Sequencing and Structure Probing of Long RNAs Using MarathonRT: A Next-Generation Reverse Transcriptase.
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ABSTRACT:
SUBMITTER: Guo LT
PROVIDER: S-EPMC7556701 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We previously reported that, based on clone-based sequencing (CBS), hepatitis B virus (HBV) heterogeneity within the reverse transcriptase (RT) region was a predictor of antiviral efficacy. Here, by comparing ultradeep pyrosequencing (UDPS), i.e., next-generation sequencing (NGS), with CBS in characterizing the genetic heterogeneity of HBV quasispecies within the RT region, we evaluated the performance of UDPS in the analysis of HBV viral populations. HBV genomic DNA was extracted from serum samples from 31 antiviral treatment-naive patients with chronic hepatitis B. The RT region quasispecies were analyzed in parallel using CBS and UDPS. Characterization of quasispecies heterogeneity was conducted using bioinformatics analysis. Quasispecies complexity values were calculated with the formula Sn = -Σi(pilnpi)/lnN. The number of qualified strains obtained by UDPS was much larger than that obtained by CBS (P < 0.001). Pearson analysis showed that there was a positive correlation of quasispecies complexity values at the nucleotide level for the two methods (P < 0.05), while the complexity value derived from UDPS data was higher than that derived from CBS data (P < 0.001). Study of the prevalences of variations within the RT region showed that CBS detected an average of 9.7 ± 1.1 amino acid substitutions/sample and UDPS detected an average of 16.2 ± 1.4 amino acid substitutions/sample. The phylogenetic analysis based on UDPS data showed more genetic entities than did that based on CBS data. Viral heterogeneity determination by the UDPS technique is more sensitive and efficient in terms of low-abundance variation detection and quasispecies simulation than that by the CBS method, although imperfect, and thus sheds light on the future clinical application of NGS in HBV quasispecies studies.
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Project description:NGPS is a method for de-novo, full-length protein sequencing in high throughput. The method is based on cleavage of the protein at semi-random sites by microwave-assisted acid hydrolysis (MAAH), enrichment of LC-MS/MS amenable peptides from the hydrolysate by solid-phase-extraction, LC-MS/MS analysis, de-novo long peptide tag sequencing of resulting peptides and assembly of peptide tags into consensus contigs.
2017-04-03 | PXD003804 | Pride
Project description:Sequencing of a bulk polymerase chain reaction (PCR) product to identify drug resistance mutations informs antiretroviral therapy selection but has limited sensitivity for minority variants. Alternatively, deep sequencing is capable of detecting minority variants but is subject to sequencing errors and PCR resampling due to low input templates. We screened for resistance mutations among 184 HIV-1-infected, therapy-naive subjects using the 454 sequencing platform to sequence two amplicons spanning HIV-1 reverse transcriptase codons 34-245. Samples from 19 subjects were also analyzed using the MiSeq sequencing platform for comparison. Errors and PCR resampling were addressed by tagging each HIV-1 RNA template copy (i.e., cDNA) with a unique sequence tag (Primer ID), allowing a consensus sequence to be constructed for each original template from resampled sequences. In control reactions, Primer ID reduced 454 and MiSeq errors from 71 to 2.6 and from 24 to 1.2 errors/10,000 nucleotides, respectively. MiSeq also allowed accurate sequencing of codon 65, an important drug resistance position embedded in a homopolymeric run that is poorly resolved by the 454 platform. Excluding homopolymeric positions, 14% of subjects had evidence of ≥1 resistance mutation among Primer ID consensus sequences, compared to 2.7% by bulk population sequencing. When calls were restricted to mutations that appeared twice among consensus sequence populations, 6% of subjects had detectable resistance mutations. The use of Primer ID revealed 5-15% template utilization on average, limiting the depth of deep sequencing sampling and revealing sampling variation due to low template utilization. Primer ID addresses important limitations of deep sequencing and produces less biased estimates of low-level resistance mutations in the viral population.
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Project description:BACKGROUND: The advent of large-scale gene expression technologies has helped to reveal in eukaryotic cells, the existence of thousands of non-coding transcripts, whose function and significance remain mostly poorly understood. Among these non-coding transcripts, long non-coding RNAs (lncRNAs) are the least well-studied but are emerging as key regulators of diverse cellular processes. In the present study, we performed a survey in bovine Longissimus thoraci of lincRNAs (long intergenic non-coding RNAs not overlapping protein-coding transcripts). To our knowledge, this represents the first such study in bovine muscle. RESULTS: To identify lincRNAs, we used paired-end RNA sequencing (RNA-Seq) to explore the transcriptomes of Longissimus thoraci from nine Limousin bull calves. Approximately 14-45 million paired-end reads were obtained per library. A total of 30,548 different transcripts were identified. Using a computational pipeline, we defined a stringent set of 584 different lincRNAs with 418 lincRNAs found in all nine muscle samples. Bovine lincRNAs share characteristics seen in their mammalian counterparts: relatively short transcript and gene lengths, low exon number and significantly lower expression, compared to protein-encoding genes. As for the first time, our study identified lincRNAs from nine different samples from the same tissue, it is possible to analyse the inter-individual variability of the gene expression level of the identified lincRNAs. Interestingly, there was a significant difference when we compared the expression variation of the 418 lincRNAs with the 10,775 known selected protein-encoding genes found in all muscle samples. In addition, we found 2,083 pairs of lincRNA/protein-encoding genes showing a highly significant correlated expression. Fourteen lincRNAs were selected and 13 were validated by RT-PCR. Some of the lincRNAs expressed in muscle are located within quantitative trait loci for meat quality traits. CONCLUSIONS: Our study provides a glimpse into the lincRNA content of bovine muscle and will facilitate future experimental studies to unravel the function of these molecules. It may prove useful to elucidate their effect on mechanisms underlying the genetic variability of meat quality traits. This catalog will complement the list of lincRNAs already discovered in cattle and therefore will help to better annotate the bovine genome.
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Project description:BackgroundSmall ncRNAs (sncRNAs) offer great hope as biomarkers of disease and response to treatment. This has been highlighted in the context of several medical conditions such as cancer, liver disease, cardiovascular disease, and central nervous system disorders, among many others. Here we assessed several steps involved in the development of an ncRNA biomarker discovery pipeline, ranging from sample preparation to bioinformatic processing of small RNA sequencing data.MethodsA total of 45 biological samples were included in the present study. All libraries were prepared using the Illumina TruSeq Small RNA protocol and sequenced using the HiSeq2500 or MiSeq Illumina sequencers. Small RNA sequencing data was validated using qRT-PCR. At each stage, we evaluated the pros and cons of different techniques that may be suitable for different experimental designs. Evaluation methods included quality of data output in relation to hands-on laboratory time, cost, and efficiency of processing.ResultsOur results show that good quality sequencing libraries can be prepared from small amounts of total RNA and that varying degradation levels in the samples do not have a significant effect on the overall quantification of sncRNAs via NGS. In addition, we describe the strengths and limitations of three commercially available library preparation methods: (1) Novex TBE PAGE gel; (2) Pippin Prep automated gel system; and (3) AMPure XP beads. We describe our bioinformatics pipeline, provide recommendations for sequencing coverage, and describe in detail the expression and distribution of all sncRNAs in four human tissues: whole-blood, brain, heart and liver.ConclusionsUltimately this study provides tools and outcome metrics that will aid researchers and clinicians in choosing an appropriate and effective high-throughput sequencing quantification method for various study designs, and overall generating valuable information that can contribute to our understanding of small ncRNAs as potential biomarkers and mediators of biological functions and disease.
| S-EPMC4487992 | biostudies-literature