Comprehensive Identification and Alternative Splicing of Microexons in Drosophila

Pang, Ting-Lin; Ding, Zhan; Liang, Shuli; Li, Liang; Zhang, Bei; Zhang, Yu; Fan, Yujie; Xu, Yan

doi:10.3389/fgene.2021.642602

Cited by 8 publications

(8 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a similar manner to before, megablast was used to compare base set transcripts, from which the reads were simulated, back to contigs and the R-package was used to calculate r-squared values. This procedure of simulating read-pairs from the base set, assembling them and calculating the r-squared values was 87 were downloaded from NCBI SRA, study no. SRP297872; run number SRR13251053 for adult 1 and run no.…”

Section: Chimerism and De Novo Assembled Contigsmentioning

confidence: 99%

“…In relation to the latter, assemblies were also created, and r-squared values calculated for contigs produced from RNA-Seq reads sequenced from fruit fly, obtained from a study on alternative splicing. 87 These too were compared to the background distribution describing the correlation between alignment lengths and base set transcript lengths at incrementing levels of chimerism.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quantification of the effects of chimerism on read mapping, differential expression and annotation following short-read de novo assembly.

Linheiro

Archer

2022

F1000Res

View full text Add to dashboard Cite

Background: De novo assembly is often required for analysing short-read RNA sequencing data. An under-characterized aspect of the contigs produced is chimerism, the extent to which affects mapping, differential expression analysis and annotation. Despite long-read sequencing negating this issue, short-reads remain in use through on-going research and archived datasets created during the last two decades. Consequently, there is still a need to quantify chimerism and its effects. Methods: Effects on mapping were quantified by simulating reads off the Drosophila melanogaster cDNA library and mapping these to related reference sets containing increasing levels of chimerism. Next, ten read datasets were simulated and divided into two conditions where, within one, reads representing 1000 randomly selected transcripts were over-represented across replicates. Differential expression analysis was performed iteratively with increasing chimerism within the reference set. Finally, an expectation of r-squared values describing the relationship between alignment and transcript lengths for matches involving cDNA library transcripts and those within sets containing incrementing chimerism was created. Similar values calculated for contigs produced by three graph-based assemblers, relative to the cDNA library from which input reads were simulated, or sequenced (relative to the species represented), were compared. Results: At 5% and 95% chimerism within reference sets, 100% and 77% of reads still mapped, making mapping success a poor indicator of chimerism. At 5% chimerism, of the 1000 transcripts selected for over-representation, 953 were identified during differential expression analysis; at 10% 936 were identified, while at 95% it was 510. This indicates that despite mapping success, per-transcript counts are unpredictably altered. R-squared values obtained for the three assemblers suggest that between 5-15% of contigs are chimeric. Conclusions: Although not evident based on mapping, chimerism had a significant impact on differential expression analysis and megablast identification. This will have consequences for past and present experiments involving short-reads.

show abstract

Section: Chimerism and De Novo Assembled Contigsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantification of the effects of chimerism on read mapping, differential expression and annotation following short-read de novo assembly.

Linheiro

Archer

2022

F1000Res

View full text Add to dashboard Cite

show abstract

“…Two adult fruit fly whole-body samples, from the Pang et al . (2021) study on alternative splicing [ 62 ], were downloaded from NCBI SRA, study no. SRP297872; run number SRR13251053 for adult 1 and run no.…”

Section: Design and Implementationmentioning

confidence: 99%

“…Additionally, the approach, or similar ones, is readily implementable within any graphbased assembler. As a demonstration of CStones ability to assemble data we compare contigs produced by CStone to those produced by two well-established assemblers, Trinity [24], and rnaSPAdes [26], using both simulated data from four species, Drosophila melanogaster (fruit fly), Panthera pardus (leopard), Rattus norvegicus (brown rat) and Serinus canaria (canary), as well as real data obtained from a study on alternative splicing in D. melanogaster [62]. Our results indicate that all three assemblers perform well, and that the increased information that CStone adds on chimerism can be of value.…”

Section: Introductionmentioning

confidence: 99%

CStone: A de novo transcriptome assembler for short-read data that identifies non-chimeric contigs based on underlying graph structure

Linheiro

Archer

2021

PLoS Comput Biol

View full text Add to dashboard Cite

With the exponential growth of sequence information stored over the last decade, including that of de novo assembled contigs from RNA-Seq experiments, quantification of chimeric sequences has become essential when assembling read data. In transcriptomics, de novo assembled chimeras can closely resemble underlying transcripts, but patterns such as those seen between co-evolving sites, or mapped read counts, become obscured. We have created a de Bruijn based de novo assembler for RNA-Seq data that utilizes a classification system to describe the complexity of underlying graphs from which contigs are created. Each contig is labelled with one of three levels, indicating whether or not ambiguous paths exist. A by-product of this is information on the range of complexity of the underlying gene families present. As a demonstration of CStones ability to assemble high-quality contigs, and to label them in this manner, both simulated and real data were used. For simulated data, ten million read pairs were generated from cDNA libraries representing four species, Drosophila melanogaster, Panthera pardus, Rattus norvegicus and Serinus canaria. These were assembled using CStone, Trinity and rnaSPAdes; the latter two being high-quality, well established, de novo assembers. For real data, two RNA-Seq datasets, each consisting of ≈30 million read pairs, representing two adult D. melanogaster whole-body samples were used. The contigs that CStone produced were comparable in quality to those of Trinity and rnaSPAdes in terms of length, sequence identity of aligned regions and the range of cDNA transcripts represented, whilst providing additional information on chimerism. Here we describe the details of CStones assembly and classification process, and propose that similar classification systems can be incorporated into other de novo assembly tools. Within a related side study, we explore the effects that chimera’s within reference sets have on the identification of differentially expression genes. CStone is available at: https://sourceforge.net/projects/cstone/.

show abstract

“…(2.2) Real data. Two adult fruit fly whole-body samples, from the Pang et al (2021) study on alternative splicing [62], were downloaded from NCBI SRA, study no. SRP297872; run number SRR13251053 for adult 1 and run no.…”

Section: Plos Computational Biologymentioning

confidence: 99%

Untitled

View full text Add to dashboard Cite

Comprehensive Identification and Alternative Splicing of Microexons in Drosophila

Cited by 8 publications

References 34 publications

Quantification of the effects of chimerism on read mapping, differential expression and annotation following short-read de novo assembly.

Quantification of the effects of chimerism on read mapping, differential expression and annotation following short-read de novo assembly.

CStone: A de novo transcriptome assembler for short-read data that identifies non-chimeric contigs based on underlying graph structure

Untitled

Contact Info

Product

Resources

About