Introduction

The first living organisms are believed to have arisen more than 3.85 billion years ago (Holland 1999). Presumably, the metabolic capability and genetic systems of the earliest cellular entities are two basic organismal systems. Genome size has been traditionally measured as the mass of DNA within the nucleus. The haploid genome size, or C-value has been given as mass in picogram (pg) of DNA per haploid nucleus (Mirsky and Ris 1951). The haploid genome size of eukaryotes vary by a factor of more than 200 000. This variation is not correlated with organismal complexity or number of coding genes- an observation formerly known as the ‘C-value paradox’ or ‘C-value enigma (Gregory, 2001). For instance, a unicellular eukaryotes include taxa with a genome that exceeds all studied genomes of multicellular animals. Theories to explain the observed pattern of genome size fall manly in two categories: those in which natural selection is viewed as the primary mechanism controlling genome size and those in which variation in genome size is thought to be essentially neutral to natural selection, with genome size instead dependent on stochastic processes and historical accident (Brainerd et al. 2001;  Cavalier-Smith 1985; Wachtel and Tiersch 1993; Petrov 2001). However, in scientific literature there are many strong relationships between genome size and energetic characteristics of large groups of animals.

  The idea that the general energy for vital activity of living organisms increased in the course of progressive evolution was assumed by Sewertzoff (1934). Handbooks of bioenergetics show that the basal metabolic rate (P, J/s) of animals is connected with their mass (M, kg) by the equation

      P = aMk                                                               (1),

where the linear coefficient ‘a’ is considered as ‘metabolic potential’ given in mW/g or in W/kg, and ‘k’ is a non-dimensional power coefficient.

Other scientists (Hemmingsen, 1960; Ivlev, 1963) proposed to use the linear coefficient ‘a’ from Eqn. (1) as a measure of standard metabolism in different species of animals. This implies that there is a comparison between hypothetical animals of 1 g or 1kg body mass that do not necessarily exist in nature. This coefficient can be regarded as ‘metabolic potential’ because of dimension given in mW per 1g or W in 1 kg body mass.  Zotin and Lamprecht 1966; Zotin and Konoplev, 1984)  are showed that the metabolic potential of organismal taxa increases in evolution and there are connection between the ‘metabolic potential’ and the time of organismal appearance (Zotin, Lamprecht and Zotin, 2001),  as well as and body temperature of organisms ( Swenson, 1991).

 Some scientists have showed that the two organismal characteristics (body size and complexity) have increased throughout the evolutionary history of life and organismal complexity is positively correlated to size (Bonner, 1968, 1988; Valentine et al., 1994; Bell and Mooers, 1997; Vermeij, 1999). While this approach is widely accepted, the mechanisms behind the evolution of organismal complexity are poorly understood (McCarthy and Enquist, 2005). However, there is not a standard definition of complexity. McShea (1996) provides several definitions for biological complexity. These include: the number of different parts within a hierarchy (genes, cells, organs, etc.), the number of interactions between parts in this hierarchy, the number of parts for a particular spatial or temporal scale and the number of interactions between parts in a spatial or temporal scale. Some conceptual models have linked the evolution of organismal complexity, measured by the number of cell types, with increases in organismal body size (Bonner, 1968, 1988). Other conceptual models have connected the evolution of metabolic intensity, the mass specific rate of energetic processing for a given body mass, with body size (Zotin and Lamprecht, 1996; Vermeij, 1999). However, non of these approaches have considered the mechanistic linkage between the number of cell types, body size and metabolic intensity. Interestingly, body size, complexity and metabolic intensity have all increased throughout macroevolutionary time (Carroll, 2001; Witting, 2003).

In scientific literature there are many strong relationships between genome size and energetic characteristics of large groups and taxa of animals.

On the cellular level, there is the strong positive correlation between red blood cell size (mean  diameter, dry cell area and cell volume) and genome size in vertebrates (Gregory 2001). The positive correlation between genome size and cell volume within and across amphibians exists also (Olmo and Morescalchi 1975). Genome size is correlated with both nuclear and cell volume in red blood cells, taken from a variety of organisms (Olmo, 1983). Recently, Kozlowski et al (2003, 2005) have developed a model, in which cell size appears a link between noncoding DNA and metabolic rate scaling.

In combined poikilotherms (pisces, reptilia, amphibians) with homeotherms (mammals and aves) the genome size is positively correlated to the total life potential (total metabolic energy per lifespan per 1kg body mass) with correlation coefficient 0.495 (Atanasov and Petrova-Tacheva, 2009).

On the level of hole organisms, in mammals the body-mass corrected basal metabolic rate is inversely related to genome size with high correlation coefficient (0.73) (Vinogradov 1995), and in passerine birds the body-mass independent resting metabolic rate is inversely related to their genome size with correlation coefficient 0.80 too  (Vinogradov 1997 ).

In Homeotherms (mammals, order Rodentia) and in poikilotherms (amphibians) the development rate is strongly linked to genome size (Gregory, 2002a, b). In this work we investigate the possible statistical connection between the values of coefficient ‘a’ in metabolism-mass relationship (named by us as metabolic potential a, W/kg) and corresponding C-value diapason of given organismal taxon.

 In birds exists a relationship between regression residuals of C-value versus body mass, and resting metabolic rate versus body mass with correlation coefficient 0.39 (Gregory 2002).

For all organismal taxa the genome size correlates to radioresistance of living organisms (Atanasov and Ignatova, 2021).