ProTECT – Prediction of T-cell Epitopes for Cancer Therapy

Mapping Intimacies ◽

10.1101/696526 ◽

2019 ◽

Author(s):

Arjun A. Rao ◽

Ada A. Madejska ◽

Jacob Pfeil ◽

Benedict Paten ◽

Sofie R. Salama ◽

...

Keyword(s):

Somatic Mutations ◽

Cytotoxic T Cells ◽

T Cell Epitopes ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

Binding Prediction ◽

Local Cluster ◽

Single Nucleotide ◽

Protein Coding ◽

Cell Therapies

AbstractSomatic mutations in cancers affecting protein coding genes can give rise to potentially therapeutic neoepitopes. These neoepitopes can guide Adoptive Cell Therapies (ACTs) and Peptide Vaccines (PVs) to selectively target tumor cells using autologous patient cytotoxic T-cells. Currently, researchers have to independently align their data, call somatic mutations and haplotype the patient’s HLA to use existing neoepitope prediction tools. We present ProTECT, a fully automated, reproducible, scalable, and efficient end-to-end analysis pipeline to identify and rank therapeutically relevant tumor neoepitopes in terms of immunogenicity starting directly from raw patient sequencing data, or from pre-processed data. The ProTECT pipeline encompasses alignment, HLA haplotyping, mutation calling (single nucleotide variants, short insertions and deletions, and gene fusions), peptide:MHC (pMHC) binding prediction, and ranking of final candidates. We demonstrate ProTECT on 326 samples from the TCGA Prostate Adenocarcinoma cohort, and compare it with published tools. ProTECT can be run on a standalone computer, a local cluster, or on a compute cloud using a Mesos backend. ProTECT is highly scalable and can process TCGA data in under 30 minutes per sample when run in large batches. ProTECT is freely available at https://www.github.com/BD2KGenomics/protect.

Implications of Genetic Distance to Reference and De Novo Genome Assembly for Clinical Genomics in Africans

10.1101/2020.09.25.20201780 ◽

2020 ◽

Author(s):

Daniel Shriner ◽

Adebowale Adeyemo ◽

Charles Rotimi

Keyword(s):

Genetic Distance ◽

De Novo ◽

Reference Sequence ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

De Novo Genome Assembly ◽

Single Nucleotide ◽

Clinical Genomics ◽

Advantages And Disadvantages ◽

False Discovery

In clinical genomics, variant calling from short-read sequencing data typically relies on a pan-genomic, universal human reference sequence. A major limitation of this approach is that the number of reads that incorrectly map or fail to map increase as the reads diverge from the reference sequence. In the context of genome sequencing of genetically diverse Africans, we investigate the advantages and disadvantages of using a de novo assembly of the read data as the reference sequence in single sample calling. Conditional on sufficient read depth, the alignment-based and assembly-based approaches yielded comparable sensitivity and false discovery rates for single nucleotide variants when benchmarked against a gold standard call set. The alignment-based approach yielded coverage of an additional 270.8 Mb over which sensitivity was lower and the false discovery rate was higher. Although both approaches detected and missed clinically relevant variants, the assembly-based approach identified more such variants than the alignment-based approach. Of particular relevance to individuals of African descent, the assembly-based approach identified four heterozygous genotypes containing the sickle allele whereas the alignment-based approach identified no occurrences of the sickle allele. Variant annotation using dbSNP and gnomAD identified systematic biases in these databases due to underrepresentation of Africans. Using the counts of homozygous alternate genotypes from the alignment-based approach as a measure of genetic distance to the reference sequence GRCh38.p12, we found that the numbers of misassemblies, total variant sites, potentially novel single nucleotide variants (SNVs), and certain variant classes (e.g., splice acceptor variants, stop loss variants, missense variants, synonymous variants, and variants absent from gnomAD) were significantly correlated with genetic distance. In contrast, genomic coverage and other variant classes (e.g., ClinVar pathogenic or likely pathogenic variants, start loss variants, stop gain variants, splice donor variants, incomplete terminal codons, variants with CADD score ≥20) were not correlated with genetic distance. With improvement in coverage, the assembly-based approach can offer a viable alternative to the alignment-based approach, with the advantage that it can obviate the need to generate diverse human reference sequences or collections of alternate scaffolds.

Highly multiplexed, fast and accurate nanopore sequencing for verification of synthetic DNA constructs and sequence libraries

Synthetic Biology ◽

10.1093/synbio/ysz025 ◽

2019 ◽

Vol 4 (1) ◽

Cited By ~ 4

Author(s):

Andrew Currin ◽

Neil Swainston ◽

Mark S Dunstan ◽

Adrian J Jervis ◽

Paul Mulherin ◽

...

Keyword(s):

Synthetic Biology ◽

Dna Sequencing ◽

Cost Effective ◽

Polymorphism Analysis ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Synthetic Dna ◽

Design Build ◽

Hardware Costs

Abstract Synthetic biology utilizes the Design–Build–Test–Learn pipeline for the engineering of biological systems. Typically, this requires the construction of specifically designed, large and complex DNA assemblies. The availability of cheap DNA synthesis and automation enables high-throughput assembly approaches, which generates a heavy demand for DNA sequencing to verify correctly assembled constructs. Next-generation sequencing is ideally positioned to perform this task, however with expensive hardware costs and bespoke data analysis requirements few laboratories utilize this technology in-house. Here a workflow for highly multiplexed sequencing is presented, capable of fast and accurate sequence verification of DNA assemblies using nanopore technology. A novel sample barcoding system using polymerase chain reaction is introduced, and sequencing data are analyzed through a bespoke analysis algorithm. Crucially, this algorithm overcomes the problem of high-error rate nanopore data (which typically prevents identification of single nucleotide variants) through statistical analysis of strand bias, permitting accurate sequence analysis with single-base resolution. As an example, 576 constructs (6 × 96 well plates) were processed in a single workflow in 72 h (from Escherichia coli colonies to analyzed data). Given our procedure’s low hardware costs and highly multiplexed capability, this provides cost-effective access to powerful DNA sequencing for any laboratory, with applications beyond synthetic biology including directed evolution, single nucleotide polymorphism analysis and gene synthesis.

neoepiscope improves neoepitope prediction with multivariant phasing

Bioinformatics ◽

10.1093/bioinformatics/btz653 ◽

2019 ◽

Vol 36 (3) ◽

pp. 713-720 ◽

Cited By ~ 5

Author(s):

Mary A Wood ◽

Austin Nguyen ◽

Adam J Struck ◽

Kyle Ellrott ◽

Abhinav Nellore ◽

...

Keyword(s):

False Negative ◽

Supplementary Information ◽

Supplementary File ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Somatic Variant ◽

Negative Results ◽

Multiple Datasets ◽

False Negative Results

Abstract Motivation The vast majority of tools for neoepitope prediction from DNA sequencing of complementary tumor and normal patient samples do not consider germline context or the potential for the co-occurrence of two or more somatic variants on the same mRNA transcript. Without consideration of these phenomena, existing approaches are likely to produce both false-positive and false-negative results, resulting in an inaccurate and incomplete picture of the cancer neoepitope landscape. We developed neoepiscope chiefly to address this issue for single nucleotide variants (SNVs) and insertions/deletions (indels). Results Herein, we illustrate how germline and somatic variant phasing affects neoepitope prediction across multiple datasets. We estimate that up to ∼5% of neoepitopes arising from SNVs and indels may require variant phasing for their accurate assessment. neoepiscope is performant, flexible and supports several major histocompatibility complex binding affinity prediction tools. Availability and implementation neoepiscope is available on GitHub at https://github.com/pdxgx/neoepiscope under the MIT license. Scripts for reproducing results described in the text are available at https://github.com/pdxgx/neoepiscope-paper under the MIT license. Additional data from this study, including summaries of variant phasing incidence and benchmarking wallclock times, are available in Supplementary Files 1, 2 and 3. Supplementary File 1 contains Supplementary Table 1, Supplementary Figures 1 and 2, and descriptions of Supplementary Tables 2–8. Supplementary File 2 contains Supplementary Tables 2–6 and 8. Supplementary File 3 contains Supplementary Table 7. Raw sequencing data used for the analyses in this manuscript are available from the Sequence Read Archive under accessions PRJNA278450, PRJNA312948, PRJNA307199, PRJNA343789, PRJNA357321, PRJNA293912, PRJNA369259, PRJNA305077, PRJNA306070, PRJNA82745 and PRJNA324705; from the European Genome-phenome Archive under accessions EGAD00001004352 and EGAD00001002731; and by direct request to the authors. Supplementary information Supplementary data are available at Bioinformatics online.

Low rate of somatic mutations in a long-lived oak tree

10.1101/149203 ◽

2017 ◽

Cited By ~ 5

Author(s):

Namrata Sarkar ◽

Emanuel Schmid-Siegert ◽

Christian Iseli ◽

Sandra Calderon ◽

Caroline Gouhier-Darimont ◽

...

Keyword(s):

Stem Cells ◽

Somatic Mutations ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Cell Divisions ◽

Gamete Formation ◽

Oak Tree ◽

Sequential Appearance ◽

Low Rate ◽

Shoot Meristems

Because plants do not possess a proper germline, deleterious somatic mutations can be passed to gametes and a large number of cell divisions separating zygote from gamete formation in long-lived plants may lead to many mutations. We sequenced the genome of two terminal branches of a 234-year-old oak tree and found few fixed somatic single-nucleotide variants (SNVs), whose sequential appearance in the tree could be traced along nested sectors of younger branches. Our data suggest that stem cells of shoot meristems are robustly protected from accumulation of mutations in trees.

Genome aging: somatic mutation in the brain links age-related decline with disease and nominates pathogenic mechanisms

Human Molecular Genetics ◽

10.1093/hmg/ddz191 ◽

2019 ◽

Vol 28 (R2) ◽

pp. R197-R206 ◽

Cited By ~ 10

Author(s):

Michael A Lodato ◽

Christopher A Walsh

Keyword(s):

Human Brain ◽

Somatic Mutation ◽

Somatic Mutations ◽

Late Onset ◽

Whole Genome ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Age Related ◽

The Brain ◽

Over Time

AbstractAging is a mysterious process, not only controlled genetically but also subject to random damage that can accumulate over time. While DNA damage and subsequent mutation in somatic cells were first proposed as drivers of aging more than 60 years ago, whether and to what degree these processes shape the neuronal genome in the human brain could not be tested until recent technological breakthroughs related to single-cell whole-genome sequencing. Indeed, somatic single-nucleotide variants (SNVs) increase with age in the human brain, in a somewhat stochastic process that may nonetheless be controlled by underlying genetic programs. Evidence from the literature suggests that in addition to demonstrated increases in somatic SNVs during aging in normal brains, somatic mutation may also play a role in late-onset, sporadic neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease. In this review, we will discuss somatic mutation in the human brain, mechanisms by which somatic mutations occur and can be controlled, and how this process can impact human health.

The discrepancy among single nucleotide variants detected by DNA and RNA high throughput sequencing data

BMC Genomics ◽

10.1186/s12864-017-4022-x ◽

2017 ◽

Vol 18 (S6) ◽

Cited By ~ 16

Author(s):

Yan Guo ◽

Shilin Zhao ◽

Quanhu Sheng ◽

David C Samuels ◽

Yu Shyr

Keyword(s):

High Throughput ◽

High Throughput Sequencing ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Dna And Rna ◽

High Throughput Sequencing Data

Misannotation of multiple-nucleotide variants risks misdiagnosis

Wellcome Open Research ◽

10.12688/wellcomeopenres.15420.1 ◽

2019 ◽

Vol 4 ◽

pp. 145

Author(s):

Matthew N. Wakeling ◽

Thomas W. Laver ◽

Kevin Colclough ◽

Andrew Parish ◽

Sian Ellard ◽

...

Keyword(s):

Best Practices ◽

False Negative ◽

Simulated Data ◽

Sequencing Analysis ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Public Resources ◽

Next Generation Sequencing Analysis ◽

Optimal Approach

Multiple Nucleotide Variants (MNVs) are miscalled by the most widely utilised next generation sequencing analysis (NGS) pipelines, presenting the potential for missing diagnoses that would previously have been made by standard Sanger (dideoxy) sequencing. These variants, which should be treated as a single insertion-deletion mutation event, are commonly called as separate single nucleotide variants. This can result in misannotation, incorrect amino acid predictions and potentially false positive and false negative diagnostic results. This risk will be increased as confirmatory Sanger sequencing of Single Nucleotide variants (SNVs) ceases to be standard practice. Using simulated data and re-analysis of sequencing data from a diagnostic targeted gene panel, we demonstrate that the widely adopted pipeline, GATK best practices, results in miscalling of MNVs and that alternative tools can call these variants correctly. The adoption of calling methods that annotate MNVs correctly would present a solution for individual laboratories, however GATK best practices are the basis for important public resources such as the gnomAD database. We suggest integrating a solution into these guidelines would be the optimal approach.

Aging and neurodegeneration are associated with increased mutations in single human neurons

10.1101/221960 ◽

2017 ◽

Cited By ~ 4

Author(s):

Michael A. Lodato ◽

Rachel E. Rodin ◽

Craig L. Bohrson ◽

Michael E. Coulter ◽

Alison R. Barton ◽

...

Keyword(s):

Somatic Mutations ◽

Genetic Disorders ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Age Related ◽

Genome Wide ◽

Normal Individuals ◽

Human Neurons ◽

Regional Specificity ◽

Associated Conditions

SummaryIt has long been hypothesized that aging and neurodegeneration are associated with somatic mutation in neurons; however, methodological hurdles have prevented testing this hypothesis directly. We used single-cell whole-genome sequencing to perform genome-wide somatic single-nucleotide variant (sSNV) identification on DNA from 161 single neurons from the prefrontal cortex and hippocampus of fifteen normal individuals (aged 4 months to 82 years) as well as nine individuals affected by early-onset neurodegeneration due to genetic disorders of DNA repair (Cockayne syndrome and Xeroderma pigmentosum). sSNVs increased approximately linearly with age in both areas (with a higher rate in hippocampus) and were more abundant in neurodegenerative disease. The accumulation of somatic mutations with age—which we term genosenium—shows age-related, region-related, and disease-related molecular signatures, and may be important in other human age-associated conditions.One-Sentence SummarySomatic single-nucleotide variants accumulate in human neurons in aging with regional specificity and in progeroid diseases.

Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

10.1101/475947 ◽

2018 ◽

Author(s):

Dimitrios Kleftogiannis ◽

Marco Punta ◽

Anuradha Jayaram ◽

Shahneen Sandhu ◽

Stephen Q. Wong ◽

...

Keyword(s):

Deep Sequencing ◽

Low Frequency ◽

Poisson Model ◽

Real Data ◽

Analytical Sensitivity ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Deep Sequencing Data ◽

Targeted Deep Sequencing

AbstractBackgroundTargeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs).MethodsTo address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection.ResultsOur tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments.ConclusionsAmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve.

dbMTS: a comprehensive database of putative human microRNA target site SNVs and their functional predictions

10.1101/554485 ◽

2019 ◽

Cited By ~ 2

Author(s):

Chang Li ◽

Michael D. Swartz ◽

Bing Yu ◽

Yongsheng Bai ◽

Xiaoming Liu

Keyword(s):

Target Site ◽

Genetic Mutations ◽

Messenger Rnas ◽

Microrna Target ◽

Functional Importance ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Protein Coding ◽

Functional Annotations ◽

Non Coding Rnas

AbstractmicroRNAs (miRNAs) are short non-coding RNAs that can repress the expression of protein coding messenger RNAs (mRNAs) by binding to the 3’UTR of the target. Genetic mutations such as single nucleotide variants (SNVs) in the 3’UTR of the mRNAs can disrupt this regulatory effect. In this study, we presented dbMTS, the database for miRNA target site (MTS) SNVs, which includes all potential MTS SNVs in the 3’UTR of human genome along with hundreds of functional annotations. This database can help studies easily identify putative SNVs that affect miRNA targeting and facilitate the prioritization of their functional importance. dbMTS is freely available at: https://sites.google.com/site/jpopgen/dbNSFP.