De novo mutations (DNMs) originating in gametogenesis are an important source of genetic variation. We use a data set of 7,216 autosomal DNMs with resolved parent of origin from whole-genome sequencing of 816 parent-offspring trios to investigate differences between maternally and paternally derived DNMs and study the underlying mutational mechanisms. Our results show that the number of DNMs in offspring increases not only with paternal age, but also with maternal age, and that some genome regions show enrichment for maternally derived DNMs. We identify parent-of-origin-specific mutation signatures that become more pronounced with increased parental age, pointing to different mutational mechanisms in spermatogenesis and oogenesis. Moreover, we find DNMs that are spatially clustered to have a unique mutational signature with no significant differences between parental alleles, suggesting a different mutational mechanism. Our findings provide insights into the molecular mechanisms that underlie mutagenesis and are relevant to disease and evolution in humans.

Germline mutations are the source of evolution and contribute substantially to many health-related processes. Here we use whole-genome deep sequencing data from 693 parents–offspring trios to examine the de novo point mutations (DNMs) in the offspring. Our estimate for the mutation rate per base pair per generation is 1.05 × 10−8, well within the range of previous studies. We show that maternal age has a small but significant correlation with the total number of DNMs in the offspring after controlling for paternal age (0.51 additional mutations per year, 95% CI: 0.29, 0.73), which was not detectable in the smaller and younger parental cohorts of earlier studies. Furthermore, while the total number of DNMs increases at a constant rate for paternal age, the contribution from the mother increases at an accelerated rate with age.These observations have implications related to the incidence of de novo mutations relating to maternal age.

Notch signaling determines and reinforces cell fate in bilaterally symmetric multicellular eukaryotes. Despite the involvement of Notch in many key developmental systems, human mutations in Notch signaling components have mainly been described in disorders with vascular and bone effects. Here, we report five heterozygous NOTCH1 variants in unrelated individuals with Adams-Oliver syndrome (AOS), a rare disease with major features of aplasia cutis of the scalp and terminal transverse limb defects. Using whole-genome sequencing in a cohort of 11 families lacking mutations in the four genes with known roles in AOS pathology (ARHGAP31, RBPJ, DOCK6, and EOGT), we found a heterozygous de novo 85 kb deletion spanning the NOTCH1 5' region and three coding variants (c.1285T>C [p.Cys429Arg], c.4487G>A [p.Cys1496Tyr], and c.5965G>A [p.Asp1989Asn]), two of which are de novo, in four unrelated probands. In a fifth family, we identified a heterozygous canonical splice-site variant (c.743-1 G>T) in an affected father and daughter. These variants were not present in 5,077 in-house control genomes or in public databases. In keeping with the prominent developmental role described for Notch1 in mouse vasculature, we observed cardiac and multiple vascular defects in four of the five families. We propose that the limb and scalp defects might also be due to a vasculopathy in NOTCH1-related AOS. Our results suggest that mutations in NOTCH1 are the most common cause of AOS and add to a growing list of human diseases that have a vascular and/or bony component and are caused by alterations in the Notch signaling pathway.

Purpose:To assess the potential of whole-genome sequencing (WGS) to replicate and augment results from conventional blood-based newborn screening (NBS). Methods:Research-generated WGS data from an ancestrally diverse cohort of 1,696 infants and both parents of each infant were analyzed for variants in 163 genes involved in disorders included or under discussion for inclusion in US NBS programs. WGS results were compared with results from state NBS and related follow-up testing.Results: NBS genes are generally well covered by WGS. There is a median of one (range: 0-6) database-annotated pathogenic variant in the NBS genes per infant. Results of WGS and NBS in detecting 28 state-screened disorders and four hemoglobin traits were concordant for 88.6% of true positives (n = 35) and 98.9% of true negatives (n = 45,757). Of the five infants affected with a state-screened disorder, WGS identified two whereas NBS detected four. WGS yielded fewer false positives than NBS (0.037 vs. 0.17%) but more results of uncertain significance (0.90 vs. 0.013%). Conclusion:WGS may help rule in and rule out NBS disorders, pinpoint molecular diagnoses, and detect conditions not amenable to current NBS assays.

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Preterm birth (PTB) complications are the leading cause of long-term morbidity and mortality in children. By using whole blood samples, we integrated whole-genome sequencing (WGS), RNA sequencing (RNA-seq), and DNA methylation data for 270 PTB and 521 control families. We analyzed this combined dataset to identify genomic variants associated with PTB and secondary analyses to identify variants associated with very early PTB (VEPTB) as well as other subcategories of disease that may contribute to PTB. We identified differentially expressed genes (DEGs) and methylated genomic loci and performed expression and methylation quantitative trait loci analyses to link genomic variants to these expression and methylation changes. We performed enrichment tests to identify overlaps between new and known PTB candidate gene systems. We identified 160 significant genomic variants associated with PTB-related phenotypes. The most significant variants, DEGs, and differentially methylated loci were associated with VEPTB. Integration of all data types identified a set of 72 candidate biomarker genes for VEPTB, encompassing genes and those previously associated with PTB. Notably, PTB-associated genes RAB31 and RBPJ were identified by all three data types (WGS, RNA-seq, and methylation). Pathways associated with VEPTB include EGFR and prolactin signaling pathways, inflammation- and immunity-related pathways, chemokine signaling, IFN-γ signaling, and Notch1 signaling. Progress in identifying molecular components of a complex disease is aided by integrated analyses of multiple molecular data types and clinical data. With these data, and by stratifying PTB by subphenotype, we have identified associations between VEPTB and the underlying biology.

Technological advances coupled with decreasing costs are bringing whole genome and whole exome sequencing closer to routine clinical use. One of the hurdles to clinical implementation is the high number of variants of unknown significance. For cancer-susceptibility genes, the difficulty in interpreting the clinical relevance of the genomic variants is compounded by the fact that most of what is known about these variants comes from the study of highly selected populations, such as cancer patients or individuals with a family history of cancer. The genetic variation in known cancer-susceptibility genes in the general population has not been well characterized to date. To address this gap, we profiled the nonsynonymous genomic variation in 158 genes causally implicated in carcinogenesis using high-quality whole genome sequences from an ancestrally diverse cohort of 681 healthy individuals. We found that all individuals carry multiple variants that may impact cancer susceptibility, with an average of 68 variants per individual. Of the 2,688 allelic variants identified within the cohort, most are very rare, with 75% found in only 1 or 2 individuals in our population. Allele frequencies vary between ancestral groups, and there are 21 variants for which the minor allele in one population is the major allele in another. Detailed analysis of a selected subset of 5 clinically important cancer genes, BRCA1, BRCA2, KRAS, TP53, and PTEN, highlights differences between germline variants and reported somatic mutations. The dataset can serve a resource of genetic variation in cancer-susceptibility genes in 6 ancestry groups, an important foundation for the interpretation of cancer risk from personal genome sequences.

Arginase is the final enzyme in the urea cycle. Its deficiency is the least frequently described disorder of this cycle. It results primarily in elevated blood arginine, and less frequently in either persistent or acute elevations in blood ammonia. This appears to be due to a second arginase locus, expressed primarily in the kidney, which can be recruited to compensate, in part, for the deficiency of liver arginase. The liver arginase gene structure permitted study of the molecular pathology of patients with the disorder and the results of these studies and the inferences about the protein structure are presented. The conserved regions among all arginases allowed the cloning of AII, the second arginase isoform. It has been localized to the mitochondrion and is thought to be involved in ornithine biosynthesis. It shares the major conserved protein sequences, and structural features of liver arginase gene are also conserved. When AI and AII from various species are compared, it appears that the two diverged some time prior to the evolution of amphibians. The evidence for the role of AII in nitric oxide and polyamine metabolism is presented and this appears consonant with the data on the tissue distribution.