Jocelyn Sunseri Selected as Recipient of 2018 Phase-I MolSSI Software Fellowship

Congratulations to Jocelyn Sunseri who was selected as one of only 11 recipients of the 2018 Phase-I MolSSI Software Fellowship. She will receive six months of support in this program funded by the National Science Foundation through Virginia Tech. Jocelyn’s adviser is Dr. David Koes.

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Raghav Partha and the Clark and Chikina labs publish in eLife

Subterranean mammals show convergent regression in ocular genes and enhancers, along with adaptation to tunneling

Raghavendran Partha, Bharesh K Chauhan, Zelia Ferreira, Joseph D Robinson, Kira Lathrop, Ken K Nischal, Maria Chikina (corresponding author), Nathan L Clark (corresponding author)

Abstract: The underground environment imposes unique demands on life that have led subterranean species to evolve specialized traits, many of which evolved convergently. We studied convergence in evolutionary rate in subterranean mammals in order to associate phenotypic evolution with specific genetic regions. We identified a strong excess of vision- and skin-related genes that changed at accelerated rates in the subterranean environment due to relaxed constraint and adaptive evolution. We also demonstrate that ocular-specific transcriptional enhancers were convergently accelerated, whereas enhancers active outside the eye were not. Furthermore, several uncharacterized genes and regulatory sequences demonstrated convergence and thus constitute novel candidate sequences for congenital ocular disorders. The strong evidence of convergence in these species indicates that evolution in this environment is recurrent and predictable and can be used to gain insights into phenotype–genotype relationships.

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Dr. Robin Lee Lab publish in Cell Systems

Lee Lab publish in Cell Systems

 

Cell Systems

NF-𝛋B Dynamics Discriminate between TNF Doses in Single Cells

Zhang Q1, Gupta S1, Schipper DL, Kowalczyk GJ, Mancini AE, Faeder JR, Lee REC*

Using an information theory framework and single-cell data, Zhang et al. set out to distinguish between different mechanisms for activation of intracellular signals. They show that heterogeneity between cellular states can lead to underestimates in the capabilities of single cells. In contrast with a switch-like model for pathway activation, they find that single cells can encode multiple levels of response that increase with stimulation strength.

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