Demographic analysis of cyanobacteria based on the mutation rates estimated from an ancient ice core

Abstract

Despite the crucial role of cyanobacteria in various ecosystems, little is known about their evolutionary histories, especially microevolutionary dynamics, because of the lack of knowledge regarding their mutation rates. Here we directly estimated cyanobacterial mutation rates based on ancient DNA analyses of ice core samples collected from Kyrgyz Republic that dates back to ~12,500 cal years before present. We successfully sequenced the 16S rRNA and 16S-23S internal transcribed spacer (ITS) region. Two cyanobacterial operational taxonomic units (OTUs) were detected from the ancient ice core samples, and these OTUs are shared with those from the modern glacier surface. The mutation rate of ITS region was estimated by comparing ancient and modern populations, and were at the magnitude of 10substitutions/sites/year. By using a model selection framework, we also demonstrated that the ancient sequences from the ice sample were not contaminated from modern samples. Bayesian demographic analysis based on coalescent theory revealed that cyanobacterial population sizes increased over Asia regions during the Holocene. Thus, our results enhance our understanding of the enigmatic timescale of cyanobacterial microevolution, which has the potential to elucidate the environmental responses of cyanobacteria to the drastic climatic change events of the Quaternary.

Effects of Habitat Partitioning on the Distribution of Bacterioplankton in Deep Lakes

“…At evolutionary time scales, the 16S rRNA gene has intrinsic limitations when the aim is to look at fine scale genetic differentiation because its molecular evolutionary rate is very slow (Ochman et al, 1999; Bahl et al, 2011; Dvořák et al, 2012; Segawa et al, 2018). Nevertheless, substitution rates in the 16S rRNA genes are highly variable across bacterial species, strongly depending on the life strategies and habitats.…”

The past, present and future of ancient bacterial DNA

“…Genes coding for the resistance to beta-lactam, tetracycline and glycopeptide antibiotics were found, revealing ancient evidence of antimicrobial resistance. Segawa et al [164] collected ice core samples from the Kyrgyz Republic dated to 12 500 YBP to look at the mutation rates of cyanobacteria through comparison to modern samples. Looking at the internal transcribed spacer region of two cyanobacterial operational taxonomic units, Segawa et al found rates of 10 Mby −1 .…”

Evaluation of reported sediment samples from 20 Ma using a molecular phylogenetic approach: comment on Liu et al. (2017)

“…For example, genomic data have been reported for a straight-tusked elephant from 244,000 years ago, Homo heidelbergensis from over 300,000 years ago, and the Middle Pleistocene horse from 720,000 years ago (Orlando et al, 2013;Meyer et al, 2014Meyer et al, , 2017. Microbiological analyses have also been reported for ancient mortal remains (Tyrolean Iceman, plague patients and periodontal disease patients), sediments and ice cores (Willerslev et al, 2007;Warinner et al, 2014;Rasmussen et al, 2015;Seersholm et al, 2016;Lugli et al, 2017;Segawa et al, 2018).…”

“…Contamination can occur during field sampling or in the laboratory during DNA extraction or gene amplification steps (Tanner et al, 1998;Salter et al, 2014;Gorgé et al, 2015;Weyrich et al, 2019). Therefore, the authenticity of an ancient DNA sample must be verified using various methods, such as DNA damage pattern analysis (DNA fragmentation and nucleotide misincorporation patterns) and a phylogenetic approach (relative rate test and model selection) (Willerslev et al, 2007;Ginolhac et al, 2011;Segawa et al, 2018). For quantifying post-mortem DNA damage, shotgun sequencing reads have been widely used to verify sequences from ancient samples using bioinformatics software such as mapDamage that can test the presence of typical nucleotide misincorporation patterns that result from inflated cytosine deamination rates at overhang regions (Ginolhac et al, 2011;Orlando et al, 2013;Pedersen et al, 2016).…”