Contact Info

Jeffrey Townsend, PhD
Lab Location
60 College Street, Ste 7th Floor
New Haven, CT 06510
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Office Location
135 College Street, Fl Floor 2 Ste Suite 200 Rm Room 222
New Haven, CT 06510
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Mailing Address
Biostatistics135 College St, Room 222
New Haven, CT 06510-2483

Townsend Lab

Research Image 1

Spotted DNA microarray. Red spots represent genes abundantly expressed in wine yeast growing in a high concentration of copper sulfate. Green spots represent genes expressed abundantly in wine yeast growing at a low concentration of copper sulfate. Copper sulfate is often applied in vineyards to control growth of fungi.

Research Image 2

Information on the Tree of Life. Recent efforts to reveal the evolutionary history of life on earth have increasingly relied on the sequencing of DNA from multiple species for multiple genes. This figure demonstrates a principle that should guide these efforts: to understand deep divergences, sample taxa that diverge deeply first. a) and b) Curves depict the cumulative support for the bold deep internode of four species (the fungi Yarrowia lipolytica, Saccharomyces cerevisiae, Coccidioides immitis, and Neurospora crassa), ranging from zero to complete sampling for several sampling schemes: the outcome based on perfect and worst-possible performance (dashed); outcome based on prioritizing sampling based on an novel theoretical prediction using rate of evolution of the sequences (solid); outcome based on prioritizing sampling of all genes for the deepest ingroup (dash-dotted); expectation for haphazard sampling (dotted). c) The established chronogram, or time tree, of the evolution of these species. Vertical bars in the plots correspond to switches from sampling characters from deeper-branching to sampling characters from shallower-branching taxa; note that the slope of the increase in cumulative information (red and green curves) declines as sequences are sampled from more recently diverged lineages in the tree, and that this pattern of high utility to sampling the deepest lineages is revealed for both the clade in panel a and the clade in panel b.

Research Image 3

Population genetic modeling of HGT suggests several key quantities are important to designing any sampling-based assay of horizontal gene transfer (HGT) in large populations. The HGT rate r and the exposed fraction X play significant but ultimately minor roles in the population dynamics, most likely impacting only the number of original opportunities for horizontal spread of genetic material. The malthusian selection coefficient m of the transferred genetic material and the time in recipient generations t from exposure play key, non-linear roles in determining the potential for detection of HGT. Sample size n is important, but frequently the practical sample sizes to be obtained are many orders of magnitude below the extant population size. It is therefore essential to wait until natural selection has had time to operate, so that it is essential to wait until natural selection has a chance to operate to have any chance of effectively detecting horizontal gene transfer events.