Identification of novel point mutations in splicing sites integrating whole-exome and RNA-seq data in myeloproliferative diseases

Point mutations in intronic regions near mRNA splice junctions can affect the splicing process. To identify novel splicing variants from exome sequencing data, we developed a bioinformatics splice-site prediction procedure to analyze next-generation sequencing (NGS) data (SpliceFinder). SpliceFinder integrates two functional annotation tools for NGS, ANNOVAR and MutationTaster and two canonical splice site prediction programs for single mutation analysis, SSPNN and NetGene2. By SpliceFinder, we identified somatic mutations affecting RNA splicing in a colon cancer sample, in eight atypical chronic myeloid leukemia (aCML), and eight CML patients. A novel homozygous splicing mutation was found in APC (NM_000038.4:c.1312+5G>A) and six heterozygous in GNAQ (NM_002072.2:c.735+1C>T), ABCC3 (NM_003786.3:c.1783-1G>A), KLHDC1 (NM_172193.1:c.568-2A>G), HOOK1 (NM_015888.4:c.1662-1G>A), SMAD9 (NM_001127217.2:c.1004-1C>T), and DNAH9 (NM_001372.3:c.10242+5G>A). Integrating whole-exome and RNA sequencing in aCML and CML, we assessed the phenotypic effect of mutations on mRNA splicing for GNAQ, ABCC3, HOOK1. In ABCC3 and HOOK1, RNA-Seq showed the presence of aberrant transcripts with activation of a cryptic splice site or intron retention, validated by the reverse transcription-polymerase chain reaction (RT-PCR) in the case of HOOK1. In GNAQ, RNA-Seq showed 22% of wild-type transcript and 78% of mRNA skipping exon 5, resulting in a 4-6 frameshift fusion confirmed by RT-PCR. The pipeline can be useful to identify intronic variants affecting RNA sequence by complementing conventional exome analysis.