Why Does the Giant Panda Eat Bamboo? A Comparative Analysis of Appetite-Reward-Related Genes among Mammals

Background: The giant panda has an interesting bamboo diet unlike the other species in the order of Carnivora. The umami taste receptor gene T1R1 has been identified as a pseudogene during its genome sequencing project and confirmed using a different giant panda sample. The estimated mutation time for this gene is about 4.2 Myr. Such mutation coincided with the giant panda’s dietary change and also reinforced its herbivorous life style. However, as this gene is preserved in herbivores such as cow and horse, we need to look for other reasons behind the giant panda’s diet switch. Methodology/Principal Findings: Since taste is part of the reward properties of food related to its energy and nutrition contents, we did a systematic analysis on those genes involved in the appetite-reward system for the giant panda. We extracted the giant panda sequence information for those genes and compared with the human sequence first and then with seven other species including chimpanzee, mouse, rat, dog, cat, horse, and cow. Orthologs in panda were further analyzed based on the coding region, Kozak consensus sequence, and potential microRNA binding of those genes. Conclusions/Significance: Our results revealed an interesting dopamine metabolic involvement in the panda’s food choice

BMC Cancer

BACKGROUND: Although some countries have observed a stabilization in the incidence of CNS, an increasing incidence has been reported from multiple studies. Recent observations point out to the heterogeneity of incidence trends according to histological subtypes, gender and age-groups. Using a high-quality regional CNS tumor registry, this article describes the trends of CNS tumor incidence for main histological subtypes, including benign and malignant tumors, in the French department of Gironde from 2000 to 2012. METHODS: Crude and age-standardized incidence rates were calculated globally, by histological subtypes, malignant status, gender and age groups. For trends, annual percent changes (APC) were obtained from a piecewise log-linear model. RESULTS: A total of 3515 CNS tumors was registered during the period. The incidence of overall CNS tumors was 19/100000 person-years (8.3/100000 for neuroepithelial tumors and 7.3/100000 for meningeal tumors). An increased incidence of overall CNS tumors was observed from 2000 to 2012 (APC = + 2.7%; 95%-confidence interval (CI): 1.8-3.7). This trend was mainly explained by an increase in the incidence of meningiomas over the period (APC = + 5.4%, 95%-CI: 3.8-7.0). The increased incidence rate of CNS tumors was more pronounced in female and in older patients even though the incidence rate increased in all age groups. CONCLUSIONS: Part of the temporal variation may be attributed to improvement in registration, diagnosis and clinical practices but also to changes in potential risk factors. Thus, etiological studies on CNS tumors are needed to clarify this rising trend