Histone variant H3.3 is a member of the human histone H3 family, it is expressed in whole cell cycle phases. H3.3 histone is encoded by two genes named H3.3A (H3F3A) and H3.3B (H3F3B) located on chromosome 1 and chromosome 17 respectively [1-3].Several studies have shown the possible role of histones methylation and acetylation with cancer [4].The goal of the present study is to explore different SNP variations in H3.3A gene and pathogenetic variations.

Ensembl, dbSNP NCBI[5], and Uniprot databases were  used to collect gene information.To evaluate the pathological nature of those variations, we selected 19 SNVs from 10 transcripts of the gene. We compared scores and predictions with 4 different software; SIFT,Polyphen-2, REVEL, and MUTATION- Assesor .

After checking all the transcripts and exons, we compared 19 SNP (table1)
The SIFT score considers a mutation  from 0.0  as (deleterious) and  to 1.0 as  (tolerated). This method shows that 18 SNVs are considered to be deleterious.
The levels of probably damaging and possibly damaging were classified as functionally significant (≤0.5) and the benign level being classified as tolerated (≥0.51) with PolyPhen-2, and in this study, it does only considered 13 SNPs as Probably damaging and 1 as Possibly damaging
REVEL  Scores above 0.5, as ‘likely disease causing’ and display scores below 0.5 as ‘likely benign, and this tool considered 7 SNPs as likely diseases causing.For Mutation-ASSESOR, the score is one of ‘neutral’, ‘low’, ‘medium’ and ‘high’, and the rank score, which is between 0 and 1 where variants with higher scores are more likely to be deleterious, and our results show only 2 SNPs as deleterious.Combining results of all methods, only 3 mutations appear to be clinically damaging , with a change from hydrophobic to hydrophilic amino acid in only one mutation.In conclusion, the present study shows combination of different softwares by an in-silico approach, to define most diseases-associated mutations, in the H3-3A gene. Protein prediction methods are recommended to a better understanding of structures and function.

Mots clés : histone 3, Pathogenicity prediction, in silico, SNVs

Auteurs : Nawel Souad Halfaoui 1, 2, M Dali-Youcef 2, Houssam Boulenouar 1, N Denouni 2, Y Harek 2
1- Cancer lab_ Université de Tlemcen, Tlemcen, Algérie, 
2- Analytical chemistry and Electrochemistry Lab, Tlemcen, Algérie

Mail de la personne à contacter pour questions : halfaouisouad@mail.com