Infertility is a prevalent health issue, affecting ∼15% of couples of childbearing age. Nearly one-half of idiopathic infertility cases are thought to have a genetic basis, but the underlying causes are largely unknown. Traditional methods for studying inheritance, such as genome-wide association studies and linkage analyses, have been confounded by the genetic and phenotypic complexity of reproductive processes. Here we describe an association- and linkage-free approach to identify segregating infertility alleles, in which CRISPR/Cas9 genome editing is used to model putatively deleterious nonsynonymous SNPs (nsSNPs) in the mouse orthologs of fertility genes. Mice bearing "humanized" alleles of four essential meiosis genes, each predicted to be deleterious by most of the commonly used algorithms for analyzing functional SNP consequences, were examined for fertility and reproductive defects. Only a Cdk2 allele mimicking SNP rs3087335, which alters an inhibitory WEE1 protein kinase phosphorylation site, caused infertility and revealed a novel function in regulating spermatogonial stem cell maintenance. Our data indicate that segregating infertility alleles exist in human populations. Furthermore, whereas computational prediction of SNP effects is useful for identifying candidate causal mutations for diverse diseases, this study underscores the need for in vivo functional evaluation of physiological consequences. This approach can revolutionize personalized reproductive genetics by establishing a permanent reference of benign vs. infertile alleles.
Keywords: CRISPR/Cas9; cyclin; genome editing; meiosis; spermatogenesis.