A fast detection of fusion genes from paired-end RNA-seq data

Vu, Trung Nghia; Deng, Wenjiang; Trac, Quang Thinh; Calza, Stefano; Hwang, Woochang; Pawitan, Yudi

doi:10.1186/s12864-018-5156-1

Cited by 26 publications

(21 citation statements)

References 32 publications

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“…For case 1, one μg of total RNA from the tumor was sent to the Genomics Core Facility at the Norwegian Radium Hospital, Oslo University Hospital (http://genomics.no/oslo/) for highthroughput paired-end RNA-sequencing according to the Illumina TruSeq Stranded mRNA protocol. The softwares FusionCatcher, deFuse, TopHat-Fusion, and FuSeq were used to find fusion transcripts (23)(24)(25)(26)(27)(28). In addition, the "grep" command was used to search the fastq files of the sequence data for PLAG1 sequence.…”

Section: G-banding and Karyotypingmentioning

confidence: 99%

NDRG1-PLAG1 and TRPS1-PLAG1 Fusion Genes in Chondroid Syringoma

Panagopoulos

Gorunova

Andersen

et al. 2020

Cancer Genomics Proteomics

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Background/Aim: Chondroid syringoma is a rare benign tumor emanating from sweat glands. Although rearrangements of the pleomorphic adenoma gene 1 (PLAG1) have been reported in such tumors, information on PLAG1 fusion genes is very limited. Materials and Methods: Cytogenetic, fluorescence in situ hybridization, RNA sequencing, array comparative genomic hybridization, reverse transcription polymerase chain reaction, and Sanger sequencing analyses were performed on two chondroid syringoma cases. Results: Both tumors had structural rearrangements of chromosome 8. An NDRG1-PLAG1 transcript was found in the first tumor in which exon 3 of PLAG1 was fused with exon 1 of NDRG1. A TRPS1-PLAG1 chimeric transcript was detected in the second chondroid syringoma in which exon 2 or exon 3 of PLAG1 was fused with exon 1 of TRPS1. Conclusion: The NDRG1-PLAG1 and TRPS1-PLAG1 resemble other PLAG1 fusion genes inasmuch as the expression of PLAG1 comes under the control of the NDRG1 or TRPS1 promoter. Chondroid syringoma, also known as mixed tumor of the skin, is a rare benign tumor emanating from sweat glands and able to display a wide array of histological patterns (1-5). It may have histological similarities with another benign exocrine gland tumor, pleomorphic adenoma or mixed tumor of the salivary glands, something that may cause differential diagnostic difficulties (3, 5, 6). The name chondroid syringoma was coined by Hirsch and Helwing (3) because of the invariable presence in the tumor of sweat gland elements (syringoma) and because cartilage-like material (chondroid) was also present in most tumors they studied (3). Chondroid syringoma most commonly occurs in the headand-neck region of middle-aged males (3, 5, 7-9) but can also be found in the axilla and on the anterior chest, trunk, extremities, and scrotum (3, 7, 10-19). We studied genetically two chondroid syringomas finding fusion of the pleomorphic adenoma gene 1 (PLAG1) at 8q12.2 in one with the gene N-myc downstream regulated 1 (NDRG1), which maps to chromosome subband 8q24.22, and in the second with the gene transcriptional repressor GATA binding 1 (TRPS1), which maps to 8q23.3. Materials and Methods Ethics statement. The study was approved by the regional Ethics Committee (Regional komité for medisinsk forskningsetikk Sør-Øst, Norge, http://helseforskning.etikkom.no) and written informed consent was obtained from the patients. The ethics committee's approval included a review of the consent procedure. All patient information has been de-identified. Case description Case 1. A 60-year-old male without any relevant medical previous history was surgically treated for a tumor located at the left ankle. The tumor was found to be consistent with a chondroid syringoma. Surgical margins were doubtful. Six years later re-excision was performed. Macroscopically the tumor was lobulated, but well demarcated. The cut section was soft and gelatinous intermingled with harder areas. Microscopically the tumor was composed of small cystic spaces, areas with myxoid tissue and areas wit...

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Section: G-banding and Karyotypingmentioning

confidence: 99%

NDRG1-PLAG1 and TRPS1-PLAG1 Fusion Genes in Chondroid Syringoma

Panagopoulos

Gorunova

Andersen

et al. 2020

Cancer Genomics Proteomics

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“…Finally, in this work, we have focused on differential transcript usage, but EC counts have the potential to be useful in a range of other expression analysis. EC counts have already been applied to areas such as clustering and dimensionality reduction 7 , gene-level differential expression 9 , single-cell transcriptomics 7,8 and fusion detection 20 . We foresee that equivalence classes could serve as a base unit of measurement in many other types of analyses.…”

Section: Discussionmentioning

confidence: 99%

Fast and accurate differential transcript usage by testing equivalence class counts

2019

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Background: RNA sequencing has enabled high-throughput and fine-grained quantitative analyses of the transcriptome. While differential gene expression is the most widely used application of this technology, RNA-seq data also has the resolution to infer differential transcript usage (DTU), which can elucidate the role of different transcript isoforms between experimental conditions, cell types or tissues. DTU has typically been inferred from exon-count data, which has issues with assigning reads unambiguously to counting bins, and requires alignment of reads to the genome. Recently, approaches have emerged that use transcript quantifications estimates directly for DTU. Transcript counts can be inferred from 'pseudo' or lightweight aligners, which are significantly faster than traditional genome alignment. However, recent evaluations show lower sensitivity in DTU analysis. Transcript abundances are estimated from equivalence classes (ECs), which determine the transcripts that any given read is compatible with. Recent work has proposed performing differential expression testing directly on equivalence class read counts (ECs). Methods: Here we demonstrate that ECs can be used effectively with existing count-based methods for detecting DTU. We evaluate this approach on simulated human and drosophila data, as well as on a real dataset through subset testing. Results: We find that ECs counts have similar sensitivity and false discovery rates as exon-level counts but can be generated in a fraction of the time through the use of pseudo-aligners. Conclusions: We posit that equivalence class read counts are a natural unit on which to perform many types of analysis.

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“…4.3 [17] was used with Samtools mpileup to identify and calculate the VAFs of small indels and substitutions, using default parameters. To detect gene fusions, a fusion index was first built using FuSeq [18] with the default SQLite database of GRCh37 version 75. FuSeq was run under default parameters to identify gene fusions.…”

Section: Bioinformatics Analysesmentioning

confidence: 99%