Mark S. Guyer

A vision for the future of genomics research

A blueprint for the genomic era.

Replicating genotype-phenotype associations.

What constitutes replication of a genotype–phenotype association, and how best can it be achieved?

Identification of functional elements and regulatory circuits by Drosophila modENCODE

From Genome to Regulatory Networks For biologists, having a genome in hand is only the beginning—much more investigation is still needed to characterize how the genome is used to help to produce a functional organism (see the Perspective by Blaxter). In this vein, Gerstein et al. (p. 1775) summarize for the Caenorhabditis elegans genome, and The modENCODE Consortium (p. 1787) summarize for the Drosophila melanogaster genome, full transcriptome analyses over developmental stages, genome-wide identification of transcription factor binding sites, and high-resolution maps of chromatin organization. Both studies identified regions of the nematode and fly genomes that show highly occupied targets (or HOT) regions where DNA was bound by more than 15 of the transcription factors analyzed and the expression of related genes were characterized. Overall, the studies provide insights into the organization, structure, and function of the two genomes and provide basic information needed to guide and correlate both focused and genome-wide studies. The Drosophila modENCODE project demonstrates the functional regulatory network of flies. To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.

Charting a course for genomic medicine from base pairs to bedside

There has been much progress in genomics in the ten years since a draft sequence of the human genome was published. Opportunities for understanding health and disease are now unprecedented, as advances in genomics are harnessed to obtain robust foundational knowledge about the structure and function of the human genome and about the genetic contributions to human health and disease. Here we articulate a 2011 vision for the future of genomics research and describe the path towards an era of genomic medicine.

Completing the map of human genetic variation

Large-scale studies of human genetic variation have focused largely on understanding the pattern and nature of single-nucleotide differences within the human genome. Recent studies that have identified larger polymorphisms, such as insertions, deletions and inversions, emphasize the value of investing in more comprehensive and systematic studies of human structural genetic variation. We describe a community resource project recently launched by the National Human Genome Research Institute (NHGRI) to sequence large-insert clones from many individuals, systematically discovering and resolving these complex variants at the DNA sequence level. The project includes the discovery of variants through development of clone resources, sequence resolution of variants, and accurate typing of variants in individuals of African, European or Asian ancestry. Sequence resolution of both single-nucleotide and larger-scale genomic variants will improve our picture of natural variation in human populations and will enhance our ability to link genetics and human health.

The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data

Biomedical research has and will continue to generate large amounts of data (termed ‘big data’) in many formats and at all levels. Consequently, there is an increasing need to better understand and mine the data to further knowledge and foster new discovery. The National Institutes of Health (NIH) has initiated a Big Data to Knowledge (BD2K) initiative to maximize the use of biomedical big data. BD2K seeks to better define how to extract value from the data, both for the individual investigator and the overall research community, create the analytic tools needed to enhance utility of the data, provide the next generation of trained personnel, and develop data science concepts and tools that can be made available to all stakeholders.

The NIH Big Data to Knowledge (BD2K) initiative.

Understanding the human condition is a Big Data problem. This statement is nicely illustrated by the articles that follow from seven of the Centers for Data Excellence that have been funded by the National Institutes of Health (NIH) Big Data to Knowledge (BD2K) initiative. BD2K is a trans-NIH program, funded by all Institutes and Centers at NIH as well as the NIH Common Fund; it is overseen by the NIH Office of Data Science within the NIH Office of the Director. The beginnings of BD2K have been described previously,1 and the purpose here is to provide an overall context, from …

The Ethical, Legal, and Social Implications Program of the National Human Genome Research Institute: Reflections on an Ongoing Experiment*

For more than 20 years, the Ethical, Legal, and Social Implications (ELSI) Program of the National Human Genome Research Institute has supported empirical and conceptual research to anticipate and address the ethical, legal, and social implications of genomics. As a component of the agency that funds much of the underlying science, the program has always been an experiment. The ever-expanding number of issues the program addresses and the relatively low level of commitment on the part of other funding agencies to support such research make setting priorities especially challenging. Program-supported studies have had a significant impact on the conduct of genomics research, the implementation of genomic medicine, and broader public policies. The programs influence is likely to grow as ELSI research, genomics research, and policy development activities become increasingly integrated. Achieving the benefits of increased integration while preserving the autonomy, objectivity, and intellectual independence of ELSI investigators presents ongoing challenges and new opportunities.

Abstracts from the ASENT 2008 Annual Meeting March 6–8, 2008

Background and Objective An assessment of clinically important change is useful in interpreting clinical trial outcomes. The 4-point Ashworth Scale (AS) is a widely accepted measure of muscle tone, and the 9-point Physician Global Assessment Score (PGAS) is a global measure of post-treatment change as evaluated by the physician. The quantitative relationship between AS and PGAS has not previously been described in spasticity. Methods Data from three clinical trials of botulinum toxin type A (BOTOX; Allergan, Irvine, CA) in poststroke spasticity were analyzed ( n = 442). Mean change from baseline in AS score was plotted as a function of PGAS and correlations were calculated. Receiver–operator curve (ROC) analyses with the wrist flexor AS change from baseline as the independent variable and PGAS as the dependent variable were performed using the following criteria: PGAS of ≥1 (mild improvement or better) and PGAS of ≥2 (moderate improvement or better). Results In pooled data, the Pearsons correlation coefficient r between the change in wrist Ashworth Score and the PGAS was −0.44 ( p = 0, t = −26.5). Pearson correlations by individual study were also statistically significant. By ROC analysis, a PGAS of ≥1 was associated with 33% reduction of wrist AS and a PGAS of ≥2 was associated with approximately 50% reduction. In a well-powered phase 3 study, the Pearsons correlation coefficient was even higher ( r = −0.76, p = 0, t = −28.5). Conclusions Changes in disease-specific scales that correlate significantly with changes in physician global assessments are considered clinically meaningful. In clinical trials of chronic spasticity, we found that 33% and 50% changes in the Ashworth Scale scores correlate with 1-point or 2-point changes in PGAS. This is similar to findings from pooled chronic pain studies, in which 30% and 50% changes on the pain numeric rating scale were considered clinically important (Farrar et al., Pain 2001;94:149–158). Study supported by Allergan, Irvine, CA.