The Society for Integrative and Comparative Biology
Divergent Selection for Aerobic Capacity in Rats as a Model for Complex Disease1
1 Functional Genomics Laboratory, Department of Physical Medicine and Rehabilitation, University of Michigan, 1500 E. Medical Center Dr., Ann Arbor, Michigan 48109-0549
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 SYNOPSIS INTRODUCTIONINTRODUCTIONMODELS OF COMPLEX DISEASEEVOLUTION-BASED SELECTION:...SELECTION FOR AEROBIC CAPACITYUSE OF N:NIH STOCK...DESIGN OF SELECTION EXPERIMENTS:...CURRENT DATA ON RATS...References |
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Based upon ideas about evolution, we put forth the argument that the capacity to transfer energy via aerobic metabolism is such a central feature of mammalian biology, that it must also be the primary determinant of complex disease. From this, we hypothesized that artificial selection on low and high capacity for aerobic exercise would create lines that can be used to define the divide between health and disease. In 1996 we began large-scale divergent selection for aerobic treadmill running capacity in a widely heterogeneous stock of rats (N:NIH). By ten generations we developed lines of low capacity runners (LCR) and high capacity runners (HCR) that on average differed by 317%. As a correlated trait, body mass increased at each generation in the LCR while the body mass decreased in the HCR. The lines also separated for key factors of systemic oxygen transport capacity such as maximal oxygen consumption (VO2max), tissue perfusion, capillary density, and oxidative enzyme activity (citrate synthase and B-HAD). We also tested our hypothesis that differences in aerobic energy transfer would produce rats that contrast for risk factors associated with complex disease. Indeed, the lines separated for cardiovascular risk factors including differences in blood pressure, cardiac contractility, visceral adiposity, plasma free fatty acids, and triglycerides. The decrease in aerobic capacity was also associated with low amounts of several proteins required for mitochondrial function.
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INTRODUCTION |
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SYNOPSISINTRODUCTIONINTRODUCTIONMODELS OF COMPLEX DISEASEEVOLUTION-BASED SELECTION:...SELECTION FOR AEROBIC CAPACITYUSE OF N:NIH STOCK...DESIGN OF SELECTION EXPERIMENTS:...CURRENT DATA ON RATS...References |
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"Well, complex diseases are really a new frontier for genetics. ...... just like every other area of science we better build a very firm foundation. ......It is a very hard task. Single gene diseases have been worked on in some sense for the entire century. Multi-gene diseases are very much the work of the last 5 years or so. And so complex inheritance is a frontier for the next century."Eric S. Lander, DPhil (excerpt from an interview that took place at the "Winding Your Way through DNA" symposium at the University of California San Francisco in 1992) (http://www.accessexcellence.org/RC/CC/lander.html.)
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INTRODUCTION |
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SYNOPSISINTRODUCTIONINTRODUCTIONMODELS OF COMPLEX DISEASEEVOLUTION-BASED SELECTION:...SELECTION FOR AEROBIC CAPACITYUSE OF N:NIH STOCK...DESIGN OF SELECTION EXPERIMENTS:...CURRENT DATA ON RATS...References |
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Most common diseases are complex in the sense of being determined by allelic variations in possibly few to hundreds of genes (polygenic) as they interact with variable environments. Diabetes, hypertension, obesity, and coronary artery disease are examples of complex disease and are the major cause of morbidity and mortality, at least in westernized societies. About ten years ago we began selection experiments based upon ideas about evolution to create rat genetic models that divide for low and high health risks. Here we present background information on our approach to selection, the ideas we borrowed from evolution to formulate our hypothesis, and current information about our models.
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MODELS OF COMPLEX DISEASE |
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SYNOPSISINTRODUCTIONINTRODUCTIONMODELS OF COMPLEX DISEASEEVOLUTION-BASED SELECTION:...SELECTION FOR AEROBIC CAPACITYUSE OF N:NIH STOCK...DESIGN OF SELECTION EXPERIMENTS:...CURRENT DATA ON RATS...References |
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Current model approaches are less than an ideal representation of complex diseases. Physical maneuvers such as ligation of coronary arteries to model heart disease (Zolotareva and Kogan, 1978
; Ahn et al., 2004) or renal artery occlusion to emulate renovascular hypertension (Goldblatt et al., 1934; Pinet et al., 2004) more accurately reflect response to injury. Administration of chemical agents to mimic diseases such as streptozotocin-induced diabetes mellitus (Rossini et al., 1977) do not reflect the progression of disease, but represent response to chemical injury. Single gene knockout approaches are useful to determine essentiality of a gene's function, but do not represent the polygene condition of complex diseases (Williams and Wagner, 2000). Application of gametic mutagens to produce random base changes with the hope that one or more of the mutants will resemble a disease phenotype does not define the combination of alleles that are causative of complex disease. Direct selection for a disease phenotype is also problematic because it is based upon measurable traits or symptoms and not the full complement of underlying mechanisms.
For instance, hypertension is a well-characterized quantitative disease trait, by which selection models for variation in the measure of blood pressure itself seems reasonable (Rapp, 2000). Figure 1 panel A demonstrates a hypothetical selection response for extremes in the measure of blood pressure to yield lines low and high for mean blood pressure. Assuming that an average mean arterial pressure is 90 mmHg, selection on the extremes could produce divergent lines that on average demonstrate a mean arterial pressure of 140 mmHg for the high selected line and 75 mmHg for the low selected line after six generations. This approach can be described as "trait modeling" in that the models can then be used to explore mechanism for the trait. The problem is that selection based upon a single measure thought to characterize the disease will not necessarily reproduce the full array of underlying mechanisms and present the full complexity of the disease. This problem is amplified because diseases emerge not as discrete events, but as complexes, such as the cascade represented by metabolic syndrome (Gensini et al., 1998) for which hypertension, diabetes, heart failure, and obesity tend to cluster.
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From this account, it seems reasonable to build on the idea of "mechanistic modeling" in which selection is based on the mechanism underlying the disease of interest. For example, Guyton and Coleman (1967)
contend that long-term blood pressure regulation, and thus hypertension, is mediated by the kidney via a process termed pressure diuresis. The basic tenet of pressure diuresis is that an organism has just enough blood pressure to keep the input of salt and water equal to the output (Guyton, 1991). If pressure diuresis is indeed the basic mechanism of hypertension, then selection based upon low function for pressure diuresis should yield accurate models that correctly emulate the condition of hypertension. A hypothetical example of such selection is illustrated in Figure 1 panel B. Here, a pressure-diuresis index (PDI) is estimated as the product of mean arterial blood pressure and time (hr) required to excrete one-half of a 4 ml oral NaCl challenge (0.5 mequiv./ml). Presume that a founder population accomplished one-half excretion with an average mean arterial pressure equal to 100 mmHg over a 3 hour period (PDI = 300). After six generations of selection, animals with low pressure-diuresis took 6 hours to excrete the same NaCl load with an average blood pressure of 140 mmHg (PDI = 840). The animals bred for high pressure-diuresis were able to excrete the same NaCl challenge with an average blood pressure of 100 mmHg within 1 hour (PDI = 100). Thus, the high line represents a model for the trait of hypertension as well as having the underlying mechanism of low-pressure diuresis. In contrast, the low line represents a model with a high pressure-diuresis mechanism and low blood pressure. Although conceptually correct (Brand et al., 1991; Skarlatos et al., 1994; Steele et al., 2000), our efforts to yield a selection measure of pressure-diuresis that could be taken to large scale breeding have not been successful. Mechanistic modeling is difficult because, unlike pressure-diuresis for hypertension, not many complex disease examples exist for which an underlying mechanism has been resolved. |
EVOLUTION-BASED SELECTION: ENERGY TRANSFER DEFINES OUR BIOLOGICAL EXISTENCE |
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SYNOPSISINTRODUCTIONINTRODUCTIONMODELS OF COMPLEX DISEASEEVOLUTION-BASED SELECTION:...SELECTION FOR AEROBIC CAPACITYUSE OF N:NIH STOCK...DESIGN OF SELECTION EXPERIMENTS:...CURRENT DATA ON RATS...References |
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If evolution determines our current biology, then it seems reasonable to assume that mechanisms of disease originated from our evolutionary history. Ideas about evolution are of course intertwined with consideration of the driving force of life's emergence from the inanimate to the animate (Pross, 2003
) and of the environments from which natural selection occurred. We reasoned that energy transfer via aerobic metabolism is the most formative feature that typifies mammalian existence at all levels of biological organization; and thus, must also be a primary determinant of disease.
Two billion years of evolution in an oxygen environment resulted in aerobic metabolism as a central feature of mammalian biology (DesMarias, 2000; Paytan, 2000). Before an oxygen-enriched atmosphere, an organism's capacity for energy transfer was limited by operating within anaerobic pathways to support metabolism and replication. The introduction of oxygen as a final electron acceptor, created an 18-fold greater capacity to transfer energy. It is presumed that this increased free energy transfer afforded by the widened redox potential was permissive for more complexity in the sense that organisms became multicellular (Xiong et al., 2000). Obligatory for using oxygen in energy transfer pathways was the co-evolution of enzymes that detoxify the reactive oxygen species formed as by-products (Young and Woodside, 2001). Thus, the genetic substrates that mediate oxidation reactions and oxygen detoxification reactions likely form a large foundation for mammalian biology. This is consistent with the view that most diseases are caused by flaws in oxidation/detoxification pathways or defects in mitochondrial structure and function (Young and Woodside, 2001; Duchen, 2004). This supports the use of maximal oxygen consumption (VO2max) as a clinical reference point and total body aerobic capacity as a predictor of all-cause morbidity and mortality in humans (Myers et al., 2002).
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SELECTION FOR AEROBIC CAPACITY |
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SYNOPSISINTRODUCTIONINTRODUCTIONMODELS OF COMPLEX DISEASEEVOLUTION-BASED SELECTION:...SELECTION FOR AEROBIC CAPACITYUSE OF N:NIH STOCK...DESIGN OF SELECTION EXPERIMENTS:...CURRENT DATA ON RATS...References |
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The rat was chosen as the model organism for selection for three primary reasons 1) the laboratory rat (Rattus norvegicus) has been a key tool for the study of medicine and pharmacology for human health. A large database of physiological phenotypes for integrated fields such as cardiovascular, neuroscience, and exercise physiology exist in the literature (Jacob and Kwitek, 2002
). 2) To date, almost all known genes associated with disease in humans have orthologues to the rat genome (Rat genome sequencing project consortium, 2004). 3) Over 200 inbred strains of R. norvegicus have been produced from lines and colonies of rats first selectively bred for "disease" alleles (Greenhouse et al., 1990). Recent evidence from human studies suggests two genetic substrates as contributors to the aerobic energy capacity phenotype (Bouchard et al., 1999, 2000). First, there is a set of genes that determine maximal aerobic capacity in the untrained condition (intrinsic). Second, another set of genes dictate the changes in aerobic capacity acquired as a result of exercise training (adaptational). Our aim was to devise a test of treadmill running performance for the rat that most closely estimated intrinsic aerobic capacity.
It has been demonstrated that oxygen consumption increases linearly as a function of running velocity over a wide range in rats (Gleeson and Baldwin, 1981). In accord with this, Brooks and White (1978) reported a significant association (R = 0.83) between oxygen consumption and running velocity (range = 14.3 to 43.1 ml/kg/min) in untrained rats tested at a slope of 15%. The test we devised consisted of running each rat on a motorized treadmill up a 15 degree slope with incremental increases in speed until exhausted (Fig. 2). Exhaustion was operationally defined as the third time a rat could no longer keep pace with the speed of the treadmill and remained on the shock grid for two seconds rather than run. The total distance run until exhaustion (meters) was designated as the standard for the estimate of each rat's intrinsic endurance exercise capacity. Each rat was tested over five consecutive days. The single best trial of five was used as the best indicator of capacity determined by intrinsic genetic composition and least indicative of the environmental component of the trait (Barbato et al., 1998). This idea of estimating the genetic component from the one best day of performance rather than either the mean or the median of the five trials, for example, has two origins. First, the environment can have an infinite negative influence upon capacity by reducing the distance run to zero. Factors such as subtle differences in housing or daily handling could cause a genetically superior rat to perform below its capacity on a given day. Second, the environment can have only a finite positive influence upon any test of capacity such that, given the best environment, intrinsic capacity is limited by a given genotype. An extension of this logic is that the estimate of breeding value (distance run) has more error for low capacity rats compared to high capacity rats (Britton and Koch, 2001).
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For genetic model development, it is imperative to reduce environmental variance to a minimum; so that, the measure and selection of the trait is primarily for the genetic component. General environmental variance arises from non-localized, more permanent circumstances such as room temperature, light, humidity, diet, and time of day (Falconer and Mackay, 1996
). Despite experimental control for factors such as housing conditions and manner of testing, other hard to control factors like intrauterine conditions, birthing order, social interactions, and eating patterns may also contribute to general environmental variation among populations. Additionally, special environmental variance for an individual can originate from localized, temporary circumstances such as daily handling (Falconer and Mackay, 1996). While artificial selection presumably concentrates genetic components over several generations, it also inadvertently selects for lack of sensitivity to subtle variations in the general environment.
Any performance-based test, whether performed in humans or rats, contains an inherent set of behavioral factors related to age, motivation, tractability, and willingness to perform (Koch et al., 1998). Our selection test began when the rats were young adults (10 weeks of age). Each rat was introduced to treadmill exercise over a period of 5 days. The first two days of introduction to treadmill running consisted of simply placing the rat on the treadmill belt that was moving at a velocity of 10 m·min–1 (15° slope) and picking the rat up and moving it forward if it started to slide off the back of the belt. This was done over a period between 1–3 minutes. During introduction days 3–5, the belt speed was gradually increased up to 15 m·min–1 and failure to run caused the rats to slide off of the moving belt and onto a 15 x 15 cm electric shock grid that delivered 1.2 mA of current at 3 Hz. The rats were left on the grid for about 1.5 sec and then moved forward onto the moving belt. With this process, most rats learned to run for five minutes and avoid the mild shock. This amount of exposure to treadmill exercise is likely below that required to produce a significant change in aerobic capacity (Baldwin et al., 1977). The ability to achieve this minimal level of treadmill exercise at least once constituted the threshold performance necessary for inclusion in evaluation for maximal running capacity the following week.
A selection experiment for aerobic energy capacity was first done as a test case over three generations in a small outbred population of Sprague Dawley rats (Harlan Sprague-Dawley, Indianapolis, IN) shown in Figure 3 (Koch et al., 1998). The founder population (24 females and 28 males) ran to exhaustion by 396 meters with a wide range of scores (149 to 695 meters). The average time to exhaustion for each test was equivalent to about 25 minutes. An event of this duration utilizes aerobic metabolism as the major contributor for energy transfer. A high intensity of breeding selection produced low and high lines for aerobic energy capacity that differed by 70%. We thought this result warranted initiation of a more large-scale selection for treadmill running capacity.
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USE OF N:NIH STOCK AS FOUNDER POPULATION |
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SYNOPSISINTRODUCTIONINTRODUCTIONMODELS OF COMPLEX DISEASEEVOLUTION-BASED SELECTION:...SELECTION FOR AEROBIC CAPACITYUSE OF N:NIH STOCK...DESIGN OF SELECTION EXPERIMENTS:...CURRENT DATA ON RATS...References |
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In 1979, Carl Hansen and Karen Spuhler foresaw the need for a genetically heterogeneous rat stock from which selected models could originate (Hansen and Spuhler, 1984
). At that time, there were about 100 inbred rat strains available; many of which have origin back to an original Wistar Stock. The Wistar stock was made from a relatively small set of breeders as were the Sprague-Dawley and the Long-Evans rats. After phylogenetic consideration, the following eight inbred strains representing the broadest spectrum of laboratory rats available were chosen by Hansen and Spuhler for outcross breeding: Maudsely Reactor (MR/N), Wistar (WN/N), Wistar Kyoto (WKY/N), Marshall 520 (M520), Fischer (F344), A x C 9935 Irish (ACI), Brown Norway (BN/SsN), and Buffalo (BUF/N) (Fig. 4). Since its formation, the N:NIH outbred stock has been maintained as 60 outcrossed families and is available as a research resource from the National Institutes of Health (NIH) Animal Genetic Resource (NIHAGR) located at the NIH (Bethesda, MD). The availability of N:NIH heterogeneous stock of rats is of major benefit for use as a starting population for artificial selection. Because the stock was derived from eight inbred strains, deleterious alleles which may invoke inbreeding depression are already selected against which increases the opportunity for breeding fecundity during selection. At least in theory, one may ultimately be able to determine which causative allelic variants from the eight progenitor strains segregate in a selection process (Flint and Mott, 2001).
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Large-scale selection for treadmill endurance running capacity was started using a founder population of 96 male and 96 female N:NIH rats (Koch and Britton, 2001
). Each rat in the founder population was of different parentage, so that initial selection was not among brothers and sisters to obtain wider initial genetic variance (Hartl and Clark, 1988). On average (mean ± standard error), the founder population ran to exhaustion by 355 ± 11 m (23 min) with the females running significantly further than the males. The females in the N:NIH founder population ran on average for 380 ± 15 m and the males ran on average for 327 ± 16 m. Figure 5 (upper) is a frequency histogram for running capacity in the N:NIH founder population: females and males combined.
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DESIGN OF SELECTION EXPERIMENTS: ADVANTAGE OF USING DIVERGENT WITH-FAMILY ROTATIONAL BREEDING AND NON-REPLICATE LINES |
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SYNOPSISINTRODUCTIONINTRODUCTIONMODELS OF COMPLEX DISEASEEVOLUTION-BASED SELECTION:...SELECTION FOR AEROBIC CAPACITYUSE OF N:NIH STOCK...DESIGN OF SELECTION EXPERIMENTS:...CURRENT DATA ON RATS...References |
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The usual goal of selection is to induce a response attributed from increased frequency of alleles causative of the change in phenotype on which selection criteria is based (Falconer and Mackay, 1996
). Other sources of response include: 1) sampling errors in estimating the generation means, 2) random changes in gene frequency (i.e., random genetic drift), and 3) unpredictable and subtle changes in the environment. Variation from sampling errors and genetic drift are reduced by first selecting extremes from a large number of animals in the founder population and then using a large number of families for selection at each generation. It is projected that the initial response to selection is greater when the population is smaller and the intensity of selection is high; yet this approach also increases the amount of inbreeding. For relatively short-term breeding programs, inbreeding of about 1% per generation is acceptable to yield retention of genetic variation and thus increase the overall response to selection (Falconer and Mackay, 1996). For randomly bred animals with an equal representation of males and females, the rate of inbreeding per generation (DF) is calculated as:
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(where N = number of parents).
Making the contributions from each family nearly equal can further reduce the rate of inbreeding. This can be accomplished by selecting a male and female offspring from each family and using them as parents for the next generation. This is termed within-family selection. Kimura and Crow (Kimura and Crow, 1963) have evaluated the rates of inbreeding in several rotational breeding programs. Their results demonstrate that rotational within-family selective breeding gives rates of inbreeding quite close to the theoretical rate for minimally low inbreeding for equal representation of families (DF = [1/4N]) (Falconer, 1976). Thus, 13 rotational breeding pairs per selected line places the rate of inbreeding at slightly less than 1% per generation (1/[4*26] = 1/104 = 0.96%).
A prearranged schedule of 13 matings for within-family rotational breeding follows a simple pairing sequence based on assigned family number (1 to 13, F = female, M = male) as shown:
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When the rotation has completed one entire cycle (i.e., 13 generations), the 1 x 1, 2 x 2, 3 x 3 etc. matings are skipped to avoid sib-matings (Falconer, 1976).
Within-family selection is beneficial for two additional reasons. First, it eliminates a large component of environmental variance such as maternal or pre-weaning effects that can be shared if selecting several members from one family. Second, if single-pair matings are to be made, every family contributes two members equally as genetic substrate of the next generation. The contribution from random genetic drift, however, can only be estimated by replicating selected lines. Although it is ideal to utilize replicated lines, the scale of any breeding program is ultimately resource limited. The maintenance of replicate lines operates to decrease fractionally the size of each line to 1/(n + 1) compared with no replicate lines (n = number of replicate lines) (Falconer and Mackay, 1996). Our decision was to reduce sampling error and contribution from genetic drift by employing all resources for development of only one low and one high line. The tradeoff was that we have no direct estimate of the contribution of genetic drift.
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CURRENT DATA ON RATS SELECTED FOR AEROBIC CAPACITY |
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SYNOPSISINTRODUCTIONINTRODUCTIONMODELS OF COMPLEX DISEASEEVOLUTION-BASED SELECTION:...SELECTION FOR AEROBIC CAPACITYUSE OF N:NIH STOCK...DESIGN OF SELECTION EXPERIMENTS:...CURRENT DATA ON RATS...References |
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The selection response over ten generations from our ongoing experiments is shown in Figure 6 (Koch and Britton, 2001
). The 13 lowest founder females averaged 205 ± 7 m and the lowest 13 males averaged 167 ± 7 m for aerobic running capacity and were randomly mated. The 13 highest founder females averaged 633 ± 26 m and the 13 highest males averaged 541 ± 21 m for aerobic capacity and were also randomly mated to start the high line. This represents a 3.1-fold difference for the females (633/205) and a 3.2-fold difference for the males (541/167) between the low and high parents selected as progenitors for the selected lines. After ten generations of selection, a total of 2,589 rats were phenotyped for maximal aerobic running capacity. On average the low line members decreased 15 m per generation and the high line members increased 46 m per generation. The overall divergent response was 317% (688 m). At generation 10, the low-selected line averaged 217 ± 10 m (17 min) and the high line averaged 905 ± 22 m (45 min). It is obvious from inspection of the frequency distributions at generation 10 (Fig. 5 lower) that the high line responded more strongly to selection (+550 m) compared to the low line (–138 m). Selection for the low trait character is often of lesser magnitude relative to the high for two primary reasons (Falconer and Mackay, 1996). First, selection can be lower simply because the low trait approaches zero or a designated threshold as a limit. Second, it is possible that natural selection has constrained variation in aerobic capacity at the low end and competes against artificial selection to maintain a minimal threshold capacity associated with fitness. In contrast, more genetic variation may exist for high aerobic capacity because this trait has been under less evolutionary pressure (Mousseau and Roff, 1987). We named these lines Low Capacity Runners (LCR) and High Capacity Runners (HCR) which best describes the selected trait (Koch and Britton, 2001).
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A change in an unselected trait produced by selection for another trait is termed a correlated response. Correlated traits are informative and of interest to selection studies for detecting positive and negative associations between traits but can not establish direct cause and effect for three primary reasons (Falconer and Mackay, 1996
). First, the common property of pleiotropy, a genetic cause of trait differences determined by allelic variants showing a broad spectrum of effects on the expression of many traits, may be undetectable due to the net effect of all the segregating loci. Second, in connection with the process of selection, two traits may be independently influenced by a common selection environment. Third, correlated responses may be directed by evolutionary fitness and thus interconnected to viability and fertility of the lines.
Selection for aerobic running capacity produced a correlated change in body weight in both females and males. In general, the low line (LCR) became heavier by approximately 3 grams per generation and the high line (HCR) became increasingly lighter by an estimate of 1 gram per generation. By generation 10, the LCR females weighed 213 ± 3 g and the HCR females weighed 172 ± 2 g (24% difference). Similarly, the LCR males weighed 310 ± 6 g and the HCR males weighed 255 ± 3 g (22% difference). Multiple linear regression analysis showed that the concomitant changes in body weight across generations accounted for about 7% of the variation in distance run in females and 14–20% in males (Wisloff et al., 2005) As such, LCR and HCR lines might serve as contrasting models to determine selected factors that influence body weight and composition.
It seems reasonable to predict that two-way selection for treadmill running capacity would produce lines that differ in the capacity for oxygen utilization as governed by the cardiac output and the ability of peripheral tissues to extract oxygen will be at least one of the predominant factors selected, although, other factors such as skeletal mechanics, neuromuscular coordination, and heat dissipation may also be involved. At generation 7, the VO2max (maximal oxygen consumption) was 21% higher in HCR compared to the LCR rats (Henderson et al., 2002). For evaluation, oxygen transport system was considered as four sequential components of oxygen utilization: 1) pulmonary ventilation, 2) alveolar-capillary diffusion, 3) convective transport from blood to tissues, and 4) blood–to-tissue transfer. A 30% difference in oxygen transfer at the tissue level was the major factor contributing to the difference in VO2 max between the LCR and HCR rats (Henderson et al., 2002). Although the total capillary and fiber number were similar, the fiber area in the HCR was 37% less (Howlett et al., 2003). As a result, the number of capillaries per unit area of muscle was 32% more in the HCR compared to the LCR rats. Both citrate sythase and ß–hydroxyacyl-CoA dehydrognease enzyme activities were about 40% higher in the HCR relative to LCR while phosphofructokinase was lower (Table 1).
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High blood pressure, depressed cardiac contractility, body weight, and elevated blood lipid levels are standard estimates of cardiovascular disease risk. Abdominal aortic blood pressure measured via telemetry was higher in the LCR during the day (105 ± 13 vs. 89 ± 8 mm Hg), at night (98 ± 3 vs. 91 ± 7 mm Hg), and for the combined 24-hour period (102 ± 6 vs. 90 ± 7 mm Hg) (Fig. 7A). Stroke volume was 47% less in a working Langendorff preparation and field-stimulated isolated left ventricular myocytes shortened 22% less in LCR relative the HCR (Fig. 7B, 7C). Visceral adiposity relative to body weight was 63% higher, plasma free fatty acids 95% higher, and plasma triglycerides 167% higher in LCR compared to HCR rats (Fig. 2D, E, F). These data suggest increased cardiovascular risk factors associate with low aerobic capacity (Hussain et al., 2001
; Wisloff et al., 2005).
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In view of the lower aerobic capacity we hypothesized that LCR have compromised mitochondrial oxidative function relative to the HCR rats. To test this, we measured the cellular content of proteins required for mitochondrial biogenesis and function (Mootha et al., 2003
) in soleus muscle, which is composed largely of highly oxidative type I fibers. As Figure 8 reveals, the content peroxisome proliferative activated receptor, gamma, coactivator 1, alpha (PGC-1
), peroxisome proliferative activated receptor, gamma (PPAR-
), ubiquinol-cytochrome c oxidoreductase core 2 subunit (UQCRC2), cytochrome c oxidase subunit I (COXI), uncoupling protein 2 (UCP2), and ATP synthase H+ transporting mitochondrial F1 complex (F1-ATP synthase) was markedly reduced in the LCR rats by comparison to the HCR (Wisloff et al., 2005). The uniform decline in these proteins is consistent with the hypothesis that reduced aerobic metabolism plays a causal role in the development of the differences between the LCR and HCR rats. Although our experiments do not prove a direct cause and effect relationship, they are consonant with the view that impaired regulation of oxidative pathways in mitochondria may be a common factor linking reduced total-body aerobic capacity to complex disease.
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ACKNOWLEDGMENTS |
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We appreciate the collaborative efforts with U. Wisloff, O. Ellingsen, S. Najjar, S. Swoap, P. D. Wagner, R. Howlett, and N.C. Gonzalez, This work was supported by grants from the United States Public Health Service, National Institutes of Health, (Heart, Lung and Blood Institute HL 64270 and National Center for Research Resources RR 17718) to LGK and SLB.
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FOOTNOTES |
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1 From the Symposium Selection Experiments as a Tool in Evolutionary and Comparative Physiology: Insights into Complex Traits, at the Annual Meeting of the Society for Integrative and Comparative Biology, 5–8 January 2004, at New Orleans, Louisiana, USA.
2 E-mail: lgkoch{at}med.umich.edu
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References |
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SYNOPSISINTRODUCTIONINTRODUCTIONMODELS OF COMPLEX DISEASEEVOLUTION-BASED SELECTION:...SELECTION FOR AEROBIC CAPACITYUSE OF N:NIH STOCK...DESIGN OF SELECTION EXPERIMENTS:...CURRENT DATA ON RATS...References |
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