A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex.

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1-3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas-containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities-is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

CloVR-Comparative: automated, cloud-enabled comparative microbial genome sequence analysis pipeline

Abstract Background The benefit of increasing genomic sequence data to the scientific community depends on easy-to-use, scalable bioinformatics support. CloVR-Comparative combines commonly used bioinformatics tools into an intuitive, automated, and cloud-enabled analysis pipeline for comparative microbial genomics. Results CloVR-Comparative runs on annotated complete or draft genome sequences that are uploaded by the user or selected via a taxonomic tree-based user interface and downloaded from NCBI. CloVR-Comparative runs reference-free multiple whole-genome alignments to determine unique, shared and core coding sequences (CDSs) and single nucleotide polymorphisms (SNPs). Output includes short summary reports and detailed text-based results files, graphical visualizations (phylogenetic trees, circular figures), and a database file linked to the Sybil comparative genome browser. Data up- and download, pipeline configuration and monitoring, and access to Sybil are managed through CloVR-Comparative web interface. CloVR-Comparative and Sybil are distributed as part of the CloVR virtual appliance, which runs on local computers or the Amazon EC2 cloud. Representative datasets (e.g. 40 draft and complete Escherichia coli genomes) are processed in <36 h on a local desktop or at a cost of <$20 on EC2. Conclusions CloVR-Comparative allows anybody with Internet access to run comparative genomics projects, while eliminating the need for on-site computational resources and expertise

Data from: Aligner optimization increases accuracy and decreases compute times in multi-species sequence data

As sequencing technologies have evolved, the tools to analyze these sequences have made similar advances. However, for multi-species samples, we observed important and adverse differences in alignment specificity and computation time for bwa- mem (Burrows–Wheeler aligner-maximum exact matches) relative to bwa-aln. Therefore, we sought to optimize bwa-mem for alignment of data from multi-species samples in order to reduce alignment time and increase the specificity of alignments. In the multi-species cases examined, there was one majority member (i.e. Plasmodium falciparum or Brugia malayi) and one minority member (i.e. human or the Wolbachia endosymbiont wBm) of the sequence data. Increasing bwa-mem seed length from the default value reduced the number of read pairs from the majority sequence member that incorrectly aligned to the reference genome of the minority sequence member. Combining both source genomes into a single reference genome increased the specificity of mapping, while also reducing the central processing unit (CPU) time. In Plasmodium, at a seed length of 18 nt, 24.1 % of reads mapped to the human genome using 1.7±0.1 CPU hours, while 83.6 % of reads mapped to the Plasmodium genome using 0.2±0.0 CPU hours (total: 107.7 % reads mapping; in 1.9±0.1 CPU hours). In contrast, 97.1 % of the reads mapped to a combined Plasmodium–human reference in only 0.7±0.0 CPU hours. Overall, the results suggest that combining all references into a single reference database and using a 23 nt seed length reduces the computational time, while maximizing specificity. Similar results were found for simulated sequence reads from a mock metagenomic data set. We found similar improvements to computation time in a publicly available human-only data set

A multimodal cell census and atlas of the mammalian primary motor cortex

none258Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1-5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.openCallaway, Edward M.; Dong, Hong-Wei; Ecker, Joseph R.; Hawrylycz, Michael J.; Huang, Z. Josh; Lein, Ed S.; Ngai, John; Osten, Pavel; Ren, Bing; Tolias, Andreas Savas; White, Owen; Zeng, Hongkui; Zhuang, Xiaowei; Ascoli, Giorgio A.; Behrens, M. Margarita; Chun, Jerold; Feng, Guoping; Gee, James C.; Ghosh, Satrajit S.; Halchenko, Yaroslav O.; Hertzano, Ronna; Lim, Byung Kook; Martone, Maryann E.; Ng, Lydia; Pachter, Lior; Ropelewski, Alexander J.; Tickle, Timothy L.; Yang, X. William; Zhang, Kun; Bakken, Trygve E.; Berens, Philipp; Daigle, Tanya L.; Harris, Julie A.; Jorstad, Nikolas L.; Kalmbach, Brian E.; Kobak, Dmitry; Li, Yang Eric; Liu, Hanqing; Matho, Katherine S.; Mukamel, Eran A.; Naeemi, Maitham; Scala, Federico; Tan, Pengcheng; Ting, Jonathan T.; Xie, Fangming; Zhang, Meng; Zhang, Zhuzhu; Zhou, Jingtian; Zingg, Brian; Armand, Ethan; Yao, Zizhen; Bertagnolli, Darren; Casper, Tamara; Crichton, Kirsten; Dee, Nick; Diep, Dinh; Ding, Song-Lin; Dong, Weixiu; Dougherty, Elizabeth L.; Fong, Olivia; Goldman, Melissa; Goldy, Jeff; Hodge, Rebecca D.; Hu, Lijuan; Keene, C. Dirk; Krienen, Fenna M.; Kroll, Matthew; Lake, Blue B.; Lathia, Kanan; Linnarsson, Sten; Liu, Christine S.; Macosko, Evan Z.; McCarroll, Steven A.; McMillen, Delissa; Nadaf, Naeem M.; Nguyen, Thuc Nghi; Palmer, Carter R.; Pham, Thanh; Plongthongkum, Nongluk; Reed, Nora M.; Regev, Aviv; Rimorin, Christine; Romanow, William J.; Savoia, Steven; Siletti, Kimberly; Smith, Kimberly; Sulc, Josef; Tasic, Bosiljka; Tieu, Michael; Torkelson, Amy; Tung, Herman; van Velthoven, Cindy T. J.; Vanderburg, Charles R.; Yanny, Anna Marie; Fang, Rongxin; Hou, Xiaomeng; Lucero, Jacinta D.; Osteen, Julia K.; Pinto-Duarte, Antonio; Poirion, Olivier; Preissl, Sebastian; Wang, Xinxin; Aldridge, Andrew I.; Bartlett, Anna; Boggeman, Lara; O’Connor, Carolyn; Castanon, Rosa G.; Chen, Huaming; Fitzpatrick, Conor; Luo, Chongyuan; Nery, Joseph R.; Nunn, Michael; Rivkin, Angeline C.; Tian, Wei; Dominguez, Bertha; Ito-Cole, Tony; Jacobs, Matthew; Jin, Xin; Lee, Cheng-Ta; Lee, Kuo-Fen; Miyazaki, Paula Assakura; Pang, Yan; Rashid, Mohammad; Smith, Jared B.; Vu, Minh; Williams, Elora; Biancalani, Tommaso; Booeshaghi, A. Sina; Crow, Megan; Dudoit, Sandrine; Fischer, Stephan; Gillis, Jesse; Hu, Qiwen; Kharchenko, Peter V.; Niu, Sheng-Yong; Ntranos, Vasilis; Purdom, Elizabeth; Risso, Davide; de Bézieux, Hector Roux; Somasundaram, Saroja; Street, Kelly; Svensson, Valentine; Vaishnav, Eeshit Dhaval; Van den Berge, Koen; Welch, Joshua D.; An, Xu; Bateup, Helen S.; Bowman, Ian; Chance, Rebecca K.; Foster, Nicholas N.; Galbavy, William; Gong, Hui; Gou, Lin; Hatfield, Joshua T.; Hintiryan, Houri; Hirokawa, Karla E.; Kim, Gukhan; Kramer, Daniel J.; Li, Anan; Li, Xiangning; Luo, Qingming; Muñoz-Castañeda, Rodrigo; Stafford, David A.; Feng, Zhao; Jia, Xueyan; Jiang, Shengdian; Jiang, Tao; Kuang, Xiuli; Larsen, Rachael; Lesnar, Phil; Li, Yaoyao; Li, Yuanyuan; Liu, Lijuan; Peng, Hanchuan; Qu, Lei; Ren, Miao; Ruan, Zongcai; Shen, Elise; Song, Yuanyuan; Wakeman, Wayne; Wang, Peng; Wang, Yimin; Wang, Yun; Yin, Lulu; Yuan, Jing; Zhao, Sujun; Zhao, Xuan; Narasimhan, Arun; Palaniswamy, Ramesh; Banerjee, Samik; Ding, Liya; Huilgol, Dhananjay; Huo, Bingxing; Kuo, Hsien-Chi; Laturnus, Sophie; Li, Xu; Mitra, Partha P.; Mizrachi, Judith; Wang, Quanxin; Xie, Peng; Xiong, Feng; Yu, Yang; Eichhorn, Stephen W.; Berg, Jim; Bernabucci, Matteo; Bernaerts, Yves; Cadwell, Cathryn René; Castro, Jesus Ramon; Dalley, Rachel; Hartmanis, Leonard; Horwitz, Gregory D.; Jiang, Xiaolong; Ko, Andrew L.; Miranda, Elanine; Mulherkar, Shalaka; Nicovich, Philip R.; Owen, Scott F.; Sandberg, Rickard; Sorensen, Staci A.; Tan, Zheng Huan; Allen, Shona; Hockemeyer, Dirk; Lee, Angus Y.; Veldman, Matthew B.; Adkins, Ricky S.; Ament, Seth A.; Bravo, Héctor Corrada; Carter, Robert; Chatterjee, Apaala; Colantuoni, Carlo; Crabtree, Jonathan; Creasy, Heather; Felix, Victor; Giglio, Michelle; Herb, Brian R.; Kancherla, Jayaram; Mahurkar, Anup; McCracken, Carrie; Nickel, Lance; Olley, Dustin; Orvis, Joshua; Schor, Michael; Hood, Greg; Dichter, Benjamin; Grauer, Michael; Helba, Brian; Bandrowski, Anita; Barkas, Nikolaos; Carlin, Benjamin; D’Orazi, Florence D.; Degatano, Kylee; Gillespie, Thomas H.; Khajouei, Farzaneh; Konwar, Kishori; Thompson, Carol; Kelly, Kathleen; Mok, Stephanie; Sunkin, SusanCallaway, Edward M.; Dong, Hong-Wei; Ecker, Joseph R.; Hawrylycz, Michael J.; Huang, Z. Josh; Lein, Ed S.; Ngai, John; Osten, Pavel; Ren, Bing; Tolias, Andreas Savas; White, Owen; Zeng, Hongkui; Zhuang, Xiaowei; Ascoli, Giorgio A.; Behrens, M. Margarita; Chun, Jerold; Feng, Guoping; Gee, James C.; Ghosh, Satrajit S.; Halchenko, Yaroslav O.; Hertzano, Ronna; Lim, Byung Kook; Martone, Maryann E.; Ng, Lydia; Pachter, Lior; Ropelewski, Alexander J.; Tickle, Timothy L.; Yang, X. William; Zhang, Kun; Bakken, Trygve E.; Berens, Philipp; Daigle, Tanya L.; Harris, Julie A.; Jorstad, Nikolas L.; Kalmbach, Brian E.; Kobak, Dmitry; Li, Yang Eric; Liu, Hanqing; Matho, Katherine S.; Mukamel, Eran A.; Naeemi, Maitham; Scala, Federico; Tan, Pengcheng; Ting, Jonathan T.; Xie, Fangming; Zhang, Meng; Zhang, Zhuzhu; Zhou, Jingtian; Zingg, Brian; Armand, Ethan; Yao, Zizhen; Bertagnolli, Darren; Casper, Tamara; Crichton, Kirsten; Dee, Nick; Diep, Dinh; Ding, Song-Lin; Dong, Weixiu; Dougherty, Elizabeth L.; Fong, Olivia; Goldman, Melissa; Goldy, Jeff; Hodge, Rebecca D.; Hu, Lijuan; Keene, C. Dirk; Krienen, Fenna M.; Kroll, Matthew; Lake, Blue B.; Lathia, Kanan; Linnarsson, Sten; Liu, Christine S.; Macosko, Evan Z.; Mccarroll, Steven A.; Mcmillen, Delissa; Nadaf, Naeem M.; Nguyen, Thuc Nghi; Palmer, Carter R.; Pham, Thanh; Plongthongkum, Nongluk; Reed, Nora M.; Regev, Aviv; Rimorin, Christine; Romanow, William J.; Savoia, Steven; Siletti, Kimberly; Smith, Kimberly; Sulc, Josef; Tasic, Bosiljka; Tieu, Michael; Torkelson, Amy; Tung, Herman; van Velthoven, Cindy T. J.; Vanderburg, Charles R.; Yanny, Anna Marie; Fang, Rongxin; Hou, Xiaomeng; Lucero, Jacinta D.; Osteen, Julia K.; Pinto-Duarte, Antonio; Poirion, Olivier; Preissl, Sebastian; Wang, Xinxin; Aldridge, Andrew I.; Bartlett, Anna; Boggeman, Lara; O’Connor, Carolyn; Castanon, Rosa G.; Chen, Huaming; Fitzpatrick, Conor; Luo, Chongyuan; Nery, Joseph R.; Nunn, Michael; Rivkin, Angeline C.; Tian, Wei; Dominguez, Bertha; Ito-Cole, Tony; Jacobs, Matthew; Jin, Xin; Lee, Cheng-Ta; Lee, Kuo-Fen; Miyazaki, Paula Assakura; Pang, Yan; Rashid, Mohammad; Smith, Jared B.; Vu, Minh; Williams, Elora; Biancalani, Tommaso; Booeshaghi, A. Sina; Crow, Megan; Dudoit, Sandrine; Fischer, Stephan; Gillis, Jesse; Hu, Qiwen; Kharchenko, Peter V.; Niu, Sheng-Yong; Ntranos, Vasilis; Purdom, Elizabeth; Risso, Davide; de Bézieux, Hector Roux; Somasundaram, Saroja; Street, Kelly; Svensson, Valentine; Vaishnav, Eeshit Dhaval; Van den Berge, Koen; Welch, Joshua D.; An, Xu; Bateup, Helen S.; Bowman, Ian; Chance, Rebecca K.; Foster, Nicholas N.; Galbavy, William; Gong, Hui; Gou, Lin; Hatfield, Joshua T.; Hintiryan, Houri; Hirokawa, Karla E.; Kim, Gukhan; Kramer, Daniel J.; Li, Anan; Li, Xiangning; Luo, Qingming; Muñoz-Castañeda, Rodrigo; Stafford, David A.; Feng, Zhao; Jia, Xueyan; Jiang, Shengdian; Jiang, Tao; Kuang, Xiuli; Larsen, Rachael; Lesnar, Phil; Li, Yaoyao; Li, Yuanyuan; Liu, Lijuan; Peng, Hanchuan; Qu, Lei; Ren, Miao; Ruan, Zongcai; Shen, Elise; Song, Yuanyuan; Wakeman, Wayne; Wang, Peng; Wang, Yimin; Wang, Yun; Yin, Lulu; Yuan, Jing; Zhao, Sujun; Zhao, Xuan; Narasimhan, Arun; Palaniswamy, Ramesh; Banerjee, Samik; Ding, Liya; Huilgol, Dhananjay; Huo, Bingxing; Kuo, Hsien-Chi; Laturnus, Sophie; Li, Xu; Mitra, Partha P.; Mizrachi, Judith; Wang, Quanxin; Xie, Peng; Xiong, Feng; Yu, Yang; Eichhorn, Stephen W.; Berg, Jim; Bernabucci, Matteo; Bernaerts, Yves; Cadwell, Cathryn René; Castro, Jesus Ramon; Dalley, Rachel; Hartmanis, Leonard; Horwitz, Gregory D.; Jiang, Xiaolong; Ko, Andrew L.; Miranda, Elanine; Mulherkar, Shalaka; Nicovich, Philip R.; Owen, Scott F.; Sandberg, Rickard; Sorensen, Staci A.; Tan, Zheng Huan; Allen, Shona; Hockemeyer, Dirk; Lee, Angus Y.; Veldman, Matthew B.; Adkins, Ricky S.; Ament, Seth A.; Bravo, Héctor Corrada; Carter, Robert; Chatterjee, Apaala; Colantuoni, Carlo; Crabtree, Jonathan; Creasy, Heather; Felix, Victor; Giglio, Michelle; Herb, Brian R.; Kancherla, Jayaram; Mahurkar, Anup; Mccracken, Carrie; Nickel, Lance; Olley, Dustin; Orvis, Joshua; Schor, Michael; Hood, Greg; Dichter, Benjamin; Grauer, Michael; Helba, Brian; Bandrowski, Anita; Barkas, Nikolaos; Carlin, Benjamin; D’Orazi, Florence D.; Degatano, Kylee; Gillespie, Thomas H.; Khajouei, Farzaneh; Konwar, Kishori; Thompson, Carol; Kelly, Kathleen; Mok, Stephanie; Sunkin, Susa