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...

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Autores principales:	Bruno Contreras‐Moreira, Carla V Filippi, Guy Naamati, Carlos García Girón, James E Allen, Paul Flicek
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Plant culture SB1-1110 Genetics QH426-470
Acceso en línea:	https://doaj.org/article/b532ac8f92da477eab4920c1f846cd9b
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spelling	oai:doaj.org-article:b532ac8f92da477eab4920c1f846cd9b2021-12-05T07:50:12ZK‐mer counting and curated libraries drive efficient annotation of repeats in plant genomes1940-337210.1002/tpg2.20143https://doaj.org/article/b532ac8f92da477eab4920c1f846cd9b2021-11-01T00:00:00Zhttps://doi.org/10.1002/tpg2.20143https://doaj.org/toc/1940-3372Abstract 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.Bruno Contreras‐MoreiraCarla V FilippiGuy NaamatiCarlos García GirónJames E AllenPaul FlicekWileyarticlePlant cultureSB1-1110GeneticsQH426-470ENThe Plant Genome, Vol 14, Iss 3, Pp n/a-n/a (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Plant culture SB1-1110 Genetics QH426-470
spellingShingle	Plant culture SB1-1110 Genetics QH426-470 Bruno Contreras‐Moreira Carla V Filippi Guy Naamati Carlos García Girón James E Allen Paul Flicek K‐mer counting and curated libraries drive efficient annotation of repeats in plant genomes
description	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.
format	article
author	Bruno Contreras‐Moreira Carla V Filippi Guy Naamati Carlos García Girón James E Allen Paul Flicek
author_facet	Bruno Contreras‐Moreira Carla V Filippi Guy Naamati Carlos García Girón James E Allen Paul Flicek
author_sort	Bruno Contreras‐Moreira
title	K‐mer counting and curated libraries drive efficient annotation of repeats in plant genomes
title_short	K‐mer counting and curated libraries drive efficient annotation of repeats in plant genomes
title_full	K‐mer counting and curated libraries drive efficient annotation of repeats in plant genomes
title_fullStr	K‐mer counting and curated libraries drive efficient annotation of repeats in plant genomes
title_full_unstemmed	K‐mer counting and curated libraries drive efficient annotation of repeats in plant genomes
title_sort	k‐mer counting and curated libraries drive efficient annotation of repeats in plant genomes
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/b532ac8f92da477eab4920c1f846cd9b
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K‐mer counting and curated libraries drive efficient annotation of repeats in plant genomes

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