ICCFGG 2022
#57 ANNEXA: Analysis of Nanopore transcriptomic data with Nextflow for Extended Annotation Thomas Derrien , Matthias Lorthiois, Édouard Cadieu, Armel Houel, Catherine André, Christophe Hitte, Benoit Hédan Thomas.derrien@univ-rennes1.fr Univ Rennes, CNRS, Rennes, France The development of long-read transcriptome sequencing (LR-RNAseq) promises to facilitate the process of genome annotation. By providing reads spanning repeats and direct exon/exon connec- tivity, LR-RNAseq represents an unfragmented vision of the transcriptome which thus allows the refinement of gene/transcript reconstruction and quantification. Yet, it requires the development of novel bioinformatic solutions specifically adapted to these novel technologies. Based on nanoseq, a Nextflow-based workflow dedicated to long-read analysis, we developed ANNEXA, an all-in-one reproductible pipeline which allows users to analyze LR-RNAseq sequences from Oxford Nanopore Technologies (ONT), and to reconstruct and quantify known novel genes and isoforms. Specifically, ANNEXA provides users with an extended annotation distinguishing between novel protein-cod- ing (mRNA) versus long non-coding RNAs (lncRNA) genes. All known and novel gene/transcript models are further characterized through structural and quantitative features (length, number of spliced transcripts, normalized expression levels...) available as graphical outputs. To demonstrate the usability of the program, we sequenced 2 human and 7 dog cancer cell lines from mucosal melanomas and histiocytic sarcomas using ONT direct cDNA kits, representing ~60M nanopore reads (mean=6.5M reads/sample). We then applied ANNEXA on these two species-specific read sets and were able to reconstruct and quantify 1,842 and 8,262 new multi-exonic human and canine genes, respectively, all supported by at least 5 reads in both species. Overall, our work presents a new bioinformatic pipeline to automatically reconstruct and characterize mRNAs and lncRNAs from ONT transcriptome data and is freely available at: https://github.com/mlorthiois/ANNEXA. #58 Identification of novel epilepsy and dyskinesia loci and candidate genes in Labrador Retrievers Tiina Heinonen 1,2 , Hytönen MK1,2, Niskanen J1,2, Pääkkönen T1, Mandigers P3, Minor K4, Ricketts S5, Jenkins C5, Leeb T6, Tipold A7, Fischer A8, Lohi H1,2 tiina.heinonen@helsinki.fi 1University of Helsinki, Finland; 2Folkhälsan Research Center, Finland; 3University of Utrecht, Netherlands; 4University of Minnesota, US; 5University of Cambridge, UK; 6University of Bern, Switzerland; 7University of Veterinary Medicine Hannover, Germany; 8Ludwig Maximilian University of Munich, Germany Idiopathic epilepsy (IE) is a common neurological disorder in many dog breeds, including Labrador Retrievers (LRs), one of the most popular breeds in the world. The typical clinical picture in LRs varies from focal to generalized seizures. LRs can also suffer from paroxysmal dyskinesia (PD). Genetics plays a significant role in both diseases, but gene discoveries are absent. We aimed to identify new genes associated with IE and PD in LRs. Towards this goal, we genotyped 200 LR cases with IE or PD and 400 controls using Illumina’s 173k arrays. Then we performed a GWAS using a mixed model that corrects population stratification using the GENESIS package.
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