Entrepreneurial Experiments in Science Policy: Analizing the Human Genome Project

We re-conceptualize the role of science policy makers, envisioning and illustrating their move from being simple investors in scientific projects to entrepreneurs who create the conditions for entrepreneurial experiments and initiate them. We argue that reframing science policy around the notion of conducting entrepreneurial experiments – experiments that increase the diversity of technical, organizational and institutional arrangements in which scientific research is conducted – can provide policy makers with a wider repertoire of effective interventions. To illustrate the power of this approach, we analyze the Human Genome Project (HGP) as a set of successful, entrepreneurial experiments in organizational and institutional innovation. While not designed as such, the HGP was an experiment in funding a science project across a variety of organizational settings, including seven public and one private (Celera) research centers. We assess the major characteristics and differences between these organizational choices, using a mix of qualitative and econometric analyses to examine their impact on scientific progress. The planning and direction of the Human Genome Project show that policy makers can use the levers of entrepreneurial experimentation to transform scientific progress, much as entrepreneurs have transformed economic progress.Entrepreneurial Experiments; Science Policy; Human Genome Project

Principles for the post-GWAS functional characterisation of risk loci

Several challenges lie ahead in assigning functionality to susceptibility SNPs. For example, most effect sizes are small relative to effects seen in monogenic diseases, with per allele odds ratios usually ranging from 1.15 to 1.3. It is unclear whether current molecular biology methods have enough resolution to differentiate such small effects. Our objective here is therefore to provide a set of recommendations to optimize the allocation of effort and resources in order maximize the chances of elucidating the functional contribution of specific loci to the disease phenotype. It has been estimated that 88% of currently identified disease-associated SNP are intronic or intergenic. Thus, in this paper we will focus our attention on the analysis of non-coding variants and outline a hierarchical approach for post-GWAS functional studies

Towards Better Understanding of Artifacts in Variant Calling from High-Coverage Samples

Motivation: Whole-genome high-coverage sequencing has been widely used for personal and cancer genomics as well as in various research areas. However, in the lack of an unbiased whole-genome truth set, the global error rate of variant calls and the leading causal artifacts still remain unclear even given the great efforts in the evaluation of variant calling methods. Results: We made ten SNP and INDEL call sets with two read mappers and five variant callers, both on a haploid human genome and a diploid genome at a similar coverage. By investigating false heterozygous calls in the haploid genome, we identified the erroneous realignment in low-complexity regions and the incomplete reference genome with respect to the sample as the two major sources of errors, which press for continued improvements in these two areas. We estimated that the error rate of raw genotype calls is as high as 1 in 10-15kb, but the error rate of post-filtered calls is reduced to 1 in 100-200kb without significant compromise on the sensitivity. Availability: BWA-MEM alignment: http://bit.ly/1g8XqRt; Scripts: https://github.com/lh3/varcmp; Additional data: https://figshare.com/articles/Towards_better_understanding_of_artifacts_in_variating_calling_from_high_coverage_samples/981073Comment: Published versio

Assessing the Benefits of Public Research Within an Economic Framework: The Case of USDA's Agricultural Research Service

Evaluation of publicly funded research can help provide accountability and prioritize programs. In addition, Federal intramural research planning generally involves an institutional assessment of the appropriate Federal role, if any, and whether the research should be left to others, such as universities or the private sector. Many methods of evaluation are available, peer review—used primarily for establishing scientific merit—being the most common. Economic analysis focuses on quantifying ultimate research outcomes, whether measured in goods with market prices or in nonmarket goods such as environmental quality or human health. However, standard economic techniques may not be amenable for evaluating some important public research priorities or for institutional assessments. This report reviews quantitative methods and applies qualitative economic reasoning and stakeholder interviewing methods to the evaluation of economic benefits of Federal intramural research using three case studies of research conducted by USDA’s Agricultural Research Service (ARS). Differences among the case studies highlight the need to select suitable assessment techniques from available methodologies, the limited scope for comparing assessment results across programs, and the inherent difficulty in quantifying benefits in some research areas. When measurement and attribution issues make it difficult to quantify these benefits, the report discusses how qualitative insights based on economic concepts can help research prioritization.Agricultural Research Service, Federal intramural research, publicly funded research, Environmental Economics and Policy, Food Consumption/Nutrition/Food Safety, Livestock Production/Industries, Productivity Analysis,

The genetics of cardiovascular disease

Recent advances in genotyping technology and insights into disease mechanisms have increased interest in the genetics of cardiovascular disease. Several candidate genes involved in cardiovascular diseases were identified from studies using animal models, and the translation of these findings to human disease is an exciting challenge. There is a trend towards large-scale genome-wide association studies that are subject to strict quality criteria with regard to both genotyping and phenotyping. Here, we review some of the strategies that have been developed to translate findings from experimental models to human disease and outline the need for optimizing global approaches to analyze such results. Findings from ongoing studies are interpreted in the context of disease pathways instead of the more traditional focus on single genetic variants

From cheek swabs to consensus sequences : an A to Z protocol for high-throughput DNA sequencing of complete human mitochondrial genomes

Background: Next-generation DNA sequencing (NGS) technologies have made huge impacts in many fields of biological research, but especially in evolutionary biology. One area where NGS has shown potential is for high-throughput sequencing of complete mtDNA genomes (of humans and other animals). Despite the increasing use of NGS technologies and a better appreciation of their importance in answering biological questions, there remain significant obstacles to the successful implementation of NGS-based projects, especially for new users. Results: Here we present an ‘A to Z’ protocol for obtaining complete human mitochondrial (mtDNA) genomes – from DNA extraction to consensus sequence. Although designed for use on humans, this protocol could also be used to sequence small, organellar genomes from other species, and also nuclear loci. This protocol includes DNA extraction, PCR amplification, fragmentation of PCR products, barcoding of fragments, sequencing using the 454 GS FLX platform, and a complete bioinformatics pipeline (primer removal, reference-based mapping, output of coverage plots and SNP calling). Conclusions: All steps in this protocol are designed to be straightforward to implement, especially for researchers who are undertaking next-generation sequencing for the first time. The molecular steps are scalable to large numbers (hundreds) of individuals and all steps post-DNA extraction can be carried out in 96-well plate format. Also, the protocol has been assembled so that individual ‘modules’ can be swapped out to suit available resources