BACKGROUND AND AIMS: It has been proposed that having too much DNA may carry physiological consequences for plants. The strong correlation between DNA content, cell size and cell division rate could lead to predictable morphological variation in plants, including a negative relationship with leaf mass per unit area (LMA). In addition, the possible increased demand for resources in species with high DNA content may have downstream effects on maximal metabolic efficiency, including decreased metabolic rates. METHODS: Tests were made for genome size-dependent variation in LMA and metabolic rates (mass-based photosynthetic rate and dark respiration rate) using our own measurements and data from a plant functional trait database (Glopnet). These associations were tested using two metrics of genome size: bulk DNA amount (2C DNA) and monoploid genome size (1Cx DNA). The data were analysed using an evolutionary framework that included a regression analysis and independent contrasts using a phylogenetic tree with estimates of molecular diversification times. A contribution index for the LMA data set was also calculated to determine which divergences have the greatest influence on the relationship between genome size and LMA. KEY RESULTS AND CONCLUSIONS: A significant negative association was found between bulk DNA amount and LMA in angiosperms. This was primarily a result of influential divergences that may represent early shifts in growth form. However, divergences in bulk DNA amount were positively associated with divergences in LMA, suggesting that the relationship may be indirect and mediated through other traits directly related to genome size. There was a significant negative association between genome size and metabolic rates that was driven by a basal divergence between angiosperms and gymnosperms; no significant independent contrast results were found. Therefore, it is concluded that genome size-dependent constraints acting on metabolic efficiency may not exist within seed plants.
BACKGROUND AND AIMS: It has been proposed that having too much DNA may carry physiological consequences for plants. The strong correlation between DNA content, cell size and cell division rate could lead to predictable morphological variation in plants, including a negative relationship with leaf mass per unit area (LMA). In addition, the possible increased demand for resources in species with high DNA content may have downstream effects on maximal metabolic efficiency, including decreased metabolic rates. METHODS: Tests were made for genome size-dependent variation in LMA and metabolic rates (mass-based photosynthetic rate and dark respiration rate) using our own measurements and data from a plant functional trait database (Glopnet). These associations were tested using two metrics of genome size: bulk DNA amount (2C DNA) and monoploid genome size (1Cx DNA). The data were analysed using an evolutionary framework that included a regression analysis and independent contrasts using a phylogenetic tree with estimates of molecular diversification times. A contribution index for the LMA data set was also calculated to determine which divergences have the greatest influence on the relationship between genome size and LMA. KEY RESULTS AND CONCLUSIONS: A significant negative association was found between bulk DNA amount and LMA in angiosperms. This was primarily a result of influential divergences that may represent early shifts in growth form. However, divergences in bulk DNA amount were positively associated with divergences in LMA, suggesting that the relationship may be indirect and mediated through other traits directly related to genome size. There was a significant negative association between genome size and metabolic rates that was driven by a basal divergence between angiosperms and gymnosperms; no significant independent contrast results were found. Therefore, it is concluded that genome size-dependent constraints acting on metabolic efficiency may not exist within seed plants.
Authors: Mariska te Beest; Johannes J Le Roux; David M Richardson; Anne K Brysting; Jan Suda; Magdalena Kubesová; Petr Pysek Journal: Ann Bot Date: 2011-10-31 Impact factor: 4.357
Authors: Peter J Franks; Rob P Freckleton; Jeremy M Beaulieu; Ilia J Leitch; David J Beerling Journal: Philos Trans R Soc Lond B Biol Sci Date: 2012-02-19 Impact factor: 6.237
Authors: Karla S C Yotoko; Marcelo C Dornelas; Pakisa D Togni; Tamara C Fonseca; Francisco M Salzano; Sandro L Bonatto; Loreta B Freitas Journal: PLoS One Date: 2011-03-28 Impact factor: 3.240