Rate of de novo mutations and the importance of father’s age to disease risk

Abstract

Mutations generate sequence diversity and provide a substrate for selection. The rate of de novo mutations is therefore of major importance to evolution. We conducted a study of genomewide mutation rate by sequencing the entire genomes of 78 Icelandic parent-offspring trios at high coverage. Here we show that in our samples, with an average father’s age of 29.7, the average de novo mutation rate is 1.20×10−8 per nucleotide per generation. Most strikingly, the diversity in mutation rate of single-nucleotide polymorphism (SNP) is dominated by the age of the father at conception of the child. The effect is an increase of about 2 mutations per year. After accounting for random Poisson variation, father’s age is estimated to explain nearly all of the remaining variation in the de novo mutation counts. These observations shed light on the importance of the father’s age on the risk of diseases such as schizophrenia and autism.

The ‘extremely ancient’ chromosome that isn’t: a forensic bioinformatic investigation of Albert Perry’s X-degenerate portion of the Y chromosome

“…20 In humans, the relevance of male mutation bias is particularly manifested in older fathers, whose offspring harbor more autosomal mutations than the offspring of younger fathers. 15,34 However, it is not clear whether the huge variation in paternal age at conception assumed by Mendez et al 2 is a reasonable assumption in modern human populations, let alone in ancient ones. For instance, even among developed nations, where age at conception is delayed, generation times ranges from 20 to 30 years 35 and stands at B25 in the US.…”

“…4,13,14 Instead, they derived a substitution rate for the Y chromosome (6.12 Â 10 À10 ) using autosomal mutation rates reported from an Icelandic data set of parent-offspring trios in which one child is either autistic or schizophrenic. 15 Interestingly, the authors even acknowledge that the TMRCA would have been much shorter had they used the Y-specific mutation rate in the literature. For example, Xue et al 13 sequenced approximately 10.15 Mb from two Y chromosomes of two European individuals separated by 13 generations and inferred a substitution rate of 1 Â 10 À9 substitutions per nucleotide per year, under the assumption that the generation time is 30 years.…”

“…For these analyses, Mendez et al 2 presumed that long-term substitution rates are equal to singlegeneration mutation rates as determined by Kong et al, 15 and assumed a complete lack of purifying or advantageous selection on the Y chromosome. Is this a reasonable assumption?…”

World’s whaling slaughter tallied

“…Sperm are produced throughout a man's life, whereas women are born with a full array of eggs. The constant division of sperm precursor cells means that men tend to pass on more new mutations to their offspring than women -four times as many, according to a 2012 estimate 4 -and older fathers transmit more mutations than young ones. This means that changes in the biology of sperm production or paternal age over evolutionary time could influence mutation rate.…”

Phelan‐McDermid syndrome data network: Integrating patient reported outcomes with clinical notes and curated genetic reports

“…Research investigations using Genome Wide Association Study (GWAS) (Network and Pathway Analysis Subgroup of the Psychiatric Genomics Consortium, 2015; Wood, 2013), exome‐based sequencing (Girard et al, 2011; Iossifov et al, 2012; O'Roak et al, 2011; Vissers et al, 2010; Xu et al, 2012), and whole genome sequencing (Kong et al, 2012) techniques have revealed several candidate genes that are associated with common neuropsychiatric disorders such as Autism Spectrum Disorder (ASD), intellectual disability, and schizophrenia. However, in the case of rare disorders, understanding the genetic origins and progressions of disorders—one of the key objectives of Precision Medicine research (Collins & Varmus, 2015; Kohane, 2015; Kohane, Churchill, & Murphy, 2012)—is hindered by small patient population size, the consequent paucity of patient data, and the lack of robust phenotyping protocols (Baynam et al, 2015; Delude, 2015; Robinson, Mungall, & Haendel, 2015).…”