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3D-cardiomics: A spatial transcriptional atlas of the mammalian heart

  • Monika Mohenska
  • , Nathalia M. Tan
  • , Alex Tokolyi
  • , Milena B. Furtado
  • , Mauro W. Costa
  • , Andrew J. Perry
  • , Jessica Hatwell-Humble
  • , Karel van Duijvenboden
  • , Hieu T. Nim
  • , Yuan M. M. Ji
  • , Natalie Charitakis
  • , Denis Bienroth
  • , Francesca Bolk
  • , Celine Vivien
  • , Anja S. Knaupp
  • , David R. Powell
  • , David A. Elliott
  • , Enzo R. Porrello
  • , Susan K. Nilsson
  • , Gonzalo del Monte-Nieto
  • Nadia A. Rosenthal, Fernando J. Rossello*, Jose M. Polo, Mirana Ramialison
*Corresponding author for this work
  • Monash University
  • Jackson Laboratory
  • CSIRO
  • Amsterdam UMC - University of Amsterdam
  • Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC, Australia
  • Systems Biology Institute Australia, Clayton, Victoria, Australia
  • University of Melbourne
  • Imperial College London

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Understanding the spatial gene expression and regulation in the heart is key to uncovering its developmental and physiological processes, during homeostasis and disease. Numerous techniques exist to gain gene expression and regulation information in organs such as the heart, but few utilize intuitive true-to-life three-dimensional representations to analyze and visualise results. Here we combined transcriptomics with 3D-modelling to interrogate spatial gene expression in the mammalian heart. For this, we microdissected and sequenced transcriptome-wide 18 anatomical sections of the adult mouse heart. Our study has unveiled known and novel genes that display complex spatial expression in the heart sub-compartments. We have also created 3D-cardiomics, an interface for spatial transcriptome analysis and visualization that allows the easy exploration of these data in a 3D model of the heart. 3D-cardiomics is accessible from http://3d-cardiomics.erc.monash.edu/.
Original languageEnglish
Pages (from-to)20-32
Number of pages13
JournalJournal of molecular and cellular cardiology
Volume163
DOIs
Publication statusPublished - 1 Feb 2022

Keywords

  • 3D organ
  • Bioinformatics
  • Cardiac model
  • Cardiac systems
  • Data visualization
  • Spatial transcriptomics
  • Systems biology

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