Genetic variation of Mehraban sheep using two intersimple sequence repeat (ISSR) markers

Genetic diversity within Mehraban sheep populations, as one of the main breeds of Iranian sheep, was studied using (AG)9C and (GA)9C as two inter-simple sequence repeat (ISSR) markers. Blood samples were collected from 210 animals in 6 flocks, 35 heads each, in different parts of Hamedan province. In the polymerase chain reaction (PCR) products, (AG)9C and (GA)9C primers amplified 28 and 36 fragments, respectively, which ranged from 100 to more than 3100 bp. Percentages of polymorphic bands in the different populations ranged from 69 to 77%. In the pooled population, all inter-simple sequence repeat (ISSR) fragments were polymorphic. Shannon and Nei gene diversity indices were 0.2256 and 0.1258, respectively, which indicated low genetic diversity of Mehraban sheep. The population studied was at Hardy-Weinberg equilibrium for most of the ISSR-loci. Analysis of molecular variance (AMOVA) partitioned the ISSR variation into inter and intra population components, where inter-populations and intra-populations accounted for 9 and 91% of the total variation, respectively. The results of this study showed that the Mehraban sheep is a pure native breed that has a low genetic diversity between subpopulations and could be noticed for its potentials in response to selection or crossing with other breeds.Key words: Inter-simple sequence repeat (ISSR) markers, Mehraban sheep, genetic diversity

An assessment of the Accounting Perspective on Intellectual Capital and some results from the European Union

The work reports the use of two financial indicators of intellectual and human capital and their empirical findings from the study of European Union companies. The authors use the VAIC indicator (similar to the earlier chapter) and the impact intellectual and human capital has on firm financial performances. They report that the impact is not consistent among samples and business performance indicators in terms of both significance and sign of coefficients. The second model used is a modification of, and a partial repetition and validation of, the method originally developed by Olhson. The authors report that the indicators of structural capital and human capital are always significant, suggesting that this information is relevant for investors that operate on the European stock markets. This chapter is a worthy example of the use of two quantitative methods when conducting a rigorous financial analysis of intellectual capital and human capital, suggesting to researchers and practitioners that different methods and tools have very different validities for predicting future outcomes