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Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)4 have become integral in the interpretation of single-nucleotide variants (SNVs)5. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25-29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage6. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings7. This SV resource is freely distributed via the gnomAD browser8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

Soft robots possess many attributes that are difficult, if not impossible, to achieve with conventional robots composed of rigid materials. Yet, despite recent advances, soft robots must still be tethered to hard robotic control systems and power sources. New strategies for creating completely soft robots, including soft analogues of these crucial components, are needed to realize their full potential. Here we report the untethered operation of a robot composed solely of soft materials. The robot is controlled with microfluidic logic that autonomously regulates fluid flow and, hence, catalytic decomposition of an on-board monopropellant fuel supply. Gas generated from the fuel decomposition inflates fluidic networks downstream of the reaction sites, resulting in actuation. The body and microfluidic logic of the robot are fabricated using moulding and soft lithography, respectively, and the pneumatic actuator networks, on-board fuel reservoirs and catalytic reaction chambers needed for movement are patterned within the body via a multi-material, embedded 3D printing technique. The fluidic and elastomeric architectures required for function span several orders of magnitude from the microscale to the macroscale. Our integrated design and rapid fabrication approach enables the programmable assembly of multiple materials within this architecture, laying the foundation for completely soft, autonomous robots.

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes.sup.1. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases. A catalogue of predicted loss-of-function variants in 125,748 whole-exome and 15,708 whole-genome sequencing datasets from the Genome Aggregation Database (gnomAD) reveals the spectrum of mutational constraints that affect these human protein-coding genes., Author(s): Konrad J. Karczewski [sup.1] [sup.2] , Laurent C. Francioli [sup.1] [sup.2] , Grace Tiao [sup.1] [sup.2] , Beryl B. Cummings [sup.1] [sup.2] [sup.3] , Jessica Alföldi [sup.1] [sup.2] , [...]

The depletion of disruptive variation caused by purifying natural selection (constraint) has been widely used to investigate protein-coding genes underlying human disorders1–4, but attempts to assess constraint for non-protein-coding regions have proved more difficult. Here we aggregate, process and release a dataset of 76,156 human genomes from the Genome Aggregation Database (gnomAD)—the largest public open-access human genome allele frequency reference dataset—and use it to build a genomic constraint map for the whole genome (genomic non-coding constraint of haploinsufficient variation (Gnocchi)). We present a refined mutational model that incorporates local sequence context and regional genomic features to detect depletions of variation. As expected, the average constraint for protein-coding sequences is stronger than that for non-coding regions. Within the non-coding genome, constrained regions are enriched for known regulatory elements and variants that are implicated in complex human diseases and traits, facilitating the triangulation of biological annotation, disease association and natural selection to non-coding DNA analysis. More constrained regulatory elements tend to regulate more constrained protein-coding genes, which in turn suggests that non-coding constraint can aid the identification of constrained genes that are as yet unrecognized by current gene constraint metrics. We demonstrate that this genome-wide constraint map improves the identification and interpretation of functional human genetic variation.A genomic constraint map for the human genome constructed using data from 76,156 human genomes from the Genome Aggregation Database shows that non-coding constrained regions are enriched for regulatory elements and variants associated with complex diseases and traits. [ABSTRACT FROM AUTHOR]

Light- and ink-based three-dimensional (3D) printing methods allow the rapid design and fabrication of materials without the need for expensive tooling, dies or lithographic masks. They have led to an era of manufacturing in which computers can control the fabrication of soft matter that has tunable mechanical, electrical and other functional properties. The expanding range of printable materials, coupled with the ability to programmably control their composition and architecture across various length scales, is driving innovation in myriad applications. This is illustrated by examples of biologically inspired composites, shape-morphing systems, soft sensors and robotics that only additive manufacturing can produce., Author(s): Ryan L. Truby [1, 2]; Jennifer A. Lewis (corresponding author) [1, 2] Additive manufacturing, which encompasses a broad range of light- and ink-based printing techniques that allow the digital [...]

Autism is a multifactorial neurodevelopmental disorder affecting more males than females; consequently, under a multifactorial genetic hypothesis, females are affected only when they cross a higher biological threshold. We hypothesize that deleterious variants at conserved residues are enriched in severely affected patients arising from female-enriched multiplex families with severe disease, enhancing the detection of key autism genes in modest numbers of cases. Here we show the use of this strategy by identifying missense and dosage sequence variants in the gene encoding the adhesive junction-associated δ-catenin protein (CTNND2) in female-enriched multiplex families and demonstrating their loss-of-function effect by functional analyses in zebrafish embryos and cultured hippocampal neurons from wild-type and Ctnnd2 null mouse embryos. Finally, through gene expression and network analyses, we highlight a critical role for CTNND2 in neuronal development and an intimate connection to chromatin biology. Our data contribute to the understanding of the genetic architecture of autism and suggest that genetic analyses of phenotypic extremes, such as female-enriched multiplex families, are of innate value in multifactorial disorders., Autism is a common neurodevelopmental disorder with a profound sex-bias: four times more males than females are affected (1) whereas disease recurrence risk to siblings of autistic females is larger [...]

A Correction to this paper has been published: https://doi.org/10.1038/s41586-020-03174-8., Author(s): Konrad J. Karczewski [sup.1] [sup.2] , Laurent C. Francioli [sup.1] [sup.2] , Grace Tiao [sup.1] [sup.2] , Beryl B. Cummings [sup.1] [sup.2] [sup.3] , Jessica Alföldi [sup.1] [sup.2] , [...]

A Correction to this paper has been published: https://doi.org/10.1038/s41586-020-03176-6., Author(s): Ryan L. Collins [sup.1] [sup.2] [sup.3] , Harrison Brand [sup.1] [sup.2] [sup.4] , Konrad J. Karczewski [sup.1] [sup.5] , Xuefang Zhao [sup.1] [sup.2] [sup.4] , Jessica Alföldi [sup.1] [sup.5] [...]

Author(s): Ryan L. Sriver [1]; Matthew Huber (corresponding author) [1, 2] Ocean mixing affects global climate and the marine biosphere because it is linked to the ocean's ability to store [...]

Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which loss-of-function variants are not tolerated, can be highly successful as targets of inhibitory drugs. Second, in most genes, loss-of-function variants are sufficiently rare that genotype-based ascertainment of homozygous or compound heterozygous 'knockout' humans will await sample sizes that are approximately 1,000 times those presently available, unless recruitment focuses on consanguineous individuals. Third, automated variant annotation and filtering are powerful, but manual curation remains crucial for removing artefacts, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human knockout studies and should guide the interpretation of loss-of-function variants in drug development. Analysis of predicted loss-of-function variants from 125,748 human exomes and 15,708 whole genomes in the Genome Aggregation Database (gnomAD) provides a roadmap for human 'knockout' studies and a guide for future research into disease biology and drug-target selection. [ABSTRACT FROM AUTHOR]

The acceleration of DNA sequencing in samples from patients and population studies has resulted in extensive catalogues of human genetic variation, but the interpretation of rare genetic variants remains problematic. A notable example of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy individuals. Here, by manual curation of putative loss-of-function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD)1, we show that one explanation for this paradox involves alternative splicing of mRNA, which allows exons of a gene to be expressed at varying levels across different cell types. Currently, no existing annotation tool systematically incorporates information about exon expression into the interpretation of variants. We develop a transcript-level annotation metric known as the 'proportion expressed across transcripts', which quantifies isoform expression for variants. We calculate this metric using 11,706 tissue samples from the Genotype Tissue Expression (GTEx) project2 and show that it can differentiate between weakly and highly evolutionarily conserved exons, a proxy for functional importance. We demonstrate that expression-based annotation selectively filters 22.8% of falsely annotated pLoF variants found in haploinsufficient disease genes in gnomAD, while removing less than 4% of high-confidence pathogenic variants in the same genes. Finally, we apply our expression filter to the analysis of de novo variants in patients with autism spectrum disorder and intellectual disability or developmental disorders to show that pLoF variants in weakly expressed regions have similar effect sizes to those of synonymous variants, whereas pLoF variants in highly expressed exons are most strongly enriched among cases. Our annotation is fast, flexible and generalizable, making it possible for any variant file to be annotated with any isoform expression dataset, and will be valuable for the genetic diagnosis of rare diseases, the analysis of rare variant burden in complex disorders, and the curation and prioritization of variants in recall-by-genotype studies. A novel variant annotation metric that quantifies the level of expression of genetic variants across tissues is validated in the Genome Aggregation Database (gnomAD) and is shown to improve rare variant interpretation. [ABSTRACT FROM AUTHOR]

A tropical cyclone is a rare occurrence. It requires a delicate combination of environmental conditions, including a particular amount of heat in the upper ocean, a certain distribution of moisture [...]

A Correction to this paper has been published: https://doi.org/10.1038/s41586-020-03177-5 [ABSTRACT FROM AUTHOR]

A Correction to this paper has been published: https://doi.org/10.1038/s41586-020-03175-7 [ABSTRACT FROM AUTHOR]

The article discusses a research study on relationship of anthropogenic air pollution with the destructiveness of cyclone in Arabian Sea. A. T. Evans and his co-researchers show the increase in the average Arabian cyclone intensity within the past 30 years which suggests that human activity may play a direct part in modulating cyclone activity. The result also concludes that climatic changes could influence the variability of tropical cyclone activity in the area.

The author discusses an article by A. V. Fedorov, in this issue, and colleagues regarding increased tropical-cyclone activity as a key contributor to the climate of the early Pliocene. He used a multifaceted modeling approach to demonstrate that the large-scale atmospheric conditions could have favored widespread cyclone activity, with twice the frequency that of the present day. The author comments that the given studies may have implications for the future incidence of El Nino events.