Exploring evolution of brain genes involved in microcephaly through phylogeny and synteny analysis.

Abstract

Background: Human brain development is a complicated process. When normal growth and development of brain or central nervous system is impaired, it leads to neurodevelopemental disorders (NDDs). Autosomal Recessive Primary Microcephaly (MCPH) is one of those, for which seven loci (MCPH1-MCPH7) with the corresponding genes (MCPH1, WDR62, CDK5RAP2, CEP152, ASPM, CENPJ, and STIL) have been reported so far. An important field of study is to find out diversity among organisms due to evolution. How species are related to each other can be inferred through finding evolutionary relationship between organisms in the form of ancestors and descendents.

Methods: MEGA5 was used for phylogenetic tree reconstruction. Pair-wise and multiple alignment was built through ClustalW algorithm. Neighbor joining (NJ) and maximum parsimony (MP) methods were used for tree reconstruction. Bootstrap analysis was done to check the reliability of trees. Synteny analysis was performed using Ensemble synteny view in ensemble database and genome synteny viewer (GSV).

Results: Evolutionary time for single gene trees showed that CENPJ (0.02) evolving rapidly while CDK5RAP2 (0.1) evolving with least rate as compare to other genes. All trees were reconciling the species divergence time. Chimpanzee was inferred as closest specie of Human. In MCPH combined tree, five duplications were observed. Four duplications were before and one was after vertebrate and invertebrate divergence. Two genes MCPH1 and WDR62 were closely related with each other. Synteny analysis indicated that maximum conservation of Human was with Chimpanzee. Highly conserved synteny was observed for Human and Chimpanzee in case of CENPJ with no deletion.

Conclusion: It has been hypothesized that due to having closest relationship, mutations can affect Chimpanzee likewise as these affect Human. Conservation shows that apart from sequence similarity, function of MCPH genes in closely related species is also same and this function disrupts as a result of mutation and hence leads to the diseased state. Huge genomic and proteomic data is available today which enables us to perform In Silico analysis. Our cost and time effective analysis has opened many insights into disease understanding and it will definitely provide a way towards accurate diagnosis.