Taxonomic assignment of arbuscular mycorrhizal fungi in an 18S metagenomic dataset: a case study with saltcedar (Tamarix aphylla)

生物 球囊菌门 GenBank公司 系统发育树 血球 操作分类学单元 系统发育学 植物 共生 遗传学 菌根 16S核糖体RNA 基因 孢子 细菌
作者
Franck Stefani,Karima Bencherif,Stéphanie Sabourin,Anissa Lounès‐Hadj Sahraoui,Claudia Banchini,Sylvie Séguin,Yolande Dalpé
出处
期刊:Mycorrhiza [Springer Science+Business Media]
卷期号:30 (2-3): 243-255 被引量:35
标识
DOI:10.1007/s00572-020-00946-y
摘要

Many studies describing communities of arbuscular mycorrhizal fungi (AMF, Glomeromycota) based on high-throughput sequencing target the V4 variable region of the 18S ribosomal gene. However, an accurate taxonomic assignment of these short 18S sequences is challenging. Here we describe a simple approach based on a phylogenetic analysis using a backbone of reference sequences with taxonomic names updated in MycoBank to improve the taxonomic assignment of amplicon sequence variants (ASVs). As a case study, paired-end sequencing (2 × 250 bp) was carried out to describe the community of AMF associated with Tamarix aphylla from Algerian steppe ecosystems. AMF from root and soil samples were targeted with a nested PCR, using the AMF-discriminating primers pair AML1/AML2 for the first amplification and a new primer pair for the second. The proportion of the sequences assigned to Glomeromycota was 85.9%, representing a total of 87 ASVs. Seven well-defined genera (Claroideoglomus, Dominikia, Funneliformis, Innospora, Microkamienskia, Rhizophagus, Septoglomus) and seven phylogenetic divergent clades of Glomus (27% of the ASVs) were identified with the proposed approach. This taxonomic assignment was in sharp contrast with querying the MaarjAM or GenBank databases. Out-of-date taxonomy led the MaarjAM database to attribute 85% of the ASVs to the genus Glomus and the GenBank database to assign 18% of the ASVs to unclassified taxa. We recommend using the simple workflow presented in this study so that up-to-date taxonomic information is accurately assigned to AMF communities analyzed by high-throughput sequencing.
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