Genotyping of selected germline adaptive immune system loci using short-read sequencing data

BackgroundAll jawed-vertebrates have four T cell receptor (TCR) chains: alpha (TRA), beta (TRB), gamma (TRG) and delta (TRD). Marsupials appear unique by having an additional TCR: mu (TRM). The evolutionary origin of TRM and its relationship to other TCR remain obscure, and is confounded by previous results that support TRM being a hybrid between a TCR and immunoglobulin locus. The availability of the first marsupial genome sequence allows investigation of these evolutionary relationships.ResultsThe organization of the conventional TCR loci, encoding the TRA, TRB, TRG and TRD chains, in the opossum Monodelphis domestica are highly conserved with and of similar complexity to that of eutherians (placental mammals). There is a high degree of conserved synteny in the genomic regions encoding the conventional TCR across mammals and birds. In contrast the chromosomal region containing TRM is not well conserved across mammals. None of the conventional TCR loci contain variable region gene segments with homology to those found in TRM; rather TRM variable genes are most similar to that of immunoglobulin heavy chain genes.ConclusionComplete genomic analyses of the opossum TCR loci continue to support an origin of TRM as a hybrid between a TCR and immunoglobulin locus. None of the conventional TCR loci contain evidence that such a recombination event occurred, rather they demonstrate a high degree of stability across distantly related mammals. TRM, therefore, appears to be derived from receptor genes no longer extant in placental mammals. These analyses provide the first genomic scale structural detail of marsupial TCR genes, a lineage of mammals used as models of early development and human disease.

Rationale: We have previously shown reduced total IgG, IgG subclasses, and levels/function of pneumococcal-specific antibodies are associated with increased risk for exacerbations of COPD (ECOPD). The binding of IgG to its receptor, the Fc receptor for IgG (FcγR) on immune cells, has a critical role in determining antibody levels and function. In addition to our research demonstrating that IgG heavy chain gene (IGHG) variants are associated with ECOPD, single nucleotide variants (SNVs) in genes encoding FcγR (FCGR1-3, which encode receptor subtypes FcγRI, FcγRIIa/b/c, and FcγRIIIa/b) may also result in antibody deficiency and increased exacerbation risk. Due to technical challenges in accurately identifying SNVs in FCGR, this region has not been well-characterized. The limited data that exist are from people of European descent, and prior studies have not included African American participants. We therefore sought to investigate the hypothesis that distinct SNVs in genes encoding FcγR are associated with disease severity and history of exacerbations in African American people with COPD. Methods: We developed a novel pipeline to identify SNVs in the coding (CDS) regions of chromosome 1 using short-read whole genome sequence data. The pipeline was benchmarked using paired long-read samples from Genome in a Bottle. SNVs were called within CDS regions and analyzed in a meta-analysis of self-reported African American participants in SPIROMICS and COPDGene (n=3063). Genetic variants were tested for association with COPD severity (GOLD spirometry stage 1-2 vs 3-4) as well as COPD exacerbations, adjusting for age, sex and principal components controlling for population structure. Results: Eight SNVs were significantly associated with frequent ECOPD (≥2 in one year) in the meta-analysis of African American COPDGene and SPIROMICS participants (Table). Seven of these 8 SNVs were found in FCGR3; 4 in the activating FCGR3A subtype, and 3 in FCGR3B. Seven of 11 SNVs associated with COPD severity were in FCGR3 (4 in FCGR3A; 3 in FCGR3B). One SNV (rs371849) was associated with both frequent exacerbations (P=0.002) and COPD severity (P=0.044). Conclusions: We used a cutting-edge variant calling pipeline to identify multiple SNVs in FCGR, primarily involving FcγRIII receptor subtypes, associated with COPD severity and exacerbations in African American participants in SPIROMICS and COPDGene. FcγRIII variants are known to cause impaired antibody levels and function in people of European descent. The structural and functional importance of newly recognized variants in African American cohorts require further study, as they may represent immunogenetic risk factors for antibody deficiency and exacerbations.

Motivation:de novo variant (DNV) calling is challenging from parent-child sequenced trio data. We developed Hare And Tortoise (HAT) to work as an automated workflow to detect DNVs in highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genetics studies (e.g., autism, epilepsy).Results:HAT is a workflow to detect DNVs from short-read and long read sequencing data. This workflow begins with aligned read data (i.e., CRAM or BAM) from a parent-child sequenced trio and outputs DNVs. HAT detects high-quality DNVs from short-read whole-exome sequencing, short-read whole-genome sequencing, and highly accurate long-read sequencing data.

BackgroundGenomic data have become major resources to understand complex mechanisms at fine-scale temporal and spatial resolution in functional and evolutionary genetic studies, including human diseases, such as cancers. Recently, a large number of whole genomes of evolving populations of yeast (Saccharomyces cerevisiae W303 strain) were sequenced in a time-dependent manner to identify temporal evolutionary patterns. For this type of study, a chromosome-level sequence assembly of the strain or population at time zero is required to compare with the genomes derived later. However, there is no fully automated computational approach in experimental evolution studies to establish the chromosome-level genome assembly using unique features of sequencing data.Methods and resultsIn this study, we developed a new software pipeline, the integrative meta-assembly pipeline (IMAP), to build chromosome-level genome sequence assemblies by generating and combining multiple initial assemblies using three de novo assemblers from short-read sequencing data. We significantly improved the continuity and accuracy of the genome assembly using a large collection of sequencing data and hybrid assembly approaches. We validated our pipeline by generating chromosome-level assemblies of yeast strains W303 and SK1, and compared our results with assemblies built using long-read sequencing and various assembly evaluation metrics. We also constructed chromosome-level sequence assemblies of S. cerevisiae strain Sigma1278b, and three commonly used fungal strains: Aspergillus nidulans A713, Neurospora crassa 73, and Thielavia terrestris CBS 492.74, for which long-read sequencing data are not yet available. Finally, we examined the effect of IMAP parameters, such as reference and resolution, on the quality of the final assembly of the yeast strains W303 and SK1.ConclusionsWe developed a cost-effective pipeline to generate chromosome-level sequence assemblies using only short-read sequencing data. Our pipeline combines the strengths of reference-guided and meta-assembly approaches. Our pipeline is available online at http://github.com/jkimlab/IMAP including a Docker image, as well as a Perl script, to help users install the IMAP package, including several prerequisite programs. Users can use IMAP to easily build the chromosome-level assembly for the genome of their interest.

Copy Number Alterations (CNAs) such as deletions and duplications; compose a larger percentage of genetic variations than single nucleotide polymorphisms or other structural variations in cancer genomes that undergo major chromosomal re-arrangements. It is, therefore, imperative to identify cancer-specific somatic copy number alterations (SCNAs), with respect to matched normal tissue, in order to understand their association with the disease. We have devised an accurate, sensitive, and easy-to-use tool, COPS, COpy number using Paired Samples, for detecting SCNAs. We rigorously tested the performance of COPS using short sequence simulated reads at various sizes and coverage of SCNAs, read depths, read lengths and also with real tumor:normal paired samples. We found COPS to perform better in comparison to other known SCNA detection tools for all evaluated parameters, namely, sensitivity (detection of true positives), specificity (detection of false positives) and size accuracy. COPS performed well for sequencing reads of all lengths when used with most upstream read alignment tools. Additionally, by incorporating a downstream boundary segmentation detection tool, the accuracy of SCNA boundaries was further improved. Here, we report an accurate, sensitive and easy to use tool in detecting cancer-specific SCNAs using short-read sequence data. In addition to cancer, COPS can be used for any disease as long as sequence reads from both disease and normal samples from the same individual are available. An added boundary segmentation detection module makes COPS detected SCNA boundaries more specific for the samples studied. COPS is available at ftp://115.119.160.213 with username “cops” and password “cops”.

Adaptive immune responses are mediated by the production of adaptive immune receptors, antibodies, and T-cell receptors, which bind antigens, thus causing their neutralization. Unlike other proteins, adaptive immune receptors are not fully encoded in the germline genome and result from a complex of somatic processes collectively called V(D)J recombination affecting germline immunoglobulin (IG) and T-cell receptor (TR) loci consisting of template genes. While various existing studies report extreme diversity of antibodies and T-cell receptors, little is known about the diversity of germline IG and TR loci. To overcome this gap, the first comparative analysis of full-length sequences of IG/TR loci across 46 mammalian species from 13 taxonomic orders was performed. First, germline gene counts were shown to correlate in immunoglobulin heavy chain immunoglobulin heavy chain (IGH)/immunoglobulin lambda (IGL) loci and T-cell receptor alpha (TRA)/T-cell receptor beta (TRB) and anticorrelate in immunoglobulin kappa (IGK)/IGL, possibly indicating coevolution between corresponding chains. Second, structures of IG/TR loci were analyzed, and it was shown that IG/TR loci formed by long arrays of high multiplicity repeats are more common for species that have experienced population bottlenecks. Finally, haplotypes of IG/TR loci with little or no sequence similarity within a species were found, suggesting that they may have a limited potential for homologous recombination. These results demonstrate that IG/TR loci are rapidly evolving genomic regions whose structural variation is shaped by the population history of the species and open new perspectives for immunogenomics studies.

Structural variations (SVs) are differences in genomic regions that are larger than 1 kilobase-pair (Kbp) between individuals, and can arise from errant DNA repair mechanisms, whole genome duplications, and transposable element activity across the genome. Recent advances, optimizations, and cost reductions in next generation sequencing technologies have facilitated the exponential increase in the amount of available short read genomic data. Here we present SaVor, a flexible, reproducible SV calling workflow that accepts single or multi-lane short-read paired-end Illumina sequence data, or BAM files as input to generate a consensus SV call-set based on user-provided merge parameters. We tested SaVor on 1,165 Arabidopsis thaliana whole genome sequences and benchmarked its performance on a set of SVs derived from the same accessions using Lumpy. Intersection calls i.e. SVs supported by 3 SV callers showed the highest precision (>0.91) while union calls supported by at least 1 caller showed the highest recall (>0.88). We found that the former suffers from decreased recall (<0.51) and the latter decreased precision (<0.57). Depending on the merge strategy, trade-offs in recall and precision need to be considered for downstream analyses of SV call-sets from short-read data. SaVor is an open-source Snakemake pipeline and is available on GitHub at https://github.com/ChabbyTMD/SaVor

Acute Myeloid Leukemia (AML) is a hematological malignancy with a 5 year overall survival of less than 30%. DNA hypomethylating agents such as 5-Azacytidine (5-Aza) have been increasingly used in AML therapy. The effect of hypomethylating agents on T-cell driven anti-leukemia responses remains unclear. For anti-leukemia responses, T-cells must express a T-cell receptor (TCR) with specificity for cancer antigens. TCR recombination, the rearrangement of V, D (beta only) and J segments across the TCR alpha and beta loci into a mature TCR locus, shapes the antigen specificity of TCRs. DNA methylation across the TCR loci may limit the rearrangement of particular V, D, J segments and impact TCR repertoire composition. Whether 5-Aza can alter TCR loci methylation patterns, increase TCR diversity and enhance T-cell driven anti-leukemia responses is unknown. In a cohort of 23 patient with AML, we performed TCR-seq on pre- (diagnostic) and post-therapy (day 5 post 5-Aza) peripheral blood RNA samples obtained from 13 responders and 10 non-responders. Illumina compatible libraries were generated from patient samples using a 5'RACE like approach and sequenced on the MiSeq platform, generating 300x2bp reads. Reads were processed and analyzed using MiXCR and VDJTools, respectively. GraphPad Prism 8 (Two-sided T test) was used for statistical comparisons, P values &amp;lt; 0.05 were considered significant after adjusting for multiple comparisons using the Bonferroni-Dunn method. We obtained an average of 1,146,043 (SD± 767,216) reads and identified an average of 15,732 (SD ± 17,388) clones per sample. We compared pre- and post-therapy TCR diversity among both outcome groups using the Shannon diversity index. TCR diversity did not significantly change following 5-Aza treatment (4827 vs 6159, P= 0.55). Also, TCR diversity was not significantly different between outcome groups pre- and post-therapy. We designated clones as minor (&amp;lt; 10 reads) or major (&amp;gt; 10 reads). We compared pre- and post-therapy minor clone TRBV exon patterns and discovered a 2.2 fold increase in unique clones containing TRBV16 among responders post therapy (P = 0.017). We also observed a 2.5 fold increase in unique clones containing TRBV7-4 in non-responders post therapy (P = 0.034). There were no significant exon pattern changes in non-stratified analysis. When pre-therapy minor clone exon patterns were compared between outcome groups, a higher frequency of unique clones containing TRBV12-2 in responders versus non-responders was observed (2.8 fold, P &amp;lt; 0.001). In addition, we observed a higher frequency of major clones containing TRBV12-5 among responders post therapy (2.4 fold, P = 0.0558). In the pre-therapy samples, there was a higher frequency of clones containing TRBV5-4 among responders compared to non-responders (2.7 fold, P =0.045). In conclusion, changes in TCR repertoire features such as the utilization of specific V exons may associate with response to 5-Azacytidine therapy. Citation Format: John Beckford, Noreen Fulton, Toyosi Odenike, Wendy Stock, Houda Alachkar. Characterization of the T-Cell receptor repertoire in patients with acute myeloid leukemia treated with 5-Azacytidine plus chemotherapy [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 4492.

BackgroundInsertion sequences (IS) are small transposable elements, commonly found in bacterial genomes. Identifying the location of IS in bacterial genomes can be useful for a variety of purposes including epidemiological tracking and predicting antibiotic resistance. However IS are commonly present in multiple copies in a single genome, which complicates genome assembly and the identification of IS insertion sites. Here we present ISMapper, a mapping-based tool for identification of the site and orientation of IS insertions in bacterial genomes, directly from paired-end short read data.ResultsISMapper was validated using three types of short read data: (i) simulated reads from a variety of species, (ii) Illumina reads from 5 isolates for which finished genome sequences were available for comparison, and (iii) Illumina reads from 7 Acinetobacter baumannii isolates for which predicted IS locations were tested using PCR. A total of 20 genomes, including 13 species and 32 distinct IS, were used for validation. ISMapper correctly identified 97 % of known IS insertions in the analysis of simulated reads, and 98 % in real Illumina reads. Subsampling of real Illumina reads to lower depths indicated ISMapper was able to correctly detect insertions for average genome-wide read depths >20x, although read depths >50x were required to obtain confident calls that were highly-supported by evidence from reads. All ISAba1 insertions identified by ISMapper in the A. baumannii genomes were confirmed by PCR. In each A. baumannii genome, ISMapper successfully identified an IS insertion upstream of the ampC beta-lactamase that could explain phenotypic resistance to third-generation cephalosporins. The utility of ISMapper was further demonstrated by profiling genome-wide IS6110 insertions in 138 publicly available Mycobacterium tuberculosis genomes, revealing lineage-specific insertions and multiple insertion hotspots.ConclusionsISMapper provides a rapid and robust method for identifying IS insertion sites directly from short read data, with a high degree of accuracy demonstrated across a wide range of bacteria.

Tandem duplication of coding sequence is an important mechanism of somatic mutation capable of activating oncogenes such as fms-related tyrosine kinase 3 (FLT3) as well as the potential for underlying constitutional or germline disease. Detection of internal tandem duplication (ITD) in short-read sequencing data remains challenging due to deficiencies in short-read alignment where reads carrying signatures of ITD are often unmapped. Assembly based approaches collapse repetitive sequences, resulting in reduced or lost genomic complexity. The majority of structural variation detection tools are limited to finding insertions that are contained entirely within individual read alignments, and are unable to detect read-spanning duplications. Tools designed to detect large structural variation from paired-end reads that map discordantly based on expected fragment size and orientation do not provide the precision needed to detect ITDs. Only tools that consider the characteristic alignment features that signal the presence of ITDs will be able to detect them; these alignment features include: an excess of reads with unaligned, soft-clipped bases, read pairs where one end is unmapped located near the site of insertion, and read pairs where both ends are unmapped. We introduce ITD Assembler, a novel approach that searches all unmapped reads from exome capture or whole genome sequencing data to identify duplications. From the entire set of unmapped reads plus subset of mapped reads harboring soft-clipped bases, de Bruijn graph assembly is applied to select reads that form cycles, indicative of duplicated sequence structures. Reads from de Bruijn graph cycles are then assembled using an Overlap Layout Consensus (OLC) methodology thereby alleviating the collapse of repeat sequences affecting de Bruijn graph assembly approaches. Resulting OLC assembled contigs are locally aligned to the reference sequence to annotate the position of ITDs. ITD Assembler was run on The Cancer Genome Atlas (TCGA) acute myeloid leukemia (AML) dataset, and FLT3-ITD detection rates were compared against orthogonal algorithms. ITD Assembler identified the highest percentage of TCGA FLT3-ITDs, reported significantly higher allele fractions, and discovered additional ITDs in the KIT, CEBPA and WT1 cancer genes. Citation Format: Oliver A. Hampton, Navin Rustagi, Jie Li, Liu Xi, Richard A. Gibbs, Sharon E. Plon, Marek Kimmel, David A. Wheeler. ITD Assembler: An algorithm for internal tandem duplication discovery from short-read sequencing data. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4856. doi:10.1158/1538-7445.AM2015-4856

Short read whole genome sequencing has become widely used to detect structural variants in human genetic studies and clinical practices. However, accurate detection of structural variants is a challenging task. Especially existing structural variant detection approaches produce a large proportion of incorrect calls, so effective structural variant filtering approaches are urgently needed. In this study, we propose a novel deep learning-based approach, DeepSVFilter, for filtering structural variants in short read whole genome sequencing data. DeepSVFilter encodes structural variant signals in the read alignments as images and adopts the transfer learning with pre-trained convolutional neural networks as the classification models, which are trained on the well-characterized samples with known high confidence structural variants. We use two well-characterized samples to demonstrate DeepSVFilter's performance and its filtering effect coupled with commonly used structural variant detection approaches. The software DeepSVFilter is implemented using Python and freely available from the website at https://github.com/yongzhuang/DeepSVFilter.

Background: Hypertension (HTN) is a common cardiovascular condition that is associated with an increased risk of experiencing heart disease. Chronic pressure overload due to HTN can induce cardiac hypertrophy, which may present in the form of concentric (thickening of the heart walls) or eccentric (expansion of the heart cavity) hypertrophy. Both HTN and cardiac hypertrophy are independent risk factors for experiencing heart failure and co-incident HTN and cardiac hypertrophy exacerbates that heart failure risk. If we can identify those who are most at risk for experiencing cardiac hypertrophy in the presence of HTN, early preventative measures may be initiated to minimize the progression toward heart failure. In this study, we sought to identify if common genetic variants associated with cardiac hypertrophy in the presence of hypertension. Methods: A multi-ancestry cohort (N=82180) consisting of individuals with short-read whole genome sequencing data and an occurrence of essential HTN in their medical record was constructed from the All of Us version 7 dataset. Cardiac hypertrophy – defined as an occurrence of cardiomegaly, left ventricular hypertrophy, hypertrophic cardiomyopathy, or dilated cardiomyopathy – was excluded from controls (N=72960, mean age at initial HTN=58, 56% female) or included in cases (N=9220, mean age at initial HTN=60, 50% female). Genome-wide association studies (GWAS) were conducted using logistic multivariate regression models to test for associations between variants and hypertensive cardiac hypertrophy. These GWAS were stratified by ancestry, included three principal components, and were adjusted by sex and age at initial HTN. Results: European ancestry GWAS identified three genome-wide significant and four suggestive significant variants in the ARVCF gene. Ancestry stratification confirmed that statistical or suggestive associations between ARVCF variants and hypertensive cardiac hypertrophy were observed only in those of European ancestry. None of these variants have previously reported associations with HTN or cardiac hypertrophy. Conclusion: We have discovered loci in the ARVCF gene that associate with hypertensive cardiac hypertrophy among Europeans in the All of Us research program. We intend to replicate our work in other large European cohorts to confirm the potential value of this gene for future biomedical studies.

Motivationde novo variants (DNVs) are variants that are present in offspring but not in their parents. DNVs are both important for examining mutation rates as well as in the identification of disease-related variation. While efforts have been made to call DNVs, calling of DNVs is still challenging from parent–child sequenced trio data. We developed Hare And Tortoise (HAT) as an automated DNV detection workflow for highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genomics and HAT addresses this need.ResultsHAT is a computational workflow that begins with aligned read data (i.e. CRAM or BAM) from a parent–child sequenced trio and outputs DNVs. HAT detects high-quality DNVs from Illumina short-read whole-exome sequencing, Illumina short-read whole-genome sequencing, and highly accurate PacBio HiFi long-read whole-genome sequencing data. The quality of these DNVs is high based on a series of quality metrics including number of DNVs per individual, percent of DNVs at CpG sites, and percent of DNVs phased to the paternal chromosome of origin.Availability and implementationhttps://github.com/TNTurnerLab/HAT

BackgroundBacterial whole-genome sequencing based on short-read technologies often results in a draft assembly formed by contiguous sequences. The introduction of long-read sequencing technologies permits those contiguous sequences to be unambiguously bridged into complete genomes. However, the elevated costs associated with long-read sequencing frequently limit the number of bacterial isolates that can be long-read sequenced. Here we evaluated the recently released 96 barcoding kit from Oxford Nanopore Technologies (ONT) to generate complete genomes on a high-throughput basis. In addition, we propose an isolate selection strategy that optimizes a representative selection of isolates for long-read sequencing considering as input large-scale bacterial collections.ResultsDespite an uneven distribution of long reads per barcode, near-complete chromosomal sequences (assembly contiguity = 0.89) were generated for 96 Escherichia coli isolates with associated short-read sequencing data. The assembly contiguity of the plasmid replicons was even higher (0.98), which indicated the suitability of the multiplexing strategy for studies focused on resolving plasmid sequences. We benchmarked hybrid and ONT-only assemblies and showed that the combination of ONT sequencing data with short-read sequencing data is still highly desirable (i) to perform an unbiased selection of isolates for long-read sequencing, (ii) to achieve an optimal genome accuracy and completeness, and (iii) to include small plasmids underrepresented in the ONT library.ConclusionsThe proposed long-read isolate selection ensures the completion of bacterial genomes that span the genome diversity inherent in large collections of bacterial isolates. We show the potential of using this multiplexing approach to close bacterial genomes on a high-throughput basis.

Here, we present Lancet2, an open-source somatic variant caller designed to improve detection of small variants in short-read sequencing data. Lancet2 introduces significant enhancements, including: (i) Improved variant discovery and genotyping through partial order multiple sequence alignment of assembled haplotype contigs, and re-alignment of sample reads to the best supporting allele. (ii) Optimized somatic variant scoring with explainable machine learning models, leading to better somatic filtering throughout the sensitivity scale. (iii) Integration with Sequence Tube Map for enhanced visualization of variants with aligned sample reads in graph space. When benchmarked against enhanced two-tech truth sets generated using high-coverage short-read (Illumina) and long-read (Oxford Nanopore) data from four well characterized matched tumor/normal cell lines, Lancet2 outperformed other industry-leading tools in variant calling performance, especially for InDels. In addition, significant runtime performance improvements were observed compared to Lancet1 (∼10× speedup and 50% less peak memory usage), and most other state-of-the-art somatic variant callers (at least 2× speedup with eight cores or more), making Lancet2 an ideal tool for accurate and efficient somatic variant calling.