Dataset Information

Proper Read Filtering Method to Adequately Analyze Whole-Transcriptome Sequencing and RNA Based Immune Repertoire Sequencing Data for Tumor Milieu Research.

ABSTRACT: Analysis of the T-cell receptor (TCR) repertoire is essential to characterize the extensive collections of T-cell populations with recognizing antigens in cancer research, and whole transcriptome sequencing (WTS) and immune repertoire sequencing (IR-seq) are commonly used for this measure. To date, no standard read filtering method for IR measurement has been presented. We assessed the diversity of the TCR repertoire results from the paired WTS and IR-seq data of 31 multiple myeloma (MM) patients. To invent an adequate read filtering strategy for IR analysis, we conducted comparisons with WTS results. First, our analyses for determining an optimal threshold for selecting clonotypes showed that the clonotypes supported by a single read largely affected the shared clonotypes and manifested distinct patterns of mapping qualities, unlike clonotypes with multiple reads. Second, although IR-seq could reflect a wider TCR region with a higher capture rate than WTS, an adequate comparison with the removal of unwanted bias from potential sequencing errors was possible only after applying our read filtering strategy. As a result, we suggest that TCR repertoire analysis be carried out through IR-seq to produce reliable and accurate results, along with the removal of single-read clonotypes, to conduct immune research in cancer using high-throughput sequencing.

SUBMITTER: Lee S

PROVIDER: S-EPMC7763492 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Proper Read Filtering Method to Adequately Analyze Whole-Transcriptome Sequencing and RNA Based Immune Repertoire Sequencing Data for Tumor Milieu Research.

Lee Sungyoung S Song Seulki S Yoon Sung-Soo SS Koh Youngil Y Yun Hongseok H

Cancers 20201209 12

Analysis of the T-cell receptor (TCR) repertoire is essential to characterize the extensive collections of T-cell populations with recognizing antigens in cancer research, and whole transcriptome sequencing (WTS) and immune repertoire sequencing (IR-seq) are commonly used for this measure. To date, no standard read filtering method for IR measurement has been presented. We assessed the diversity of the TCR repertoire results from the paired WTS and IR-seq data of 31 multiple myeloma (MM) patient ...[more]

PMID: 33317041

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Project description:Next-generation sequencing of the transcriptome (RNA-Seq) is a powerful method that allows for the quantitative determination of absolute gene expression, and can be used to investigate how these levels change in response to an experimental manipulation or disease condition. The sensitivity of this method allows one to analyze transcript levels of all expressed genes, including low abundance transcripts that encode important regulatory molecules, providing valuable insights into the global effects of experimental manipulations. However, this increased sensitivity can also make it challenging to ascertain which expression changes are biologically significant. Here, we describe a novel set of filtering criteria - based on biological insights and computational approaches - that were applied to prioritize genes for further study from an extensive number of differentially expressed transcripts in lenses lacking Smad interacting protein 1 (Sip1) obtained via RNA-Seq by Manthey and colleagues in Mechanisms of Development (Manthey et al., 2014). Notably, this workflow allowed an original list of over 7,100 statistically significant differentially expressed genes (DEGs) to be winnowed down to 190 DEGs that likely play a biologically significant role in Sip1 function during lens development. Focusing on genes whose expression was upregulated or downregulated in a manner opposite to what normally occurs during lens development, we identified 78 genes that appear to be strongly dependent on Sip1 function. From these data (GEO accession number GSE49949), it appears that Sip1 regulates multiple genes in the lens that are generally distinct from those regulated by Sip1 in other cellular contexts, including genes whose expression is prominent in the early head ectoderm, from which the lens differentiates. Further, the analysis criteria outlined here represent a filtering scheme that can be used to prioritize genes in future RNA-Seq investigations performed at this stage of ocular lens development.

Dataset Information

Proper Read Filtering Method to Adequately Analyze Whole-Transcriptome Sequencing and RNA Based Immune Repertoire Sequencing Data for Tumor Milieu Research.

Publications

Proper Read Filtering Method to Adequately Analyze Whole-Transcriptome Sequencing and RNA Based Immune Repertoire Sequencing Data for Tumor Milieu Research.

Similar Datasets

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