Highly deleterious variations in COX1, CYTB, SCG5, FK2, PRL and PGF genes are the potential adaptation of the immigrated African ostrich population. (1st September 2018) - Al-Shuhaib, Mohammed Baqur S.; Al-Kafajy, Fadhil R.; Badi, Milad Ali; AbdulAzeez, Sayed; Marimuthu, Kasi; Al-Juhaishi, Hussein Ali Imran; Borgio, J. Francis
Abstract: Because of variable inconvenient living conditions in some places around the world, it is difficult to collect reliable physiological data for ostriches. Therefore, this study aims to provide a comprehensive in silico insight for the nature of polymorphism of important genetic loci that are related to physiological and reproductive traits. Sixty-nine mature ostriches ranging over half of Iraq were screened. Six exonic genetic loci, including cytochrome c oxidase I ( COX1 ), cytochrome b ( CYTB ), secretogranin V ( SCG5 ), feather keratin 2-like ( FK2 ), prolactin ( PRL ) and placenta growth factor ( PGF ) were genotyped by PCR-single stranded conformation polymorphism (SSCP). Thirty-six novel SNPs, including seventeen nonsynonymous (ns) SNPs, were observed. Several computational software programs were utilized to assess the extent of the nsSNPs on their corresponding proteins structure, function and stability. The results showed several deleterious functional and stability changes in almost all the proteins studied. The total severity of each missense mutation was evaluated and compared with other nsSNPs accumulatively. It is evident from the extensive cumulative in silico computation that both p.E34D and p.E60K in PGF have the highest deleterious effect. The cumulative predictions from the present study are an impressive guide for the genotypes of African ostriches, which bypassed the expensive protocols for wet laboratory screening, to identify the effects of variants. To the best of our knowledge, this is the first investigation of its kind on the analyses and prediction outcome of missense mutations in African ostrich populations. The highly deleterious nsSNPs in the placenta growth factor are possible adaptive mutations which might be associated with adaptation in extreme and new environments. The flow and protocol of the computational predictions can be extended for various wild animals to identify the molecular nature of adaptations.