Unique Molecular Identifier-Based High-Resolution HLA Typing and Transcript Quantitation Using Long-Read Sequencing.
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ABSTRACT:
SUBMITTER: Cornaby C
PROVIDER: S-EPMC9308011 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundHuman leucocyte antigen (HLA) genes play an important role in determining the outcome of organ transplantation and are linked to many human diseases. Because of the diversity and polymorphisms of HLA loci, HLA typing at high resolution is challenging even with whole-genome sequencing data.ResultsWe have developed a computational tool, HLA-VBSeq, to estimate the most probable HLA alleles at full (8-digit) resolution from whole-genome sequence data. HLA-VBSeq simultaneously optimizes read alignments to HLA allele sequences and abundance of reads on HLA alleles by variational Bayesian inference. We show the effectiveness of the proposed method over other methods through the analysis of predicting HLA types for HLA class I (HLA-A, -B and -C) and class II (HLA-DQA1,-DQB1 and -DRB1) loci from the simulation data of various depth of coverage, and real sequencing data of human trio samples.ConclusionsHLA-VBSeq is an efficient and accurate HLA typing method using high-throughput sequencing data without the need of primer design for HLA loci. Moreover, it does not assume any prior knowledge about HLA allele frequencies, and hence HLA-VBSeq is broadly applicable to human samples obtained from a genetically diverse population.
| S-EPMC4331721 | biostudies-literature
Project description:The incidence of narcolepsy type 1 (NT1) increased in Sweden following the 2009-2010 mass-vaccination with the influenza Pandemrix-vaccine. NT1 has been associated with Human leukocyte antigen (HLA) DQB1*06:02 but full high-resolution HLA-typing of all loci in vaccine-induced NT1 remains to be done. Therefore, here we performed HLA typing by sequencing HLA-DRB3, DRB4, DRB5, DRB1, DQA1, DQB1, DPA1 and DPB1 in 31 vaccine-associated NT1 patients and 66 of their first-degree relatives (FDR), and compared these data to 636 Swedish general population controls (GP). Previously reported disease-related alleles in the HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01 extended haplotype were increased in NT1 patients (34/62 haplotypes, 54.8%) compared to GP (194/1272 haplotypes, 15.3%, p = 6.17E-16). Indeed, this extended haplotype was found in 30/31 patients (96.8%) and 178/636 GP (28.0%). In total, 15 alleles, four extended haplotypes, and six genotypes were found to be increased or decreased in frequency among NT1 patients compared to GP. Among subjects with the HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02-DQB1*06:02 haplotype, a second DRB4*01:03:01-DRB1*04:01:01-DQA1*03:02//*03:03:01-DQB1*03:01:01 haplotype (p = 2.02E-2), but not homozygosity for DRB1*15:01:01-DQB1*06:02:01 (p = 7.49E-1) conferred association to NT1. Alleles with increased frequency in DQA1*01:02:01 (p = 1.07E-2) and DQA1*03:02//*03:03:01 (p = 3.26E-2), as well as with decreased frequency in DRB3*01:01:02 (p = 8.09E-3), DRB1*03:01:01 (p = 1.40E-2), and DQB1*02:01:01 (p = 1.40E-2) were found among patients compared to their FDR. High-resolution HLA sequencing in Pandemrix-associated NT1 confirmed the strong association with the DQB1*06:02:01-containing haplotype but also revealed an increased association to the not previously reported extended HLA-DRB4*01:03:01-DRB1*04:01:01-DQA1*03:02//*03:03:01-DQB1*03:01:01 haplotype. High-resolution HLA typing should prove useful in dissecting the immunological mechanisms of vaccination-associated NT1.
| S-EPMC6774514 | biostudies-literature
Project description:RNA sequencing (RNA-seq) enables characterization and quantification of individual transcriptomes as well as detection of patterns of allelic expression and alternative splicing. Current RNA-seq protocols depend on high-throughput short-read sequencing of cDNA. However, as ongoing advances are rapidly yielding increasing read lengths, a technical hurdle remains in identifying the degree to which differences in read length influence various transcriptome analyses. In this study, we generated two paired-end RNA-seq datasets of differing read lengths (2×75 bp and 2×262 bp) for lymphoblastoid cell line GM12878 and compared the effect of read length on transcriptome analyses, including read-mapping performance, gene and transcript quantification, and detection of allele-specific expression (ASE) and allele-specific alternative splicing (ASAS) patterns. Our results indicate that, while the current long-read protocol is considerably more expensive than short-read sequencing, there are important benefits that can only be achieved with longer read length, including lower mapping bias and reduced ambiguity in assigning reads to genomic elements, such as mRNA transcript. We show that these benefits ultimately lead to improved detection of cis-acting regulatory and splicing variation effects within individuals.
| S-EPMC4176000 | biostudies-literature
Project description:Gene fusions are found as cancer drivers in diverse adult and pediatric cancers. Accurate detection of fusion transcripts is essential in cancer clinical diagnostics, prognostics, and for guiding therapeutic development. Most currently available methods for fusion transcript detection are compatible with Illumina RNA-seq involving highly accurate short read sequences. Recent advances in long read isoform sequencing enable the detection of fusion transcripts at unprecedented resolution in bulk and single cell samples. Here we developed a new computational tool CTAT-LR-fusion to detect fusion transcripts from long read RNA-seq with or without companion short reads, with applications to bulk or single cell transcriptomes. We demonstrate that CTAT-LR-fusion exceeds fusion detection accuracy of alternative methods as benchmarked with simulated and real long read RNA-seq. Using short and long read RNA-seq, we further apply CTAT-LR-fusion to bulk transcriptomes of nine tumor cell lines, and to tumor single cells derived from a melanoma sample and three metastatic high grade serous ovarian carcinoma samples. In both bulk and in single cell RNA-seq, long isoform reads yielded higher sensitivity for fusion detection than short reads with notable exceptions. By combining short and long reads in CTAT-LR-fusion, we are able to further maximize detection of fusion splicing isoforms and fusion-expressing tumor cells. CTAT-LR-fusion is available at https://github.com/TrinityCTAT/CTAT-LR-fusion/wiki.
| S-EPMC10925146 | biostudies-literature
Project description:The chicken has long served as an important model organism in many fields, and continues to aid our understanding of animal development. Functional genomics studies aimed at probing the mechanisms that regulate development require high-quality genomes and transcript annotations. The quality of these resources has improved dramatically over the last several years, but many isoforms and genes have yet to be identified. We hope to contribute to the process of improving these resources with the data presented here: a set of long cDNA sequencing reads, and a curated set of new genes and transcript isoforms not currently represented in the most up-to-date genome annotation currently available to the community of researchers who rely on the chicken genome.
| S-EPMC3988055 | biostudies-literature
Project description:With the emergence of zebrafish as an important model organism, a concerted effort has been made to study its transcriptome. This effort is limited, however, by gaps in zebrafish annotation, which are especially pronounced concerning transcripts dynamically expressed during zygotic genome activation (ZGA). To date, short-read sequencing has been the principal technology for zebrafish transcriptome annotation. In part because these sequence reads are too short for assembly methods to resolve the full complexity of the transcriptome, the current annotation is rudimentary. By providing direct observation of full-length transcripts, recently refined long-read sequencing platforms can dramatically improve annotation coverage and accuracy. Here, we leveraged the SMRT platform to study the transcriptome of zebrafish embryos before and after ZGA. Our analysis revealed additional novelty and complexity in the zebrafish transcriptome, identifying 2539 high-confidence novel transcripts that originated from previously unannotated loci and 1835 high-confidence new isoforms in previously annotated genes. We validated these findings using a suite of computational approaches including structural prediction, sequence homology, and functional conservation analyses, as well as by confirmatory transcript quantification with short-read sequencing data. Our analyses provided insight into new homologs and paralogs of functionally important proteins and noncoding RNAs, isoform switching occurrences, and different classes of novel splicing events. Several novel isoforms representing distinct splicing events were validated through PCR experiments, including the discovery and validation of a novel 8-kb transcript spanning multiple mir-430 elements, an important driver of early development. Our study provides a significantly improved zebrafish transcriptome annotation resource.
| S-EPMC6120630 | biostudies-literature
Project description:BackgroundVancomycin-resistant enterococci (VRE) are successful nosocomial pathogens able to cause hospital outbreaks. In the Netherlands, core-genome MLST (cgMLST) based on short-read sequencing is often used for molecular typing. Long-read sequencing is more rapid and provides useful information about the genome's structural composition but lacks the precision required for SNP-based typing and cgMLST. Here we compared prophages among 50 complete E. faecium genomes belonging to different lineages to explore whether a phage signature would be usable for typing and identifying an outbreak caused by VRE. As a proof of principle, we investigated if long-read sequencing data would allow for identifying phage signatures and thereby outbreak-related isolates.ResultsAnalysis of complete genome sequences of publicly available isolates showed variation in phage content among different lineages defined by MLST. We identified phage present in multiple STs as well as phages uniquely detected within a single lineage. Next, in silico phage typing was applied to twelve MinION sequenced isolates belonging to two different genetic backgrounds, namely ST117/CT24 and ST80/CT16. Genomic comparisons of the long-read-based assemblies allowed us to correctly identify isolates of the same complex type based on global genome architecture and specific phage signature similarity.ConclusionsFor rapid identification of related VRE isolates, phage content analysis in long-read sequencing data is possible. This allows software development for real-time typing analysis of long-read sequencing data, which will generate results within several hours. Future studies are required to assess the discriminatory power of this method in the investigation of ongoing outbreaks over a longer time period.
| S-EPMC8542323 | biostudies-literature
Project description:The major histocompatibility complex (MHC) plays a critical role in the vertebrate immune system. Accurate MHC typing is critical to understanding not only host fitness and disease susceptibility, but also the mechanisms underlying host-pathogen co-evolution. However, due to the high degree of gene duplication and diversification of MHC genes, it is often technically challenging to accurately characterise MHC genetic diversity in non-model species. Here we conducted a systematic review to identify common issues associated with current widely used MHC typing approaches. Then to overcome these challenges, we developed a long-read based MHC typing method along with a new analysis pipeline. Our approach enables the sequencing of fully phased MHC alleles spanning all key functional domains and the separation of highly similar alleles as well as the removal of technical artefacts such as PCR heteroduplexes and chimeras. Using this approach, we performed population-scale MHC typing in the Tasmanian devil (Sarcophilus harrisii), revealing previously undiscovered MHC functional diversity in this endangered species. Our new method provides a better solution for addressing research questions that require high MHC typing accuracy. Since the method is not limited by species or the number of genes analysed, it will be applicable for studying not only the MHC but also other complex gene families.
| S-EPMC9293008 | biostudies-literature
Project description:Ongoing improvements to next generation sequencing technologies are leading to longer sequencing read lengths, but a thorough understanding of the impact of longer reads on RNA sequencing analyses is lacking. To address this issue, we generated and compared two RNA sequencing datasets of differing read lengths -- 2x75 bp (L75) and 2x262 bp (L262) -- and investigated the impact of read length on various aspects of analysis, including the performance of currently available read-mapping tools, gene and transcript quantification, and detection of allele-specific expression patterns. Our results indicate that, while the scalability of read-mapping tools and the cost-effectiveness of long read protocol is an issue that requires further attention, longer reads enable more accurate quantification of diverse aspects of gene expression, including individual-specific patterns of allele-specific expression and alternative splicing. Two RNA-Seq datasets of differing read lengths (2x262 bp and 2x75 bp)
2014-09-25 | E-GEOD-57862 | biostudies-arrayexpress
Project description:MotivationThe human leukocyte antigen (HLA) locus plays a critical role in tissue compatibility and regulates the host response to many diseases, including cancers and autoimmune di3orders. Recent improvements in the quality and accessibility of next-generation sequencing have made HLA typing from standard short-read data practical. However, this task remains challenging given the high level of polymorphism and homology between HLA genes. HLA typing from RNA sequencing is further complicated by post-transcriptional modifications and bias due to amplification.ResultsHere, we present arcasHLA: a fast and accurate in silico tool that infers HLA genotypes from RNA-sequencing data. Our tool outperforms established tools on the gold-standard benchmark dataset for HLA typing in terms of both accuracy and speed, with an accuracy rate of 100% at two-field resolution for Class I genes, and over 99.7% for Class II. Furthermore, we evaluate the performance of our tool on a new biological dataset of 447 single-end total RNA samples from nasopharyngeal swabs, and establish the applicability of arcasHLA in metatranscriptome studies.Availability and implementationarcasHLA is available at https://github.com/RabadanLab/arcasHLA.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC6956775 | biostudies-literature