K‐mer counting and curated libraries drive efficient annotation of repeats in plant genomes
Abstract The annotation of repetitive sequences within plant genomes can help in the interpretation of observed phenotypes. Moreover, repeat masking is required for tasks such as whole‐genome alignment, promoter analysis, or pangenome exploration. Although homology‐based annotation methods are compu...
Enregistré dans:
| Auteurs principaux: | , , , , , |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
Wiley
2021
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/b532ac8f92da477eab4920c1f846cd9b |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| Résumé: | Abstract The annotation of repetitive sequences within plant genomes can help in the interpretation of observed phenotypes. Moreover, repeat masking is required for tasks such as whole‐genome alignment, promoter analysis, or pangenome exploration. Although homology‐based annotation methods are computationally expensive, k‐mer strategies for masking are orders of magnitude faster. Here, we benchmarked a two‐step approach, where repeats were first called by k‐mer counting and then annotated by comparison to curated libraries. This hybrid protocol was tested on 20 plant genomes from Ensembl, with the k‐mer‐based Repeat Detector (Red) and two repeat libraries (REdat, last updated in 2013, and nrTEplants, curated for this work). Custom libraries produced by RepeatModeler were also tested. We obtained repeated genome fractions that matched those reported in the literature but with shorter repeated elements than those produced directly by sequence homology. Inspection of the masked regions that overlapped genes revealed no preference for specific protein domains. Most Red‐masked sequences could be successfully classified by sequence similarity, with the complete protocol taking less than 2 h on a desktop Linux box. A guide to curating your own repeat libraries and the scripts for masking and annotating plant genomes can be obtained at https://github.com/Ensembl/plant‐scripts. |
|---|