Publications des scientifiques de l'IRD

Orozco-Arias S., Tobon-Orozco N., Pina J. S., Jimenez-Varon C. F., Tabares-Soto R., Guyot Romain. (2020). TIP_finder : an HPC software to detect transposable element insertion polymorphisms in large genomic datasets. Biology, 9 (9), p. 281 [17 p.].

Titre du document
TIP_finder : an HPC software to detect transposable element insertion polymorphisms in large genomic datasets
Année de publication
2020
Type de document
Article référencé dans le Web of Science WOS:000580012300001
Auteurs
Orozco-Arias S., Tobon-Orozco N., Pina J. S., Jimenez-Varon C. F., Tabares-Soto R., Guyot Romain
Source
Biology, 2020, 9 (9), p. 281 [17 p.]
Transposable elements (TEs) are non-static genomic units capable of moving indistinctly from one chromosomal location to another. Their insertion polymorphisms may cause beneficial mutations, such as the creation of new gene function, or deleterious in eukaryotes, e.g., different types of cancer in humans. A particular type of TE called LTR-retrotransposons comprises almost 8% of the human genome. Among LTR retrotransposons, human endogenous retroviruses (HERVs) bear structural and functional similarities to retroviruses. Several tools allow the detection of transposon insertion polymorphisms (TIPs) but fail to efficiently analyze large genomes or large datasets. Here, we developed a computational tool, named TIP_finder, able to detect mobile element insertions in very large genomes, through high-performance computing (HPC) and parallel programming, using the inference of discordant read pair analysis. TIP_finder inputs are (i) short pair reads such as those obtained by Illumina, (ii) a chromosome-level reference genome sequence, and (iii) a database of consensus TE sequences. The HPC strategy we propose adds scalability and provides a useful tool to analyze huge genomic datasets in a decent running time. TIP_finder accelerates the detection of transposon insertion polymorphisms (TIPs) by up to 55 times in breast cancer datasets and 46 times in cancer-free datasets compared to the fastest available algorithms. TIP_finder applies a validated strategy to find TIPs, accelerates the process through HPC, and addresses the issues of runtime for large-scale analyses in the post-genomic era.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Informatique [122]
Localisation
Fonds IRD [F B010079857]
Identifiant IRD
fdi:010079857
Contact