Analysis of plant pan-genomes and transcriptomes with GET_HOMOLOGUES-EST, a clustering solution for sequences of the same species

Contreras-Moreira, B. (Universidad de Zaragoza) ; Cantalapiedra, C.P. ; García-Pereira, M.J. ; Gordon, S.P. ; Vogel, J.P. ; Igartua, E. ; Casas, A.M. ; Vinuesa, P.

Resumen: The pan-genome of a species is defined as the union of all the genes and noncoding sequences found in all its individuals. However, constructing a pan-genome for plants with large genomes is daunting both in sequencing cost and the scale of the required computational analysis. A more affordable alternative is to focus on the genic repertoire by using transcriptomic data. Here, the software GET_HOMOLOGUES-EST was benchmarked with genomic and RNA-seq data of 19 Arabidopsis thaliana ecotypes and then applied to the analysis of transcripts from 16 Hordeum vulgare genotypes. The goal was to sample their pan-genomes and classify sequences as core, if detected in all accessions, or accessory, when absent in some of them. The resulting sequence clusters were used to simulate pan-genome growth, and to compile Average Nucleotide Identity matrices that summarize intra-species variation. Although transcripts were found to under-estimate pan-genome size by at least 10%, we concluded that clusters of expressed sequences can recapitulate phylogeny and reproduce two properties observed in A. thaliana gene models: accessory loci show lower expression and higher non-synonymous substitution rates than core genes. Finally, accessory sequences were observed to preferentially encode transposon components in both species, plus disease resistance genes in cultivated barleys, and a variety of protein domains from other families that appear frequently associated with presence/absence variation in the literature. These results demonstrate that pan-genome analyses are useful to explore germplasm diversity.

Idioma: Inglés

DOI: 10.3389/fpls.2017.00184

Año: 2017

Publicado en: FRONTIERS IN PLANT SCIENCE 8 (2017), 184 [16 pp]
ISSN: 1664-462X

Factor impacto JCR: 3.678 (2017)

Categ. JCR: PLANT SCIENCES rank: 24 / 222 = 0.108 (2017) - Q1 - T1

Factor impacto SCIMAGO: 1.731 - Plant Science (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/AGL2010-21929
Financiación: info:eu-repo/grantAgreement/ES/MINECO/AGL2013-487569
Financiación: info:eu-repo/grantAgreement/ES/MINECO/BES-2011-045905

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Bioquímica y Biolog.Mole. (Dpto. Bioq.Biolog.Mol. Celular)