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In Silico Typing of Classical and Non-classical HLA Alleles from Standard RNA-Seq Reads

In Silico Typing of Classical and Non-classical HLA Alleles ...

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作者： Sebastian Boegel Thomas Bukur John C. Castle Ugur Sahin

Next-Generation Sequencing (NGS) enables the rapid generation of billions of short nucleic acid sequence fragments (i.e., “sequencing reads”). Especially, the adoption of gene expression profiling using whole transcriptome sequencing (i.e., “RNA-Seq”) has been rapid. Here, we describe an in silico method, seq2HLA, that takes standard RNA-Seq reads as input and determines a sample’s (classical and non-classical) HLA class I and class II types as well as HLA expression. We demonstrate the application of seq2HLA using publicly available RNA-Seq data from the Burkitt’s lymphoma cell line DAUDI and the choriocarcinoma cell line JEG-3. less

关键词： RNA-seq Gene Expression Profiling Bowtie Statistical Calculation Major Histocompatibility Typing Assay Library Preparation Whole transcriptome sequencing Python programming language Homo sapiens Daudi cell line NGS In silico Immunoinformatics HLA expression HLA type Non-classical HLA class I

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Profiling of MicroRNAs in the Biofluids of Livestock Species

Profiling of MicroRNAs in the Biofluids of Livestock Species

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作者： Jason Ioannidis Judith Risse F. Xavier Donadeu

The value of circulating microRNAs (miRNAs) as noninvasive biomarkers of human disease has been extensively demonstrated. Significant potential also exists in other species, particularly in relation to control of veterinary diseases and selection/monitoring of production traits in livestock. Although robust protocols have been developed for miRNA profiling of human biofluids, significant optimization may be required before these can be applied to other species. In this chapter, we describe protocols for small-RNA sequencing and RT-qPCR analyses of plasma samples from livestock species. In addition, we provide brief data analysis protocols for small-RNA sequencing and RT-qPCR data. Finally, we highlight important considerations for these protocols such as low RNA yield, platform-specific biases, and optimal normalization approaches. less

关键词： RNA Extraction Quantitative Reverse Transcription PCR Real-time PCR Small RNA-seq Library Preparation Statistical Calculation Nucleic Acid Microarray Differential Expression Analysis Bowtie Data analysis TruSeq DNA Ligation programming language Bos taurus Sequencing miRNA microRNA Biomarker Plasma Follicular fluid

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Determining mRNA Decay Rates Using RNA Approach to Equilibrium Sequencing (RATE-Seq)

Determining mRNA Decay Rates Using RNA Approach to Equilibri...

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作者： Farah Abdul-Rahman David Gresham

RATE-seq is a 4-thiouracil (4-tU)-based method that enables the in vivo measurement of transcriptome-wide RNA degradation rates. 4-tU is an analog of uracil that is rapidly incorporated into newly synthesized RNA and facilitates the conjugation of a biotinylated molecule containing a reactive thiol group. The biotinylated RNA can then be fractionated from the unlabeled RNA with streptavidin magnetic beads. By adding 4-tU to a culture of cells growing in steady-state conditions, fractionating the labeled population of RNA at multiple time points following 4-tU addition, and quantifying the abundance of newly transcribed RNAs using RNAseq, it is possible to estimate the degradation rates of all transcripts in a single experiment. The analysis of the RATE-seq data entails normalization of RNAseq libraries to thiolated RNA spike-ins and nonlinear model fitting to estimate the degradation rate constant for each RNA species. less

关键词： Metabolic Labeling RNA Extraction Fractionation RNA-seq PCR Cell And Tissue Culture In Vitro Transcription programming language Escherichia coli Saccharomyces cerevisiae RNA degradation RNA stability RNA turnover 4-thiouracil

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Versatile Identification of Copy Number Variants with Canvas

Versatile Identification of Copy Number Variants with Canvas

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作者： Sergii Ivakhno Eric Roller

Versatile and efficient variant calling tools are needed to analyze large-scale sequencing datasets. In particular, identification of copy number changes remains a challenging task due to their complexity, susceptibility to sequencing biases, variation in coverage data and dependence on genome-wide sample properties, such as tumor polyploidy, polyclonality in cancer samples, or frequency of de novo variation in germline genomes of pedigrees. The frequent need of core sequencing facilities to process samples from both normal and tumor sources favors multipurpose variant calling tools with functionality to process these diverse sets within a single software framework. This not only simplifies the overall bioinformatics workflow but also streamlines maintenance by shortening the software update cycle and requiring only limited staff training. Here we introduce Canvas, a tool for identification of copy number changes from diverse sequencing experiments including whole-genome matched tumor–normal, small pedigree, and single-sample normal resequencing, as well as whole-exome matched and unmatched tumor–normal studies. In addition to variant calling, Canvas infers genome-wide parameters such as cancer ploidy, purity, and heterogeneity. It provides fast and easy-to-run workflows that can scale to thousands of samples and can be easily incorporated into variant calling pipelines. less

关键词： Variant Calling Whole-genome Sequencing Whole-exome sequencing Genomics Genome Visualization Sequence Analysis Illumina Sequencing Targeted sequencing bedtools programming language Copy number variation Small pedigree Somatic variation

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Integration of Comparative Genomics with Genome-Scale Metabolic Modeling to Investigate Strain-Specific Phenotypical Differences

Integration of Comparative Genomics with Genome-Scale Metabo...

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作者： Jonathan Monk Emanuele Bosi

Genome-scale metabolic reconstructions are powerful resources that allow translation biological knowledge and genomic information to phenotypical predictions using a number of constraint-based methods. This approach has been applied in recent years to gain deep insights into the cellular phenotype role of the genes at a systems-level, driving the design of targeted experiments and paving the way for knowledge-based synthetic biology. The identification of genetic determinants underlying the variability at the phenotypical level is crucial to understand the evolutionary trajectories of a bacterial species. Recently, genome-scale metabolic models of different strains have been assembled to highlight the intra-species diversity at the metabolic level. The strain-specific metabolic capabilities and auxotrophies can be used to identify factors related to the lifestyle diversity of a bacterial species. In this chapter, we present the computational steps to perform genome-scale metabolic modeling in the context of comparative genomics, and the different challenges related to this task. less

关键词： Genomics Genome Annotation Statistical Calculation Sequence Comparison Python programming language Flux balance analysis Niche adaptation Microbial evolution Constraint-based metabolic modeling

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A Complete Pipeline for Generating a High-Resolution LC-MS-Based Reference Mass Spectra Library

A Complete Pipeline for Generating a High-Resolution LC-MS-B...

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作者： Nir Shahaf Asaph Aharoni Ilana Rogachev

Databases containing mass spectrometry (MS) spectral data (i.e., MS reference libraries) are currently the most reliable and widely accepted approach to annotate unknown features in MS-based metabolomics. While for gas chromatography (GC)-MS data, a strategy for collecting, storing, and comparing to raw data has been established, this is not the case for liquid chromatography (LC)-MS data. Here, we present our approach for high-throughput data collection and automated MS reference library generation, as applied recently in the WEIZMASS library of plant metabolites. Methodologies to experimentally generate pools of chemical standards and computationally convert them into a unique source of reference data are detailed. less

关键词： Mass Spectrometry Liquid Chromatography-mass Spectrometry Metabolomics Gas Chromatography (GC) Liquid Chromatography (LC) HPLC Electrospray Ionization (ESI) Ultra-performance Liquid Chromatography Python programming language Chemoinformatics Metabolites Plant metabolism Reference libraries

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Parsing Compound–Protein Bioactivity Tables

Parsing Compound–Protein Bioactivity Tables

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作者： J. B. Brown

With the availability of a multitude of databases that contain information on the bioactivity between compounds and proteins, several fundamental tasks arise. These include parsing of the original data in order to filter out unusable data, merging of multiple databases, identification of the sets of unique molecules, and selection of subsets of parsed data. In this chapter, we address these issues by providing solutions to each of the problems. Solutions are presented using standardized and freely available data processing tools, as well as computer program code. less

关键词： Binding Assay Statistical Calculation Python programming language Visualization Data management Chemogenomic data Bioactivity database Compound–protein dataset

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High-Resolution and High-Speed Atomic Force Microscope Imaging

High-Resolution and High-Speed Atomic Force Microscope Imagi...

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作者： Francesca Zuttion Lorena Redondo-Morata Arin Marchesi Ignacio Casuso

The advent of high-speed atomic force microscopy (HS-AFM) over the recent years has opened up new horizons for the study of structure, function and dynamics of biological molecules. HS-AFM is capable of 1000 times faster imaging than conventional AFM. This circumstance uniquely enables the observation of the dynamics of all the molecules present in the imaging area. Over the last 10 years, the HS-AFM has gone from a prototype-state technology that only a few labs in the world had access to (including ours) to an established commercialized technology that is present in tens of labs around the world. In this protocol chapter we share with the readers our practical know-how on high resolution HS-AFM imaging. less

关键词： Amplitude-modulation Atomic Force Microscopy Atomic Force Microscopy (AFM) Plasma Etching ImageJ Image Processing MATLAB Data analysis programming language PID Cantilever High speed atomic force microscope HS-AFM Electron beam deposited tip Plasma EBD tip sharpening Tip–sample approach Oscillation amplitude Feedback optimization Image treatment

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Identifying Differentially Expressed Genes Using Fluorescence-Activated Cell Sorting (FACS) and RNA Sequencing from Low Input Samples

Identifying Differentially Expressed Genes Using Fluorescenc...

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作者： Natalie M. Clark Adam P. Fisher Rosangela Sozzani

Cell type-specific gene expression profiles are useful for understanding genes that are important for the development of different tissues and organs. Here, we describe how to perform fluorescence-activated cell sorting (FACS) on Arabidopsis root protoplasts to isolate specific cell types in the root. We then detail how to extract and process RNA from a very low number of cells (≥40 cells) for RNA sequencing (RNA seq). Finally, we describe how to process RNA seq data using TopHat and how to identify differentially expressed genes using PoissonSeq. less

关键词： FACS RNA-seq RNA Extraction TopHat Library Preparation Bowtie Gene Expression Analysis Cuffdiff Smart-seq SAMtools programming language Arabidopsis Protoplasting Differential expression Low input samples

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Mixed-species RNA-seq for elucidation of non-cell-autonomous control of gene transcription

Mixed-species RNA-seq for elucidation of non-cell-autonomous...

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作者： Jing Qiu Owen Dando Paul S. Baxter Philip Hasel Samuel Heron T. Ian Simpson Giles E. Hardingham

Transcriptomic changes induced in one cell type by another mediate many biological processes in the brain and elsewhere; however, achieving artifact-free physical separation of cell types to study them is challenging and generally allows for analysis of only a single cell type. We describe an approach using a co-culture of distinct cell types from different species that enables physical cell sorting to be replaced by in silico RNA sequencing (RNA-seq) read sorting, which is possible because of evolutionary divergence of messenger RNA (mRNA) sequences. As an exemplary experiment, we describe the co-culture of purified neurons, astrocytes, and microglia from different species (12–14 d). We describe how to use our Python tool, Sargasso, to separate the reads from conventional RNA-seq according to species and to eliminate any artifacts borne of imperfect genome annotation (10 h). We show how this procedure, which requires no special skills beyond those that might normally be expected of wet lab and bioinformatics researchers, enables the simultaneous transcriptomic profiling of different cell types, revealing the distinct influence of microglia on astrocytic and neuronal transcriptomes under inflammatory conditions. less

关键词： Cell And Tissue Culture RNA-seq Transcriptomics Co-culture Cell Separation And Isolation Genome Annotation Dissection Immunostaining RNA Extraction Statistical Calculation RNA-Seq Analysis Genome Visualization Python programming language Ensembl Homo sapiens Mus musculus Rattus norvegicus Bioinformatics Glial biology Anti-rabbit Anti-mouse

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