Germline Mutation Rates Across Vertebrates

Interspecific variation in germline mutation rates across vertebrates

• Germline mutations are the main source of genomic innovation and inherited diseases.

• Germline mutation rates (GMRs) vary across taxa, from 10^-11 mutations per site per generation in unicellular eukaryotes to 10^-7 mutations per site per generation in multicellular eukaryotes.

• Several hypotheses have been proposed to explain variation in GMRs among lineages, including molecular mechanisms and external factors.

• Life-history traits such as generation time and metabolic rate have also been suggested to be associated with germline mutations.

• Accurate and standardized GMR estimation is necessary to test current hypotheses of GMR evolution.

• High-depth genome sequences were generated for 323 individuals representing 151 trios of 68 vertebrate species using consistent bioinformatics pipelines.

• Per-generation mutation rates vary by a factor of 40 across all species, with reptiles and birds having higher rates than mammals and fishes.

• Species with longer generation intervals have higher per-generation mutation rates.

• Mutations from C:G to T:A are the most common, with high mutation rates at CpG sites being a conserved feature across vertebrates.

• Mammals and birds show a male bias in GMRs, with primates having the largest male bias and rodents having the lowest.

• Reptiles and fishes have a relatively small male bias, with fishes having a greater proportion of mutations of maternal origin.

• Species with lower sex bias also exhibit a larger proportion of shared mutations between siblings.Genome-wide mutation rates and life-history traits in mammals and birds

• The study aimed to estimate genome-wide mutation rates (GMRs) and their relationship with life-history traits in mammals and birds.

• The dataset included 68 species with available reference genomes, representing 151 trios for which parentage had been genetically determined.

• The study found a significant difference in male-biased contribution to de novo mutations (DNMs) between mammals and birds, with mammals exhibiting higher male-biased mutations.

• The study also found a large interspecific variation in yearly mutation rates, ranging from 0.16 to 19.6 mutations per site per year, with the Texas banded gecko having the highest rate and the griffon vulture and snowy owl having the lowest rates.

• The study identified several life-history traits that were significantly associated with GMR variation, including generation time, maturation time, and the number of offspring per generation.

• The study also found a significant negative association between GMRs and effective population size, supporting the drift barrier hypothesis.

• The study used a model that incorporates mutational contribution at birth to estimate yearly mutation rates, which yielded similar results to the naive method of dividing the per-generation rate by parental age.

• The study found a significant positive correlation between mutation rates and long-term evolutionary substitution rates, especially in mammals.

• The study suggested that a higher number of primordial germ cell specification mutations in some vertebrate groups could be an alternative explanation for the lower male-biased contribution to DNMs.

• The study highlighted the importance of considering life-history traits and effective population size when studying GMRs and their evolutionary implications.

• The study used BGIseq libraries and whole-genome paired-end sequencing to obtain 60-80x raw sequence coverage per sample.

• The study filtered variant positions based on several parameters, including QualByDepth, FisherStrand, and RMSMappingQuality.Genome-wide de novo mutation rate and spectrum in vertebrates

• Researchers analyzed de novo mutations (DNMs) in 68 vertebrate species to estimate mutation rates and spectra.

• DNMs were identified using strict filters, including those for depth, genotype quality, allelic balance, and Mendelian inheritance.

• False-positive DNMs were removed by calling variants with bcftools and manually checking with IGV.

• The per-generation mutation rate was estimated by correcting for the false-negative rate and dividing the number of candidate DNMs by the callable genome.

• Yearly mutation rates were calculated by adjusting for the average age of parents at the time of reproduction and correcting for differences in generation time among species.

• The phylogenetic tree was built using ultraconserved elements and calibrated with previously published calibrations.

• The mutational spectrum was analyzed by grouping trios into higher taxonomic levels and determining the genomic context of mutations.

• Parental biases in the contribution of DNMs were identified by phasing mutations.

• The effect of parental age on mutation rate was quantified using linear regression.

• The effect of various life-history traits on mutation rate was tested using phylogenetic generalized least squares analysis.

• Effective population size was estimated using pairwise sequentially Markovian coalescent models.

• Nucleotide diversity was calculated using ANGSD and a sliding window approach.

Interspecific variation in germline mutation rates across vertebrates

• Germline mutations are the main source of genomic innovation and inherited diseases.

• Germline mutation rates (GMRs) vary across taxa, from 10^-11 mutations per site per generation in unicellular eukaryotes to 10^-7 mutations per site per generation in multicellular eukaryotes.

• Several hypotheses have been proposed to explain variation in GMRs among lineages, including molecular mechanisms and external factors.

• Life-history traits such as generation time and metabolic rate have also been suggested to be associated with germline mutations.

• Accurate and standardized GMR estimation is necessary to test current hypotheses of GMR evolution.

• High-depth genome sequences were generated for 323 individuals representing 151 trios of 68 vertebrate species using consistent bioinformatics pipelines.

• Per-generation mutation rates vary by a factor of 40 across all species, with reptiles and birds having higher rates than mammals and fishes.

• Species with longer generation intervals have higher per-generation mutation rates.

• Mutations from C:G to T:A are the most common, with high mutation rates at CpG sites being a conserved feature across vertebrates.

• Mammals and birds show a male bias in GMRs, with primates having the largest male bias and rodents having the lowest.

• Reptiles and fishes have a relatively small male bias, with fishes having a greater proportion of mutations of maternal origin.

• Species with lower sex bias also exhibit a larger proportion of shared mutations between siblings.Genome-wide mutation rates and life-history traits in mammals and birds

• The study aimed to estimate genome-wide mutation rates (GMRs) and their relationship with life-history traits in mammals and birds.

• The dataset included 68 species with available reference genomes, representing 151 trios for which parentage had been genetically determined.

• The study found a significant difference in male-biased contribution to de novo mutations (DNMs) between mammals and birds, with mammals exhibiting higher male-biased mutations.

• The study also found a large interspecific variation in yearly mutation rates, ranging from 0.16 to 19.6 mutations per site per year, with the Texas banded gecko having the highest rate and the griffon vulture and snowy owl having the lowest rates.

• The study identified several life-history traits that were significantly associated with GMR variation, including generation time, maturation time, and the number of offspring per generation.

• The study also found a significant negative association between GMRs and effective population size, supporting the drift barrier hypothesis.

• The study used a model that incorporates mutational contribution at birth to estimate yearly mutation rates, which yielded similar results to the naive method of dividing the per-generation rate by parental age.

• The study found a significant positive correlation between mutation rates and long-term evolutionary substitution rates, especially in mammals.

• The study suggested that a higher number of primordial germ cell specification mutations in some vertebrate groups could be an alternative explanation for the lower male-biased contribution to DNMs.

• The study highlighted the importance of considering life-history traits and effective population size when studying GMRs and their evolutionary implications.

• The study used BGIseq libraries and whole-genome paired-end sequencing to obtain 60-80x raw sequence coverage per sample.

• The study filtered variant positions based on several parameters, including QualByDepth, FisherStrand, and RMSMappingQuality.Genome-wide de novo mutation rate and spectrum in vertebrates

• Researchers analyzed de novo mutations (DNMs) in 68 vertebrate species to estimate mutation rates and spectra.

• DNMs were identified using strict filters, including those for depth, genotype quality, allelic balance, and Mendelian inheritance.

• False-positive DNMs were removed by calling variants with bcftools and manually checking with IGV.

• The per-generation mutation rate was estimated by correcting for the false-negative rate and dividing the number of candidate DNMs by the callable genome.

• Yearly mutation rates were calculated by adjusting for the average age of parents at the time of reproduction and correcting for differences in generation time among species.

• The phylogenetic tree was built using ultraconserved elements and calibrated with previously published calibrations.

• The mutational spectrum was analyzed by grouping trios into higher taxonomic levels and determining the genomic context of mutations.

• Parental biases in the contribution of DNMs were identified by phasing mutations.

• The effect of parental age on mutation rate was quantified using linear regression.

• The effect of various life-history traits on mutation rate was tested using phylogenetic generalized least squares analysis.

• Effective population size was estimated using pairwise sequentially Markovian coalescent models.

• Nucleotide diversity was calculated using ANGSD and a sliding window approach.