Molecular phenology in plants: in natura systems biology for the comprehensive understanding of seasonal responses under natural environments

New Phytol. 2016 Apr;210(2):399-412. doi: 10.1111/nph.13733. Epub 2015 Nov 2.

Abstract

Phenology refers to the study of seasonal schedules of organisms. Molecular phenology is defined here as the study of the seasonal patterns of organisms captured by molecular biology techniques. The history of molecular phenology is reviewed briefly in relation to advances in the quantification technology of gene expression. High-resolution molecular phenology (HMP) data have enabled us to study phenology with an approach of in natura systems biology. I review recent analyses of FLOWERING LOCUS C (FLC), a temperature-responsive repressor of flowering, along the six steps in the typical flow of in natura systems biology. The extensive studies of the regulation of FLC have made this example a successful case in which a comprehensive understanding of gene functions has been progressing. The FLC-mediated long-term memory of past temperatures creates time lags with other seasonal signals, such as photoperiod and short-term temperature. Major signals that control flowering time have a phase lag between them under natural conditions, and hypothetical phase lag calendars are proposed as mechanisms of season detection in plants. Transcriptomic HMP brings a novel strategy to the study of molecular phenology, because it provides a comprehensive representation of plant functions. I discuss future perspectives of molecular phenology from the standpoints of molecular biology, evolutionary biology and ecology.

Keywords: FLOWERING LOCUS C (FLC); flowering time; gene expression; high-resolution molecular phenology (HMP); in natura systems biology; phase lag calendar; phenological modeling; temperature response.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Environment*
  • Genes, Plant
  • Models, Biological
  • Seasons*
  • Signal Transduction
  • Systems Biology*