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Exact transcript quantification over splice graphs

ALGORITHMS FOR MOLECULAR BIOLOGY 2021年第1期16卷 1-15页

作者： Ma, Cong Zheng, Hongyu Kingsford, Carl Carnegie Mellon Univ Sch Comp Sci Computat Biol Dept 5000 Forbes Ave Pittsburgh PA 15213 USA Princeton Univ Sch Engn & Appl Sci Comp Sci Dept 35 Olden St Princeton NJ 08544 USA

Background The probability of sequencing a set of RNA-seq reads can be directly modeled using the abundances of splice junctions in splice graphs instead of the abundances of a list of transcripts. We call this model graph quantification, which was first proposed by Bernard et al. (Bioinformatics 30:2447-55, 2014). The model can be viewed as a generalization of transcript expression quantification where every full path in the splice graph is a possible transcript. However, the previous graph quantification model assumes the length of single-end reads or paired-end fragments is fixed. Results We provide an improvement of this model to handle variable-length reads or fragments and incorporate bias correction. We prove that our model is equivalent to running a transcript quantifier with exactly the set of all compatible transcripts. The key to our method is constructing an extension of the splice graph based on Aho-Corasick automata. The proof of equivalence is based on a novel reparameterization of the read generation model of a state-of-art transcript quantification method. Conclusion We propose a new approach for graph quantification, which is useful for modeling scenarios where reference transcriptome is incomplete or not available and can be further used in transcriptome assembly or alternative splicing analysis.

关键词： RNA-seq Alternative splicing transcript quantification Splice graph Network flow

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transcript quantification of Genes Involved in Steviol Glycoside Biosynthesis in

Transcript Quantification of Genes Involved in Steviol Glyco...

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作者： Arpan Modi Nitish Kumar Subhash Narayanan

Stevia (Stevia rebaudiana Bertoni) is a medicinal plant having sweet, diterpenoid glycosides known as steviol glycosides which are 200–300 times sweeter than sucrose (0.4 % solution). They are synthesized mainly in the leaves via plastid localized 2-C-methyl-D-erythrose-4-phosphate pathway (MEP pathway). Fifteen genes are involved in the formation of these glycosides. In the present protocol, a method for the quantification of transcripts of these genes is shown. The work involves RNA extraction and cDNA preparation, and therefore, procedures for the confirmation of DNA-free cDNA preparation have also been illustrated. Moreover, details of plant treatments are not mentioned as this protocol may apply to relative gene expression profile in any medicinal plant with any treatment. The treatments are numbered as T0 (Control), T1, T2, T3, and T4. less

关键词： Real-time PCR RNA Extraction Total RNA Extraction Electrophoresis Stevioside transcript quantification Secondary metabolism Stevia Steviol glycosides

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The effect of alginate as an elicitor on transcription of steviol glycosides biosynthesis pathway related key genes and sweeteners content in in vitro cultured Stevia rebaudiana

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MOLECULAR BIOLOGY REPORTS 2023年第3期50卷 2283-2291页

作者： Tehranian, Alireza S. Askari, Hossein Rezadoost, Hassan Shahid Beheshti Univ Fac Sci & Biotechnol Dept Cellular & Mol Biol Tehran *** Iran Shahid Beheshti Univ Med Plants & Drugs Res Inst Tehran Iran

Background Stevia rebaudiana is a medicinal herb that accumulates non-caloric sweeteners called steviol glycosides (SGs) which are approximately 300 times sweeter than sucrose. This study used alginate (ALG) as an elicitor to increase steviol glycosides accumulation and elucidate gene transcription in the steviol glycosides biosynthesis pathway. Methods and Results To minimize the grassy taste associated with stevia sweeteners, plantlets were grown in complete darkness. ALG was applied to stevia plants grown in suspension culture with a Murashige and Skoog (MS) medium to determine its effect on SGs' content and the transcription profile of SG-related genes using the HPLC and RT-qPCR methods, respectively. Treatment with alginate did not significantly affect plantlet growth parameters such as shoot number, dry and fresh weight. Rebaudioside A (Reb A) content increased approximately sixfold in the presence of 1g L-1 alginate and KS, KAH, and UGT74G1 genes showed significant up-regulation. When the concentration was increased to 2g L-1, the transcription of KO and UGT76G1, responsible for the conversion of stevioside to Reb A, was increased about twofold. Conclusions The current study proposes that adding alginate to the MS suspension medium can increase Reb A levels by altering the SG biosynthesize pathway's transcription profile. The present experiment provides new insights into the biochemical and transcriptional response mechanisms of suspension-cultured stevia plants to alginate.

关键词： Dark condition Glycosides biosynthesis genes Rebaudioside A Secondary metabolites transcript quantification

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Pipeline for Antimicrobial Resistance Gene quantification from Host Tissue

CURRENT PROTOCOLS

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CURRENT PROTOCOLS 2025年第3期5卷 e70116页

作者： Svaren, Levi M. Li, Wenli ARS USDA Madison WI 53706 USA

Antibiotics are frequently used in food production animals to control disease and improve productivity, but this promotes the development of antimicrobial resistance (AMR) and subsequent broader spread of AMR bacteria throughout food chain, endangering the well-being and health of both animals and humans. In humans, the gut microbiome harbors a diverse range of AMR bacteria, known as the resistome. To effectively mitigate AMR in food animals requires first determining the expression and abundance of AMR-related genes in the gut resistome. Currently, such knowledge in regard to food animals is largely lacking. Gut tissue RNA sequencing (GTRS) can capture metabolically active transcripts from both the host and the microbes attached to the gut epithelium. Ideally, AMR genes can be quantified using GTRS data, making it possible to study the relationship between host and microbe. For the majority of these GTRS studies, only host transcriptome changes have been reported, while the microbial AMR remains largely unexamined, mainly due to the lack of easily implementable bioinformatics tools. Here we present a straightforward workflow to accomplish that using common command-line bioinformatics tools. With this pipeline, the host is considered noise, and host data are filtered out from the microbial reads. transcript quantification of the AMR genes is then performed. The pipeline then continues through AMR transcript quantification, differential gene expression, and SNP analysis. Using open-source tools, we made this analytical pipeline easy to implement and able to generate results ready to be incorporated into publishable reports. Published 2025. This article is a U.S. Government work and is in the public domain in the USA. Basic Protocol: Running the gene quantification pipeline Support Protocol 1: Downloading FASTQ files from the NCBI database Support Protocol 2: Building a genome reference index of the host Support Protocol 3: Differential gene expression analysis Suppor

关键词： antimicrobial resistance gut tissue RNA sequencing single nucleotide polymorphisms transcript quantification

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SCAPTURE: a deep learning-embedded pipeline that captures polyadenylation information from 3′ tag-based RNA-seq of single cells

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GENOME BIOLOGY 2021年第1期22卷 1-24页

作者： Li, Guo-Wei Nan, Fang Yuan, Guo-Hua Liu, Chu-Xiao Liu, Xindong Chen, Ling-Ling Tian, Bin Yang, Li Univ Chinese Acad Sci Chinese Acad Sci Shanghai Inst Nutr & Hlth CAS Key Lab Computat Biol Shanghai 200031 Peoples R China Univ Chinese Acad Sci State Key Lab Mol Biol Shanghai Key Lab Mol AndrolCAS Ctr Excellence Mo Chinese Acad SciShanghai Inst Biochem & Cell Bio 320 Yueyang Rd Shanghai 200031 Peoples R China Third Mil Med Univ Southwest Hosp Inst Pathol Army Med Univ Chongqing 400038 Peoples R China Third Mil Med Univ Southwest Hosp Southwest Canc Ctr Army Med Univ Chongqing 400038 Peoples R China ShanghaiTech Univ Sch Life Sci & Technol Shanghai 201210 Peoples R China Univ Chinese Acad Sci Sch Life Sci Hangzhou Inst Adv Study Hangzhou 310024 Peoples R China Wistar Inst Anat & Biol Program Gene Express & Regulat Philadelphia PA 19104 USA Wistar Inst Anat & Biol Ctr Syst & Computat Biol Philadelphia PA 19104 USA

Single-cell RNA-seq (scRNA-seq) profiles gene expression with high resolution. Here, we develop a stepwise computational method-called SCAPTURE to identify, evaluate, and quantify cleavage and polyadenylation sites (PASs) from 3 ' tag-based scRNA-seq. SCAPTURE detects PASs de novo in single cells with high sensitivity and accuracy, enabling detection of previously unannotated PASs. Quantified alternative PAS transcripts refine cell identity analysis beyond gene expression, enriching information extracted from scRNA-seq data. Using SCAPTURE, we show changes of PAS usage in PBMCs from infected versus healthy individuals at single-cell resolution.

关键词： scRNA-seq PAS APA Deep learning Peak calling transcript quantification

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Next-generation transcriptome assembly and analysis: Impact of ploidy

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METHODS 2020年 176卷 14-24页

作者： Voshall, Adam Moriyama, Etsuko N. Univ Nebraska Ctr Plant Sci Innovat Lincoln NE 68588 USA Univ Nebraska Sch Biol Sci Lincoln NE 68588 USA Univ Nebraska Dept Comp Sci & Engn Lincoln NE 68588 USA

Whole genome duplications (WGD) occur widely in plants, but the effects of these events impact all branches of life. WGD events have major evolutionary impacts, often leading to major structural changes within the chromosomes and massive changes in gene expression that facilitate rapid speciation and gene diversification. Even for species that currently have diploid genomes, the impact of ancestral duplication events is still present in the genomes, especially in the context of highly similar gene families that are retained from WGD. However, the impact of these ploidies on various bioinformatics workflows has not been studied well. In this review, we overview biological significance of polyploidy in different organisms. We describe the impact of having polyploid transcriptomes on bioinformatics analyses, especially focusing on transcriptome assembly and transcript quantification. We discuss the benefits of using simulated benchmarking data when we examine the performance of various methods. We also present an example strategy to generate simulated allopolyploid transcriptomes and RNAseq datasets and how these benchmark datasets can be used to assess the performance of transcript assembly and quantification methods. Our benchmarking study shows that all transcriptome assembly methods are affected by having polyploid genomes. quantification accuracy is also impacted by polyploidy depending on the method. These simulated datasets can be adapted for testing, such as, read mapping, variant calling, and differential expression using biologically realistic conditions.

关键词： Whole genome duplication Polyploidy RNAseq Simulation transcriptome assembly transcript quantification

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Reduction of Pyrrolizidine Alkaloid Levels in Comfrey (Symphytum officinale) Hairy Roots by RNAi Silencing of Homospermidine Synthase

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PLANTA MEDICA 2019年第14-15期85卷 1177-1186页

作者： Kruse, Lars H. Stegemann, Thomas Jensen-Kroll, Julia Engelhardt, Annika Wesseling, Anne-Maria Lippert, Annemarie Ludwig-Mueller, Jutta Ober, Dietrich Univ Kiel Bot Inst Bot Garten 1-9 D-24118 Kiel Germany Tech Univ Dresden Inst Bot Dresden Germany Cornell Univ Sch Integrat Plant Sci Plant Biol Sect Ithaca NY 14853 USA

Comfrey is a medicinal plant, extracts of which are traditionally used for the treatment of painful inflammatory muscle and joint problems, because the plant contains allantoin and rosmarinic acid. However, its medicinal use is limited because of its toxic pyrrolizidine alkaloid (PA) content. PAs encompass more than 400 different compounds that have been identified from various plant lineages. To date, only the first pathway-specific enzyme, homospermidine synthase (HSS), has been characterized. HSS catalyzes the formation of homospermidine, which is exclusively incorporated into PAs. HSS has been recruited several times independently in various plant lineages during evolution by duplication of the gene encoding deoxyhypusine synthase (DHS), an enzyme of primary metabolism. Here, we describe the establishment of RNAi knockdown hairy root mutants of HSS in Symphytum officinale. A knockdown of HSS by 60 - 80% resulted in a significant reduction of homospermidine by similar to 86% and of the major PA components 7-acetylintermedineN-oxide and 3-acetylmyoscorpineN-oxide by approximately 60%. The correlation of reduced transcript levels of HSS with reduced levels of homospermidine and PAs providesin plantasupport for HSS being the central enzyme in PA biosynthesis. Furthermore, the generation of PA-depleted hairy roots might be a cost-efficient way for reducing toxic by-products that limit the medicinal applicability ofS. officinaleextracts.

关键词： Symphytum officinale alkaloid extraction transgenic tissue culture transcript quantification Boraginaceae

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Elicitor-Induced transcriptional Changes of Genes of the Steviol Glycoside Biosynthesis Pathway in Stevia rebaudiana Bertoni

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JOURNAL OF PLANT GROWTH REGULATION 2018年第3期37卷 971-985页

作者： Lucho, Simone Ribeiro do Amaral, Marcelo Nogueira Milech, Cristini Ferrer, Maria Angeles Calderon, Antonio Asensio Bianchi, Valmor Joo Bolacel Braga, Eugenia Jacira Univ Fed Pelotas Dept Bot Pelotas RS Brazil Univ Politecn Cartagena Dept Agr Sci & Technol Paseo Alfonso 13 48 Cartagena 30203 Spain

Stevia rebaudiana is a medicinal plant widely used as a sweetener, and the sweetening power comes from the diterpenoid glycosides known as steviol glycosides (SGs). The studies of gene expression patterns in response to elicitors treatment are of extreme importance for biotechnological purposes. Methyl jasmonate (MeJa), spermidine (SPD), salicylic acid (SA), and paclobutrazol (PBZ) (100 A mu M) were applied to stevia plants growing in a hydroponic system to examine the effect of these elicitors along the time (24, 48, 72, and 96 h). SGs' contents and transcription levels of fifteen genes involved in the three stages comprising their biosynthesis pathway were evaluated. The results provide direct evidence that HDR, GGDPS, CDPS, KS, KO, and KAH are elicitor-responsive genes and they can be effectively regulated at least at the transcriptional level. MeJa and SPD treatments resulted in positive effects on the transcription of SGs biosynthetic genes, with SPD exhibiting the highest number of regulated genes at 48 h of exposure. PBZ treatment down-regulated genes encoding kaurenoid enzymes. SA treatment did not affect transcription of UGT85C2, UGT74G1, and UGT76G1 and decreased stevioside levels. Overall, this study offers new insights into the transcriptional response mechanisms in S. rebaudiana plants under the effect of the elicitors MeJa, SPD, SA, and PBZ.

关键词： transcript quantification Elicitors Secondary metabolism Stevioside

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Quantitative Detection of Low-Abundance transcripts at Single-Cell Level in Human Epidermal Keratinocytes by Digital Droplet Reverse transcription-Polymerase Chain Reaction

Quantitative Detection of Low-Abundance Transcripts at Singl...

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作者： Frédéric Auvré Julien Coutier Michèle T. Martin Nicolas O. Fortunel

Genetic and epigenetic characterization of the large cellular diversity observed within tissues is essential to understanding the molecular networks that ensure the regulation of homeostasis, repair, and regeneration, but also pathophysiological processes. Skin is composed of multiple cell lineages and is therefore fully concerned by this complexity. Even within one particular lineage, such as epidermal keratinocytes, different immaturity statuses or differentiation stages are represented, which are still incompletely characterized. Accordingly, there is presently great demand for methods and technologies enabling molecular investigation at single-cell level. Also, most current methods used to analyze gene expression at RNA level, such as RT-qPCR, do not directly provide quantitative data, but rather comparative ratios between two conditions. A second important need in skin biology is thus to determine the number of RNA molecules in a given cell sample. Here, we describe a workflow that we have set up to meet these specific needs, by means of transcript quantification in cellular micro-samples using flow cytometry sorting and reverse transcription-digital droplet polymerase chain reaction. As a proof-of-principle, the workflow was tested for the detection of transcription factor transcripts expressed at low levels in keratinocyte precursor cells. A linear correlation was found between quantification values and keratinocyte input numbers in a low quantity range from 40 cells to 1 cell. Interpretable signals were repeatedly obtained from single-cell samples corresponding to estimated expression levels as low as 10–20 transcript copies per keratinocyte or less. The present workflow may have broad applications for the detection and quantification of low-abundance nucleic acid species in single cells, opening up perspectives for the study of cell-to-cell genetic and molecular heterogeneity. Interestingly, the process described here does not require internal references su

关键词： Droplet Digital PCR PCR Flow Cytometry Cell Lysis Quantitative Reverse transcription PCR Reverse transcription PCR Cell Separation And Isolation Data analysis Homo sapiens Keratinocytes Low-abundance nucleic acids Single-cell level transcript quantification

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Computational Analysis of RNA-Seq Data from Airway Epithelial Cells for Studying Lung Disease

Computational Analysis of RNA-Seq Data from Airway Epithelia...

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作者： Nathan D. Jackson Lando Ringel Max A. Seibold

Airway epithelial cells (AECs) play a central role in the pathogenesis of many lung diseases. Consequently, advancements in our understanding of the underlying causes of lung diseases, and the development of novel treatments, depend on continued detailed study of these cells. Generation and analysis of high-throughput gene expression data provide an indispensable tool for carrying out the type of broad-scale investigations needed to identify the key genes and molecular pathways that regulate, distinguish, and predict distinct pulmonary pathologies. Of the available technologies for generating genome-wide expression data, RNA sequencing (RNA-seq) has emerged as the most powerful. Hence many researchers are turning to this approach in their studies of lung disease. For the relatively uninitiated, computational analysis of RNA-seq data can be daunting, given the large number of methods and software packages currently available. The aim of this chapter is to provide a broad overview of the major steps involved in processing and analyzing RNA-seq data, with a special focus on methods optimized for data generated from AECs. We take the reader from the point of obtaining sequence reads from the lab to the point of making biological inferences with expression data. Along the way, we discuss the statistical and computational considerations one typically confronts during different phases of analysis and point to key methods, software packages, papers, online guides, and other resources that can facilitate successful RNA-seq analysis. less

关键词： Functional Enrichment RNA-seq RNA-Seq Analysis Library Preparation Illumina Sequencing High-Throughput Sequencing Statistical Calculation TopHat Genome Assembly Genome Visualization Sequence Annotation Cufflinks Deep Sequencing Differential Expression Analysis K Means Clustering Machine Learning Cytoscape Pathway Or Network Visualization Gene Expression Correlation Analysis Data analysis DNA Ligation Trimmomatic Cutadapt Ensembl Python Data normalization Differential expression Clustering transcript quantification Pathway analysis Gene quantification Gene mapping WGCNA transcriptome alignment

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