenance and transmission from bats to other interacting species and the environment. Here, we sampled bat ectoparasites parasitizing a diverse selection of bat species in the families Rhinolophidae, Vespertilionidae, Megadermatidae, Hipposideridae and Pteropodidae in Yunnan Province, China. We show that the ectoparasite prevalence was generally higher in male compared to female bats. Most ectoparasites were found to fall within the Nycteribiidae, Spinturnicidae and Streblidae bat ectoparasite families. We subsequently applied a non-biased sequencing of libraries prepared from the pooled ectoparasites, followed by an in-silico virus-centric analysis of the resultant reads. We show that ectoparasites hosted by the sampled families of bats are found to carry, in addition to a diverse set of phages, vertebrate and insect viruses in the families Aliusviridae, Ascoviridae, Chuviridae, Circoviridae, Flaviviridae, Hepadnaviridae, Hepeviridae, Herpesviridae, Iridoviridae, Marseilleviridae, Nairoviridae, Orthomyxoviridae, Parvoviridae, Poxviridae, Reoviridae, Retroviridae, and Rhabdoviridae. We further report a partial Parvovirus VP1/VP2 gene and partial Poxvirus ubiquitin-like gene predicted by two independent next generation sequencing data analysis pipelines. This study describes the natural virome of bat ectoparasites, providing a platform for understanding the role these ectoparasites play in the maintenance and spread of viruses to other animals.

Whole exome sequencing reveals novel risk genes of pituitary neuroendocrine tumors.

Somatic genetic alterations in pituitary neuroendocrine tumors (PitNET) tissues have been identified in several studies, but detection of overlapping somatic PitNET candidate genes is rare. We sequenced and by employing multiple data analysis methods studied the exomes of 15 PitNET patients to improve discovery of novel factors involved in PitNET development. PitNET patients were recruited to the study before PitNET removal surgery. For each patient, two samples for DNA extraction were acquired: venous blood and PitNET tissue. Exome sequencing was performed using Illumina NexSeq 500 sequencer and data analyzed using two separate workflows and variant calling algorithms: GATK and Strelka2. A combination of two data analysis pipelines discovered 144 PitNET specific somatic variants (mean = 9.6, range 0-19 per PitNET) of which all were SNVs. Also, we detected previously known GNAS PitNET mutation and identified somatic variants in 11 genes, which have contained somatic variants in previous WES and WGS studies of PitNETs. Noteworthy, this is the third study detecting somatic variants in gene RYR1 in the exomes of PitNETs. In conclusion, we have identified two novel PitNET candidate genes (AC002519.6 and AHNAK) with recurrent somatic variants in our PitNET cohort and found 13 genes overlapping from previous PitNET studies that contain somatic variants. Our study demonstrated that the use of multiple sequencing data analysis pipelines can provide more accurate identification of somatic variants in PitNETs.

GenomeSidekick: A user-friendly epigenomics data analysis tool.

Recent advances in epigenomics measurements have resulted in a preponderance of genomic sequencing datasets that require focused analyses to discover mechanisms governing biological processes. In addition, multiple epigenomics experiments are typically performed within the same study, thereby increasing the complexity and difficulty of making meaningful inferences from large datasets. One gap in the sequencing data analysis pipeline is the availability of tools to efficiently browse genomic data for scientists that do not have bioinformatics training. To bridge this gap, we developed genomeSidekick, a graphical user interface written in R that allows researchers to perform bespoke analyses on their transcriptomic and chromatin accessibility or chromatin immunoprecipitation data without the need for command line tools. Importantly, genomeSidekick outputs lists of up- and downregulated genes or chromatin features with differential accessibility or occupancy; visualizes omics data using interactive volcano plots; performs Gene Ontology analyses locally; and queries PubMed for selected gene candidates for further evaluation. Outputs can be saved using the user interface and the code underlying genomeSidekick can be edited for custom analyses. In summary, genomeSidekick brings wet lab scientists and bioinformaticians into a shared fluency with the end goal of driving mechanistic discovery.

Unveiling forensically relevant biogeographic, phenotype and Y-chromosome SNP variation in Pakistani ethnic groups using a customized hybridisation enrichment forensic intelligence panel.

Massively parallel sequencing following hybridisation enrichment provides new opportunities to obtain genetic data for various types of forensic testing and has proven successful on modern as well as degraded and ancient DNA. A customisable forensic intelligence panel that targeted 124 SNP markers (67 ancestry informative markers, 23 phenotype markers from the HIrisplex panel, and 35 Y-chromosome SNPs) was used to examine biogeographic ancestry, phenotype and sex and Y-lineage in samples from different ethnic populations of Pakistan including Pothwari, Gilgit, Baloach, Pathan, Kashmiri and Siraiki. Targeted sequencing and computational data analysis pipeline allowed filtering of variants across the targeted loci. Study samples showed an admixture between East Asian and European ancestry. Eye colour was predicted accurately based on the highest p-value giving overall prediction accuracy of 92.8%. Predictions were consistent with reported hair colour for all samples, using the combined highest p-value approach and step-wise model incorporating probability thresholds for light or dark shade. Y-SNPs were successfully recovered only from male samples which indicates the ability of this method to identify biological sex and allow inference of Y-haplogroup. Our results demonstrate practicality of using hybridisation enrichment and MPS to aid in human intelligence gathering and will open many insights into forensic research in South Asia.

Mycobacterium tuberculosis complex lineage 5 exhibits high levels of within-lineage genomic diversity and differing gene content compared to the type strain H37Rv.

Pathogens of the Mycobacterium tuberculosis complex (MTBC) are considered to be monomorphic, with little gene content variation between strains. Nevertheless, several genotypic and phenotypic factors separate strains of the different MTBC lineages (L), especially L5 and L6 (traditionally termed Mycobacterium africanum) strains, from each other. However, this genome variability and gene content, especially of L5 strains, has not been fully explored and may be important for pathobiology and current approaches for genomic analysis of MTBC strains, including transmission studies. By comparing the genomes of 355 L5 clinical strains (including 3 complete genomes and 352 Illumina whole-genome sequenced isolates) to each other and to H37Rv, we identified multiple genes that were differentially present or absent between H37Rv and L5 strains. Additionally, considerable gene content variability was found across L5 strains, including a split in the L5.3 sub-lineage into L5.3.1 and L5.3.2. These gene content differences had a small knock-on effect on transmission cluster estimation, with clustering rates influenced by the selected reference genome, and with potential overestimation of recent transmission when using H37Rv as the reference genome. We conclude that full capture of the gene diversity, especially high-resolution outbreak analysis, requires a variation of the single H37Rv-centric reference genome mapping approach currently used in most whole-genome sequencing data analysis pipelines. Moreover, the high within-lineage gene content variability suggests that the pan-genome of M. tuberculosis is at least several kilobases larger than previously thought, implying that a concatenated or reference-free genome assembly (de novo) approach may be needed for particular questions.

Genome analysis of the monoclonal marbled crayfish reveals genetic separation over a short evolutionary timescale

The marbled crayfish (Procambarus virginalis) represents a very recently evolved parthenogenetic freshwater crayfish species that has invaded diverse habitats in Europe and in Madagascar. However, population genetic analyses have been hindered by the homogeneous genetic structure of the population and the lack of suitable tools for data analysis. We have used whole-genome sequencing to characterize reference specimens from various known wild populations. In parallel, we established a whole-genome sequencing data analysis pipeline for the population genetic analysis of nearly monoclonal genomes. Our results provide evidence for systematic genetic differences between geographically separated populations and illustrate the emerging differentiation of the marbled crayfish genome. We also used mark-recapture population size estimation in combination with genetic data to model the growth pattern of marbled crayfish populations. Our findings uncover evolutionary dynamics in the marbled crayfish genome over a very short evolutionary timescale and identify the rapid growth of marbled crayfish populations as an important factor for ecological monitoring.

Cascabel: A Scalable and Versatile Amplicon Sequence Data Analysis Pipeline Delivering Reproducible and Documented Results.

Marker gene sequencing of the rRNA operon (16S, 18S, ITS) or cytochrome c oxidase I (CO1) is a popular means to assess microbial communities of the environment, microbiomes associated with plants and animals, as well as communities of multicellular organisms via environmental DNA sequencing. Since this technique is based on sequencing a single gene, or even only parts of a single gene rather than the entire genome, the number of reads needed per sample to assess the microbial community structure is lower than that required for metagenome sequencing. This makes marker gene sequencing affordable to nearly any laboratory. Despite the relative ease and cost-efficiency of data generation, analyzing the resulting sequence data requires computational skills that may go beyond the standard repertoire of a current molecular biologist/ecologist. We have developed Cascabel, a scalable, flexible, and easy-to-use amplicon sequence data analysis pipeline, which uses Snakemake and a combination of existing and newly developed solutions for its computational steps. Cascabel takes the raw data as input and delivers a table of operational taxonomic units (OTUs) or Amplicon Sequence Variants (ASVs) in BIOM and text format and representative sequences. Cascabel is a highly versatile software that allows users to customize several steps of the pipeline, such as selecting from a set of OTU clustering methods or performing ASV analysis. In addition, we designed Cascabel to run in any linux/unix computing environment from desktop computers to computing servers making use of parallel processing if possible. The analyses and results are fully reproducible and documented in an HTML and optional pdf report. Cascabel is freely available at Github: https://github.com/AlejandroAb/CASCABEL.

De Novo Assembly-Based Analysis of RPGR Exon ORF15 in an Indigenous African Cohort Overcomes Limitations of a Standard Next-Generation Sequencing (NGS) Data Analysis Pipeline.

RPGR exon ORF15 variants are one of the most frequent causes for inherited retinal disorders (IRDs), in particular retinitis pigmentosa. The low sequence complexity of this mutation hotspot makes it prone to indels and challenging for sequence data analysis. Whole-exome sequencing generally fails to provide adequate coverage in this region. Therefore, complementary methods are needed to avoid false positives as well as negative results. In this study, next-generation sequencing (NGS) was used to sequence long-range PCR amplicons for an IRD cohort of African ancestry. By developing a novel secondary analysis pipeline based on de novo assembly, we were able to avoid the miscalling of variants generated by standard NGS analysis tools. We identified pathogenic variants in 11 patients (13% of the cohort), two of which have not been reported previously. We provide a novel and alternative end-to-end secondary analysis pipeline for targeted NGS of ORF15 that is less prone to false positive and negative variant calls.

Effect of Donor Simvastatin Treatment on Gene Expression Profiles in Human Cardiac Allografts during Ischemia-Reperfusion Injury

Numerous studies have shown that statin therapy initiated early after heart transplantation has beneficial effects on the development of cardiac allograft vasculopathy. Recently, we were able to show in a randomized clinical trial that simvastatin treatment of brain-dead donors conditions the heart transplant to withstand ischemia-reperfusion injury and to reduce the need for rejection treatments early after transplantation. In this study, we analyzed myocardial gene expression profiles in cardiac allografts after donor simvastatin treatment. 84 heart transplant donors received 80 mg of simvastatin via nasogastric tube (n=42), or no treatment (n=42) in a prospective, double-blinded randomized controlled trial. Transmural Tru-Cut biopsies were taken from the apex of the donor heart's left ventricle immediately before reperfusion and 1 hour after reperfusion. The transcriptome of the biopsies will be analyzed with RNA sequencing. The preliminary analysis of RNA sequencing data from myocardial biopsies of 20 + 20 patients revealed altogether 137 significantly differentially expressed genes in all pairwise comparisons. The overall biological functions of these genes were related to gene ontology terms such as response to toxic substance, leukocyte migration, neutrophil mediated immunity, response to lipopolysaccharide, and response to oxidative stress. Enrichment pathway analysis indicated alterations in Th17, TGF-β, and muscle repair signaling pathways. At time of abstract submission, data of the remaining samples is about to enter the sequencing data analysis pipeline. We have shown in previous studies that donor simvastatin treatment induces protective effects against IRI in heart transplant recipients. In this study, we were able to detect significantly differentially expressed genes related to effects of simvastatin treatment. In order to single out genes that show beneficial effects of simvastatin treatment, further analysis will be conducted by exploring gene expression changes in specific biological functional categories, such as interleukin signaling and neutrophil degranulation. The complete analysis will be presented at the ISHLT 2020 congress.

Cascabel: a flexible, scalable and easy to use amplicon sequence data analysis pipeline

Cascabel: a flexible, scalable and easy to use amplicon sequence data analysis pipeline

Transcriptome Profiles of the Circulating Extracellular Vesicles in Acute Lung Allograft Rejection

Summary of Objectives The potential of Extracellular Vesicles (EVs) as novel diagnostic, prognostic and predictive biomarkers in transplantation has been noticed as they are known to contain various molecules related to cell-cell communication that vary depending on the EV's origin, such as DNA, RNA and miRNA, and their ability to deliver these molecules to target cells. Given this factor, we hypothesize that circulating EV from patients may contain transcriptomes derived from host immune cells and allograft endothelium, epithelium, and parenchymal cells that regulate the gene expression related to the development of acute rejection and chronic lung allograft dysfunction. Therefore, we will investigate the circulating EVs' transcriptome by next generation sequencing analysis and compare these results with clinical findings and transcriptomics from transbronchial biopsies to discover novel molecular mechanisms and to develop liquid biopsies for acute rejection in a prospective study. Methods We have collected the recipient's and donor's plasma and transbronchial biopsies. The samples are taken at the time of organ procurement from the donor, and at the time of transplantation, 1 week, 1, 3, and 6 months, and 1 year after lung transplantation and every time when there is clinical suspicion of acute rejection. For this preliminary study, four rejection patients proven with the ISHLT grading system and one patient with suspected acute rejection were randomly chosen. All samples from the five patients and their donors were processed to obtain plasma-derived EVs (n=39). EVs were isolated with ExoRNeasy kit (Qiagen) and the whole transcriptome sequencing was performed to obtain at least 15m pair-ended reads by Illumina HiSeq2000. The sequenced data will be processed further with a bioinformatics pipeline for a downstream analysis to observe differential expression patterns, alternative splicing events, and the discovery of biomarkers. Endpoints We were able to validate the morphology and size distribution of EVs isolated from plasma by electron microscopy and nanoparticle tracking analysis. Since the data are currently in the sequencing data analysis pipeline, we expect the results of this preliminary study to be finished by December 2018. If successful, we will confirm the results with a larger cohort.

Abstract P5-08-01: DPYSL3 modulates mitosis, migration and epithelial to mesenchymal transition in claudin-low breast cancer

Abstract Proteogenomics is the field of integrating data from mass spectrometry-based shotgun proteomics, and phosphoproteomics into next-generation RNA and DNA sequencing data analysis pipelines that promises new insights into cancer biology and therapeutic targeting. As well as analyses of clinical samples for disease phenotype association analysis, the application of proteogenomics to model systems also has considerable potential. A Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteogenomic analysis prioritized dihydropyrimidinase-like-3 (DPYSL3) as a multi-level (RNA/Protein/Phosphoprotein) expression outlier specific to the Claudin-Low (CLOW) subset of triple negative breast cancers. A Pubmed informatics tool indicated a paucity of data in the context of breast cancer which further prioritized DPYSL3 for study. DPYSL3 was identified as a protein that is regulated during neuronal differentiation in the cerebral cortex and in neuronal cell lines and plays a role in regulating neurite outgrowth somehow through an association with vesicles in the growth cone. In addition, DPYSL3 expression has been observed in several malignant tumors, including prostate cancer, pancreatic cancer, gastric cancer and neuroblastoma. DPYSL3 is reported to play a role in cell migration and metastasis suppression in prostate cancer. However, in pancreatic cancer, DPYSL3 is positively associated with liver metastasis and poor outcome. DPYSL3 knock-down in DPYSL3 (+) CLOW cell lines demonstrated reduced proliferation, yet enhanced motility and increased expression of Epithelial to Mesenchymal Transition (EMT) markers suggesting that DPYSL3 is a multi-functional signaling modulator. Slower proliferation in DPYSL3 (-) CLOW cells was associated with accumulation of multi-nucleated cells indicating a mitotic defect that was associated with a collapse of the vimentin (VIM) microfilament networkinduced by VIM hyperphosphorylation. On the other hand, DPYSL3 suppressed the expression of EMT regulators TWIST and SNAIL and opposed p21 activated kinase 2 (PAK2) dependent migration, but these EMT regulators in turn induced DPYSL3 expression, suggesting DPYSL3 participates in negative feedback in EMT. Cell migration in DPYSL3 (-) cells correlated with increased phosphorylation of PAK2 on Ser20 and was sensitive to PAK2 siRNA and pharmacological PAK inhibition.Immunoprecipitation and mass spectrometry-based proteomics or western blotting strongly suggests that PAKs interact such that DPYSL3 may function as a direct negative regulator of PAK family kinases. Thus, a PAK inhibitor could potentially mitigate increase migration as an adverse effect of DPYSL3 suppression. In conclusion, DPYSL3 is a remarkable multifunctional signaling scaffold that should be examined further to provide insights into the stem cell-like state of claudin-low breast cancers, particularly in terms of their cell cycle dependencies, migratory activity and capacity for EMT. Citation Format: Matsunuma R, Chan DW, Kim B-J, Singh P, Han A, Saltzman A, Cheng C, Lei JT, Sahin E, Leng M, Fan C, Perou CM, Malovannaya A, Ellis MJ. DPYSL3 modulates mitosis, migration and epithelial to mesenchymal transition in claudin-low breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-08-01.

Whisper: read sorting allows robust mapping of DNA sequencing data.

Mapping reads to a reference genome is often the first step in a sequencing data analysis pipeline. The reduction of sequencing costs implies a need for algorithms able to process increasing amounts of generated data in reasonable time. We present Whisper, an accurate and high-performant mapping tool, based on the idea of sorting reads and then mapping them against suffix arrays for the reference genome and its reverse complement. Employing task and data parallelism as well as storing temporary data on disk result in superior time efficiency at reasonable memory requirements. Whisper excels at large NGS read collections, in particular Illumina reads with typical WGS coverage. The experiments with real data indicate that our solution works in about 15% of the time needed by the well-known BWA-MEM and Bowtie2 tools at a comparable accuracy, validated in a variant calling pipeline. Whisper is available for free from https://github.com/refresh-bio/Whisper or http://sun.aei.polsl.pl/REFRESH/Whisper/. Supplementary data are available at Bioinformatics online.

High-Throughput flaA Short Variable Region Sequencing to Assess Campylobacter Diversity in Fecal Samples From Birds.

Current approach to identify sources of human pathogens is largely dependent on the cultivation and isolation of target bacteria. For rapid pathogen source identification, culture-independent strain typing method is necessary. In this study, we designed new primer set that broadly covers flaA short variable region (SVR) of various Campylobacter species, and applied the flaA SVR sequencing method to examine the diversity of Campylobacter spp. in geese fecal samples (n = 16) with and without bacteria cultivation. Twenty-three Campylobacter strains isolated from the 16 geese fecal samples were grouped similarly by conventional flaA restriction fragment length polymorphism (RFLP) method and by the flaA SVR sequencing method, but higher discriminant power was observed in the flaA SVR sequencing approach. For culture-independent flaA SVR sequencing analysis, we developed and optimized the sequence data analysis pipeline to identify as many genotypes as possible, while minimizing the detection of genotypes generated by sequencing errors. By using this pipeline, 51,629 high-quality flaA sequence reads were clustered into 16 operational taxonomic units (=genotypes) by using 98% sequence similarity and >50 sequence duplicates. Almost all flaA genotypes obtained by culture-dependent method were also identified by culture-independent flaA SVR MiSeq sequencing method. In addition, more flaA genotypes were identified probably due to high throughput nature of the MiSeq sequencing. These results suggest that the flaA SVR sequencing could be used to analyze the diversity of Campylobacter spp. without bacteria isolation. This method is promising to rapidly identify potential sources of Campylobacter pathogens.

Non-biological synthetic spike-in controls and the AMPtk software pipeline improve mycobiome data.

High-throughput amplicon sequencing (HTAS) of conserved DNA regions is a powerful technique to characterize microbial communities. Recently, spike-in mock communities have been used to measure accuracy of sequencing platforms and data analysis pipelines. To assess the ability of sequencing platforms and data processing pipelines using fungal internal transcribed spacer (ITS) amplicons, we created two ITS spike-in control mock communities composed of cloned DNA in plasmids: a biological mock community, consisting of ITS sequences from fungal taxa, and a synthetic mock community (SynMock), consisting of non-biological ITS-like sequences. Using these spike-in controls we show that: (1) a non-biological synthetic control (e.g., SynMock) is the best solution for parameterizing bioinformatics pipelines, (2) pre-clustering steps for variable length amplicons are critically important, (3) a major source of bias is attributed to the initial polymerase chain reaction (PCR) and thus HTAS read abundances are typically not representative of starting values. We developed AMPtk, a versatile software solution equipped to deal with variable length amplicons and quality filter HTAS data based on spike-in controls. While we describe herein a non-biological SynMock community for ITS sequences, the concept and AMPtk software can be widely applied to any HTAS dataset to improve data quality.

MutScan: fast detection and visualization of target mutations by scanning FASTQ data

BackgroundSome types of clinical genetic tests, such as cancer testing using circulating tumor DNA (ctDNA), require sensitive detection of known target mutations. However, conventional next-generation sequencing (NGS) data analysis pipelines typically involve different steps of filtering, which may cause miss-detection of key mutations with low frequencies. Variant validation is also indicated for key mutations detected by bioinformatics pipelines. Typically, this process can be executed using alignment visualization tools such as IGV or GenomeBrowse. However, these tools are too heavy and therefore unsuitable for validating mutations in ultra-deep sequencing data.ResultWe developed MutScan to address problems of sensitive detection and efficient validation for target mutations. MutScan involves highly optimized string-searching algorithms, which can scan input FASTQ files to grab all reads that support target mutations. The collected supporting reads for each target mutation will be piled up and visualized using web technologies such as HTML and JavaScript. Algorithms such as rolling hash and bloom filter are applied to accelerate scanning and make MutScan applicable to detect or visualize target mutations in a very fast way.ConclusionMutScan is a tool for the detection and visualization of target mutations by only scanning FASTQ raw data directly. Compared to conventional pipelines, this offers a very high performance, executing about 20 times faster, and offering maximal sensitivity since it can grab mutations with even one single supporting read. MutScan visualizes detected mutations by generating interactive pile-ups using web technologies. These can serve to validate target mutations, thus avoiding false positives. Furthermore, MutScan can visualize all mutation records in a VCF file to HTML pages for cloud-friendly VCF validation. MutScan is an open source tool available at GitHub: https://github.com/OpenGene/MutScan

Development of amplicon deep sequencing markers and data analysis pipeline for genotyping multi-clonal malaria infections

BackgroundAmplicon deep sequencing permits sensitive detection of minority clones and improves discriminatory power for genotyping multi-clone Plasmodium falciparum infections. New amplicon sequencing and data analysis protocols are needed for genotyping in epidemiological studies and drug efficacy trials of P. falciparum.MethodsTargeted sequencing of molecular marker csp and novel marker cpmp was conducted in duplicate on mixtures of parasite culture strains and 37 field samples. A protocol allowing to multiplex up to 384 samples in a single sequencing run was applied. Software “HaplotypR” was developed for data analysis.ResultsCpmp was highly diverse (He = 0.96) in contrast to csp (He = 0.57). Minority clones were robustly detected if their frequency was >1%. False haplotype calls owing to sequencing errors were observed below that threshold.ConclusionsTo reliably detect haplotypes at very low frequencies, experiments are best performed in duplicate and should aim for coverage of >10′000 reads/amplicon. When compared to length polymorphic marker msp2, highly multiplexed amplicon sequencing displayed greater sensitivity in detecting minority clones.

Determination of disease phenotypes and pathogenic variants from exome sequence data in the CAGI 4 gene panel challenge.

The use of gene panel sequence for diagnostic and prognostic testing is now widespread, but there are so far few objective tests of methods to interpret these data. We describe the design and implementation of a gene panel sequencing data analysis pipeline (VarP) and its assessment in a CAGI4 community experiment. The method was applied to clinical gene panel sequencing data of 106 patients, with the goal of determining which of 14 disease classes each patient has and the corresponding causative variant(s). The disease class was correctly identified for 36 cases, including 10 where the original clinical pipeline did not find causative variants. For a further seven cases, we found strong evidence of an alternative disease to that tested. Many of the potentially causative variants are missense, with no previous association with disease, and these proved the hardest to correctly assign pathogenicity or otherwise. Post analysis showed that three-dimensional structure data could have helped for up to half of these cases. Over-reliance on HGMD annotation led to a number of incorrect disease assignments. We used a largely ad hoc method to assign probabilities of pathogenicity for each variant, and there is much work still to be done in this area.

A System Architecture for Efficient Transmission of Massive DNA Sequencing Data.

The DNA sequencing data analysis pipelines require significant computational resources. In that sense, cloud computing infrastructures appear as a natural choice for this processing. However, the first practical difficulty in reaching the cloud computing services is the transmission of the massive DNA sequencing data from where they are produced to where they will be processed. The daily practice here begins with compressing the data in FASTQ file format, and then sending these data via fast data transmission protocols. In this study, we address the weaknesses in that daily practice and present a new system architecture that incorporates the computational resources available on the client side while dynamically adapting itself to the available bandwidth. Our proposal considers the real-life scenarios, where the bandwidth of the connection between the parties may fluctuate, and also the computing power on the client side may be of any size ranging from moderate personal computers to powerful workstations. The proposed architecture aims at utilizing both the communication bandwidth and the computing resources for satisfying the ultimate goal of reaching the results as early as possible. We present a prototype implementation of the proposed architecture, and analyze several real-life cases, which provide useful insights for the sequencing centers, especially on deciding when to use a cloud service and in what conditions.

MiRDis: a Web tool for endogenous and exogenous microRNA discovery based on deep-sequencing data analysis.

Small RNA sequencing is the most widely used tool for microRNA (miRNA) discovery, and shows great potential for the efficient study of miRNA cross-species transport, i.e., by detecting the presence of exogenous miRNA sequences in the host species. Because of the increased appreciation of dietary miRNAs and their far-reaching implication in human health, research interests are currently growing with regard to exogenous miRNAs bioavailability, mechanisms of cross-species transport and miRNA function in cellular biological processes. In this article, we present microRNA Discovery (miRDis), a new small RNA sequencing data analysis pipeline for both endogenous and exogenous miRNA detection. Specifically, we developed and deployed a Web service that supports the annotation and expression profiling data of known host miRNAs and the detection of novel miRNAs, other noncoding RNAs, and the exogenous miRNAs from dietary species. As a proof-of-concept, we analyzed a set of human plasma sequencing data from a milk-feeding study where 225 human miRNAs were detected in the plasma samples and 44 show elevated expression after milk intake. By examining the bovine-specific sequences, data indicate that three bovine miRNAs (bta-miR-378, -181* and -150) are present in human plasma possibly because of the dietary uptake. Further evaluation based on different sets of public data demonstrates that miRDis outperforms other state-of-the-art tools in both detection and quantification of miRNA from either animal or plant sources. The miRDis Web server is available at: http://sbbi.unl.edu/miRDis/index.php.