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Genetic recombination is an essential process in generating genetic diversity. Recombination occurs both through the shuffling of maternal and paternal chromosomes and through mutations generated by resolution of the physical breaks necessary for this process. Halldorsson et al. sequenced the full genomes of parents and offspring to create a map of human recombination and estimate the relationship with de novo mutations. Interestingly, transcribed regions of the genome were less likely to have crossovers, suggesting that there may be selection to reduce changes in genetic sequences via recombination or mutation in these regions. Science , this issue p. eaau1043 A high-resolution human genetic map from whole genomes identifies patterns of recombination and de novo mutation. Genetic diversity arises from recombination and de novo mutation (DNM). Using a combination of microarray genotype and whole-genome sequence data on parent-child pairs, we identified 4,531,535 crossover recombinations and 200,435 DNMs. The resulting genetic map has a resolution of 682 base pairs. Crossovers exhibit a mutagenic effect, with overrepresentation of DNMs within 1 kilobase of crossovers in males and females. In females, a higher mutation rate is observed up to 40 kilobases from crossovers, particularly for complex crossovers, which increase with maternal age. We identified 35 loci associated with the recombination rate or the location of crossovers, demonstrating extensive genetic control of meiotic recombination, and our results highlight genes linked to the formation of the synaptonemal complex as determinants of crossovers.

Genetic variants in parents may affect the fitness of their offspring, even if the child does not carry the allele. This indirect effect is referred to as “genetic nurture.” Kong et al. used data from genome-wide association studies of educational attainment to construct polygenic scores for parents that only considered the nontransmitted alleles (see the Perspective by Koellinger and Harden). The findings suggest that genetic nurture is ultimately due to genetic variation in the population and is mediated by the environment that parents create for their children. Science , this issue p. 424 ; see also p. 386 Behavioral genetics can transmit an environmental effect from parents and other related caregivers to their children. Sequence variants in the parental genomes that are not transmitted to a child (the proband) are often ignored in genetic studies. Here we show that nontransmitted alleles can affect a child through their impacts on the parents and other relatives, a phenomenon we call “genetic nurture.” Using results from a meta-analysis of educational attainment, we find that the polygenic score computed for the nontransmitted alleles of 21,637 probands with at least one parent genotyped has an estimated effect on the educational attainment of the proband that is 29.9% ( P = 1.6 × 10 −14 ) of that of the transmitted polygenic score. Genetic nurturing effects of this polygenic score extend to other traits. Paternal and maternal polygenic scores have similar effects on educational attainment, but mothers contribute more than fathers to nutrition- and heath-related traits.

Large, rare chromosomal deletions and duplications known as copy number variants (CNVs) have been implicated in neurodevelopmental disorders similar to attention-deficit hyperactivity disorder (ADHD). We aimed to establish whether burden of CNVs was increased in ADHD, and to investigate whether identified CNVs were enriched for loci previously identified in autism and schizophrenia. We undertook a genome-wide analysis of CNVs in 410 children with ADHD and 1156 unrelated ethnically matched controls from the 1958 British Birth Cohort. Children of white UK origin, aged 5–17 years, who met diagnostic criteria for ADHD or hyperkinetic disorder, but not schizophrenia and autism, were recruited from community child psychiatry and paediatric outpatient clinics. Single nucleotide polymorphisms (SNPs) were genotyped in the ADHD and control groups with two arrays; CNV analysis was limited to SNPs common to both arrays and included only samples with high-quality data. CNVs in the ADHD group were validated with comparative genomic hybridisation. We assessed the genome-wide burden of large (>500 kb), rare (<1% population frequency) CNVs according to the average number of CNVs per sample, with significance assessed via permutation. Locus-specific tests of association were undertaken for test regions defined for all identified CNVs and for 20 loci implicated in autism or schizophrenia. Findings were replicated in 825 Icelandic patients with ADHD and 35 243 Icelandic controls. Data for full analyses were available for 366 children with ADHD and 1047 controls. 57 large, rare CNVs were identified in children with ADHD and 78 in controls, showing a significantly increased rate of CNVs in ADHD (0·156 vs 0·075; p=8·9×10 −5). This increased rate of CNVs was particularly high in those with intellectual disability (0·424; p=2·0×10 −6), although there was also a significant excess in cases with no such disability (0·125, p=0·0077). An excess of chromosome 16p13.11 duplications was noted in the ADHD group (p=0·0008 after correction for multiple testing), a finding that was replicated in the Icelandic sample (p=0·031). CNVs identified in our ADHD cohort were significantly enriched for loci previously reported in both autism (p=0·0095) and schizophrenia (p=0·010). Our findings provide genetic evidence of an increased rate of large CNVs in individuals with ADHD and suggest that ADHD is not purely a social construct. Action Research; Baily Thomas Charitable Trust; Wellcome Trust; UK Medical Research Council; European Union.

Background Long-read sequencing can enable the detection of base modifications, such as CpG methylation, in single molecules of DNA. The most commonly used methods for long-read sequencing are nanopore developed by Oxford Nanopore Technologies (ONT) and single molecule real-time (SMRT) sequencing developed by Pacific Bioscience (PacBio). In this study, we systematically compare the performance of CpG methylation detection from long-read sequencing. Results We demonstrate that CpG methylation detection from 7179 nanopore-sequenced DNA samples is highly accurate and consistent with 132 oxidative bisulfite-sequenced (oxBS) samples, isolated from the same blood draws. We introduce quality filters for CpGs that further enhance the accuracy of CpG methylation detection from nanopore-sequenced DNA, while removing at most 30% of CpGs. We evaluate the per-site performance of CpG methylation detection across different genomic features and CpG methylation rates and demonstrate how the latest R10.4 flowcell chemistry and base-calling algorithms improve methylation detection from nanopore sequencing. Additionally, we show how the methylation detection of 50 SMRT-sequenced genomes compares to nanopore sequencing and oxBS. Conclusions This study provides the first systematic comparison of CpG methylation detection tools for long-read sequencing methods. We compare two commonly used computational methods for the detection of CpG methylation in a large number of nanopore genomes, including samples sequenced using the latest R10.4 nanopore flowcell chemistry and 50 SMRT sequenced samples. We provide insights into the strengths and limitations of each sequencing method as well as recommendations for standardization and evaluation of tools designed for genome-scale modified base detection using long-read sequencing.

Asthma is one of the most common chronic diseases affecting both children and adults. We report a genome-wide association meta-analysis of 69,189 cases and 702,199 controls from Iceland and UK biobank. We find 88 asthma risk variants at 56 loci, 19 previously unreported, and evaluate their effect on other asthma and allergic phenotypes. Of special interest are two low frequency variants associated with protection against asthma; a missense variant in TNFRSF8 and 3‘ UTR variant in TGFBR1 . Functional studies show that the TNFRSF8 variant reduces TNFRSF8 expression both on cell surface and in soluble form, acting as loss of function. eQTL analysis suggests that the TGFBR1 variant acts through gain of function and together with an intronic variant in a downstream gene, SMAD3 , points to defective TGFβR1 signaling as one of the biological perturbations increasing asthma risk. Our results increase the number of asthma variants and implicate genes with known role in T cell regulation, inflammation and airway remodeling in asthma pathogenesis. Asthma is a common allergic airway disease with significant inter-individual heterogeneity. Here, Olafsdottir et al. report a genome-wide meta-analysis of two large population-based cohorts to identify sequence variants that associate with asthma risk and perform follow-up functional analyses on a protective loss-of-function variant in TNFRSF8 .

Analysis of sequence diversity in the human genome is fundamental for genetic studies. Structural variants (SVs) are frequently omitted in sequence analysis studies, although each has a relatively large impact on the genome. Here, we present GraphTyper2, which uses pangenome graphs to genotype SVs and small variants using short-reads. Comparison to the syndip benchmark dataset shows that our SV genotyping is sensitive and variant segregation in families demonstrates the accuracy of our approach. We demonstrate that incorporating public assembly data into our pipeline greatly improves sensitivity, particularly for large insertions. We validate 6,812 SVs on average per genome using long-read data of 41 Icelanders. We show that GraphTyper2 can simultaneously genotype tens of thousands of whole-genomes by characterizing 60 million small variants and half a million SVs in 49,962 Icelanders, including 80 thousand SVs with high-confidence. Structural variants may be omitted in sequence analysis despite their importance in genome variation and phenotypic impact. Here the authors present GraphTyper2, which uses pangenome graphs to genotype structural variants using short-reads and can be applied in large-scale sequencing studies.

Variable number tandem repeats (VNTRs) account for significant genetic variation in many organisms. In humans, VNTRs have been implicated in both Mendelian and complex disorders, but are largely ignored by genomic pipelines due to the complexity of genotyping and the computational expense. We describe adVNTR-NN, a method that uses shallow neural networks to genotype a VNTR in 18 seconds on 55X whole genome data, while maintaining high accuracy. We use adVNTR-NN to genotype 10,264 VNTRs in 652 GTEx individuals. Associating VNTR length with gene expression in 46 tissues, we identify 163 “eVNTRs”. Of the 22 eVNTRs in blood where independent data is available, 21 (95%) are replicated in terms of significance and direction of association. 49% of the eVNTR loci show a strong and likely causal impact on the expression of genes and 80% have maximum effect size at least 0.3. The impacted genes are involved in diseases including Alzheimer’s, obesity and familial cancers, highlighting the importance of VNTRs for understanding the genetic basis of complex diseases. Variable number tandem repeats (VNTRs) are implicated in human diseases yet have been difficult to analyse computationally. Here, the authors describe a neural network method, adVNTR-NN, that allows rapid and accurate genotyping of VNTRs from large whole genome sequencing datasets.

Preeclampsia is a serious complication of pregnancy, affecting both maternal and fetal health. In genome-wide association meta-analysis of European and Central Asian mothers, we identify sequence variants that associate with preeclampsia in the maternal genome at ZNF831 /20q13 and FTO /16q12. These are previously established variants for blood pressure (BP) and the FTO variant has also been associated with body mass index (BMI). Further analysis of BP variants establishes that variants at MECOM /3q26, FGF5 /4q21 and SH2B3 /12q24 also associate with preeclampsia through the maternal genome. We further show that a polygenic risk score for hypertension associates with preeclampsia. However, comparison with gestational hypertension indicates that additional factors modify the risk of preeclampsia. Studies to identify maternal variants associated with preeclampsia have been limited by sample size. Here, the authors meta-analyze eight GWAS of 9,515 preeclamptic women, identifying five variants associated with preeclampsia and showing that genetic predisposition to hypertension is a major risk factor for preeclampsia.

Nonalcoholic fatty liver (NAFL) and its sequelae are growing health problems. We performed a genome-wide association study of NAFL, cirrhosis and hepatocellular carcinoma, and integrated the findings with expression and proteomic data. For NAFL, we utilized 9,491 clinical cases and proton density fat fraction extracted from 36,116 liver magnetic resonance images. We identified 18 sequence variants associated with NAFL and 4 with cirrhosis, and found rare, protective, predicted loss-of-function variants in MTARC1 and GPAM , underscoring them as potential drug targets. We leveraged messenger RNA expression, splicing and predicted coding effects to identify 16 putative causal genes, of which many are implicated in lipid metabolism. We analyzed levels of 4,907 plasma proteins in 35,559 Icelanders and 1,459 proteins in 47,151 UK Biobank participants, identifying multiple proteins involved in disease pathogenesis. We show that proteomics can discriminate between NAFL and cirrhosis. The present study provides insights into the development of noninvasive evaluation of NAFL and new therapeutic options. Genome-wide analyses identify loci associated with nonalcoholic fatty liver disease, including rare, protective loss-of-function variants in MTARC1 and GPAM . Plasma proteomic analyses provide insight into proteins involved in disease pathogenesis.

A coding mutation in APP , the gene that encodes the amyloid-β precursor protein, is found to protect against Alzheimer’s disease and cognitive decline in the elderly without Alzheimer’s disease. 'Natural' protection against Alzheimer's disease Alzheimer's disease is characterized by the existence in the brain of amyloid plaques, which form as a consequence of proteolic cleavage of amyloid precursor protein (APP). By screening almost 2,000 genomes, Kari Stefansson and colleagues find a coding mutation in the APP gene that protects against Alzheimer's disease and cognitive decline in elderly people who lack symptoms of Alzheimer's disease. The mutation causes an approximately 40% reduction in the formation of amyloidogenic peptides in vitro . The strong protective effect of this mutation, which lies next to the aspartyl protease beta-site in APP, provides support for the hypothesis that reducing the beta-cleavage of APP may protect against Alzheimer's. The results also raise the possibility that Alzheimer's disease and cognitive decline in the elderly are mechanistically related. The prevalence of dementia in the Western world in people over the age of 60 has been estimated to be greater than 5%, about two-thirds of which are due to Alzheimer’s disease 1 , 2 , 3 , 4 . The age-specific prevalence of Alzheimer’s disease nearly doubles every 5 years after age 65, leading to a prevalence of greater than 25% in those over the age of 90 (ref. 3 ). Here, to search for low-frequency variants in the amyloid-β precursor protein ( APP ) gene with a significant effect on the risk of Alzheimer’s disease, we studied coding variants in APP in a set of whole-genome sequence data from 1,795 Icelanders. We found a coding mutation (A673T) in the APP gene that protects against Alzheimer’s disease and cognitive decline in the elderly without Alzheimer’s disease. This substitution is adjacent to the aspartyl protease β-site in APP, and results in an approximately 40% reduction in the formation of amyloidogenic peptides in vitro . The strong protective effect of the A673T substitution against Alzheimer’s disease provides proof of principle for the hypothesis that reducing the β-cleavage of APP may protect against the disease. Furthermore, as the A673T allele also protects against cognitive decline in the elderly without Alzheimer’s disease, the two may be mediated through the same or similar mechanisms.