Pooled image-base screening of mitochondria with microraft isolation distinguishes pathogenic mitofusin 2 mutations.

Most human genetic variation is classified as variants of uncertain significance. While advances in genome editing have allowed innovation in pooled screening platforms, many screens deal with relatively simple readouts (viability, fluorescence) and cannot identify the complex cellular phenotypes that underlie most human diseases. In this paper, we present a generalizable functional genomics platform that combines high-content imaging, machine learning, and microraft isolation in a method termed "Raft-Seq". We highlight the efficacy of our platform by showing its ability to distinguish pathogenic point mutations of the mitochondrial regulator Mitofusin 2, even when the cellular phenotype is subtle. We also show that our platform achieves its efficacy using multiple cellular features, which can be configured on-the-fly. Raft-Seq enables a way to perform pooled screening on sets of mutations in biologically relevant cells, with the ability to physically capture any cell with a perturbed phenotype and expand it clonally, directly from the primary screen.

Domain-centric database to uncover structure of minimally characterized viral genomes.

Protein domain-based approaches to analyzing sequence data are valuable tools for examining and exploring genomic architecture across genomes of different organisms. Here, we present a complete dataset of domains from the publicly available sequence data of 9,051 reference viral genomes. The data provided contain information such as sequence position and neighboring domains from 30,947 pHMM-identified domains from each reference viral genome. Domains were identified from viral whole-genome sequence using automated profile Hidden Markov Models (pHMM). This study also describes the framework for constructing "domain neighborhoods", as well as the dataset representing it. These data can be used to examine shared and differing domain architectures across viral genomes, to elucidate potential functional properties of genes, and potentially to classify viruses.