Fine Identification and Classification of a Novel Beneficial Talaromyces Fungal Species from Masson Pine Rhizosphere Soil.
Xiao-Rui SunMing-Ye XuWei-Liang KongFei WuYu ZhangXing-Li XieDe-Wei LiXiao-Qin WuPublished in: Journal of fungi (Basel, Switzerland) (2022)
Rhizosphere fungi have the beneficial functions of promoting plant growth and protecting plants from pests and pathogens. In our preliminary study, rhizosphere fungus JP-NJ4 was obtained from the soil rhizosphere of Pinus massoniana and selected for further analyses to confirm its functions of phosphate solubilization and plant growth promotion. In order to comprehensively investigate the function of this strain, it is necessary to ascertain its taxonomic position. With the help of genealogical concordance phylogenetic species recognition (GCPSR) using five genes/regions (ITS, BenA , CaM , RPB1 , and RPB2 ) as well as macro-morphological and micro-morphological characters, we accurately determined the classification status of strain JP-NJ4. The concatenated phylogenies of five (or four) gene regions and single gene phylogenetic trees (ITS, BenA , CaM , RPB1 , and RPB2 genes) all show that strain JP-NJ4 clustered together with Talaromyces brevis and Talaromyces liani , but differ markedly in the genetic distance (in BenA gene) from type strain and multiple collections of T . brevis and T . liani . The morphology of JP-NJ4 largely matches the characteristics of genes Talaromyces , and the rich and specific morphological information provided by its colonies was different from that of T. brevis and T. liani . In addition, strain JP-NJ4 could produce reduced conidiophores consisting of solitary phialides. From molecular and phenotypic data, strain JP-NJ4 was identified as a putative novel Talaromyces fungal species, designated T. nanjingensis .
Keyphrases
- plant growth
- genome wide
- genome wide identification
- microbial community
- copy number
- machine learning
- dna methylation
- bioinformatics analysis
- deep learning
- genome wide analysis
- gene expression
- electronic health record
- air pollution
- big data
- multidrug resistant
- gram negative
- health information
- artificial intelligence
- genetic diversity