Genome‐wide scans to detect positive selection in Large White and Tongcheng pigs

Due to the direction, intensity, duration and consistency of genetic selection, especially recent artificial selection, the production performance of domestic pigs has been greatly changed. Therefore, we reasoned that there must be footprints or selection signatures that had been left during domestication. In this study, with porcine 60K BeadChip genotyping data from both commercial Large White and local Chinese Tongcheng pigs, we calculated the extended haplotype homozygosity values of the two breeds using the long‐range haplotype method to detect selection signatures. We found 34 candidate regions, including 61 known genes, from Large White pigs and 25 regions comprising 57 known genes from Tongcheng pigs. Many selection signatures were found on SSC1, SSC4, SSC7 and SSC14 regions in both populations. According to quantitative trait loci and network pathway analyses, most of the regions and genes were linked to growth, reproduction and immune responses. In addition, the average genetic differentiation coefficient F_ST was 0.254, which means that there had already been a significant differentiation between the breeds. The findings from this study can contribute to further research on molecular mechanisms of pig evolution and domestication and also provide valuable references for improvement of their breeding and cultivation.     

Obesity in Older Adults: Technical Review and Position Statement of the American Society for Nutrition and NAASO,The Obesity Society

Obesity causes serious medical complications and impairs quality of life. Moreover, in older persons, obesity can exacerbate the age‐related decline in physical function and lead to frailty. However, appropriate treatment for obesity in older persons is controversial because of the reduction in relative health risks associated with increasing body mass index and the concern that weight loss could have potential harmful effects in the older population. This joint position statement from the American Society for Nutrition and NAASO, The Obesity Society reviews the clinical issues related to obesity in older persons and provides health professionals with appropriate weight‐management guidelines for obese older patients. The current data show that weight‐loss therapy improves physical function, quality of life, and the medical complications associated with obesity in older persons. Therefore, weight‐loss therapy that minimizes muscle and bone losses is recommended for older persons who are obese and who have functional impairments or medical complications that can benefit from weight loss.     

Mitochondrial DNA haplogrouping of the brown bear,Ursus arctos (Carnivora: Ursidae) in Asia,based on a newly developed APLP analysis

Sequence analyses of the complete brown bear, Ursus arctos, mitochondrial DNA (mtDNA) genome have detected scattered single nucleotide polymorphisms (SNPs) that define distinct mtDNA haplogroups in phylogeographical studies. The degraded DNA in historical samples, such as stuffed or excavated specimens, however, is often not suitable for sequence analyses. To address this problem, we developed an amplified product length polymorphism (APLP) analysis for mtDNA‐haplogrouping U. arctos specimens by detecting haplogroup‐specific SNPs. We verified the validity and utility of this method by analysing up to 170‐year‐old skin samples from U. arctos specimens collected widely across continental Eurasia. We detected some of the same haplogroups as those occurring in eastern Hokkaido (Japan) and eastern Alaska in continental Eurasia (the Altai and the Caucasus). Our results show that U. arctos in eastern Hokkaido and eastern Alaska descended from a common ancestor in continental Eurasia, and suggest that U. arctos occupied several refugia in southern Asia during the Last Glacial Maximum. © 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111 , 627–635.     

pathmatrix: a geographical information system tool to compute effective distances among samples

pathmatrix is a tool used to compute matrices of effective geographical distances among samples using a least‐cost path algorithm. This program is dedicated to the study of the role of the environment on the spatial genetic structure of populations. Punctual locations (e.g. individuals) or zones encompassing sample data points (e.g. demes) are used in conjunction with a species‐specific friction map representing the cost of movement through the landscape. Matrices of effective distances can then be exported to population genetic software to test, for example, for isolation by distance. pathmatrix is an extension to the geographical information system (GIS) software arcview 3.x.     

Mitotic drug targets

Mitosis is the key event of the cell cycle during which the sister chromatids are segregated onto two daughter cells. It is well established that abrogation of the normal mitotic progression is a highly efficient concept for anti‐cancer treatment. In fact, various drugs that target microtubules and thus interfere with the function of the mitotic spindle are in clinical use for the treatment of various human malignancies for many years. However, since microtubule inhibitors not only target proliferating cells severe side effects limit their use. Therefore, the identification of novel mitotic drug targets other than microtubules have gained recently much attention. This review will summarize the latest developments on the identification and clinical evaluation of novel mitotic drug targets and will introduce novel concepts for chemotherapy that are based on recent progress in our understanding how mitotic progression is regulated and how anti‐mitotic drugs induce tumor cell death. J. Cell. Biochem. 111: 258–265, 2010. © 2010 Wiley‐Liss, Inc.     

Assessment of Optimal Selected Prognostic Factors

The identification and assessment of prognostic factors is one of the major tasks in clinical research. The assessment of one single prognostic factor can be done by recently established methods for using optimal cutpoints. Here, we suggest a method to consider an optimal selected prognostic factor from a set of prognostic factors of interest. This can be viewed as a variable selection method and is the underlying decision problem at each node of various tree building algorithms. We propose to use maximally selected statistics where the selection is defined over the set of prognostic factors and over all cutpoints in each prognostic factor. We demonstrate that it is feasible to compute the approximate null distribution. We illustrate the new variable selection test with data of the German Breast Cancer Study Group and of a small study on patients with diffuse large B‐cell lymphoma. Using the null distribution for a p‐value adjusted regression trees algorithm, we adjust for the number of variables analysed at each node as well. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)