Biology subjects

Liebeskind, B. J.

Publications and source records attributed to Liebeskind, B. J..

3 recordsLinked to original sources

bioRxiv2024

Quantifying transcriptome turnover on phylogenies bymodeling gene expression as a binary trait

Changes in gene expression are a key driver of phenotypic evolution, leading to a persistent interest in the evolution of transcriptomes. Traditionally, gene expression is modeled as a continuous trait, leaving qualitative transitions largely unexplored. In this paper, we detail the development of new Bayesian inference techniques to study the evolutionary turnover of organ-specific transcriptomes, which we define as instances where orthologous genes gain or lose expression in a particular organ. To test these techniques, we analyze the transcriptomes of two male reproductive organs, testes and accessory glands, across 11 species of the Drosophila melanogaster species group. We first discretize gene expression states by estimating the probability that each gene is expressed in each organ and species. We then define a phylogenetic model of correlated transcriptome evolution in two or more organs and fit it to the expression state data. Inferences under this model show that many genes have gained and lost expression in each organ, and that the two organs experienced accelerated transcriptome turnover on different branches of the Drosophila phylogeny.

evolutionary biology↗

bioRxiv2020

Mapping Functional Protein Neighborhoods in the Mouse Brain

New proteomics methods make it possible to determine protein interaction maps at the proteome scale without the need for genetically encoded tags, opening up new organisms and tissue types to investigation. Current molecular and computational methods are oriented towards protein complexes that are soluble, stable, and discrete. However, the mammalian brain, among the most complicated and most heavily studied tissue types, derives many of its unique functions from protein interactions that are neither discrete nor soluble. Proteomics investigations into the global protein interaction landscape of the brain have therefore leveraged non-proteomics datasets to supplement their experiments. Here, we develop a novel, integrative proteomics pipeline and apply it to infer a global map of functional protein neighborhoods in the mouse brain without the aid of external datasets. By leveraging synaptosome enrichment and interactomics methods that target both soluble and insoluble protein fractions, we resolved protein interactions for key neural pathways, including those from refractory subcellular fractions such as the membrane and cytoskeleton. In comparison to external datasets, our observed interactions perform similarly to hand-curated synaptic protein interactions while also suggesting thousands of novel connections. We additionally employed cleavable chemical cross-linkers to detect direct binding partners and provide structural context. Our combined map suggests new protein pathways and novel mechanisms for proteins that underlie neurological diseases, including autism and epilepsy. Our results show that proteomics methods alone are sufficient to determine global interaction maps for proteins that are of broad interest to neuroscience. We anticipate that our map will be used to prioritize new research avenues and will pave the way towards future proteomics techniques that resolve protein interactions at ever greater resolution.

systems biology↗

bioRxiv2017

Evolution of Animal Neural Systems

Nervous systems are one of the most spectacular products of evolution. Their provenance and evolution have been an area of interest and often intense debate since the late 19th century. The genomics era has provided researchers with a new set of tools with which to study the early evolution of neurons, and recent progress on the molecular evolution of the first neurons has been both exciting and frustrating. It has become increasingly obvious that genomic data is often insufficient to reconstruct complex phenotypes in deep evolutionary time. We review this recent progress and its attendant challenges, and suggest ways forward.

evolutionary biology↗