Complete sequencing of ape genomes

Kavli Affiliate: Erich Jarvis

| Authors: DongAhn Yoo, Arang Rhie, Prajna Hebbar, Francesca Antonacci, Glennis A. Logsdon, Steven J. Solar, Dmitry Antipov, Brandon D. Pickett, Yana Safonova, Francesco Montinaro, Yanting Luo, Joanna Malukiewicz, Jessica M. Storer, Jiadong Lin, Abigail N. Sequeira, Riley J. Mangan, Glenn Hickey, Graciela Monfort Anez, Parithi Balachandran, Anton Bankevich, Christine R. Beck, Arjun Biddanda, Matthew Borchers, Gerard G. Bouffard, Emry Brannan, Shelise Y. Brooks, Lucia Carbone, Laura Carrel, Agnes P. Chan, Juyun Crawford, Mark Diekhans, Eric Engelbrecht, Cedric Feschotte, Giulio Formenti, Gage H. Garcia, Luciana de Gennaro, David Gilbert, Richard E. Green, Andrea Guarracino, Ishaan Gupta, Diana Haddad, Junmin Han, Robert S. Harris, Gabrielle A. Hartley, William T. Harvey, Michael Hiller, Kendra Hoekzema, Marlys L. Houck, Hyeonsoo Jeong, Kaivan Kamali, Manolis Kellis, Bryce Ki lle, Chul Lee, Youngho Lee, William Lees, Alexandra P. Lewis, Qiuhui Li, Mark Loftus, Yong Hwee Eddie Loh, Hailey Loucks, Jian Ma, Yafei Mao, Juan F. I. Martinez, Patrick Masterson, Rajiv C. McCoy, Barbara McGrath, Sean McKinney, Britta S. Meyer, Karen H. Miga, Saswat K. Mohanty, Katherine M. Munson, Karol Pal, Matt Pennell, Pavel A. Pevzner, David Porubsky, Tamara Potapova, Francisca R. Ringeling, Joana L. Rocha, Oliver A. Ryder, Samuel Sacco, Swati Saha, Takayo Sasaki, Michael C. Schatz, Nicholas J. Schork, Cole Shanks, Linnea Smeds, Dongmin R. Son, Cynthia Steiner, Alexander P. Sweeten, Michael G. Tassia, Francoise Thibaud-Nissen, Edmundo Torres-Gonzalez, Mihir Trivedi, Wenjie Wei, Julie Wertz, Muyu Yang, Panpan Zhang, Shilong Zhang, Yang Zhang, Zhenmiao Zhang, Sarah A. Zhao, Yixin Zhu, Erich D. Jarvis, Jennifer L. Gerton, Iker Rivas-Gonzalez, Benedict Paten, Zachary A. Szpiech, Christian D. Huber, Tobias L. Lenz, Miriam K. Konkel, Soojin V. Yi, Stefan Canzar, Corey T. Wa tson, Peter H. Sudmant, Erin Molloy, Erik Garrison, Craig B. Lowe, Mario Ventura, Rachel J. O’Neill, Sergey Koren, Kateryna D. Makova, Adam M. Phillippy and Evan E. Eichler

| Summary:

Approximately four in five neurons are excitatory. This is true across functional regions and species. Why do we have so many excitatory neurons? Little is known. Here we provide a normative answer to this question. We designed a task-agnostic, learning-independent and experiment-testable measurement of functional complexity, which quantifies the network’s ability to solve complex problems. Using the first neuron level full connectome of a species—the larva Drosophila—we discovered the optimal Excitatory-Inhibitory (E-I) ratio that maximizes the functional complexity: 75-81% percentage of neurons are excitatory. This number is consistent with the true distribution observed via scRNA-seq. We found that the abundance of excitatory neurons confers an advantage in functional complexity, but only when inhibitory neurons are highly connected. In contrast, when the E-I identities are sampled uniformly (not dependent on connectivity), the optimal E-I ratio falls around equal population size, and its overall achieved functional complexity is sub-optimal. Our functional complexity measurement offers a normative explanation for the over-abundance of excitatory neurons in the brain. We anticipate that this approach will further uncover the functional significance of various neural network structures.

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