Changes of energy metabolism, thermogenesis and body mass in the tree shrew (Tupaia belangeri chinensisTupaiidae, Scandebtia) during cold exposure

Population genomics provides insights into the evolution and adaptation of tree shrews (Tupaia belangeri) in China

Physiological adaptation of tree shrews (Tupaia belangeri) to changing environmental temperature has been reported in detail. However, the T. belangeri origin (mainland or island), population history, and adaptation to historical climate change remain largely unknown or controversial. Here, for the first time, we sequenced the simplified genome of 134 T. belangeri individuals from 12 populations in China and further resequenced one individual from each population. Using population genomic approaches, we first observed considerable genetic variation in T. belangeri. Moreover, T. belangeri populations formed obvious genetic structure and reflected different demographic histories; they generally exhibited high genetic diversity, although the isolated populations had relatively low genetic diversity. The results presented in this study indicate that T. b. modesta and T. b. tonquinia were separated recently and with a similar population dynamics. Second, physical barriers rather than distance were the driving factors of divergence, and environmental heterogeneity may play an important role in genetic differentiation in T. belangeri. Moreover, our analyses highlight the role of historical global climates in the T. belangeri population dynamics and indicate that the decrease of the T. belangeri population size may be due to the low temperature. Finally, we identified the olfaction-associated adaptive genes between different altitude populations and found that olfactory-related genes of high-altitude populations were selectively eliminated. Our study provides demographic history knowledge of T. belangeri; their adaption history offers new insights into their evolution and adaptation, and provides valuable baseline information for conservation measures.

Comparative analyses of basal rate of metabolism in mammals: data selection does matter

Basal rate of metabolism (BMR) is a physiological parameter that should be measured under strictly defined experimental conditions. In comparative analyses among mammals BMR is widely used as an index of the intensity of the metabolic machinery or as a proxy for energy expenditure. Many databases with BMR values for mammals are available, but the criteria used to select metabolic data as BMR estimates have often varied and the potential effect of this variability has rarely been questioned. We provide a new, expanded BMR database reflecting compliance with standard criteria (resting, postabsorptive state; thermal neutrality; adult, non-reproductive status for females) and examine potential effects of differential selectivity on the results of comparative analyses. The database includes 1739 different entries for 817 species of mammals, compiled from the original sources. It provides information permitting assessment of the validity of each estimate and presents the value closest to a proper BMR for each entry. Using different selection criteria, several alternative data sets were extracted and used in comparative analyses of (i) the scaling of BMR to body mass and (ii) the relationship between brain mass and BMR. It was expected that results would be especially dependent on selection criteria with small sample sizes and with relatively weak relationships. Phylogenetically informed regression (phylogenetic generalized least squares, PGLS) was applied to the alternative data sets for several different clades (Mammalia, Eutheria, Metatheria, or individual orders). For Mammalia, a 'subsampling procedure' was also applied, in which random subsamples of different sample sizes were taken from each original data set and successively analysed. In each case, two data sets with identical sample size and species, but comprising BMR data with different degrees of reliability, were compared. Selection criteria had minor effects on scaling equations computed for large clades (Mammalia, Eutheria, Metatheria), although less-reliable estimates of BMR were generally about 12-20% larger than more-reliable ones. Larger effects were found with more-limited clades, such as sciuromorph rodents. For the relationship between BMR and brain mass the results of comparative analyses were found to depend strongly on the data set used, especially with more-limited, order-level clades. In fact, with small sample sizes (e.g. <100) results often appeared erratic. Subsampling revealed that sample size has a non-linear effect on the probability of a zero slope for a given relationship. Depending on the species included, results could differ dramatically, especially with small sample sizes. Overall, our findings indicate a need for due diligence when selecting BMR estimates and caution regarding results (even if seemingly significant) with small sample sizes.