Bioinformatics analysis of gene causing Vankoni's syndrome

Nowadays the research on cancer has been a hot issue and in the process of the research on diseases related to cancer, much attention has also been paid to some indirect cause leading to cancer, like Fanconi anemia. Fanconi anemia is a kind of X chromosome chain of genetic diseases, which is not common currently and sometimes will also be a autosomal disease. For this kind of disease, most of the onset ages is at5to10years old and it is characterized by progressive failure in the bone marrow hematopoietic function. And the patients with this disease will often be accompanied by congenital deformities, which is relatively easy to develop into cancer and eventually into malignant tumors by about20%. So far at least9gene subtypes are found, for which the coding of the core protein complexes and the breast cancer susceptibility genes (BRCA) can make up a complex function network and the mutations in the genes of Fanconi anemia will lead to the impairment of the network’s DNA repair function, which can make people get sick. Therefore, the research on the relationship between the genes and proteins in the pathway of Fan Keni will have great theoretical and pratical significane in the bioinformatics analysis of FA.This study adopts two different research methods, namely, the traditional mathematical analysis-Boolean network research in Fanconi anemia pathways and the bioinformatics analysis of Fanconi anemia.In the first part, the mathematical model of Boolean network and the research progress of its evolution----probabilistic Boolean networks are involved and then the Boolean network is applied in the study of Fanconi anemia pathways and in this paper parts of the state of genetic truth table are presented. FA disease gene regulatory network is built through the combination of the existing data and logic structure among genes, and the inhibitory and non-inhibitory network are applied to the analysis of the classification of well structured FA probability Boolean network, which will be of great value to the treatment of Fanconi anemia syndrome.In the second part, this article adopts the research method of comparative genome to analyze the similarity and homology of gene sequence between the Fanconi anemia pathway of zebrafish and mankind. The sequences and data in this paper are from NCBI and the sequence alignment involved is ClustalX software which is commonly used. NCBI is rich in the sequences and genome structure of human and zebrafish. First, after the introduction of research significance, the distribution position on chromosome of all Fanconi anemia genes subtypes in human and zebrafish is presented. As in Fanconi anemia disease-causing genes, FANCA (about60%), FANCC (about15%) and FANCG (around10%) in all kinds of disease have the highest percentage of mutations in the crowd, we then show an analysis on FANCA\FANCC\FANCG genes respectively. The results are the followings:(1) from the comparison the exons distribution structions of the three kinds of genes, the absence or mutation or increase or decrease of the exons substructure is not greatly different.(2) from the mRNA sequence comparison, the results also show that the sequence difference in human has a small difference with that in zebrafish.(3) the distribution position of various genes in their respective chromosome loci is presented, the corresponding results are obtained from the similarity.Through the analysis, it proves that the Fan maintains linear conservative in the evolution of zebrafish and human. Because the embryos of zebrafish are transparent, biologists can easily observe the influence of drugs on its internal organs. In this way, scientists can develop drugs to zebrafish to observe its different phenotypes, from which some relative scientific conclusions can be obtained to make a significant difference to the overcome of this kind of disease for human.Although the two methods are different, the expected research purposes can be achieved. In the research process, the model design is abstracted by mathematics, which may have slight deviation with the actual biological process. And the bioinformatics analysis is done through a large number of genes comparison, which also can’t involve all genes in biology, so there may be individual differences, which need to be further solved. We are looking forward to the improvement of the research in Fanconi anemia through the cooperation of different disciplines.