SNPs are neutral markers of parentage rather than functionally important. Many studies have shown that the SNP approach in livestock and humans fails to identify these critical sequences and can be misleading at best. The difference is fundamental to the discovery of gene clusters with coherent cis and trans interactions between conserved sequences known as ancestral haplotypes. The term genome is used here to refer to the architecture of DNA sequences, whereas others have come to use the term in the context of single-nucleotide polymorphisms wherever they occur. Because the generation time and life expectancy are much shorter, there are excellent opportunities to study and treat genetically determined diseases prospectively. Thirdly, cattle are plentiful and even more so than humans. Metabolic and inflammatory pathways are relatively well understood and are supported by inestimable funding available to ensure future supplies of meat, milk, cheese, butter, leather, and fertilizer. There is great potential for meaningful studies of population genetics and family and haplotype associations and, even more so, for structure-function genomics. Many of these breeds have been closed for hundreds of years and then intentionally crossed with each other. Innumerable breeds can be compared often under different environmental conditions. There are huge databases and DNA banks which have been in existence for 50 years. Secondly, domestic cattle are well maintained, closely observed, and very well understood. We argue that cattle are both relevant and relatively safe for translational studies. As for example in the case of pox and tuberculosis. As one example, infections can be similar and, in some cases, are transmissible from one to the other, but close exposure to cattle is generally innocuous implying some form of immunity. The same window may explain the fact that the two species have synergized over some 40,000 years of contact and at least 7000 years of domestication. Firstly, cattle are close to humans in evolutionary time and fall within that window of 50–100 million years of separation (or last common ancestor) which is characterized by very similar proteins but vastly different regulations of expression. However, the approach presented by Thiel and colleagues (2015), in which all parameter domains relevant for interspecies differences can be stepwise adjusted, represents an important step to improve extrapolations from rodent models to predict the human situation.Interspecies translation from cattle to man has unrecognized potential. PBPK modeling has been used since long to predict absorption, distribution, metabolism and excretion (Sterner et al., 2013 Lee et al., 2007 Jonsson et al., 2001 El-Masri et al., 1996). However, differences in metabolism represent only one of several aspects which can explain interspecies differences. Rodent to human comparisons have often been performed by comparing data in human and mouse or rat hepatocytes (Carmo et al., 2004, 2005 Reder-Hilz et al., 2004 Hewitt et al., 2007 Gebhardt et al., 2003 Godoy et al., 2013 Hengstler et al., 1999). Interspecies differences represent a major problem in toxicology (Dohnal et al., 2014 Bernauer et al., 2000 Brüning et al., 2014 Gerbracht and Spielmann, 1998 Unkila et al., 1995 Leist and Hartung, 2013). In future, predictions may become even more accurate if RNA based data could be replaced by metabolic activities. A limitation of the current approach is that gene expression data were used to adjust for interspecies differences in metabolism. Next the authors showed that knowledge-based adjustment of each of the four model domains leads to an improvement and allows predictions which closely resemble the measured situation in humans. This naïve extrapolation usually resulted in predictions that strongly deviate from the real human situation. The authors start with a naïve extrapolation where humans are considered as 'large mice' where the same dose per body weight was administered (Thiel et al., 2015). Tissue-specific gene expression of the metabolizing key enzymes and transporters.
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