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A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.

Aravind Subramanian1, Rajiv Narayan1, Steven M Corsello2

  • 1Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.

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Summary
This summary is machine-generated.

The Connectivity Map (CMap) has been scaled up 1,000-fold using the L1000 profiling method. This expanded CMap connects genes, drugs, and diseases via gene-expression signatures for drug discovery and clinical applications.

Keywords:
Functional genomicschemical biologygene expression profiling

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Area of Science:

  • Genomics
  • Systems biology
  • Pharmacogenomics

Background:

  • The Connectivity Map (CMap) links biological states through gene-expression signatures.
  • Previous CMap versions were limited in scale and scope.

Purpose of the Study:

  • To report a 1,000-fold scale-up of the CMap using the L1000 technology.
  • To demonstrate the utility of the expanded CMap for biological discovery and clinical applications.

Main Methods:

  • Developed and implemented a low-cost, high-throughput reduced representation expression profiling method termed L1000.
  • Generated over 1.3 million L1000 profiles as part of the NIH LINCS Consortium.
  • Validated L1000 reproducibility and its ability to computationally infer unmeasured transcript expression.

Main Results:

  • The expanded CMap significantly increases the scale of gene-expression data available.
  • L1000 profiling is highly reproducible and comparable to RNA sequencing.
  • Computational inference successfully predicted expression levels for 81% of non-measured transcripts.
  • The expanded CMap facilitates discovery of small molecule mechanisms of action.
  • It aids in functional annotation of genetic variants in disease genes.
  • Informs clinical trial design and patient stratification.

Conclusions:

  • The scaled-up CMap, powered by L1000, represents a major advancement in systems pharmacology.
  • This resource enables novel insights into drug mechanisms, disease genetics, and personalized medicine.
  • The data and analysis tools are publicly available at https://clue.io.