Dissecting transcriptome complexity in chronic myeloid leukemia using TIF-Seq2

Eukaryotic transcriptomes are complex involving thousands of overlapping transcripts. The interleaved nature of the transcriptome complicates its annotation, limits our ability to identify regulatory regions and, in some cases, can lead to misinterpretation of gene expression. Long-read technologies promise to solve this problem, however short-read approaches have still better throughput and quality. To bridge this gap, we have developed an optimized method, TIF-Seq2, able to sequence simultaneously the 5’ and 3’ end of individual mRNA molecules at single-nucleotide resolution. We investigate the transcriptome of a well-characterized human cell line (K562) and identify thousands of new transcript isoforms. By focusing on mRNAs challenging to investigate with RNA-Seq, we accurately define boundaries of low expressed intergenic and read-through transcripts. We validate those novel features in cell lines and in chronic myeloid leukaemia patients. Our results demonstrate that TIF-Seq2 improves the annotation of complex genomes facilitating the assignment of promoters to genes and the identification of transcriptionally fused proteins. We performed an optimised TIF-seq2 method to determine the co-occurrence of transcription start sites and poly(A) sites in human cell line K562, together with 3'T-fill sequencing approach (PMID: 23295673) to define the PAS in the same cell line. In order to validate selected isoforms discovered by TIF-Seq2, we performed targeted long-read sequencing on the Pacific Biosciences platform.