Generation Sequencing Pipelines Research Articles

COVID-19 progression towards ARDS: a genome wide study reveals host factors underlying critical COVID-19.

Coronavirus disease 2019 (COVID-19) is a viral infection produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus epidemic, which was declared a global pandemic in March 2020. The World Health Organization has recorded around 43.3 billion cases and 59.4 million casualties to date, posing a severe threat to global health. Severe COVID-19 indicates viral pneumonia caused by the SARS-CoV-2 infections, which can induce fatal consequences, including acute respiratory distress syndrome (ARDS). The purpose of this research is to better understand the COVID-19 and ARDS pathways, as well as to find targeted single nucleotide polymorphism. To accomplish this, we retrieved over 100 patients' samples from the Sequence Read Archive, National Center for Biotechnology Information. These sequences were processed through the Galaxy server next generation sequencing pipeline for variant analysis and then visualized in the Integrative Genomics Viewer, and performed statistical analysis using t-tests and Bonferroni correction, where six major genes were identified as DNAH7, CLUAP1, PPA2, PAPSS1, TLR4, and IFITM3. Furthermore, a complete understanding of the genomes of COVID-19-related ARDS will aid in the early identification and treatment of target proteins. Finally, the discovery of novel therapeutics based on discovered proteins can assist to slow the progression of ARDS and lower fatality rates.

SARS-CoV-2 coinfections with variant genomic lineages identified by multiplex fragment analysis.

Immunocompromised patients can experience prolonged SARS-CoV-2 infections in the setting of a lack of protectivity immunity despite vaccination. As circulating SARS-CoV-2 strains become more heterogeneous, concomitant infection with multiple SARS-CoV-2 variants has become an increasing concern. Immunocompromised patient populations represent potential reservoirs for the emergence of novel SARS-CoV-2 variants through mutagenic change or coinfection followed by recombinatory events. Identification of SARS-CoV-2 coinfections is challenging using traditional next generation sequencing pipelines; however, targeted genotyping approaches can facilitate detection. Here we describe five COVID-19 cases caused by coinfection with different SARS-CoV-2 variants (Delta/Omicron BA.1 and Omicron BA.1/BA.2) as identified by multiplex fragment analysis.

Clonal Hematopoiesis is Common within the Advanced Heart Failure Population and is Associated with Improved Heart Transplant Outcomes

<h3>Purpose</h3> Clonal hematopoiesis (CH) is considered a deleterious cardiovascular risk factor as it is associated with atherosclerosis and heart failure progression. The prevalence of CH in the pediatric and adult advanced heart failure population and associated demographic and clinical features are unknown. Furthermore, the relationship between CH and heart transplant outcomes including primary graft dysfunction and allograft rejection remains to be defined. The purpose of our study is to measure the prevalence of CH across age in the advanced heart failure population and delineate the impact of CH on heart transplant outcomes. <h3>Methods</h3> We established pediatric and adult advanced heart failure registries with comprehensive clinical phenotyping (n=112 patients). Enrolled subjects underwent either ventricular assist device placement and/or heart transplantation. CH was measured using a custom next generation sequencing pipeline with >1,500X coverage of 76 genes. CH prevalence, gene distribution, variant allelic fraction (VAF), and relationships between CH, demographic variables, and outcomes were quantified. <h3>Results</h3> CH was detected in 22% of patients (26% adults, 5% pediatric) and included 28 mutations in 21 genes. High confidence variants were identified in <i>TET2, DNMT3A, ASXL1, PPM1D</i>, and <i>JAK2</i>. The most frequently mutated genes were <i>TET2</i> (VAF: 3.5-15%) and <i>DNMT3A</i> (VAF: 2.5-45.7%). Age, hypertension, diabetes, dyslipidemia, smoking, and prior history of cancer were associated with CH. Among patients who underwent heart transplantation, the composite outcome of cardiovascular mortality, ISHLT grade >2R cellular rejection, antibody mediated rejection, and primary graft dysfunction was significantly reduced in individuals with CH (14% vs. 52%, p<0.03). These findings are consistent with our pre-clinical data indicating that <i>TET2</i> CH in recipient mice improves long-term allograft acceptance with suboptimal immunosuppression. <h3>Conclusion</h3> CH is present across a spectrum of age in the advanced heart failure population and is associated with improved clinical outcomes. Future studies are required to externally replicate these findings and uncover underlying mechanisms.

Low Detection Rates of Genetic FH in Cohort of Patients With Severe Hypercholesterolemia in the United Arabic Emirates.

Background: Programs to screen for Familial hypercholesterolemia (FH) are conducted worldwide. In Western societies, these programs have been shown to be cost-effective with hit/detection rates of 1 in 217–250. Thus far, there is no published data on genetic FH in the Gulf region. Using United Arab Emirates as a proxy for the Gulf region, we assessed the prevalence of genetically confirmed FH in the Emirati population sample. Materials and Methods: We recruited 229 patients with LDL-C >95th percentile and employed a customized next generation sequencing pipeline to screen canonical FH genes (LDLR, APOB, PCSK9, LDLRAP1). Results: Participants were characterized by mean total cholesterol and low-density lipoprotein cholesterol (LDL-c) of 6.3 ± 1.1 and 4.7 ± 1.1 mmol/L respectively. Ninety-six percent of the participants were using lipid-lowering medication with mean corrected LDL-c values of 10.0 ± 3.0 mmol/L 15 out of 229 participants were found to suffer from genetically confirmed FH. Carriers of causal genetic variants for FH had higher on-treatment LDL-c compared to those without causal variants (5.7 ± 1.5 vs 4.7 ± 1.0; p = 3.7E-04). The groups did not differ regarding high-density lipoprotein cholesterol, triglycerides, body mass index, blood pressure, glucose, and glycated haemoglobin. Conclusion: This study reveals a low 7% prevalence of genetic FH in Emiratis with marked hypercholesterolemia as determined by correcting LDL-c for the use of lipid-lowering treatment. The portfolio of mutations identified is, to a large extent, unique and includes gene duplications. Our findings warrant further studies into origins of hypercholesterolemia in these patients. This is further supported by the fact that these patients are also characterized by high prevalence of type 2 diabetes (42% in the current study cohort) which already puts them at an increased risk of atherosclerotic cardiovascular disease. These results may also be useful in public health initiatives for FH cascade screening programs in the UAE and maybe the Gulf region.

PEGR: a management platform for ChIP-based next generation sequencing pipelines.

There has been a rapid development in genome sequencing, including high-throughput next generation sequencing (NGS) technologies, automation in biological experiments, new bioinformatics tools and utilization of high-performance computing and cloud computing. ChIP-based NGS technologies, e.g. ChIP-seq and ChIP-exo, are widely used to detect the binding sites of DNA-interacting proteins in the genome and help us to have a deeper mechanistic understanding of genomic regulation. As sequencing data is generated at an unprecedented pace from the ChIP-based NGS pipelines, there is an urgent need for a metadata management system. To meet this need, we developed the Platform for Eukaryotic Genomic Regulation (PEGR), a web service platform that logs metadata for samples and sequencing experiments, manages the data processing workflows, and provides reporting and visualization. PEGR links together people, samples, protocols, DNA sequencers and bioinformatics computation. With the help of PEGR, scientists can have a more integrated understanding of the sequencing data and better understand the scientific mechanisms of genomic regulation. In this paper, we present the architecture and the major functionalities of PEGR. We also share our experience in developing this application and discuss the future directions.

ECuADOR-Easy Curation of Angiosperm Duplicated Organellar Regions, a tool for cleaning and curating plastomes assembled from next generation sequencing pipelines.

BackgroundWith the rapid increase in availability of genomic resources offered by Next-Generation Sequencing (NGS) and the availability of free online genomic databases, efficient and standardized metadata curation approaches have become increasingly critical for the post-processing stages of biological data. Especially in organelle-based studies using circular chloroplast genome datasets, the assembly of the main structural regions in random order and orientation represents a major limitation in our ability to easily generate “ready-to-align” datasets for phylogenetic reconstruction, at both small and large taxonomic scales. In addition, current practices discard the most variable regions of the genomes to facilitate the alignment of the remaining coding regions. Nevertheless, no software is currently available to perform curation to such a degree, through simple detection, organization and positioning of the main plastome regions, making it a time-consuming and error-prone process. Here we introduce a fast and user friendly software ECuADOR, a Perl script specifically designed to automate the detection and reorganization of newly assembled plastomes obtained from any source available (NGS, sanger sequencing or assembler output).MethodsECuADOR uses a sliding-window approach to detect long repeated sequences in draft sequences, which then identifies the inverted repeat regions (IRs), even in case of artifactual breaks or sequencing errors and automates the rearrangement of the sequence to the widely used LSC–Irb–SSC–IRa order. This facilitates rapid post-editing steps such as creation of genome alignments, detection of variable regions, SNP detection and phylogenomic analyses.ResultsECuADOR was successfully tested on plant families throughout the angiosperm phylogeny by curating 161 chloroplast datasets. ECuADOR first identified and reordered the central regions (LSC–Irb–SSC–IRa) for each dataset and then produced a new annotation for the chloroplast sequences. The process took less than 20 min with a maximum memory requirement of 150 MB and an accuracy of over 99%.ConclusionsECuADOR is the sole de novo one-step recognition and re-ordination tool that provides facilitation in the post-processing analysis of the extra nuclear genomes from NGS data. The program is available at https://github.com/BiodivGenomic/ECuADOR/.

Review of 12 months of copy number variant calling on a clinical next generation sequencing pipeline

Review of 12 months of copy number variant calling on a clinical next generation sequencing pipeline

Holistic optimization of an RNA-seq workflow for multi-threaded environments.

For many next generation-sequencing pipelines, the most computationally intensive step is the alignment of reads to a reference sequence. As a result, alignment software such as the Burrows-Wheeler Aligner is optimized for speed and is often executed in parallel on the cloud. However, there are other less demanding steps that can also be optimized to significantly increase the speed especially when using many threads. We demonstrate this using a unique molecular identifier RNA-sequencing pipeline consisting of 3 steps: split, align, and merge. Optimization of all three steps yields a 40% increase in speed when executed using a single thread. However, when executed using 16 threads, we observe a 4-fold improvement over the original parallel implementation and more than an 8-fold improvement over the original single-threaded implementation. In contrast, optimizing only the alignment step results in just a 13% improvement over the original parallel workflow using 16 threads. Code (M.I.T. license), supporting scripts and Dockerfiles are available at https://github.com/BioDepot/LINCS_RNAseq_cpp and Docker images at https://hub.docker.com/r/biodepot/rnaseq-umi-cpp/. Supplementary data are available at Bioinformatics online.

Validation of a hepatitis B virus (HBV) Next Generation Sequencing (NGS) pipeline at Barts Health NHS Trust

At Barts Health NHS Trust, historically HBV genotyping and resistance testing is performed using nested PCR followed by Sanger sequencing. With the development of NGS assays for HIV and HCV, in order to harmonise workflows an NGS HBV pipeline was developed. Primers were designed for the whole genome amplification of HBV. Plasma samples were extracted for nucleic acid using a Qiagen Qiasymphony. Whole genomes of HBV were amplified in a single round PCR and quantified using a Qubit fluorometer. Libraries were prepared using the Nextera XT library preparation kit and sequencing was performed on an Illumina Miseq. Sequencing reads were assembled into consensus sequences using a Linex-based pipeline. Resistances and genotypes were determined using the HBV Grade website. Minority variants were variants &lt;20 % of the overall population. Pan-genotypic PCR primers were designed in the nick region of the partially double stranded HBV genome. In-silico analysis allowed primers to be designed to bind multiple genotypes. Sensitivity analysis of primers was investigated for the most common circulating genotypes. A panel of HBV positive and external quality assurance samples showed good comparability to Sanger sequencing results. Inter- and intra-assay variability showed the assay was robust and fit for purpose. No resistance associated minority variants were observed. The development an NGS pipeline for analysis of HBV allowed the harmonisation of diagnostic pathways within the virology sequencing laboratory. Introduction of this test would allow data to be gathered to assess the importance of minority variants in HBV infection.

Identification of LAMP2 Mutations in Early-Onset Danon Disease With Hypertrophic Cardiomyopathy by Targeted Next-Generation Sequencing

Danon disease is an X-linked disorder with the clinical triad of cardiomyopathy, skeletal myopathy, and mental retardation. Early diagnosis of this disease remains a challenge, especially in the pediatric population. In this study, we developed a targeted panel-based next generation sequencing pipeline to identify mutations by sequencing of selected candidate genes in 136 pediatric patients with either hypertrophic cardiomyopathy (HC) or idiopathic dilated cardiomyopathy (IDC). This led to the identification of lysosome-associated membrane protein 2 (LAMP2) mutations in 4 of the 64 (6%) probands with HC, including 3 novel nonsense mutations (p.Q240X, p.S250X, and p.G22X). No LAMP2 mutation was detected in the other 72 probands with IDC. All 4 probands and one additional affected family member (2 men and 3 women) had an early-onset age and presented either HC alone or combined with Wolff-Parkinson-White syndrome and skeletal myopathy. Immunofluorescence staining and Western blot analysis revealed absent LAMP2 expression in both cardiac and skeletal muscle samples of the first proband and severely decreased LAMP2 expression in the skeletal muscle samples of the second proband. In conclusion, cardiomyopathy in the patients with Danon disease may occur during early childhood and tend to be HC rather than IDC in both affected men and women. Therefore, Danon disease should be considered as one of the leading causes of unexplained ventricular hypertrophy in pediatric patients. The inclusion of LAMP2 gene in cardiomyopathy genetic screening panels may contribute to early diagnosis of Danon disease.

NINJA-OPS: Fast Accurate Marker Gene Alignment Using Concatenated Ribosomes.

The explosion of bioinformatics technologies in the form of next generation sequencing (NGS) has facilitated a massive influx of genomics data in the form of short reads. Short read mapping is therefore a fundamental component of next generation sequencing pipelines which routinely match these short reads against reference genomes for contig assembly. However, such techniques have seldom been applied to microbial marker gene sequencing studies, which have mostly relied on novel heuristic approaches. We propose NINJA Is Not Just Another OTU-Picking Solution (NINJA-OPS, or NINJA for short), a fast and highly accurate novel method enabling reference-based marker gene matching (picking Operational Taxonomic Units, or OTUs). NINJA takes advantage of the Burrows-Wheeler (BW) alignment using an artificial reference chromosome composed of concatenated reference sequences, the “concatesome,” as the BW input. Other features include automatic support for paired-end reads with arbitrary insert sizes. NINJA is also free and open source and implements several pre-filtering methods that elicit substantial speedup when coupled with existing tools. We applied NINJA to several published microbiome studies, obtaining accuracy similar to or better than previous reference-based OTU-picking methods while achieving an order of magnitude or more speedup and using a fraction of the memory footprint. NINJA is a complete pipeline that takes a FASTA-formatted input file and outputs a QIIME-formatted taxonomy-annotated BIOM file for an entire MiSeq run of human gut microbiome 16S genes in under 10 minutes on a dual-core laptop.

Next generation sequencing pipelines in Docker

Next generation sequencing pipelines in Docker

NGSeasy: a next generation sequencing pipeline in Docker containers

Motivation: Bioinformatic pipelines often use large numbers of components and deploying them incurs substantial configuration and maintenance burden that remains a significant barrier to reproducible research. Our aim is to define a new paradigm and best practices for developing, distributing and running pipelines encapsulated in Docker containers (lightweight virtualization), with a focus on next generation sequencing (NGS) workflows. This approach provides several advantages, namely: efficiency, portability, versioning and reproducibility. Using the NGSeasy pipeline, a user can quickly deploy any pipeline version in any environment (e.g. operating systems, workstations, clusters, clouds). While this might also be achieved with a virtual machine (VM); VMs lack portability, have substantial overhead (disk, CPU, RAM), and require allocated resources to be provisioned statically – Docker, to a large extent, solves these issues.Results: We demonstrate best practices for packaging and execution of a multicomponent pipeline for NGS using a set of container building blocks which are versioned, modular and reusable. We present a basic ”proof of concept” evaluation of a next generation sequencing pipeline in Docker containers, capable of producing meaningful results, that are comparable with public and ”best practice” workflows, with little to no impact on standard computing performance.Availability: Both versioned Dockerfiles and container images for each component are published on GitHub and Docker Hub, respectively. The pipeline and containers can be pulled from Docker Hub and executed on any environment capable of running the Docker platform with minimum hardware requirements for running an NGS pipeline.

A Traveler's Guide to Next Generation Sequencing: Navigating the Sea of Genetic Variants

Recent advances in technology and cost effectiveness of next generation sequencing has led to its progressively wider implementation in both research and clinical settings. The amount of data it produces, however, can be overwhelming—typically over three million variants per genome. The challenges for many researchers today are how to make sense of this huge volume of data in the context of the scientific question being asked, and how to identify those variants that provide meaningful and relevant information. In this webinar we will discuss current approaches to variant analysis and how they can be most effectively integrated into the next generation sequencing pipeline.

COST Action BM 1006 (SeqAhead): MC BUSINESS MEETING AND SCIENTIFIC MEETING

SeqAhead is a COST Action created by a group of researchers involved in the development of Next Generation Sequencing (NGS) data-analysis software and pipelines. The primary objective of SeqAhead is to develop a coordinated action plan to help the scientific community to handle the flood of NGS data in an efficient and coherent manner, using state-of-the-art bioinformatics. Establishment of a strong European network of NGS, data-analysis and informatics centres will facilitate and stimulate the exchange of data, protocols, software, experiences and ideas.

EMBRACE workshop “NEXT GENERATION SEQUENCING II”

After the success of the EMBRACE (1) workshop on "Building Next Generation Sequencing platforms and pipeline solutions" in Rome in November 2009 with more that 60 international participants (2), the organization committee decided to try to organize at least two such events each year to keep pace of the fast development of the Next Generation Sequencing (NGS) technology and the tools and methods to analyse and interpret the data produced. This is the report of the “NEXT GENERATION SEQUENCING II” workshop in in Ruvo di Puglia in June 2010.