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Immunoglobulin transcript sequence and somatic hypermutation computation from unselected RNA-seq reads in Chronic Lymphocytic Leukemia

ABSTRACT: IGHV mutation status is a well-established prognostic factor in chronic lymphocytic leukemia, and also provides crucial insights into tumor cell biology and function. Currently, determination of IGHV transcript sequence, from which mutation status is calculated, requires a specialized laboratory procedure. RNA sequencing is a method that provides high resolution, high dynamic range transcriptome data that can be used for differential expression, isoform discovery, and variant determination. In this paper, we demonstrate that unselected next-generation RNA sequencing can accurately determine the IGH@ sequence, including the complete sequence of the complementarity-determining region 3 (CDR3), and mutation status of CLL cells, potentially replacing the current method which is a specialized, single-purpose Sanger-sequencing based test.

ORGANISM(S): Homo sapiens

PROVIDER: GSE66228 | GEO | 2015/04/02

SECONDARY ACCESSION(S): PRJNA276143

REPOSITORIES: GEO

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Project description:Chronic lymphocytic leukemia (CLL) is a biologically and clinically heterogeneous disease. The somatic hypermutation status of the immunoglobulin heavy chain variable (IGHV) genes has been identified as one of the most robust prognostic markers in CLL. Patients with unmutated IGHV status (U-CLL) typically experience an inferior outcome compared to those whose clones express mutated IGHV genes (M-CLL). We conducted a genome-wide DNA methylation analysis in CD19+ B-cells from a group of 43 CLL patients using reduced representation bisulfite sequencing (RRBS). Using base-pair resolution methylation sequencing, 2323 differentially methylated regions between CLL and normal B-cells (CLL-specific DMRs) and 569 between M-CLL and U-CLL samples (IGHV-specific DMRs) were identified in the CLL genomes. The IGHV-specific DMRs are mostly unique when compared to the CLL-specific DMRs. Less than 10% of the IGHV-specific DMRs are located in promoter regions; however, more than half of these overlap with known DNase I hypersensitive sites, enhancer regions marked by histone modification (H3K4Me1 and H3K27Ac), and transcription factor binding sites in the ENCODE datasets, which indicates that these DMRs contain regulatory sequences. Distinctive DNA methylation patterns were observed in M-CLL and U-CLL samples. Overall, U-CLL was found to contain 50% more hypermethylated regions than M-CLL samples. The hypermethylated loci observed in the U-CLL samples also appear to be hypermethylated in normal naïve B-cells as compared memory B-cells, suggesting that M-CLL and U-CLL differ in differentiation status corresponding to normal B-cell differentiation stages. RNA-seq analysis performed using matched samples (n=34), in which both DNA methylation and gene expression data were available, demonstrated excellent correlation between DNA methylation and gene expression. Several genes whose expression status was previously shown to be associated with CLL prognosis such as ZAP70, CRY1, LDOC1, SEPT10, LAG3, and LPL were differentially methylated in the promoter regions between M-CLL and U-CLL samples indicating that DNA methylation plays an important role in defining the gene expression patterns of these prognostic genes. We further validated 9 genes with IGHV-specific DMRs in the promoter regions using bisulfite pyrosequencing, and the results demonstrated excellent correlation between differential methylation and IGHV mutation status. These novel differentially methylated genes could be developed into biomarkers for CLL prognosis. In addition, DNA hypomethylation was observed in a significant number of genes involved in lymphocyte activation such as PDCD1, NFAT1, and CD5. DNA hypomethylation was observed in the proximal promoter and far up-stream enhancer regions of CD5, an important cell surface marker that uniquely identifies CLL. Overall, the DNA methylation landscape in CLL patients indicates that CLL B cells possess an active B-cell phenotype; at the same time, U-CLL and M-CLL are faithfully committed to their lineage resembling either naïve or memory B-cells. In summary, this comprehensive DNA methylation analysis has identified a large number of novel epigenetic changes in CLL patients. The results from this study will further advance our understanding of the epigenetic contribution to molecular subtypes in CLL. To perform a transcriptome analysis in CLL, we generated sequencing libraries from total RNA isolated from purified B-cells of CLL patients and healthy donnors. The RNA-seq libraries were sequenced using Illumina HiSeq2000 sequencer with a read length of 100bp. 11 CLL B-cell samples, 3 normal control samples including one each of normal CD19+ B cells were studied. We generated 20-30 million Illumina sequencing reads for each sample.

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Immunoglobulin transcript sequence and somatic hypermutation computation from unselected RNA-seq reads in Chronic Lymphocytic Leukemia

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