The Landscape and Implications of Chimeric RNAs in Cervical Cancer

Wu, Peng; Yang, Shuo; Singh, Sandeep; Qin, Fujun; Kumar, Shailesh; Wang, Ling; Ma, Ding; Li, Hui

doi:10.1016/j.ebiom.2018.10.059

Cited by 35 publications

(32 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, without the additional information provided by TIF-Seq2, those same RNA-seq datasets were not sufficient to confidently classify them as read-through transcripts. Interestingly, during the preparation of this work, a few cases have been investigated in detail and independently reported as fusion transcripts in agreement with our findings 26,27 .…”

Section: Identifying Read-through Transcriptssupporting

confidence: 90%

Dissecting chronic myeloid leukaemia overlapping transcriptome with TIF-Seq2

Wang

Marques

et al. 2019

Preprint

View full text Add to dashboard Cite

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. To improve the annotation of complex genomes, 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 RNAs challenging to investigate with RNA-seq, we accurately define boundaries of lowly 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. Main

show abstract

Section: Identifying Read-through Transcriptssupporting

confidence: 90%

Dissecting chronic myeloid leukaemia overlapping transcriptome with TIF-Seq2

Wang

Marques

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…LHX6-NDUFA8, SLC2A11-MIF, and SLC45A3-ELK4 are con rmed cis-SAGe events in HeLa [31,32]. The parental genes SLC45A3 and ELK4 were not listed as having poly(A) tails in Chang et al [13].…”

Section: Stfusion Veri Cation For Gene Fusions and Cis-sagementioning

confidence: 96%

“…Indeed, this event was con rmed with STfusion. The fusions TINF2-NEDD8 and DHRS13-FLOT2 were experimentally con rmed [31], but both parental genes were polyadenylated. This data suggests that these fusions are caused by a trans-splicing event.…”

Section: Stfusion Veri Cation For Gene Fusions and Cis-sagementioning

confidence: 97%

See 1 more Smart Citation

Fusion transcript detection using spatial transcriptomics

Friedrich

Sonnhammer

2020

Preprint

View full text Add to dashboard Cite

Background Fusion transcripts are involved in tumourigenesis and play a crucial role in tumour heterogeneity, tumour evolution and cancer treatment resistance. However, fusion transcripts have not been studied at high spatial resolution in tissue sections due to the lack of full-length transcripts with spatial information. New high-throughput technologies like spatial transcriptomics measure the transcriptome of tissue sections on almost single-cell level. While this technique does not allow for direct detection of fusion transcripts, we show that they can be inferred using the relative poly(A) tail abundance of the involved parental genes. Method We present a new method STfusion, which uses spatial transcriptomics to infer the presence and absence of poly(A) tails. A fusion transcript lacks a poly(A) tail for the 5´ gene and has an elevated number of poly(A) tails for the 3´ gene. Its expression level is defined by the upstream promoter of the 5´ gene. STfusion measures the difference between the observed and expected number of poly(A) tails with a novel C-score. Results We verified the STfusion ability to predict fusion transcripts on HeLa cells with known fusions. STfusion and C-score applied to clinical prostate cancer data revealed the spatial distribution of the cis-SAGe SLC45A3-ELK4 in 12 tissue sections with almost single-cell resolution. The cis-SAGe occurred in disease areas, e.g. inflamed, prostatic intraepithelial neoplastic, or cancerous areas, and occasionally in normal glands. Conclusions STfusion detects fusion transcripts in cancer cell line and clinical tissue data, and distinguishes chimeric transcripts from chimeras caused by trans-splicing events. With STfusion and the use of C-scores, fusion transcripts can be spatially localised in clinical tissue sections on almost single cell level.

show abstract

“…To verify STfusion accuracy, we applied it to HeLa cancer cells. P. Wu et al [31] experimentally identified nine chimeric RNAs in HeLa cells. Further detected in Hela cancer cells were the cis-SAGe SLC45A3-ELK4 by Zhang et al [32] and the trans-splicing fusion event VMP1-RPS6KB1 by L. Wu et al [33].…”

Section: Stfusion Verification In Hela Cellsmentioning

confidence: 99%

Fusion transcript detection using spatial transcriptomics

Friedrich

Sonnhammer

2020

BMC Med Genomics

View full text Add to dashboard Cite

Background: Fusion transcripts are involved in tumourigenesis and play a crucial role in tumour heterogeneity, tumour evolution and cancer treatment resistance. However, fusion transcripts have not been studied at high spatial resolution in tissue sections due to the lack of full-length transcripts with spatial information. New highthroughput technologies like spatial transcriptomics measure the transcriptome of tissue sections on almost singlecell level. While this technique does not allow for direct detection of fusion transcripts, we show that they can be inferred using the relative poly(A) tail abundance of the involved parental genes. Method: We present a new method STfusion, which uses spatial transcriptomics to infer the presence and absence of poly(A) tails. A fusion transcript lacks a poly(A) tail for the 5′ gene and has an elevated number of poly(A) tails for the 3′ gene. Its expression level is defined by the upstream promoter of the 5′ gene. STfusion measures the difference between the observed and expected number of poly(A) tails with a novel C-score. Results: We verified the STfusion ability to predict fusion transcripts on HeLa cells with known fusions. STfusion and C-score applied to clinical prostate cancer data revealed the spatial distribution of the cis-SAGe SLC45A3-ELK4 in 12 tissue sections with almost single-cell resolution. The cis-SAGe occurred in disease areas, e.g. inflamed, prostatic intraepithelial neoplastic, or cancerous areas, and occasionally in normal glands. Conclusions: STfusion detects fusion transcripts in cancer cell line and clinical tissue data, and distinguishes chimeric transcripts from chimeras caused by trans-splicing events. With STfusion and the use of C-scores, fusion transcripts can be spatially localised in clinical tissue sections on almost single cell level.

show abstract

The Landscape and Implications of Chimeric RNAs in Cervical Cancer

Cited by 35 publications

References 22 publications

Dissecting chronic myeloid leukaemia overlapping transcriptome with TIF-Seq2

Dissecting chronic myeloid leukaemia overlapping transcriptome with TIF-Seq2

Fusion transcript detection using spatial transcriptomics

Fusion transcript detection using spatial transcriptomics

Contact Info

Product

Resources

About