Taken together, the papers are a key body of work for the scientific community seeking to understand brain development at its most fundamental level. “Nothing quite like this exists in the stem cell literature,” says Sharad Ramanathan, Ph.D., Professor of Molecular and Cellular Biology and of Applied Physics at Harvard University. “Any complex language is governed by grammatical rules, and we wanted to know whether the development of early human cortex could be decoded by understanding its underlying rules, or grammar. We’ve combined a series of approaches to address this question in a way that sheds valuable light on a difficult to study topic.” “We are learning about the brain in some of its earliest moments of development, and uncovering the patterns that give rise to what it may look like and how it may function in adulthood,” says Boaz Levi, Ph.D., Assistant Investigator at the Allen Institute for Brain Science. “This takes a unique combination of novel computational approaches, dedicated, fastidious bench work, and a willingness to dive into new technologies and see how they can benefit our research.” Learn more about each paper below, and click to view the full manuscripts on the publisher’s website. Discovering sparse transcription factor codes for cell states and state transitions during development, eLife Leon A. Furchtgott, Samuel Melton, Vilas Menon, Sharad Ramanathan This elegant computational study develops a statistical framework using gene expression patterns to simultaneously infer both lineage transitions and the genes that determine these relationships. Extending their methodology into gene expression information from early human cells, they were able to identify a key early developmental split and the genes that could control this lineage decision. Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states, eLife Sumin Jang, Sandeep Choubey, Leon Furchtgott, Ling-Nan Zou, Adele Doyle, Vilas Menon, Ethan Loew, Anne-Rachel Krostag, Refugio Martinez, Linda Madisen, Boaz Levi, Sharad Ramanathan This study applies the computational framework developed in the first paper to characterize the early germ layer differentiation lineage of mouse embryonic stem cells using data and a cell line generated at the Allen Institute. They characterize and experimentally validate the transitions between nine discrete cell states detected in the early differentiations, as well as some key molecular regulators of those transitions. Single-Cell Profiling of an In Vitro Model of Human Interneuron Development Reveals Temporal Dynamics of Cell Type Production and Maturation, Neuron Jennie L. Close, Zizhen Yao, Boaz P. Levi, Jeremy A. Miller, Trygve E. Bakken, Vilas Menon, Jonathan T. Ting, Abigail Wall, Anne-Rachel Krostag, Elliot R. Thomsen, Angel M. Nelson, John K. Mich, Rebecca D. Hodge, Soraya I. Shehata, Ian A. Glass, Susan Bort, Nadiya V. Shapovalova, N. Kiet Ngo, Joshua S. Grimley, John W. Phillips, Carol L. Thompson, Sharad Ramanathan, Ed Lein This paper presents a recipe for growing a class of GABAergic interneurons in a dish. After characterizing cell types present during in vitro production of human interneurons, researchers identified the genes expressed during maturation and developed computational methods that allowed them to describe those changes over time. Read the news story about this paper.