RESUMO
Specialized RNA-seq methods are required to identify the 5' ends of transcripts, which are critical for studies of gene regulation, but these methods have not been systematically benchmarked. We directly compared six such methods, including the performance of five methods on a single human cellular RNA sample and a new spike-in RNA assay that helps circumvent challenges resulting from uncertainties in annotation and RNA processing. We found that the 'cap analysis of gene expression' (CAGE) method performed best for mRNA and that most of its unannotated peaks were supported by evidence from other genomic methods. We applied CAGE to eight brain-related samples and determined sample-specific transcription start site (TSS) usage, as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.
Assuntos
RNA/química , Análise de Sequência de RNA/métodos , Sequência de Bases , Encéfalo , Células-Tronco Embrionárias , Biblioteca Gênica , Humanos , RNA/genética , RNA/metabolismoRESUMO
The original version of this paper contained an incorrect primer sequence. In the Methods subsection "Rampage libraries," the text for modification 3 stated that the reverse primer used for library indexing was 5'-CAAGCAGAAGACGGCATACGAGATXXXXXXXXGTGACTGGAGT-3'. The correct sequence of the oligonucleotide used is 5'-CAAGCAGAAGACGGCATACGAGATXXXXXXXXGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT-3'. This error has been corrected in the PDF and HTML versions of the paper.
RESUMO
RNA-seq is an effective method for studying the transcriptome, but it can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations or cadavers. Recent studies have proposed several methods for RNA-seq of low-quality and/or low-quantity samples, but the relative merits of these methods have not been systematically analyzed. Here we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and compared them against two control libraries. We found that the RNase H method performed best for chemically fragmented, low-quality RNA, and we confirmed this through analysis of actual degraded samples. RNase H can even effectively replace oligo(dT)-based methods for standard RNA-seq. SMART and NuGEN had distinct strengths for measuring low-quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development.
Assuntos
Algoritmos , Artefatos , Perfilação da Expressão Gênica/métodos , RNA/genética , Tamanho da Amostra , Análise de Sequência de RNA/métodos , Software , Transcriptoma/genéticaRESUMO
MOTIVATION: A common question arises at the beginning of every experiment where RNA-Seq is used to detect differential gene expression between two conditions: How many reads should we sequence? RESULTS: Scotty is an interactive web-based application that assists biologists to design an experiment with an appropriate sample size and read depth to satisfy the user-defined experimental objectives. This design can be based on data available from either pilot samples or publicly available datasets. AVAILABILITY: Scotty can be freely accessed on the web at http://euler.bc.edu/marthlab/scotty/scotty.php
Assuntos
Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Software , Expressão Gênica , Humanos , InternetRESUMO
BACKGROUND: The evolution of gene expression is a challenging problem in evolutionary biology, for which accurate, well-calibrated measurements and methods are crucial. RESULTS: We quantified gene expression with whole-transcriptome sequencing in four diploid, prototrophic strains of Saccharomyces species grown under the same condition to investigate the evolution of gene expression. We found that variation in expression is gene-dependent with large variations in each gene's expression between replicates of the same species. This confounds the identification of genes differentially expressed across species. To address this, we developed a statistical approach to establish significance bounds for inter-species differential expression in RNA-Seq data based on the variance measured across biological replicates. This metric estimates the combined effects of technical and environmental variance, as well as Poisson sampling noise by isolating each component. Despite a paucity of large expression changes, we found a strong correlation between the variance of gene expression change and species divergence (R² = 0.90). CONCLUSION: We provide an improved methodology for measuring gene expression changes in evolutionary diverged species using RNA Seq, where experimental artifacts can mimic evolutionary effects.GEO Accession Number: GSE32679.
Assuntos
Saccharomyces/genética , Transcriptoma , Reação em Cadeia da Polimerase , Saccharomyces/classificação , Especificidade da EspécieRESUMO
The basal complex in Toxoplasma functions as the contractile ring in the cell division process. Basal complex contraction tapers the daughter cytoskeleton toward the basal end and is required for daughter segregation. We have previously shown that the protein MORN1 is essential for basal complex assembly and likely acts as a scaffolding protein. To further our understanding of the basal complex, we combined subcellular fractionation with an affinity purification of the MORN1 complex and identified its protein composition. We identified two new components of the basal complex, one of which uniquely associated with the basal complex in mature parasites, the first of its kind. In addition, we identified several other novel cytoskeleton proteins with different spatiotemporal dynamics throughout cell division. Since many of these proteins are unique to Apicomplexa this study significantly contributes to the annotation of their unique cytoskeleton. Furthermore, we show that G-actin binding protein TgCAP is localized at the apical cap region in intracellular parasites, but quickly redistributes to a cytoplasmic localization pattern upon egress. © 2012 Wiley Periodicals, Inc.