Accelerating de novo SINE annotation in plant and animal genomes

Genome annotation is an important but challenging task. Accurate identification of short interspersed nuclear elements (SINEs) is particularly difficult due to their lack of highly conserved sequences. AnnoSINE is state-of-the-art software for annotating SINEs in plant genomes, but it is computationally inefficient for large genomes. Moreover, its applicability to animals is limited due to the absence of animal pHMMs in its HMM library. Therefore, we propose AnnoSINE_v2, which extends accurate SINE annotation for animal genomes with greatly optimized computational efficiency. Our results show that AnnoSINE_v2's annotation of SINEs has over 20% higher F1-score compared to the existing tools on animal genomes and enables the processing of complicated genomes, like human and zebrafish, which were beyond the capabilities of AnnoSINE_v1. AnnoSINE_v2 is freely available on Conda and GitHub: https://github.com/liaoherui/AnnoSINE_v2 .

Authors

Institutions

Publication Details

Journal
Mobile DNA
Published
2024-10-19
DOI
https://doi.org/10.1186/s13100-024-00331-y
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Accelerating de novo SINE annotation in plant and animal genomes

Herui Liao, Shujun Ou, Yanni Sun
Mobile DNA
Genomics and Phylogenetic Studies
article

Accelerating de novo SINE annotation in plant and animal genomes

Herui Liao, Shujun Ou, Yanni Sun
article en

Abstract

Genome annotation is an important but challenging task. Accurate identification of short interspersed nuclear elements (SINEs) is particularly difficult due to their lack of highly conserved sequences. AnnoSINE is state-of-the-art software for annotating SINEs in plant genomes, but it is computationally inefficient for large genomes. Moreover, its applicability to animals is limited due to the absence of animal pHMMs in its HMM library. Therefore, we propose AnnoSINE_v2, which extends accurate SINE annotation for animal genomes with greatly optimized computational efficiency. Our results show that AnnoSINE_v2's annotation of SINEs has over 20% higher F1-score compared to the existing tools on animal genomes and enables the processing of complicated genomes, like human and zebrafish, which were beyond the capabilities of AnnoSINE_v1. AnnoSINE_v2 is freely available on Conda and GitHub: https://github.com/liaoherui/AnnoSINE_v2 .

Mobile DNAVol. 15(1)
City University of Hong Kong (HK), The Ohio State University (US)
City University of Hong Kong
Openalex Percentile: Top 83%
Genomics and Phylogenetic Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.