So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

/pdf/analysis-of-protein-coding-genetic-variation-in-60-706-43wjw7d23z.pdf

Analysis of protein-coding genetic variation in 60,706 humans

The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.

/pdf/the-uk-biobank-resource-with-deep-phenotyping-and-genomic-2fs3jmksld.pdf

The UK Biobank resource with deep phenotyping and genomic data

The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

Integrative analysis of 111 reference human epigenomes

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

/pdf/ld-score-regression-distinguishes-confounding-from-58i9nc2cv7.pdf

LD score regression distinguishes confounding from polygenicity in genome-wide association studies :

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance levels of one or multiple proteins. In this work we introduce a powerful strategy that integrates gene expression measurements with large-scale genome-wide association data to identify genes whose cis-regulated expression is associated to complex traits. We use a relatively small reference panel of individuals for which both genetic variation and gene expression have been measured to impute gene expression into large cohorts of individuals and identify expression-trait associations. We extend our methods to allow for indirect imputation of the expression-trait association from summary association statistics of large-scale GWAS1-3. We applied our approaches to expression data from blood and adipose tissue measured in ~3,000 individuals overall. We then imputed gene expression into GWAS data from over 900,000 phenotype measurements4-6 to identify 69 novel genes significantly associated to obesity-related traits (BMI, lipids, and height). Many of the novel genes were associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Overall our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits.

https://www.biorxiv.org/content/biorxiv/early/2015/08/10/024083.full.pdf

Integrative approaches for large-scale transcriptome-wide association studies

Adapalene Microemulsion for Transfollicular Drug Delivery

Driving through intersections can be potentially dangerous because nearly 23 percent of the total automotive related fatalities and almost 1 million injury-causing crashes occur at or within intersections every year [1]. The impact of traffic intersections on trip delays also leads to waste of human and natural resources. Our goal is to increase the safety and throughput of traffic intersections using co-operative driving. In earlier work [2], we have proposed a family of vehicular network protocols, which use Dedicated Short Range Communications (DSRC) and Wireless Access in Vehicular Environment (WAVE) technologies to manage a vehicle’s movement at intersections Specifically, we have provided a collision detection algorithm at intersections (CDAI) to avoid potential crashes at or near intersections and improve safety. We have shown that vehicle-to-vehicle (V2V) communications can be used to significantly decrease the trip delays introduced by traffic lights and stop signs. In this paper, we investigate the use of more realistic controller models and higher concurrency to improve V2V intersection protocols for autonomous driving at intersections. We quantify the throughput enhancements due to the use of V2V under various driving conditions, while maintaining safe passage through intersections.

https://users.ece.cmu.edu/~sazimi/SAE2012.pdf

Intersection Management using Vehicular Networks

One embodiment of the present invention provides a system that facilitates end-to-end identity propagation to a backend-tier application that is not single sign-on enabled. During operation, the system receives request from a user at a middle-tier application to access private data from the backend-tier application. Upon receiving this request, the system redirects the user to a single sign-on server that verifies authentication credentials of the user. The middle-tier application then receives a token from the single sign-on server authorizing access to a backend-tier application. Next, the middle-tier application uses the token to access the private data from the backend-tier application, and then provides the private data to the user.

Method and apparatus for end-to-end identity propagation

Nonobstetrical causes of pain during pregnancy are very common and can be incapacitating if not treated appropriately. Recent reports in the literature show that a significant percentage of pregnant women are treated with opioids during pregnancy. To address common pain conditions that present during pregnancy and the available pharmacological and nonpharmacological treatment options, for each of the pain conditions identified, a search using MEDLINE, PubMed, Embase, and Cochrane databases was performed. The quality of the evidence was evaluated in the context of study design. This paper is a narrative summary of the results obtained from individual reviews. There were significant disparities in the studies in terms of design, research and methodology, and outcomes analyzed. There is reasonable evidence available for pharmacological approaches; however, these are also associated with adverse events. Evidence for nonpharmacological approaches is limited and hence their efficacy is unclear, although they do appear to be primarily safe. A multimodal approach using a combination of nonpharmacological and pharmacological options to treat these pain conditions is likely to have the most benefit while limiting risk. Research trials with sound methodology and analysis of outcome data are needed.

/pdf/pain-management-in-pregnancy-multimodal-approaches-2txn7oy9jp.pdf

Gaurav Bhatia

Papers

Integrative approaches for large-scale transcriptome-wide association studies

Adapalene Microemulsion for Transfollicular Drug Delivery

Intersection Management using Vehicular Networks

Method and apparatus for end-to-end identity propagation

Pain Management in Pregnancy: Multimodal Approaches