Pedigree-based and phylogenetic methods support surprising patterns of mutation rate and spectrum in the gray mouse lemur

Abstract

Mutations are the raw material on which evolution acts, and knowledge of their frequency and genomic distribution is crucial for understanding how evolution operates at both long and short timescales. At present, the rate and spectrum of de novo mutations have been directly characterized in relatively few lineages. Our study provides the first direct mutation rate estimate for a strepsirrhine (i.e., the lemurs and lorises), which comprise nearly half of the primate clade. Using high-coverage linkedread sequencing for a focal quartet of gray mouse lemurs (Microcebus murinus), we estimated the mutation rate to be 1.52 × 10 -8 (95% credible interval: 1.28 × 10 −8 to 1.78 × 10 −8 ) mutations/site/generation, a rate among the highest calculated for a mammal.Further, we found an unexpectedly low count of paternal mutations, and only a modest overrepresentation of mutations at CpG-sites. Despite the surprising nature of these results, we found both the rate and spectrum to be robust to the manipulation of a wide range of computational filtering criteria. We also sequenced a technical replicate to estimate a false negative and false positive rate for our data and show that any point estimate of a de novo mutation rate should be considered with a large degree of uncertainty. To validate these observations, we conducted an independent analysis of context-dependent substitution types for gray mouse lemur and five additional primate species for which de novo mutation rates have also been estimated. These comparisons revealed general consistency of the mutation spectrum between the pedigree-based and the substitution rate analyses for all species compared.

Past environmental changes affected lemur population dynamics prior to human impact in Madagascar

“…S15), and a mutation rate of 1.2 × 10 −8 11 , 82 , 83 . This mutation rate is the most accurate estimate available for mouse lemurs and was calculated from average pedigree-based estimates of seven primate species, including that of one mouse lemur species 83 , 84 . To evaluate the impact of the relatively low genome-wide coverage in our PSMC inferences, we also ran simulations for variant coverage divergence based on minimum read depth option per site (-d) between 1 and 9 for both study sites.…”

The Mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates

“…1.52 2 ♂: 4.55 and ♀: 1.45 (Campbell et al, 2021) Mouse (Mus musculus) 0.57 0.39 8 15 unspecified ~ 0.47 (Milholland et al, 2017) (Lindsay et al, 2019) Cattle (Bos taurus) 1.17 5 unspecified (Harland et al, 2017) Wolf (Canis lupus) 0.45 4 ♂: 4.00 and ♀: 2.25 (Koch et al, (Malinsky et al, 2018) The key principle of the pedigree-based approach is to detect de novo mutations (DNMs)…”

Mutationathon: towards standardization in estimates of pedigree-based germline mutation rates

“…Different algorithms have been shown to perform similarly well in calling nucleotide variants (Li, 2014). GATK (Auwera and O’Connor, 2020) is widely used among studies that call germline DNMs (Bergeron et al, 2021; Besenbacher et al, 2019; Campbell et al, 2021; Feng et al, 2017; Harland et al, 2017; Jónsson et al, 2017; Koch et al, 2019; Malinsky et al, 2018; Maretty et al, 2017; Milholland et al, 2017; Pfeifer, 2017; Sasani et al, 2019; Smeds et al, 2016; Tatsumoto et al, 2017; Thomas et al, 2018; Turner et al, 2017; Wang et al, 2021b, 2020; Wong et al, 2016; Wu et al, 2020). Other commonly used variant callers are GraphTyper (Eggertsson et al, 2017; e.g., utilized by Beyter et al, 2021; Halldorsson et al, 2019; Jónsson et al, 2021, 2018) and FreeBayes (Garrison and Marth, 2012; e.g., utilized by Turner et al, 2017).…”

“…However, it remains unclear if alternative library preparation and sequencing platforms introduce additional biases compared to standard Illumina protocols. Most pedigree-based studies of germline mutations have sequenced each individual to a depth between 30X and 50X (Besenbacher et al, 2019; Campbell et al, 2021; Jónsson et al, 2017; Kessler et al, 2020; Malinsky et al, 2018; Milholland et al, 2017; Sasani et al, 2019; Smeds et al, 2016; Thomas et al, 2018; Turner et al, 2017; Wang et al, 2020; Wu et al, 2020), three studies sequenced at a higher depth of ∼ 80X (Bergeron et al, 2021; Maretty et al, 2017) and 150X (Tatsumoto et al, 2017), while six studies sequenced at a depth lower than 25X on average (Harland et al, 2017; Koch et al, 2019; Lindsay et al, 2019; Martin et al, 2018; Pfeifer, 2017; Rahbari et al, 2016). A minimum coverage of 15X has been advised to call single nucleotide polymorphisms (SNPs) accurately (Fumagalli et al, 2013).…”

“…1.52 2 ♂: 4.55 and ♀: 1.45 (Campbell et al, 2021) Mouse (Mus musculus) 0.57 0.39 8 15 unspecified ~ 0.47 (Milholland et al, 2017) (Lindsay et al, 2019) Cattle (Bos taurus) 1.17 5 unspecified (Harland et al, 2017) Wolf (Canis lupus) 0.45 4 ♂: 4.00 and ♀: 2.25 (Koch et al, 2019) Domestic cat (Felis catus) 0.86 11 ♂: 4.70 and ♀: 2.90 (Wang et al, 2021b) Platypus (Ornithorhynchus anatinus) 0.70 2 unspecified (Martin et al, 2018) Collared flycatcher (Ficedula albicollis) 0.46 7 unspecified (Smeds et al, 2016) Herring (Clupea harengus) 0.20 12 unspecified (Feng et al, 2017) Cichlid (Astatotilapia calliptera, Aulonocara stuartgranti and Lethrino ps lethrinus) 0.35 9 unspecified (Malinsky et al, 2018) (and accounting for the diploid length of the genome, as mutations can be transmitted by both the mother and father). As mutations are rare events, detecting all the true DNMs (or having a high sensitivity) while avoiding errors (or increasing precision) from a single generation remains challenging.…”