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Record W4388489852 · doi:10.1016/j.cell.2023.09.025

Debugging and consolidating multiple synthetic chromosomes reveals combinatorial genetic interactions

2023· article· en· W4388489852 on OpenAlexfundno aff
Yu Zhao, Camila Coelho, Amanda L. Hughes, Luciana Lazar‐Stefanita, Sandy Yang, Aaron N. Brooks, Roy Walker, Weimin Zhang, Stephanie Lauer, Cindy Hernandez, Jitong Cai, Leslie A. Mitchell, Neta Agmon, Yue Shen, Joseph Sall, Viola Fanfani, Anavi Jalan, Jordan Rivera, Feng‐Xia Liang, Joel S. Bader, Giovanni Stracquadanio, Lars M. Steinmetz, Yizhi Cai, Jef D. Boeke

Bibliographic record

VenueCell · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
FundersTianjin UniversityTsinghua UniversityMacquarie UniversityVolkswagen FoundationYork UniversityJohns Hopkins UniversityImperial College LondonNational Cancer InstituteNational Institutes of HealthNational University of SingaporeNational Science Foundation
KeywordsBiologyGeneticsCRISPRGenomeComputational biologyChromosomeCas9Gene

Abstract

fetched live from OpenAlex

The Sc2.0 project is building a eukaryotic synthetic genome from scratch. A major milestone has been achieved with all individual Sc2.0 chromosomes assembled. Here, we describe the consolidation of multiple synthetic chromosomes using advanced endoreduplication intercrossing with tRNA expression cassettes to generate a strain with 6.5 synthetic chromosomes. The 3D chromosome organization and transcript isoform profiles were evaluated using Hi-C and long-read direct RNA sequencing. We developed CRISPR Directed Biallelic URA3 -assisted Genome Scan, or "CRISPR D-BUGS," to map phenotypic variants caused by specific designer modifications, known as "bugs." We first fine-mapped a bug in synthetic chromosome II ( synII ) and then discovered a combinatorial interaction associated with synIII and synX , revealing an unexpected genetic interaction that links transcriptional regulation, inositol metabolism, and tRNA Ser CGA abundance. Finally, to expedite consolidation, we employed chromosome substitution to incorporate the largest chromosome ( synIV ), thereby consolidating >50% of the Sc2.0 genome in one strain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.276
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations101
Published2023
Admission routes1
Has abstractno

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