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RNA drugs lower lipoprotein(a) and genetically driven cholesterol
Cormac SheridanÂÂ
Standardized annotation of translated open reading frames
Jonathan M. Mudge, Jorge Ruiz-Orera, John R. Prensner, Marie A. Brunet, Ferriol Calvet, Irwin Jungreis, Jose Manuel Gonzalez, Michele Magrane, Thomas F. Martinez, Jana Felicitas Schulz, Yucheng T. Yang, M. Mar Albà , Julie L. Aspden, Pavel V. Baranov, Ariel A. Bazzini, Elspeth Bruford, Maria Jesus Martin, Lorenzo Calviello, Anne-Ruxandra Carvunis, Jin Chen, Juan Pablo Couso, Eric W. Deutsch, Paul Flicek, Adam Frankish, …Sebastiaan van HeeschÂ
PRO-ACTive sharing of clinical data
Neta Zach & Melanie L. LeitnerÂ
Sizing up beta cells made from stem cells
Kim-Vy Nguyen-Ngoc, Matthew Wortham & Maike SanderÂ
Sustainable bioimaging using a fluorescent protein with unprecedented photostability
Smartphone apps in the COVID-19 pandemic
doi : 10.1038/s41587-022-01350-x
At the beginning of the COVID-19 pandemic, analog tools such as nasopharyngeal swabs for PCR tests were center stage and the major prevention tactics of masking and physical distancing were a throwback to the 1918 influenza pandemic.
SignalP 6.0 predicts all five types of signal peptides using protein language models
Felix Teufel, José Juan Almagro Armenteros, Alexander Rosenberg Johansen, Magnús Halldór GÃÂslason, Silas Irby Pihl, Konstantinos D. Tsirigos, Ole Winther, Søren Brunak, Gunnar von Heijne & Henrik NielsenÂ
doi : 10.1038/s41587-021-01156-3
Signal peptides (SPs) are short amino acid sequences that control protein secretion and translocation in all living organisms. SPs can be predicted from sequence data, but existing algorithms are unable to detect all known types of SPs. We introduce SignalP 6.0, a machine learning model that detects all five SP types and is applicable to metagenomic data.
Fast nanopore sequencing data analysis with SLOW5
Hasindu Gamaarachchi, Hiruna Samarakoon, Sasha P. Jenner, James M. Ferguson, Timothy G. Amos, Jillian M. Hammond, Hassaan Saadat, Martin A. Smith, Sri Parameswaran & Ira W. DevesonÂ
doi : 10.1038/s41587-021-01147-4
Nanopore sequencing depends on the FAST5 file format, which does not allow efficient parallel analysis. Here we introduce SLOW5, an alternative format engineered for efficient parallelization and acceleration of nanopore data analysis.
Mitochondrial variant enrichment from high-throughput single-cell RNA sequencing resolves clonal populations
Tyler E. Miller, Caleb A. Lareau, Julia A. Verga, Erica A. K. DePasquale, Vincent Liu, Daniel Ssozi, Katalin Sandor, Yajie Yin, Leif S. Ludwig, Chadi A. El Farran, Duncan M. Morgan, Ansuman T. Satpathy, Gabriel K. Griffin, Andrew A. Lane, J. Christopher Love, Bradley E. Bernstein, Vijay G. Sankaran & Peter van GalenÂ
doi : 10.1038/s41587-022-01210-8
The combination of single-cell transcriptomics with mitochondrial DNA variant detection can be used to establish lineage relationships in primary human cells, but current methods are not scalable to interrogate complex tissues.
Accelerated identification of disease-causing variants with ultra-rapid nanopore genome sequencing
Sneha D. Goenka, John E. Gorzynski, Kishwar Shafin, Dianna G. Fisk, Trevor Pesout, Tanner D. Jensen, Jean Monlong, Pi-Chuan Chang, Gunjan Baid, Jonathan A. Bernstein, Jeffrey W. Christle, Karen P. Dalton, Daniel R. Garalde, Megan E. Grove, Joseph Guillory, Alexey Kolesnikov, Maria Nattestad, Maura R. Z. Ruzhnikov, Mehrzad Samadi, Ankit Sethia, Elizabeth Spiteri, Christopher J. Wright, Katherine Xiong, Tong Zhu, …Euan A. AshleyÂ
doi : 10.1038/s41587-022-01221-5
Whole-genome sequencing (WGS) can identify variants that cause genetic disease, but the time required for sequencing and analysis has been a barrier to its use in acutely ill patients. In the present study, we develop an approach for ultra-rapid nanopore WGS that combines an optimized sample preparation protocol, distributing sequencing over 48 flow cells, near real-time base calling and alignment, accelerated variant calling and fast variant filtration for efficient manual review.
Functional, metabolic and transcriptional maturation of human pancreatic islets derived from stem cells
Diego Balboa, Tom Barsby, Väinö Lithovius, Jonna Saarimäki-Vire, Muhmmad Omar-Hmeadi, Oleg Dyachok, Hossam Montaser, Per-Eric Lund, Mingyu Yang, Hazem Ibrahim, Anna Näätänen, Vikash Chandra, Helena Vihinen, Eija Jokitalo, Jouni Kvist, Jarkko Ustinov, Anni I. Nieminen, Emilia Kuuluvainen, Ville Hietakangas, Pekka Katajisto, Joey Lau, Per-Ola Carlsson, Sebastian Barg, Anders Tengholm & Timo OtonkoskiÂ
doi : 10.1038/s41587-022-01219-z
Transplantation of pancreatic islet cells derived from human pluripotent stem cells is a promising treatment for diabetes. Despite progress in the generation of stem-cell-derived islets (SC-islets), no detailed characterization of their functional properties has been conducted.
A comparison of experimental assays and analytical methods for genome-wide identification of active enhancers
Li Yao, Jin Liang, Abdullah Ozer, Alden King-Yung Leung, John T. Lis & Haiyuan YuÂ
doi : 10.1038/s41587-022-01211-7
Mounting evidence supports the idea that transcriptional patterns serve as more specific identifiers of active enhancers than histone marks; however, the optimal strategy to identify active enhancers both experimentally and computationally has not been determined.
CoSpar identifies early cell fate biases from single-cell transcriptomic and lineage information
Shou-Wen Wang, Michael J. Herriges, Kilian Hurley, Darrell N. Kotton & Allon M. KleinÂ
doi : 10.1038/s41587-022-01209-1
A goal of single-cell genome-wide profiling is to reconstruct dynamic transitions during cell differentiation, disease onset and drug response. Single-cell assays have recently been integrated with lineage tracing, a set of methods that identify cells of common ancestry to establish bona fide dynamic relationships between cell states.
Multiplex de Bruijn graphs enable genome assembly from long, high-fidelity reads
Anton Bankevich, Andrey V. Bzikadze, Mikhail Kolmogorov, Dmitry Antipov & Pavel A. PevznerÂ
doi : 10.1038/s41587-022-01220-6
Although most existing genome assemblers are based on de Bruijn graphs, the construction of these graphs for large genomes and large k-mer sizes has remained elusive.
Single-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue
Simon A. Hardwick, Wen Hu, Anoushka Joglekar, Li Fan, Paul G. Collier, Careen Foord, Jennifer Balacco, Samantha Lanjewar, Maureen McGuirk Sampson, Frank Koopmans, Andrey D. Prjibelski, Alla Mikheenko, Natan Belchikov, Julien Jarroux, Anne Bergstrom Lucas, Miklós Palkovits, Wenjie Luo, Teresa A. Milner, Lishomwa C. Ndhlovu, August B. Smit, John Q. Trojanowski, Virginia M. Y. Lee, Olivier Fedrigo, Steven A. Sloan, …Hagen U. TilgnerÂ
doi : 10.1038/s41587-022-01231-3
Single-nuclei RNA sequencing characterizes cell types at the gene level. However, compared to single-cell approaches, many single-nuclei cDNAs are purely intronic, lack barcodes and hinder the study of isoforms.
Endogenous ADAR-mediated RNA editing in non-human primates using stereopure chemically modified oligonucleotides
Prashant Monian, Chikdu Shivalila, Genliang Lu, Mamoru Shimizu, David Boulay, Karley Bussow, Michael Byrne, Adam Bezigian, Arindom Chatterjee, David Chew, Jigar Desai, Frank Favaloro, Jack Godfrey, Andrew Hoss, Naoki Iwamoto, Tomomi Kawamoto, Jayakanthan Kumarasamy, Anthony Lamattina, Amber Lindsey, Fangjun Liu, Richard Looby, Subramanian Marappan, Jake Metterville, Ronelle Murphy, …Chandra VargeeseÂ
doi : 10.1038/s41587-022-01225-1
Technologies that recruit and direct the activity of endogenous RNA-editing enzymes to specific cellular RNAs have therapeutic potential, but translating them from cell culture into animal models has been challenging.
Synthetic introns enable splicing factor mutation-dependent targeting of cancer cells
Khrystyna North, Salima Benbarche, Bo Liu, Joseph Pangallo, Sisi Chen, Maximilian Stahl, Jan Philipp Bewersdorf, Robert F. Stanley, Caroline Erickson, Hana Cho, Jose Mario Bello Pineda, James D. Thomas, Jacob T. Polaski, Andrea E. Belleville, Austin M. Gabel, Dylan B. Udy, Olivier Humbert, Hans-Peter Kiem, Omar Abdel-Wahab & Robert K. BradleyÂ
doi : 10.1038/s41587-022-01224-2
Many cancers carry recurrent, change-of-function mutations affecting RNA splicing factors. Here, we describe a method to harness this abnormal splicing activity to drive splicing factor mutation-dependent gene expression to selectively eliminate tumor cells.
Learning protein fitness models from evolutionary and assay-labeled data
Chloe Hsu, Hunter Nisonoff, Clara Fannjiang & Jennifer ListgartenÂ
Designing sensitive viral diagnostics with machine learning
Hayden C. Metsky, Nicole L. Welch, Priya P. Pillai, Nicholas J. Haradhvala, Laurie Rumker, Sreekar Mantena, Yibin B. Zhang, David K. Yang, Cheri M. Ackerman, Juliane Weller, Paul C. Blainey, Cameron Myhrvold, Michael Mitzenmacher & Pardis C. SabetiÂ
doi : 10.1038/s41587-022-01213-5
Design of nucleic acid-based viral diagnostics typically follows heuristic rules and, to contend with viral variation, focuses on a genome’s conserved regions. A design process could, instead, directly optimize diagnostic effectiveness using a learned model of sensitivity for targets and their variants.
A highly photostable and bright green fluorescent protein
Masahiko Hirano, Ryoko Ando, Satoshi Shimozono, Mayu Sugiyama, Noriyo Takeda, Hiroshi Kurokawa, Ryusaku Deguchi, Kazuki Endo, Kei Haga, Reiko Takai-Todaka, Shunsuke Inaura, Yuta Matsumura, Hiroshi Hama, Yasushi Okada, Takahiro Fujiwara, Takuya Morimoto, Kazuhiko Katayama & Atsushi MiyawakiÂ
doi : 10.1038/s41587-022-01278-2
The low photostability of fluorescent proteins is a limiting factor in many applications of fluorescence microscopy. Here we present StayGold, a green fluorescent protein (GFP) derived from the jellyfish Cytaeis uchidae.
Computationally designed dual-color MRI reporters for noninvasive imaging of transgene expression
Hyla Allouche-Arnon, Olga Khersonsky, Nishanth D. Tirukoti, Yoav Peleg, Orly Dym, Shira Albeck, Alexander Brandis, Tevie Mehlman, Liat Avram, Talia Harris, Nirbhay N. Yadav, Sarel J. Fleishman & Amnon Bar-ShirÂ
doi : 10.1038/s41587-021-01162-5
Imaging of gene-expression patterns in live animals is difficult to achieve with fluorescent proteins because tissues are opaque to visible light. Imaging of transgene expression with magnetic resonance imaging (MRI), which penetrates to deep tissues, has been limited by single reporter visualization capabilities.
Publisher Correction: Biotech patenting 2019
Brady Huggett & Kathryn PaisnerÂ
Publisher Correction: Biotech patenting 2020
Brady Huggett & Kathryn PaisnerÂ
What digitalization in biology R&D means for biotech companies and life scientists
Sybil Wong, Mingke Pan, Allen Shaw & Markus GershaterÂ
