Loss-of-function (LOF) screens provide a powerful approach to identify regulators in biological processes. Pioneered in laboratory animals, LOF screens of human genes are currently restricted to two-dimensional (2D) cell culture hindering testing of gene functions requiring tissue context. Here we present CRISPR-LIneage tracing at Cellular resolution in Heterogenous Tissue (CRISPR-LICHT), enabling parallel LOF studies in human cerebral organoid tissue. We used CRISPR-LICHT to test 173 microcephaly candidate genes revealing 25 to be involved in known and uncharacterized microcephaly-associated pathways. We characterized Immediate Early Response 3 Interacting Protein 1 (IER3IP1) regulating the unfolded protein response (UPR) and extracellular matrix (ECM) protein secretion crucial for tissue integrity, with dysregulation resulting in microcephaly. Our human tissue screening technology identifies microcephaly genes and mechanisms involved in brain size control.

Cerebral organoids model the development of the human brain and have become an indispensable tool for studying neural development and neuro-developmental diseases. Comprehensive whole-organoid lineage tracing has revealed the fates of the lineages arising from each initial stem cells to be highly diverse, with lineage sizes ranging from one to more than 20,000 cells. This variability exceeds what can be explained by existing stochastic models of corticogenesis, which indicates that an additional source of stochasticity must exist. We propose the quantitative SAN model in which this additional source of stochasticity is neutral competition within a long-lived population of symmetrically dividing cells. In this model, the eventual size of a lineage is determined by its survival time within this population of symmetrically dividing cells, which due to neutral competition varies widely between individual lineages. We demonstrate the SAN model to explain the experimentally observed variability of lineage sizes and use it to derive a formula that captures the quantitative relationship between survival time and lineage size. Finally, we show that our model implies the existence of a mechanism which keeps the size of the population of symmetrically diving cells approximately constants, and that it enables this mechanism to be probed experimentally.