Genomes reveal selective sweeps in kiang and donkey for high-altitude adaptation

Over the last several hundred years, donkeys have adapted to high-altitude conditions on the Tibetan Plateau. Interestingly, the kiang, a closely related equid species, also inhabits this region. Previous reports have demonstrated the importance of specific genes and adaptive introgression in divergent lineages for adaptation to hypoxic conditions on the Tibetan Plateau. Here, we assessed whether donkeys and kiangs adapted to the Tibetan Plateau via the same or different biological pathways and whether adaptive introgression has occurred. We assembled a de novo genome from a kiang individual and analyzed the genomes of five kiangs and 93 donkeys (including 24 from the Tibetan Plateau). Our analyses suggested the existence of a strong hard selective sweep at the EPAS1 locus in kiangs. In Tibetan donkeys, however, another gene, i.e., EGLN1, was likely involved in their adaptation to high altitude. In addition, admixture analysis found no evidence for interspecific gene flow between kiangs and Tibetan donkeys. Our findings indicate that despite the short evolutionary time scale since the arrival of donkeys on the Tibetan Plateau, as well as the existence of a closely related species already adapted to hypoxia, Tibetan donkeys did not acquire adaptation via admixture but instead evolved adaptations via a different biological pathway

Total delay and associated factors in pulmonary tuberculosis patients in Golestan province

Background: Delay in diagnosis and treatment of TB is a critical component in TB control program which thereby spreading illness in the community. Sicnce Golestan province has the high risk with high rates of tuberculosis in the country, therefore, the analysis of the factors associated with treatment delay in this province for effective interventions and proper planning is considered necessary. Methods: 689 patients documents of TB cases in the health department of Golestan University of Medical Sciences in 2016 were enrolled in this survey. The response variable in this study was having the delay or not (via determining the 34 day as cut-off point in the interval between the date of onset of the symptoms and the date of treatment start-up). The data were analyzed using SPSS 24 software and final significant level for multivariate logistic regression model was considered 0.05. Results: Median (mean) treatment delay was calculated 49(77.75) days. In the current study 60.4 of patients had total delay greater than 34 days. In final model variables such as type of PTB (OR=0.645), contact history (patients who had no contact with TB patients (OR=1.441)) and patients who their contact history were unknown (OR=1.654)) had significant relationship with delay in starting treatment after 34 days of onset of symptoms of PTB patients in Golestan (p<0.05). Conclusion: It should beam emphasis on increasing the community's awareness of the symptoms of tuberculosis and effective collaboration should be made between the Infectious Disease Control Center and the private and public sectors. © 2020 Babol University of Medical Sciences. All rights reserved