Effective requesting method to detect fusion transcripts in chronic myelomonocytic leukemia RNA-seq

Abstract

RNA sequencing technology combining short read and long read analysis can be used to detect chimeric RNAs in malignant cells. Here, we propose an integrated approach that uses k-mers to analyze indexed datasets. This approach is used to identify chimeric RNA in chronic myelomonocytic leukemia (CMML) cells, a myeloid malignancy that associates features of myelodysplastic and myeloproliferative neoplasms. In virtually every CMML patient, new generation sequencing identifies one or several somatic driver mutations, typically affecting epigenetic, splicing and signaling genes. In contrast, cytogenetic aberrations are currently detected in only one third of the cases. Nevertheless, chromosomal abnormalities contribute to patient stratification, some of them being associated with higher risk of poor outcome, e.g. through transformation into acute myeloid leukemia (AML). Our approach selects four chimeric RNAs that have been detected and validated in CMML cells. We further focus on NRIP1-MIR99AHG, as this fusion has also recently been detected in AML cells. We show that this fusion encodes three isoforms, including a novel one. Further studies will decipher the biological significance of such a fusion and its potential to improve disease stratification. Taken together, this report demonstrates the ability of a large-scale approach to detect chimeric RNAs in cancer cells.

Graphical Abstract

Figure 1.

Description of the different steps leading to chRNAs selection.

Figure 2.

ChRNAs distribution among the 20 CMML samples. (A) Repartition of chRNAs classes and read count per sample. (B) Repartition of chRNAs classes per sample after applying standard filters.

Figure 3.

Overview of chRNAs biological validations. A subset of 28 chRNAs (column 2), from different classes (column 1) found by RNA-seq short reads in CMML samples (column 3) were subjected to qPCR followed by Sanger sequencing for biological validation (column 4). RNA-seq long read sequencing (column 5) was performed on 2 samples (CMML 7 and 13) to validate 16 chRNAs (highlighted by color) identified by short read sequencing in the corresponding samples. v; detected. Green; detected by both short and long reads. Yellow; detected by short reads in one sample and confirmed by long reads in the other sample. Orange; validated by qPCR and Sanger sequencing but not by long read. Red; not validated by qPCR and Sanger or long read. No color with v; not detected by short reads but detected by long reads.

Figure 4.

Expression of the 12 selected chRNA-kmers. A- chRNA-kmers count in the 20 CMML cohort. B- chRNA-kmers count in the BEAT-AML cohort. X axis correspond to 474 samples in the beatAML cohort, IDs were removed because of lack of readability (corresponding table available in Supplementary Table S14).

Figure 5.

Molecular structure of chRNAs. Representation of the chRNA structure of class 3 YWHAZ::AZIN1 (A) and GSE1::KLHL36 (B), class 2 ANXA6::TNIP1 (C). A graphical representation of the genomic origin of the chimeras is shown at the top of each panel. The short-read sequencing results are shown below (blue and green colors indicate the different gene origins). The long read sequencing results are displayed and compared to the expected transcript of the implicated genes.

Figure 6.

Visualization of NRIP1-MIR99AHG genomic DNA rearrangement. (A) Representation of the class 4 NRIP1::MIR99AHG chRNA structure. A graphical representation of the genomic origin of the chimeras is shown with the results of the short-read sequencing (blue and green colors indicate the different gene origins). The three observed junctions are shown as well as the qPCR sequencing result for one of them. (B) Visualization of the CMML10 NRIP1::MIR99AHG DNA region with DNAg short read sequencing. Reads are displayed using the Integrative Genomics Viewer (IGV) interface. (C) Schematic view of DNA breakpoint based on illumina DNAg sequencing and alignment. Exons are indicated by vertical bars.