RESUMO
Advancements in sequencing technologies and assembly methods enable the regular production of high-quality genome assemblies characterizing complex regions. However, challenges remain in efficiently interpreting variation at various scales, from smaller tandem repeats to megabase rearrangements, across many human genomes. We present a PanGenome Research Tool Kit (PGR-TK) enabling analyses of complex pangenome structural and haplotype variation at multiple scales. We apply the graph decomposition methods in PGR-TK to the class II major histocompatibility complex demonstrating the importance of the human pangenome for analyzing complicated regions. Moreover, we investigate the Y-chromosome genes, DAZ1/DAZ2/DAZ3/DAZ4, of which structural variants have been linked to male infertility, and X-chromosome genes OPN1LW and OPN1MW linked to eye disorders. We further showcase PGR-TK across 395 complex repetitive medically important genes. This highlights the power of PGR-TK to resolve complex variation in regions of the genome that were previously too complex to analyze.
Assuntos
Genoma Humano , Genômica , Masculino , Humanos , Complexo Principal de HistocompatibilidadeRESUMO
Long-read sequencing technologies substantially overcome the limitations of short-reads but have not been considered as a feasible replacement for population-scale projects, being a combination of too expensive, not scalable enough or too error-prone. Here we develop an efficient and scalable wet lab and computational protocol, Napu, for Oxford Nanopore Technologies long-read sequencing that seeks to address those limitations. We applied our protocol to cell lines and brain tissue samples as part of a pilot project for the National Institutes of Health Center for Alzheimer's and Related Dementias. Using a single PromethION flow cell, we can detect single nucleotide polymorphisms with F1-score comparable to Illumina short-read sequencing. Small indel calling remains difficult within homopolymers and tandem repeats, but achieves good concordance to Illumina indel calls elsewhere. Further, we can discover structural variants with F1-score on par with state-of-the-art de novo assembly methods. Our protocol phases small and structural variants at megabase scales and produces highly accurate, haplotype-specific methylation calls.
Assuntos
Genoma Humano , Sequenciamento por Nanoporos , Humanos , Análise de Sequência de DNA/métodos , Haplótipos , Metilação , Projetos Piloto , Sequenciamento de Nucleotídeos em Larga Escala/métodosRESUMO
Metabolic extremes provide opportunities to understand enzymatic and metabolic plasticity and biotechnological tools for novel biomaterial production. We discovered that seed oils of many Thunbergia species contain up to 92% of the unusual monounsaturated petroselinic acid (18:1Δ6), one of the highest reported levels for a single fatty acid in plants. Supporting the biosynthetic origin of petroselinic acid, we identified a Δ6-stearoyl-acyl carrier protein (18:0-ACP) desaturase from Thunbergia laurifolia, closely related to a previously identified Δ6-palmitoyl-ACP desaturase that produces sapienic acid (16:1Δ6)-rich oils in Thunbergia alata seeds. Guided by a T. laurifolia desaturase crystal structure obtained in this study, enzyme mutagenesis identified key amino acids for functional divergence of Δ6 desaturases from the archetypal Δ9-18:0-ACP desaturase and mutations that result in nonnative enzyme regiospecificity. Furthermore, we demonstrate the utility of the T. laurifolia desaturase for the production of unusual monounsaturated fatty acids in engineered plant and bacterial hosts. Through stepwise metabolic engineering, we provide evidence that divergent evolution of extreme petroselinic acid and sapienic acid production arises from biosynthetic and metabolic functional specialization and enhanced expression of specific enzymes to accommodate metabolism of atypical substrates.
Assuntos
Acanthaceae , Ácidos Graxos Monoinsaturados , Proteínas de Plantas , Estearoil-CoA Dessaturase , Acanthaceae/metabolismo , Proteína de Transporte de Acila/metabolismo , Evolução Molecular , Ácidos Graxos Monoinsaturados/metabolismo , Mutagênese , Óleos de Plantas/química , Proteínas de Plantas/análise , Proteínas de Plantas/genética , Proteínas de Plantas/metabolismo , Sementes/enzimologia , Estearoil-CoA Dessaturase/análise , Estearoil-CoA Dessaturase/genética , Estearoil-CoA Dessaturase/metabolismoRESUMO
BACKGROUND: Systems-level analyses, such as differential gene expression analysis, co-expression analysis, and metabolic pathway reconstruction, depend on the accuracy of the transcriptome. Multiple tools exist to perform transcriptome assembly from RNAseq data. However, assembling high quality transcriptomes is still not a trivial problem. This is especially the case for non-model organisms where adequate reference genomes are often not available. Different methods produce different transcriptome models and there is no easy way to determine which are more accurate. Furthermore, having alternative-splicing events exacerbates such difficult assembly problems. While benchmarking transcriptome assemblies is critical, this is also not trivial due to the general lack of true reference transcriptomes. RESULTS: In this study, we first provide a pipeline to generate a set of the simulated benchmark transcriptome and corresponding RNAseq data. Using the simulated benchmarking datasets, we compared the performance of various transcriptome assembly approaches including both de novo and genome-guided methods. The results showed that the assembly performance deteriorates significantly when alternative transcripts (isoforms) exist or for genome-guided methods when the reference is not available from the same genome. To improve the transcriptome assembly performance, leveraging the overlapping predictions between different assemblies, we present a new consensus-based ensemble transcriptome assembly approach, ConSemble. CONCLUSIONS: Without using a reference genome, ConSemble using four de novo assemblers achieved an accuracy up to twice as high as any de novo assemblers we compared. When a reference genome is available, ConSemble using four genome-guided assemblies removed many incorrectly assembled contigs with minimal impact on correctly assembled contigs, achieving higher precision and accuracy than individual genome-guided methods. Furthermore, ConSemble using de novo assemblers matched or exceeded the best performing genome-guided assemblers even when the transcriptomes included isoforms. We thus demonstrated that the ConSemble consensus strategy both for de novo and genome-guided assemblers can improve transcriptome assembly. The RNAseq simulation pipeline, the benchmark transcriptome datasets, and the script to perform the ConSemble assembly are all freely available from: http://bioinfolab.unl.edu/emlab/consemble/ .
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Genoma , Transcriptoma , ConsensoRESUMO
Papaverine, a poorly soluble opium alkaloid, has recently been shown to reduce retinal inflammation due to which it may have therapeutic application in the management of Leber's hereditary optic neuropathy. In this study, papaverine eyedrops based on medium chain triglycerides were prepared and the effect of diethyl glycol monoethyl ether (DGME) on their ocular distribution was evaluated using an ex vivo porcine eye model. The route of drug penetration was also studied by orienting the eye to expose either only the cornea or the sclera to the formulation. Furthermore, in vivo studies were performed to confirm ocular tolerability and evaluate ocular drug distribution. Our results showed increased papaverine concentrations in the cornea and sclera in the presence of DGME but with a slight reduction in the retina-choroid (RC) drug concentration when administered via the corneal route, suggesting that DGME enhances drug accumulation in the anterior ocular tissues but with little effect on posterior drug delivery. In vivo, the papaverine eyedrop with DGME showed good ocular tolerability with the highest drug concentration being observed in the cornea (1.53 ± 0.28 µg/g of tissue), followed by the conjunctiva (0.74 ± 0.18 µg/g) and sclera (0.25 ± 0.06 µg/g), respectively. However, no drug was detected in the RC, vitreous humor or plasma. Overall, this study highlighted that DGME influences ocular distribution and accumulation of papaverine. Moreover, results suggest that for hydrophobic drugs dissolved in hydrophobic non-aqueous vehicles, transcorneal penetration via the transuveal pathway may be the predominant route for drug penetration to posterior ocular tissues. Graphical abstract.
Assuntos
Olho/metabolismo , Papaverina/farmacocinética , Veículos Farmacêuticos/administração & dosagem , Animais , Humor Aquoso/metabolismo , Soluções Oftálmicas/metabolismo , Papaverina/administração & dosagem , Coelhos , Suínos , Distribuição TecidualRESUMO
BACKGROUND: The EPOCH regimen, consisting of vincristine sulfate, doxorubicin hydrochloride, and etoposide phosphate, is typically administered by continuous infusion over four days to oncology inpatients. If the EPOCH regimen was available to be administered through portable elastomeric pumps, chemotherapy could be transitioned to an outpatient setting, reducing inpatient bed days and overall healthcare costs. However, a lack of stability data for the admixtures in the elastomeric infusion devices currently prevents the transition of the regime to an outpatient setting. The purpose of this study is to determine the physical and chemical stability of the admixture in polyisoprene elastomeric pumps under different storage conditions to support the transition of the EPOCH regime to an outpatient setting. METHODS: The physico-chemical stability of three admixtures at a range of clinically relevant concentrations compounded in polyisoprene elastomeric infusors was determined when refrigerated at 2-6â over a 14-day period followed by 35â up to 7 days in the dark, and under standardized fluorescent light to simulate scenarios in clinical practice. RESULTS: All tested admixtures were compatible and the drugs were stable in the elastomeric infusors for up to 14 days when stored at 2-6â followed by 7 days at 35â in the dark, with nominal losses of <5%. The major degradant of etoposide phosphate was its active form etoposide. There was no degradation (<1% loss) found when the admixture was exposed to a standardized fluorescent light dose of 80 klux-h (25â) for 10 h. The temperature and light conditions the infusors were exposed to during the stability study were more severe than the conditions determine during clinical administration. CONCLUSION: The extended stability of the three infusional admixtures compounded in elastomeric infusion pumps demonstrated herein permits advance preparation and storage of these drugs, reducing pharmacy compounding resources. The demonstrated stability at 35â and under light exposure, conditions more severe than those experienced during clinical practice, support continuous infusions for up to seven days from the elastomeric infusors without a loss of potency. The proven stability of the EPOCH regimens in the tested elastomeric infusion device supports the transition of treatment to an outpatient setting which will reduce inpatient bed days and overall healthcare costs.
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Assistência Ambulatorial , Protocolos de Quimioterapia Combinada Antineoplásica/química , Doxorrubicina/administração & dosagem , Doxorrubicina/química , Estabilidade de Medicamentos , Elastômeros , Etoposídeo/administração & dosagem , Etoposídeo/análogos & derivados , Etoposídeo/química , Humanos , Bombas de Infusão , Compostos Organofosforados/administração & dosagem , Compostos Organofosforados/química , Vincristina/administração & dosagem , Vincristina/químicaRESUMO
Calling structural variations (SVs) is technically challenging, but using long reads remains the most accurate way to identify complex genomic alterations. Here we present Sniffles2, which improves over current methods by implementing a repeat aware clustering coupled with a fast consensus sequence and coverage-adaptive filtering. Sniffles2 is 11.8 times faster and 29% more accurate than state-of-the-art SV callers across different coverages (5-50×), sequencing technologies (ONT and HiFi) and SV types. Furthermore, Sniffles2 solves the problem of family-level to population-level SV calling to produce fully genotyped VCF files. Across 11 probands, we accurately identified causative SVs around MECP2, including highly complex alleles with three overlapping SVs. Sniffles2 also enables the detection of mosaic SVs in bulk long-read data. As a result, we identified multiple mosaic SVs in brain tissue from a patient with multiple system atrophy. The identified SV showed a remarkable diversity within the cingulate cortex, impacting both genes involved in neuron function and repetitive elements.
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Research and medical genomics require comprehensive and scalable solutions to drive the discovery of novel disease targets, evolutionary drivers, and genetic markers with clinical significance. This necessitates a framework to identify all types of variants independent of their size (e.g., SNV/SV) or location (e.g., repeats). Here we present DRAGEN that utilizes novel methods based on multigenomes, hardware acceleration, and machine learning based variant detection to provide novel insights into individual genomes with ~30min computation time (from raw reads to variant detection). DRAGEN outperforms all other state-of-the-art methods in speed and accuracy across all variant types (SNV, indel, STR, SV, CNV) and further incorporates specialized methods to obtain key insights in medically relevant genes (e.g., HLA, SMN, GBA). We showcase DRAGEN across 3,202 genomes and demonstrate its scalability, accuracy, and innovations to further advance the integration of comprehensive genomics for research and medical applications.
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The current version of the human reference genome, GRCh38, contains a number of errors including 1.2 Mbp of falsely duplicated and 8.04 Mbp of collapsed regions. These errors impact the variant calling of 33 protein-coding genes, including 12 with medical relevance. Here, we present FixItFelix, an efficient remapping approach, together with a modified version of the GRCh38 reference genome that improves the subsequent analysis across these genes within minutes for an existing alignment file while maintaining the same coordinates. We showcase these improvements over multi-ethnic control samples, demonstrating improvements for population variant calling as well as eQTL studies.
Assuntos
Genoma Humano , Genômica , Humanos , Sequenciamento de Nucleotídeos em Larga Escala , Análise de Sequência de DNARESUMO
The presence of somatic mutations, including copy number variants (CNVs), in the brain is well recognized. Comprehensive study requires single-cell whole genome amplification, with several methods available, prior to sequencing. We compared PicoPLEX with two recent adaptations of multiple displacement amplification (MDA): primary template-directed amplification (PTA) and droplet MDA, across 93 human brain cortical nuclei. We demonstrated different properties for each, with PTA providing the broadest amplification, PicoPLEX the most even, and distinct chimeric profiles. Furthermore, we performed CNV calling on two brains with multiple system atrophy and one control brain using different reference genomes. We found that 38% of brain cells have at least one Mb-scale CNV, with some supported by bulk sequencing or single-cells from other brain regions. Our study highlights the importance of selecting whole genome amplification method and reference genome for CNV calling, while supporting the existence of somatic CNVs in healthy and diseased human brain.
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Long-read sequencing technologies substantially overcome the limitations of short-reads but to date have not been considered as feasible replacement at scale due to a combination of being too expensive, not scalable enough, or too error-prone. Here, we develop an efficient and scalable wet lab and computational protocol for Oxford Nanopore Technologies (ONT) long-read sequencing that seeks to provide a genuine alternative to short-reads for large-scale genomics projects. We applied our protocol to cell lines and brain tissue samples as part of a pilot project for the NIH Center for Alzheimer's and Related Dementias (CARD). Using a single PromethION flow cell, we can detect SNPs with F1-score better than Illumina short-read sequencing. Small indel calling remains to be difficult inside homopolymers and tandem repeats, but is comparable to Illumina calls elsewhere. Further, we can discover structural variants with F1-score comparable to state-of the-art methods involving Pacific Biosciences HiFi sequencing and trio information (but at a lower cost and greater throughput). Using ONT based phasing, we can then combine and phase small and structural variants at megabase scales. Our protocol also produces highly accurate, haplotype-specific methylation calls. Overall, this makes large-scale long-read sequencing projects feasible; the protocol is currently being used to sequence thousands of brain-based genomes as a part of the NIH CARD initiative. We provide the protocol and software as open-source integrated pipelines for generating phased variant calls and assemblies.
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In October 2021, 59 scientists from 14 countries and 13 U.S. states collaborated virtually in the Third Annual Baylor College of Medicine & DNANexus Structural Variation hackathon. The goal of the hackathon was to advance research on structural variants (SVs) by prototyping and iterating on open-source software. This led to nine hackathon projects focused on diverse genomics research interests, including various SV discovery and genotyping methods, SV sequence reconstruction, and clinically relevant structural variation, including SARS-CoV-2 variants. Repositories for the projects that participated in the hackathon are available at https://github.com/collaborativebioinformatics.
Assuntos
COVID-19 , SARS-CoV-2 , Humanos , SARS-CoV-2/genética , Genômica , SoftwareRESUMO
In October 2020, 62 scientists from nine nations worked together remotely in the Second Baylor College of Medicine & DNAnexus hackathon, focusing on different related topics on Structural Variation, Pan-genomes, and SARS-CoV-2 related research. The overarching focus was to assess the current status of the field and identify the remaining challenges. Furthermore, how to combine the strengths of the different interests to drive research and method development forward. Over the four days, eight groups each designed and developed new open-source methods to improve the identification and analysis of variations among species, including humans and SARS-CoV-2. These included improvements in SV calling, genotyping, annotations and filtering. Together with advancements in benchmarking existing methods. Furthermore, groups focused on the diversity of SARS-CoV-2. Daily discussion summary and methods are available publicly at https://github.com/collaborativebioinformatics provides valuable insights for both participants and the research community.
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COVID-19 , SARS-CoV-2 , Animais , Genoma Viral , Humanos , VertebradosRESUMO
One method for identifying noncoding regulatory regions of a genome is to quantify rates of divergence between related species, as functional sequence will generally diverge more slowly. Most approaches to identifying these conserved noncoding sequences (CNSs) based on alignment have had relatively large minimum sequence lengths (≥15 bp) compared with the average length of known transcription factor binding sites. To circumvent this constraint, STAG-CNS that can simultaneously integrate the data from the promoters of conserved orthologous genes in three or more species was developed. Using the data from up to six grass species made it possible to identify conserved sequences as short as 9 bp with false discovery rate ≤0.05. These CNSs exhibit greater overlap with open chromatin regions identified using DNase I hypersensitivity assays, and are enriched in the promoters of genes involved in transcriptional regulation. STAG-CNS was further employed to characterize loss of conserved noncoding sequences associated with retained duplicate genes from the ancient maize polyploidy. Genes with fewer retained CNSs show lower overall expression, although this bias is more apparent in samples of complex organ systems containing many cell types, suggesting that CNS loss may correspond to a reduced number of expression contexts rather than lower expression levels across the entire ancestral expression domain.