Driven in part by the Human Genome Project, genetics and genomics are taking an ever more central role in the biomedical sciences. In the same way, advances in computational methods are driving the mathematical sciences forward. These factors, the increasingly quantitative nature of the biological sciences, and the explosive growth of genetic and genomic data, have resulted in a rapidly increasing demand for investigators trained at the interface of genetics, genomics, and the mathematical sciences. The successful translation Of DNA sequence and annotation to address questions of human health and disease and to better understand human evolution require the talents and energies of individuals trained at this interface; at the same time, there is a severe shortage of individuals with this training. We propose a 5-year competing renewal of our University of Michigan Genome Science Training Program (UMGSTP) to support pre- and postdoctoral trainees at the interface between genetics, genomics, and the mathematical sciences, with particular emphasis on training statistical human geneticists, and human molecular geneticists with a strong grounding in statistics. This Training Program is based in the participating departments of Biostatistics, Human Genetics, and now also Epidemiology; other participating faculty come from Ecology and Evolutionary Biology; Mathematics; Molecular, Cellular, and Developmental Biology; and Statistics. The fundamental premise of the UMGSTP is that graduates should have substantial training in both the mathematical and biological sciences and at their interface. Such training facilitates communication between disciplines, identification of important problems, and identification of the mathematical and computational methods required to solve those problems. We request support for 6 predoctoral trainees and 2 postdoctoral trainees, consistent with our numbers in the first 10 years of the Training Program. Trainees will continue to be supported for 2 to 3 years to provide time for the degree of interdisciplinary training we have demonstrated is critical to their success. Graduates of this Training Program will continue to help fill the increasing need for statistical geneticists and genome scientists. In so doing, they will help the National Human Genome Research Institute to achieve its goals in the translation of DNA sequence and annotation into advances in our understanding of human disease and evolution.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Institutional National Research Service Award (T32)
Project #
5T32HG000040-14
Application #
7451064
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Graham, Bettie
Project Start
1995-07-01
Project End
2010-06-30
Budget Start
2008-07-01
Budget End
2009-06-30
Support Year
14
Fiscal Year
2008
Total Cost
$514,055
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Pérez Millán, María I; Vishnopolska, Sebastian A; Daly, Alexandre Z et al. (2018) Next generation sequencing panel based on single molecule molecular inversion probes for detecting genetic variants in children with hypopituitarism. Mol Genet Genomic Med :
Colacino, Justin A; Azizi, Ebrahim; Brooks, Michael D et al. (2018) Heterogeneity of Human Breast Stem and Progenitor Cells as Revealed by Transcriptional Profiling. Stem Cell Reports 10:1596-1609
Pendleton, Amanda L; Shen, Feichen; Taravella, Angela M et al. (2018) Comparison of village dog and wolf genomes highlights the role of the neural crest in dog domestication. BMC Biol 16:64
Cheung, Leonard Y M; George, Akima S; McGee, Stacey R et al. (2018) Single-Cell RNA Sequencing Reveals Novel Markers of Male Pituitary Stem Cells and Hormone-Producing Cell Types. Endocrinology 159:3910-3924
Koneva, Lada A; Zhang, Yanxiao; Virani, Shama et al. (2018) HPV Integration in HNSCC Correlates with Survival Outcomes, Immune Response Signatures, and Candidate Drivers. Mol Cancer Res 16:90-102
Carlson, Jedidiah; Locke, Adam E; Flickinger, Matthew et al. (2018) Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans. Nat Commun 9:3753
Duveau, Fabien; Hodgins-Davis, Andrea; Metzger, Brian Ph et al. (2018) Fitness effects of altering gene expression noise in Saccharomyces cerevisiae. Elife 7:
Zhao, Xuefang; Weber, Alexandra M; Mills, Ryan E (2017) A recurrence-based approach for validating structural variation using long-read sequencing technology. Gigascience 6:1-9
McConnell, Michael J; Moran, John V; Abyzov, Alexej et al. (2017) Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network. Science 356:
Liu, Dajiang J (see original citation for additional authors) (2017) Exome-wide association study of plasma lipids in >300,000 individuals. Nat Genet 49:1758-1766

Showing the most recent 10 out of 137 publications