scholarly journals CoCo: RNA-seq Read Assignment Correction for Nested Genes and Multimapped Reads

2018 ◽  
Author(s):  
Gabrielle Deschamps-Francoeur ◽  
Vincent Boivin ◽  
Sherif Abou Elela ◽  
Michelle S Scott

AbstractMotivationNext generation sequencing techniques revolutionized the study of RNA expression by permitting whole transcriptome analysis. However, sequencing reads generated from nested and multi-copy genes are often either misassigned or discarded, which greatly reduces both quantification accuracy and gene coverage.ResultsHere we present CoCo, a read assignment pipeline that takes into account the multitude of overlapping and repetitive genes in the transcriptome of higher eukaryotes. CoCo uses a modified annotation file that highlights nested genes and proportionally distributes multimapped reads between repeated sequences. CoCo salvages over 15% of discarded aligned RNA-seq reads and significantly changes the abundance estimates for both coding and non-coding RNA as validated by PCR and bed-graph comparisons.AvailabilityThe CoCo software is an open source package written in Python and available from http://gitlabscottgroup.med.usherbrooke.ca/scott-group/[email protected]

2019 ◽  
Vol 35 (23) ◽  
pp. 5039-5047 ◽  
Author(s):  
Gabrielle Deschamps-Francoeur ◽  
Vincent Boivin ◽  
Sherif Abou Elela ◽  
Michelle S Scott

Abstract Motivation Next-generation sequencing techniques revolutionized the study of RNA expression by permitting whole transcriptome analysis. However, sequencing reads generated from nested and multi-copy genes are often either misassigned or discarded, which greatly reduces both quantification accuracy and gene coverage. Results Here we present count corrector (CoCo), a read assignment pipeline that takes into account the multitude of overlapping and repetitive genes in the transcriptome of higher eukaryotes. CoCo uses a modified annotation file that highlights nested genes and proportionally distributes multimapped reads between repeated sequences. CoCo salvages over 15% of discarded aligned RNA-seq reads and significantly changes the abundance estimates for both coding and non-coding RNA as validated by PCR and bedgraph comparisons. Availability and implementation The CoCo software is an open source package written in Python and available from http://gitlabscottgroup.med.usherbrooke.ca/scott-group/coco. Supplementary information Supplementary data are available at Bioinformatics online.


2021 ◽  
Author(s):  
Xiaopeng An ◽  
Yue Zhang ◽  
Fu Li ◽  
Zhanhang Wang ◽  
Shaohua Yang ◽  
...  

Abstract BackgroundEstrous cycle is one of female characteristics after sexual maturity, including estrus (ES) and diestrus (DS) stages. Estrous cycle is important in female physiology and its disorder may lead to diseases. In the latest years, effects of non-coding RNAs and mRNA on estrous cycle start to arouse much concern, however, a whole transcriptome analysis among non-coding RNAs and mRNA has not been reported.ResultsHere we report a whole transcriptome analysis of goat ovary in estrus and diestrus periods. Estrus synchronization was conducted to induce the estrus phase and on day 32, the goats naturally shifted into diestrus stage. The ovary RNA of estrus and diestrus stages was respectively collected to perform RNA-sequencing. Then the circular RNA; microRNA; long non-coding RNA; mRNA databases of goat ovary were acquired, and the differentially expressions between estrus and diestrus stages were screened to construct circRNA-miRNA-mRNA/lncRNA and lncRNA-miRNA/mRNA networks, thus providing potential pathways that involved in the regulation of estrous cycle. Differentially expressed mRNAs, such as MMP9, TIMP1, 3BHSD and PTGIS, and differentially expressed microRNAs, such as miR-21-3p,miR-202-3p and miR-223-3p, which play key roles in estrous cycle regulation were extracted from the network.ConclusionsOur data provided the miRNA, circRNA, lncRNA and mRNA databases of goat ovary and each differentially expressed profile between ES and DS. Networks among differentially expressed miRNAs, circRNAs, lncRNAs and mRNAs were constructed to provide valuable resources for the study of estrous cycle and related diseases.


PLoS ONE ◽  
2015 ◽  
Vol 10 (2) ◽  
pp. e0118587 ◽  
Author(s):  
Yoshikazu Mikami ◽  
Atsushi Fukushima ◽  
Takao Kuwada-Kusunose ◽  
Tetsuya Sakurai ◽  
Taiichi Kitano ◽  
...  

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