Department of Neuroscience, Baylor College of Medicine, Houston, United States; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States; Department of Anatomic Pathology, University of California San Francisco, San Francisco, United States
Federico Scala
Department of Neuroscience, Baylor College of Medicine, Houston, United States; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States
Paul G Fahey
Department of Neuroscience, Baylor College of Medicine, Houston, United States; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States
Department of Neuroscience, Baylor College of Medicine, Houston, United States; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States; Department of Computer Science, University of Tübingen, Tübingen, Germany; Interfaculty Institute for Biomedical Informatics, University of Tübingen, Tübingen, Germany
Stelios Papadopoulos
Department of Neuroscience, Baylor College of Medicine, Houston, United States; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States
Zheng H Tan
Department of Neuroscience, Baylor College of Medicine, Houston, United States; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States
Per Johnsson
Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
Leonard Hartmanis
Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
Shuang Li
Department of Neuroscience, Baylor College of Medicine, Houston, United States; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States
Ronald J Cotton
Department of Neuroscience, Baylor College of Medicine, Houston, United States; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States
Department of Neuroscience, Baylor College of Medicine, Houston, United States; Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, United States
Rickard Sandberg
Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany; Department of Computer Science, University of Tübingen, Tübingen, Germany
Xiaolong Jiang
Department of Neuroscience, Baylor College of Medicine, Houston, United States; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States; Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston, United States
Department of Neuroscience, Baylor College of Medicine, Houston, United States; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States; Department of Electrical and Computer Engineering, Rice University, Houston, United States
Clones of excitatory neurons derived from a common progenitor have been proposed to serve as elementary information processing modules in the neocortex. To characterize the cell types and circuit diagram of clonally related excitatory neurons, we performed multi-cell patch clamp recordings and Patch-seq on neurons derived from Nestin-positive progenitors labeled by tamoxifen induction at embryonic day 10.5. The resulting clones are derived from two radial glia on average, span cortical layers 2–6, and are composed of a random sampling of transcriptomic cell types. We find an interaction between shared lineage and connection type: related neurons are more likely to be connected vertically across cortical layers, but not laterally within the same layer. These findings challenge the view that related neurons show uniformly increased connectivity and suggest that integration of vertical intra-clonal input with lateral inter-clonal input may represent a developmentally programmed connectivity motif supporting the emergence of functional circuits.