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Gene expression predictions and networks in natural populations supports the omnigenic theory

Authors
  • Chateigner, Aurélien1
  • Lesage-Descauses, Marie-Claude1
  • Rogier, Odile1
  • Jorge, Véronique1
  • Leplé, Jean-Charles2
  • Brunaud, Véronique3, 4
  • Roux, Christine Paysant-Le3, 4
  • Soubigou-Taconnat, Ludivine3, 4
  • Martin-Magniette, Marie-Laure3, 4, 5
  • Sanchez, Leopoldo1
  • Segura, Vincent1, 6
  • 1 BioForA, INRAE, ONF, Orléans, France , Orléans (France)
  • 2 BIOGECO, INRAE, Univ. Bordeaux, Cestas, France , Cestas (France)
  • 3 Institute of Plant Sciences Paris-Saclay (IPS2), CNRS, INRAE, Université Paris-Sud, Université d’Evry, Université Paris-Saclay, Gif sur Yvette, France , Gif sur Yvette (France)
  • 4 Institute of Plant Sciences Paris-Saclay (IPS2), CNRS, INRAE, Université Paris-Diderot, Sorbonne Paris-Cité, Gif sur Yvette, France , Gif sur Yvette (France)
  • 5 MIA-Paris, AgroParisTech, INRAE, Paris, France , Paris (France)
  • 6 AGAP, Université Montpellier, CIRAD, INRAE, Montpellier SupAgro, Montpellier, France , Montpellier (France)
Type
Published Article
Journal
BMC Genomics
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Jun 22, 2020
Volume
21
Issue
1
Identifiers
DOI: 10.1186/s12864-020-06809-2
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundRecent literature on the differential role of genes within networks distinguishes core from peripheral genes. If previous works have shown contrasting features between them, whether such categorization matters for phenotype prediction remains to be studied.ResultsWe measured 17 phenotypic traits for 241 cloned genotypes from a Populus nigra collection, covering growth, phenology, chemical and physical properties. We also sequenced RNA for each genotype and built co-expression networks to define core and peripheral genes. We found that cores were more differentiated between populations than peripherals while being less variable, suggesting that they have been constrained through potentially divergent selection. We also showed that while cores were overrepresented in a subset of genes statistically selected for their capacity to predict the phenotypes (by Boruta algorithm), they did not systematically predict better than peripherals or even random genes.ConclusionOur work is the first attempt to assess the importance of co-expression network connectivity in phenotype prediction. While highly connected core genes appear to be important, they do not bear enough information to systematically predict better quantitative traits than other gene sets.

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