bioRxivGenomicsPreprint
MCF-7 breast cancer cell line PacBio generated transcriptome has ~300 novel transcribed regions, un-annotated in both RefSeq and GENCODE, and absent in the liver, heart and brain transcriptomes
Abstract
Illuminating the dark regions of the human genome remains an ongoing effort, a decade and a half after the human genome was sequenced - RefSeq and GENCODE being two of the major annotation databases. Pacific Biosciences (PacBio) has provided open access to the transcriptome of MCF-7, a breast cancer cell line that has provided significant therapeutic advancement in breast cancer research since the 1970s. PacBio sequencing generates much longer reads compared to second-generation sequencing technologies, with a trade-off of lower throughput, higher error rate and more cost per base. Here, this transcriptome was analyzed using the YeATS pipeline, with additionally introduced kmer based algorithms, reducing computational times to a few hours on a simple workstation. Out of ~300 transcripts that have no match in both RefSeq and GENCODE, ~250 are absent in the transcriptomes of the heart, liver and brain, also provided by PacBio. Also, ~200 transcripts are absent in a recent catalogue of un-annotated long non-coding RNAs from 6,503 samples (~43 Terabases of sequence data) [1], and among 2,556 novel transcripts reported in an experimental workflow RACE-Seq [2]. 65 transcripts have >100 amino acid open reading frames, and have the potential of being protein coding genes. ORF based annotation also identified few bacterial transcripts in the PacBio database mapped to the human genome, and one human transcript that has been annotated as bacterial in the NCBI database. The current work reiterates the under-utilization of transcriptomes for annotating genomes. It also provides new leads for investigating breast cancer by virtue of exclusively expressed transcripts not expressed in other tissues, which have the prospects of breast cancer biomarkers based on further investigations.
- organism: human
- assay: long-read sequencing
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: database / resource
- approach: statistical model
- Citations
- 5
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