Supplementary Table 1 from Characterizing the Impact of Smoking and Lung Cancer on the Airway Transcriptome Using RNA-Seq
Jennifer BeaneJessica VickFrank SchembriChristina AnderlindAdam C. GowerJoshua D. CampbellLingqi LuoXiao Hui ZhangXiao‐Jun JiYuriy O. AlekseyevShenglong WangShawn LevyPierre P. MassionMarc E. LenburgAvrum Spira
0
Citation
0
Reference
10
Related Paper
Abstract:
Supplementary Table 1 from Characterizing the Impact of Smoking and Lung Cancer on the Airway Transcriptome Using RNA-SeqKeywords:
RNA-Seq
Table (database)
RNA-Seq
Cite
Citations (12,083)
RNA-Seq
Cite
Citations (81)
Sexual Differentiation
Illumina dye sequencing
RNA-Seq
Cite
Citations (18)
The transcriptome is the complete set of transcripts for certain type of cells or tissues in a specific developmental stage or physiological condition.Transcriptome analysis can provide a comprehensive understanding of molecular mechanisms involved in specific biological processes and diseases from the information on gene structure and function.RNA-seq,refers to the use of next-generation highthroughput sequencing technologies to sequence cDNA library transcribed from all RNAs in tissues or cells,can be used to quantify,profile,and discover RNA transcripts by Sequencing,assembling,mapping reads.RNA-Seq,as a new efficient and fast transcriptome sequencing technology,has been widely used in biological,medical research.The detailed principles,technical characteristics and applications of RNA-seq in leukemia and lymphoma are reviewed here.
Key words:
Transcriptome sequencing (RNA-Seq) ; Leukemia ; Lymphoma
RNA-Seq
Cite
Citations (0)
RNA-Seq
Sexual dimorphism
KEGG
Sexual Differentiation
Cite
Citations (22)
The accurate characterization of RNA transcripts and expression levels across species is critical for understanding transcriptome evolution. As available RNA-seq data accumulate rapidly, there is a great demand for tools that build gene annotations for cross-species RNA-seq analysis. However, prevailing methods of ortholog annotation for RNA-seq analysis between closely-related species do not take inter-species variation in mappability into consideration. Here we present XSAnno, a computational framework that integrates previous approaches with multiple filters to improve the accuracy of inter-species transcriptome comparisons. The implementation of this approach in comparing RNA-seq data of human, chimpanzee, and rhesus macaque brain transcriptomes has reduced the false discovery of differentially expressed genes, while maintaining a low false negative rate. The present study demonstrates the utility of the XSAnno pipeline in building ortholog annotations and improving the accuracy of cross-species transcriptome comparisons.
Cite
Citations (34)
The application of next-generation sequencing (NGS) to transcriptomics, commonly called RNA-seq, allows the nearly complete characterization of transcriptomic events occurring in a specific tissue. It has proven particularly useful in nonmodel species, which often lack the resources available for sequenced organisms. Mainly, RNA-seq does not require a reference genome to gain useful transcriptomic information. In this review, the application of RNA-seq to nonmodel plant species will be addressed. Important experimental considerations from presequencing issues to postsequencing analysis, including sample and platform selection, and useful bioinformatics tools for assembly and data analysis, are covered. Methods of assembling RNA-seq data and analyses commonly performed with RNA-seq data, including single nucleotide polymorphism detection and analysis of differential expression, are explored. In addition, studies that have used RNA-seq to elucidate nonmodel plant transcriptomics are highlighted.
RNA-Seq
Cite
Citations (214)
Transcriptome profiling has become routine in studies of many biological processes. However, the favored approaches such as short-read Illumina RNA sequencing are giving way to long-read sequencing platforms better suited to interrogating the complex transcriptomes typical of many RNA and DNA viruses. Here, we provide a guide-tailored to molecular virologists-to the ins and outs of viral transcriptome sequencing and discuss the strengths and weaknesses of the major RNA sequencing technologies as tools to analyze the abundance and diversity of the viral transcripts made during infection.
RNA-Seq
Cite
Citations (40)
Abstract Next‐generation sequencing (NGS) technologies have revolutionized the study of genomics with an ever‐expanding list of applications. RNA‐Seq has emerged as a powerful method, applying transcriptome analysis to a wider range of organisms—most significantly, non‐model organisms lacking prior genomic sequencing. Whereas an initial concern of NGS datasets was the potential limitation of short read lengths, short read sequences have been successfully employed in creation of de novo transcriptome assemblies that allow for subsequent mapping of reads for expression analysis. Prior genomic sequence knowledge is no longer a requirement for identification of functional transcriptional elements and for global gene expression characterization. Significant cost reductions in generating RNA‐Seq data, and improvements in de novo assemblers, has allowed the analysis of transcriptomes in heretofore unsequenced plant species. These protocols describe standard methods for constructing RNA‐Seq libraries to be sequenced on Illumina sequencing platforms for comprehensive transcriptome analysis. © 2016 by John Wiley & Sons, Inc.
RNA-Seq
Identification
Functional Genomics
Cite
Citations (10)