AtFusionDB: a database of fusion transcripts in<i>Arabidopsis thaliana</i>

Singh, Ajeet; Zahra, Shafaque; Das, Durdam; Kumar, Shailesh

doi:10.1093/database/bay135

Cited by 10 publications

(3 citation statements)

References 44 publications

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“…In humans, tissue-specific pseudogene expression has been reported [39] and fusion transcripts are found to play an important role in tumorigenesis [40]. Such complex transcripts and their functions in plants are underexamined but efforts have been made to start the exploration [41,42]. It requires further investigation to determine if the expressed fused or disrupted genes we found in TME204 are real or result from annotation artifacts.…”

Section: Discussionmentioning

confidence: 98%

The haplotype-resolved chromosome pairs and transcriptome of a heterozygous diploid African cassava cultivar

Lim

Patrignani

et al. 2021

Preprint

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BackgroundCassava (Manihot esculenta) is an important clonally propagated food crop in tropical and sub-tropical regions worldwide. Genetic gain by molecular breeding is limited because cassava has a highly heterozygous, repetitive and difficult to assemble genome.FindingsHere we demonstrate that Pacific Biosciences high-fidelity (HiFi) sequencing reads, in combination with the assembler hifiasm, produced genome assemblies at near complete haplotype resolution with higher continuity and accuracy compared to conventional long sequencing reads. We present two chromosome scale haploid genomes phased with Hi-C technology for the diploid African cassava variety TME204. Genome comparisons revealed extensive chromosome re-arrangements and abundant intra-genomic and inter-genomic divergent sequences despite high gene synteny, with most large structural variations being LTR-retrotransposon related. Allele-specific expression analysis of different tissues based on the haplotype-resolved transcriptome identified both stable and inconsistent alleles with imbalanced expression patterns, while most alleles expressed coordinately. Among tissue-specific differentially expressed transcripts, coordinately and biasedly regulated transcripts were functionally enriched for different biological processes. We use the reference-quality assemblies to build a cassava pan-genome and demonstrate its importance in representing the genetic diversity of cassava for downstream reference-guided omics analysis and breeding.ConclusionsThe haplotype-resolved genome allows the first systematic view of the heterozygous diploid genome organization in cassava. The completely phased and annotated chromosome pairs will be a valuable resource for cassava breeding and research. Our study may also provide insights into developing cost-effective and efficient strategies for resolving complex genomes with high resolution, accuracy and continuity.

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Section: Discussionmentioning

confidence: 98%

The haplotype-resolved chromosome pairs and transcriptome of a heterozygous diploid African cassava cultivar

Lim

Patrignani

et al. 2021

Preprint

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“…Gene fusion is a process by which two or more distinct genes are fused into a single gene [1]. Gene fusion could be the results of trans-splicing events or structural variants such as chromosomal translocation, interstitial deletion or chromosomal inversion.…”

Section: Introductionmentioning

confidence: 99%

LongGF: computational algorithm and software tool for fast and accurate detection of gene fusions by long-read transcriptome sequencing

Liu

Stucky

et al. 2020

BMC Genomics

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Background Long-read RNA-Seq techniques can generate reads that encompass a large proportion or the entire mRNA/cDNA molecules, so they are expected to address inherited limitations of short-read RNA-Seq techniques that typically generate < 150 bp reads. However, there is a general lack of software tools for gene fusion detection from long-read RNA-seq data, which takes into account the high basecalling error rates and the presence of alignment errors. Results In this study, we developed a fast computational tool, LongGF, to efficiently detect candidate gene fusions from long-read RNA-seq data, including cDNA sequencing data and direct mRNA sequencing data. We evaluated LongGF on tens of simulated long-read RNA-seq datasets, and demonstrated its superior performance in gene fusion detection. We also tested LongGF on a Nanopore direct mRNA sequencing dataset and a PacBio sequencing dataset generated on a mixture of 10 cancer cell lines, and found that LongGF achieved better performance to detect known gene fusions over existing computational tools. Furthermore, we tested LongGF on a Nanopore cDNA sequencing dataset on acute myeloid leukemia, and pinpointed the exact location of a translocation (previously known in cytogenetic resolution) in base resolution, which was further validated by Sanger sequencing. Conclusions In summary, LongGF will greatly facilitate the discovery of candidate gene fusion events from long-read RNA-Seq data, especially in cancer samples. LongGF is implemented in C++ and is available at https://github.com/WGLab/LongGF.

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“…This includes RNA-DNA differences (Blank et al, 1986;Ninio, 1991;Li et al, 2011;Bahn et al, 2012;Strathern et al, 2012;Bar-Yaacov et al, 2013;Knippa and Peterson, 2013;Zhou et al, 2013;Wang et al, 2016), post-transcriptional editing (Bass, 2002;Schaub and Keller, 2002;Chen and Bundschuh, 2012;Park et al, 2012;Wang IX et al, 2014a;Lee et al, 2015), post-transcriptional hyper editing (Porath et al, 2014) and polymerase template switching (Lee et al, 2007;Löytynoja and Goldma n, 20 17). Transcript fusion exp lains some noncanonical RNAs (Kumar et al, 2016;López-Nieva et al, 2019;Singh et al, 2019). Some rare DNAs and RNAs seerm to result from spontaneous, template-free polymerization (Béguin et al, 2015;Seligmann and Raoult, 2018).…”

Section: Introductionmentioning

confidence: 99%

Systematic Nucleotide Exchange Analysis of ESTs From the Human Cancer Genome Project Report: Origins of 347 Unknown ESTs Indicate Putative Transcription of Non-Coding Genomic Regions

2020

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Expressed sequence tags (ESTs) provide an imprint of cellular RNA diversity irrespectively of sequence homology with template genomes. NCBI databases include many unknown RNAs from various normal and cancer cells. These are usually ignored assuming sequencing artefacts or contamination due to their lack of sequence homology with template DNA. Here, we report genomic origins of 347 ESTs previously assumed artefacts/unknown, from the FAPESP/LICR Human Cancer Genome Project. EST template detection uses systematic nucleotide exchange analyses called swinger transformations. Systematic nucleotide exchanges replace systematically particular nucleotides with different nucleotides. Among 347 unknown ESTs, 51 ESTs match mitogenome transcription, 17 and 2 ESTs are from nuclear chromosome non-coding regions, and uncharacterized nuclear genes. Identified ESTs mapped on 205 proteincoding genes, 10 genes had swinger RNAs in several biosamples. Whole cell transcriptome searches for 17 ESTs mapping on non-coding regions confirmed their transcription. The 10 swinger-transcribed genes identified more than once associate with cancer induction and progression, suggesting swinger transformation occurs mainly in highly transcribed genes. Swinger transformation is a unique method to identify noncanonical RNAs obtained from NGS, which identifies putative ncRNA transcribed regions. Results suggest that swinger transcription occurs in highly active genes in normal and genetically unstable cancer cells.

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AtFusionDB: a database of fusion transcripts inArabidopsis thaliana

Cited by 10 publications

References 44 publications

The haplotype-resolved chromosome pairs and transcriptome of a heterozygous diploid African cassava cultivar

The haplotype-resolved chromosome pairs and transcriptome of a heterozygous diploid African cassava cultivar

LongGF: computational algorithm and software tool for fast and accurate detection of gene fusions by long-read transcriptome sequencing

Systematic Nucleotide Exchange Analysis of ESTs From the Human Cancer Genome Project Report: Origins of 347 Unknown ESTs Indicate Putative Transcription of Non-Coding Genomic Regions

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