摘要: Individual's phenotypic traits are the results of adaptation to ecological conditions. Therefore, different selection pressures caused by heterogeneous environments may result in phenotypic difference, especially for individuals in different geographical populations. Here, we illustrated for the first time to use social network analysis (SNA) for examining whether geographical proximity predicts the similarity patterns in call characteristics among populations of an anuran species. We recorded calls from 150 male dorsal-striped opposite-fingered treefrogs (Chiromantis doriae) at 11 populations in Hainan Province and one population in Guangdong Province in mainland China, and we measured eight acoustic variables for each male. Mantel test didn't show a correlation between geographical proximity and the similarity in call characteristics among populations. In addition, we failed to find correlations between a population's eigenvector centrality and the distance to its nearest neighbor, nor between the coefficient of variation of similarity in call characteristics of a population and the average distance to all other populations. Nevertheless, three acoustic clusters were identified by the Girvan-Newman algorithm, and clustering was partially associated with geography. Furthermore, the most central populations were included in the same cluster, but the top betweenness populations were located within different clusters, suggesting that centrality populations are not necessary bridging between clusters. These results demonstrate the potential usefulness of the SNA toolbox and indicate that SNA helps to uncover the patterns that often overlooked in other analytical methods. By using SNA in frog's call studies, researchers could further uncover the potential relationship in call characteristics between geographical populations, further reveal the effects of ecological factors on call characteristics, and probably enhance our understanding of the adaptive evolution of acoustic signals.

摘要: Objectives: The final stage of liver development is the production of hepatocytes and cholangiocytes (biliary epithelial cells) from bipotent hepatic progenitor cells. We used HepaRG cells, which are bipotent and able to differentiate into both hepatocytes and cholangiocytes, as a model to study the action of a novel lncRNA (lnc-RHL) and its role in the regulation of bipotency leading to hepatocytes and cholangiocytes. Materials and Methods: Differentiation of HepaRG cells was assessed by marker expression and morphology which revealed their ability to differentiate into hepatocytes and cholangiocytes (modelling the behaviour of hepatoblasts in vivo). Using a qRT-PCR and RACE, we cloned a novel lncRNA (lnc-RHL; regulator of hepatic lineages) that is upregulated upon HepaRG differentiation. Using inducible knockdown of lnc-RHL concurrently with differentiation, we show that lnc-RHL is required for proper HepaRG cell differentiation resulting in diminution of the hepatocyte lineage. Results: Here, we report the discovery of lnc-RHL, a spliced and polyadenylated 670 base lncRNA expressed from the 11q23.3 apolipoprotein gene cluster. lnc-RHL expression is confined to hepatic lineages and is upregulated when bipotent HepaRG cells are caused to differentiate. HepaRG cells made deficient for lnc-RHL have reduced ability to differentiate into hepatocytes, but retain their ability to differentiate into cholangiocytes. Conclusions: Deficiency for lnc-RHL in HepaRG cells converts them from bipotent progenitor cells to unipotent progenitor cells with impaired ability to yield hepatocytes. We conclude that lnc-RHL is a key regulator of bipotency in HepaRG cells.