Deep sequencing of proteotoxicity modifier genes uncovers a Presenilin-2/beta-amyloid-actin genetic risk module shared among alpha-synucleinopathies.

Whether neurodegenerative diseases linked to misfolding of the same protein share genetic risk drivers or whether different protein-aggregation pathologies in neurodegeneration are mechanistically related remains uncertain. Conventional genetic analyses are underpowered to address these questions. Through careful selection of patients based on protein aggregation phenotype (rather than clinical diagnosis) we can increase statistical power to detect associated variants in a targeted set of genes that modify proteotoxicities. Genetic modifiers of alpha-synuclein (ɑS) and beta-amyloid (Aß) cytotoxicity in yeast are enriched in risk factors for Parkinson's disease (PD) and Alzheimer's disease (AD), respectively. Here, along with known AD/PD risk genes, we deeply sequenced exomes of 430 ɑS/Aß modifier genes in patients across alpha-synucleinopathies (PD, Lewy body dementia and multiple system atrophy). Beyond known PD genes GBA1 and LRRK2, rare variants AD genes (CD33, CR1 and PSEN2) and Aß toxicity modifiers involved in RhoA/actin cytoskeleton regulation (ARGHEF1, ARHGEF28, MICAL3, PASK, PKN2, PSEN2) were shared risk factors across synucleinopathies. Actin pathology occurred in iPSC synucleinopathy models and RhoA downregulation exacerbated ɑS pathology. Even in sporadic PD, the expression of these genes was altered across CNS cell types. Genome-wide CRISPR screens revealed the essentiality of PSEN2 in both human cortical and dopaminergic neurons, and PSEN2 mutation carriers exhibited diffuse brainstem and cortical synucleinopathy independent of AD pathology. PSEN2 contributes to a common-risk signal in PD GWAS and regulates ɑS expression in neurons. Our results identify convergent mechanisms across synucleinopathies, some shared with AD.

From a genome-wide screen of RNAi molecules against SARS-CoV-2 to a validated broad-spectrum and potent prophylaxis.

Expanding the arsenal of prophylactic approaches against SARS-CoV-2 is of utmost importance, specifically those strategies that are resistant to antigenic drift in Spike. Here, we conducted a screen of over 16,000 RNAi triggers against the SARS-CoV-2 genome, using a massively parallel assay to identify hyper-potent siRNAs. We selected Ten candidates for in vitro validation and found five siRNAs that exhibited hyper-potent activity (IC50 < 20 pM) and strong blockade of infectivity in live-virus experiments. We further enhanced this activity by combinatorial pairing of the siRNA candidates and identified cocktails that were active against multiple types of variants of concern (VOC). We then examined over 2,000 possible mutations in the siRNA target sites by using saturation mutagenesis and confirmed broad protection of the leading cocktail against future variants. Finally, we demonstrated that intranasal administration of this siRNA cocktail effectively attenuates clinical signs and viral measures of disease in the gold-standard Syrian hamster model. Our results pave the way for the development of an additional layer of antiviral prophylaxis that is orthogonal to vaccines and monoclonal antibodies.

On the Opportunities and Risks of Examining the Genetics of Entrepreneurship.

Recent accomplishments in genome sequencing techniques have resulted in vast and complex genomic data sets, which have been used to uncover the genetic correlates of not only strictly medical phenomena but also psychological characteristics such as personality traits. In this commentary, we call for the use of genomic data analysis to unlock the valuable field of the genetics of entrepreneurship. Understanding what makes an entrepreneur and what explains their success is paramount given the importance of entrepreneurship to individual, organizational, and societal growth and success. Most of the studies into the genetics of entrepreneurship have investigated familial entrepreneurial inclinations in the form of parent-offspring comparisons or twin studies. However, these do not offer a complete picture of the etiology of entrepreneurship. The use of big data analytics combined with the rapidly growing field of genetic mapping has the potential to offer a more complete picture of the etiology of entrepreneurship by allowing researchers to pinpoint precisely which genes and pathways underlie entrepreneurial behavior and success. We review the risks and opportunities which accompany this endeavor and make the case that, ultimately, prioritizing more research into the genetics of entrepreneurship has the potential to be of value to both science and society.

Genome wide screen of RNAi molecules against SARS-CoV-2 creates a broadly potent prophylaxis.

Expanding the arsenal of prophylactic approaches against SARS-CoV-2 is of utmost importance, specifically those strategies that are resistant to antigenic drift in Spike. Here, we conducted a screen with over 16,000 RNAi triggers against the SARS-CoV-2 genome using a massively parallel assay to identify hyper-potent siRNAs. We selected 10 candidates for in vitro validation and found five siRNAs that exhibited hyper-potent activity with IC50<20pM and strong neutralisation in live virus experiments. We further enhanced the activity by combinatorial pairing of the siRNA candidates to develop siRNA cocktails and found that these cocktails are active against multiple types of variants of concern (VOC). We examined over 2,000 possible mutations to the siRNA target sites using saturation mutagenesis and identified broad protection against future variants. Finally, we demonstrated that intranasal administration of the siRNA cocktail effectively attenuates clinical signs and viral measures of disease in the Syrian hamster model. Our results pave the way to development of an additional layer of antiviral prophylaxis that is orthogonal to vaccines and monoclonal antibodies.

Chemical and photochemical error rates in light-directed synthesis of complex DNA libraries.

Nucleic acid microarrays are the only tools that can supply very large oligonucleotide libraries, cornerstones of the nascent fields of de novo gene assembly and DNA data storage. Although the chemical synthesis of oligonucleotides is highly developed and robust, it is not error free, requiring the design of methods that can correct or compensate for errors, or select for high-fidelity oligomers. However, outside the realm of array manufacturers, little is known about the sources of errors and their extent. In this study, we look at the error rate of DNA libraries synthesized by photolithography and dissect the proportion of deletion, insertion and substitution errors. We find that the deletion rate is governed by the photolysis yield. We identify the most important substitution error and correlate it to phosphoramidite coupling. Besides synthetic failures originating from the coupling cycle, we uncover the role of imperfections and limitations related to optics, highlight the importance of absorbing UV light to avoid internal reflections and chart the dependence of error rate on both position on the array and position within individual oligonucleotides. Being able to precisely quantify all types of errors will allow for optimal choice of fabrication parameters and array design.

A DNA-of-things storage architecture to create materials with embedded memory.

DNA storage offers substantial information density1-7 and exceptional half-life3. We devised a 'DNA-of-things' (DoT) storage architecture to produce materials with immutable memory. In a DoT framework, DNA molecules record the data, and these molecules are then encapsulated in nanometer silica beads8, which are fused into various materials that are used to print or cast objects in any shape. First, we applied DoT to three-dimensionally print a Stanford Bunny9 that contained a 45 kB digital DNA blueprint for its synthesis. We synthesized five generations of the bunny, each from the memory of the previous generation without additional DNA synthesis or degradation of information. To test the scalability of DoT, we stored a 1.4 MB video in DNA in plexiglass spectacle lenses and retrieved it by excising a tiny piece of the plexiglass and sequencing the embedded DNA. DoT could be applied to store electronic health records in medical implants, to hide data in everyday objects (steganography) and to manufacture objects containing their own blueprint. It may also facilitate the development of self-replicating machines.

Estimating variance components in population scale family trees.

The rapid digitization of genealogical and medical records enables the assembly of extremely large pedigree records spanning millions of individuals and trillions of pairs of relatives. Such pedigrees provide the opportunity to investigate the sociological and epidemiological history of human populations in scales much larger than previously possible. Linear mixed models (LMMs) are routinely used to analyze extremely large animal and plant pedigrees for the purposes of selective breeding. However, LMMs have not been previously applied to analyze population-scale human family trees. Here, we present Sparse Cholesky factorIzation LMM (Sci-LMM), a modeling framework for studying population-scale family trees that combines techniques from the animal and plant breeding literature and from human genetics literature. The proposed framework can construct a matrix of relationships between trillions of pairs of individuals and fit the corresponding LMM in several hours. We demonstrate the capabilities of Sci-LMM via simulation studies and by estimating the heritability of longevity and of reproductive fitness (quantified via number of children) in a large pedigree spanning millions of individuals and over five centuries of human history. Sci-LMM provides a unified framework for investigating the epidemiological history of human populations via genealogical records.

FactorialHMM: fast and exact inference in factorial hidden Markov models.

MOTIVATION: Hidden Markov models (HMMs) are powerful tools for modeling processes along the genome. In a standard genomic HMM, observations are drawn, at each genomic position, from a distribution whose parameters depend on a hidden state, and the hidden states evolve along the genome as a Markov chain. Often, the hidden state is the Cartesian product of multiple processes, each evolving independently along the genome. Inference in these so-called Factorial HMMs has a naïve running time that scales as the square of the number of possible states, which by itself increases exponentially with the number of sub-chains; such a running time scaling is impractical for many applications. While faster algorithms exist, there is no available implementation suitable for developing bioinformatics applications. RESULTS: We developed FactorialHMM, a Python package for fast exact inference in Factorial HMMs. Our package allows simulating either directly from the model or from the posterior distribution of states given the observations. Additionally, we allow the inference of all key quantities related to HMMs: (i) the (Viterbi) sequence of states with the highest posterior probability; (ii) the likelihood of the data and (iii) the posterior probability (given all observations) of the marginal and pairwise state probabilities. The running time and space requirement of all procedures is linearithmic in the number of possible states. Our package is highly modular, providing the user with maximal flexibility for developing downstream applications. AVAILABILITY AND IMPLEMENTATION: https://github.com/regevs/factorial_hmm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Identity inference of genomic data using long-range familial searches.

Consumer genomics databases have reached the scale of millions of individuals. Recently, law enforcement authorities have exploited some of these databases to identify suspects via distant familial relatives. Using genomic data of 1.28 million individuals tested with consumer genomics, we investigated the power of this technique. We project that about 60% of the searches for individuals of European descent will result in a third-cousin or closer match, which theoretically allows their identification using demographic identifiers. Moreover, the technique could implicate nearly any U.S. individual of European descent in the near future. We demonstrate that the technique can also identify research participants of a public sequencing project. On the basis of these results, we propose a potential mitigation strategy and policy implications for human subject research.

Quantitative analysis of population-scale family trees with millions of relatives.

Family trees have vast applications in fields as diverse as genetics, anthropology, and economics. However, the collection of extended family trees is tedious and usually relies on resources with limited geographical scope and complex data usage restrictions. We collected 86 million profiles from publicly available online data shared by genealogy enthusiasts. After extensive cleaning and validation, we obtained population-scale family trees, including a single pedigree of 13 million individuals. We leveraged the data to partition the genetic architecture of human longevity and to provide insights into the geographical dispersion of families. We also report a simple digital procedure to overlay other data sets with our resource.

Rapid re-identification of human samples using portable DNA sequencing.

DNA re-identification is used for a broad suite of applications, ranging from cell line authentication to forensics. However, current re-identification schemes suffer from high latency and limited access. Here, we describe a rapid, inexpensive, and portable strategy to robustly re-identify human DNA called 'MinION sketching'. MinION sketching requires as few as 3 min of sequencing and 60-300 random SNPs to re-identify a sample enabling near real-time applications of DNA re-identification. Our method capitalizes on the rapidly growing availability of genomic reference data for cell lines, tissues in biobanks, and individuals. This empowers the application of MinION sketching in research and clinical settings for periodic cell line and tissue authentication. Importantly, our method enables considerably faster and more robust cell line authentication relative to current practices and could help to minimize the amount of irreproducible research caused by mix-ups and contamination in human cell and tissue cultures.

Interpreting short tandem repeat variations in humans using mutational constraint.

Identifying regions of the genome that are depleted of mutations can distinguish potentially deleterious variants. Short tandem repeats (STRs), also known as microsatellites, are among the largest contributors of de novo mutations in humans. However, per-locus studies of STR mutations have been limited to highly ascertained panels of several dozen loci. Here we harnessed bioinformatics tools and a novel analytical framework to estimate mutation parameters for each STR in the human genome by correlating STR genotypes with local sequence heterozygosity. We applied our method to obtain robust estimates of the impact of local sequence features on mutation parameters and used these estimates to create a framework for measuring constraint at STRs by comparing observed versus expected mutation rates. Constraint scores identified known pathogenic variants with early-onset effects. Our metric will provide a valuable tool for prioritizing pathogenic STRs in medical genetics studies.

Genome-wide profiling of heritable and de novo STR variations.

Short tandem repeats (STRs) are highly variable elements that play a pivotal role in multiple genetic diseases, population genetics applications, and forensic casework. However, it has proven problematic to genotype STRs from high-throughput sequencing data. Here, we describe HipSTR, a novel haplotype-based method for robustly genotyping and phasing STRs from Illumina sequencing data, and we report a genome-wide analysis and validation of de novo STR mutations. HipSTR is freely available at https://hipstr-tool.github.io/HipSTR.

DNA Compass: a secure, client-side site for navigating personal genetic information.

MOTIVATION: Millions of individuals have access to raw genomic data using direct-to-consumer companies. The advent of large-scale sequencing projects, such as the Precision Medicine Initiative, will further increase the number of individuals with access to their own genomic information. However, querying genomic data requires a computer terminal and computational skill to analyze the data-an impediment for the general public. RESULTS: DNA Compass is a website designed to empower the public by enabling simple navigation of personal genomic data. Users can query the status of their genomic variants for over 1658 markers or tens of millions of documented single nucleotide polymorphisms (SNPs). DNA Compass presents the relevant genotypes of the user side-by-side with explanatory scientific resources. The genotype data never leaves the user's computer, a feature that provides improved security and performance. More than 12 000 unique users, mainly from the general genetic genealogy community, have already used DNA Compass, demonstrating its utility. AVAILABILITY AND IMPLEMENTATION: DNA Compass is freely available on https://compass.dna.land . CONTACT: yaniv@cs.columbia.edu.

DNA Fountain enables a robust and efficient storage architecture.

DNA is an attractive medium to store digital information. Here we report a storage strategy, called DNA Fountain, that is highly robust and approaches the information capacity per nucleotide. Using our approach, we stored a full computer operating system, movie, and other files with a total of 2.14 × 106 bytes in DNA oligonucleotides and perfectly retrieved the information from a sequencing coverage equivalent to a single tile of Illumina sequencing. We also tested a process that can allow 2.18 × 1015 retrievals using the original DNA sample and were able to perfectly decode the data. Finally, we explored the limit of our architecture in terms of bytes per molecule and obtained a perfect retrieval from a density of 215 petabytes per gram of DNA, orders of magnitude higher than previous reports.

Case-control association mapping by proxy using family history of disease.

Collecting cases for case-control genetic association studies can be time-consuming and expensive. In some situations (such as studies of late-onset or rapidly lethal diseases), it may be more practical to identify family members of cases. In randomly ascertained cohorts, replacing cases with their first-degree relatives enables studies of diseases that are absent (or nearly absent) in the cohort. We refer to this approach as genome-wide association study by proxy (GWAX) and apply it to 12 common diseases in 116,196 individuals from the UK Biobank. Meta-analysis with published genome-wide association study summary statistics replicated established risk loci and yielded four newly associated loci for Alzheimer's disease, eight for coronary artery disease and five for type 2 diabetes. In addition to informing disease biology, our results demonstrate the utility of association mapping without directly observing cases. We anticipate that GWAX will prove useful in future genetic studies of complex traits in large population cohorts.

The Simons Genome Diversity Project: 300 genomes from 142 diverse populations.

Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.