Dynamics of Podospora anserina Genome Evolution in a Long-Term Experiment

• Published in: International journal of molecular sciences Vol. 24; no. 15; p. 12009
• Main Authors: Kudryavtseva, Olga A, Gerasimov, Evgeny S, Glagoleva, Elena S, Gasparyan, Anna A, Agroskin, Saveliy M, Belozersky, Mikhail A, Dunaevsky, Yakov E
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 27-07-2023; MDPI
• Subjects: Adaptation; Communication; Evolution & development; Evolution, Molecular; experimental evolution; Experiments; Fungi; Genome, Fungal; Genomes; Genotype & phenotype; INDEL Mutation; Laboratories; long-term experiment; Mutation; parallel evolution; Pathogens; Podospora - genetics; Podospora anserina; Polymorphism, Single Nucleotide; parallel evolution; Podospora anserina; experimental evolution; long-term experiment
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms241512009

The
long-term evolution experiment (PaLTEE) is the only running filamentous fungus study, which is still going on. The aim of our work is to trace the evolutionary dynamics of the accumulation of mutations in the genomes of eight haploid populations of
The results of the genome-wide analysis of all of the lineages, performed 8 years after the start of the PaLTEE, are presented. Data analysis detected 312 single nucleotide polymorphisms (SNPs) and 39 short insertion-deletion mutations (indels) in total. There was a clear trend towards a linear increase in the number of SNPs depending on the experiment duration. Among 312 SNPs, 153 were fixed in the coding regions of
genome. Relatively few synonymous mutations were found, exactly 38; 42 were classified as nonsense mutations; 72 were assigned to missense mutations. In addition, 21 out of 39 indels identified were also localized in coding regions. Here, we also report the detection of parallel evolution at the paralog level in the
model system. Parallelism in evolution at the level of protein functions also occurs. The latter is especially true for various transcription factors, which may indicate selection leading to optimization of the wide range of cellular processes under experimental conditions.