Abstract
RNA-seq is a promising technology to re-sequence protein coding genes for the identification of single nucleotide variants (SNV), while simultaneously obtaining information on structural variations and gene expression perturbations. We asked whether RNA-seq is suitable for the detection of driver mutations in T-cell acute lymphoblastic leukemia (T-ALL). These leukemias are caused by a combination of gene fusions, over-expression of transcription factors and cooperative point mutations in oncogenes and tumor suppressor genes. We analyzed 31 T-ALL patient samples and 18 T-ALL cell lines by high-coverage paired-end RNA-seq. First, we optimized the detection of SNVs in RNA-seq data by comparing the results with exome re-sequencing data. We identified known driver genes with recurrent protein altering variations, as well as several new candidates including H3F3A, PTK2B, and STAT5B. Next, we determined accurate gene expression levels from the RNA-seq data through normalizations and batch effect removal, and used these to classify patients into T-ALL subtypes. Finally, we detected gene fusions, of which several can explain the over-expression of key driver genes such as TLX1, PLAG1, LMO1, or NKX2-1; and others result in novel fusion transcripts encoding activated kinases (SSBP2-FER and TPM3-JAK2) or involving MLLT10. In conclusion, we present novel analysis pipelines for variant calling, variant filtering, and expression normalization on RNA-seq data, and successfully applied these for the detection of translocations, point mutations, INDELs, exon-skipping events, and expression perturbations in T-ALL.
Highlights
T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy that accounts for approximately 15% of pediatric and 25% of adult ALL cases
Far transcriptome sequencing by RNA-seq has been mainly used for the detection of fusion genes, while few studies have assessed its value for the combined detection of SNPs, insertion and deletion (INDEL), fusions, gene expression changes, and alternative transcript events
Correct single nucleotide variants (SNV) and INDEL calling on RNA-seq data depends on accurate read mapping
Summary
T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy that accounts for approximately 15% of pediatric and 25% of adult ALL cases. Improved understanding of T-ALL biology through the identification and characterization of oncogenic lesions is expected to lead to a better prognostic classification and the development of new targeted therapeutic strategies. Chromosomal translocations in T-ALL frequently involve the Tcell receptor (TCR) loci, whereby TCR regulatory elements become juxtaposed to genes that are normally not expressed in T-cells [3,4]. In this way, a specific set of recurrently over-expressed transcription factors (TFs) have been documented, including TLX1, TLX3, TAL1, LMO1, HOXA, and NKX family members [5]. Chromosomal rearrangements can lead to large chromosomal deletions and amplifications; to focal gene deletions or amplifications, such as CDKN2A deletion and MYB duplication [7,8]; and to in-frame fusion genes encoding chimeric proteins with oncogenic properties such as the constitutively active
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