Rufaida, O. S. Omer1*; Afra, M. Bakri1; Muna, A. M. Khaier2; Hind. A. Elnasri1

1*Corresponding author 

1-Department of Biochemistry and Molecular Biology, College of Veterinary Medicine, University of Bahri 

2- Department of Parasitology, College of Veterinary Medicine, University of Bahri 



Dobulecortin domain2 gene (DCDC2) which encodes for the doublecortin protein is located in chromosome 6p22.3. The doublecortin domain has been demonstrated to bind tubulin and enhance microtubule polymerization. Variants of the DCDC2 gene may affect the protein conformation and structure which might lead to learning disability (Dyslexia disease). The aim of this study was to analyze the genetic variation that can alter the expression and the function in DCDC2 gene using computational tools. 

This study focused on the coding region. The total number of SNPs was obtained from dbSNP database. A total of 22 SNPs were found to be damaging by both SIFT and PolyPhen software.When using I-Mutant 3.0 software, 20 nsSNPs showed decreased protein stability while only 2 SNPs showed increase in protein stability.

 This gene was found to co-expressed with 14 other genes and has a physical interaction with 1 gene using GeneMANIA software. A structural and functional analysis of ns SNPs was also studied by Project HOPE and Mupro software. Based on this work, four new ns SNPs are predicted to have pathological effect. Thus the most deleterious ns SNPs with an SNP IDs (rs375996594) was  proposed as the most important one. The others (rs372751993), – (rs36881196) and – (rs141060456) may also play an important role in investigation of dyslexia disease among patients.


Keywords: DCDC2, Dyslexia, Insilico Analysis, Reading Disability, Single Nucleotide Polymorphism (SNP)




Arwa A Mohammed1,2* , Ayman MH ALnaby2,Solima M Sabeel2,3 , Fagr M AbdElmarouf2,4, Amina I Dirar2,4,
Mostafa M Ali2,5, Mustafa A Khandgawi2,3, Abdelhameed M Yousif2,Eman M Abdulgadir2, Magdi A Sabahalkhair2,6, Ayman E Abbas2,7and Mohammed A Hassan2

1- Department of Pharmacy, Sudan Medical Council, Khartoum, Sudan
2- Department ofBiotechnology, Africa City of Technology, Khartoum, Sudan
3- Faculty of Medical Laboratory Sciences, University of Khartoum, Khartoum, Sudan
4- Faculty of Pharmacy, University of Khartoum,Khartoum, Sudan
5- Faculty of Medical Laboratory, University of Sciences and Technology,Omdurman, Sudan
6- Faculty of Pharmacy, The National Ribat University, Khartoum, Sudan
7- Facultyof Medicine and Health Sciences, Omdurman Islamic University, Omdurman, Sudan

Mycetoma is a distinct body tissue destructive and neglected tropical disease. It is endemic in many tropical and subtropical countries. Mycetoma is caused by bacterial infections actinomycetoma such as Streptomyces somaliensis and Nocardiae or true fungi eumycetoma such as Madurella mycetomatis. To date, treatments fail to cure the infection and the available marketed drugs are expensive and toxic upon prolonged usage. Moreover, no vaccine was prepared yet against mycetoma.
The aim of this study is to predict effective epitope-based vaccine against fructose-bisphosphate aldolase enzymes of M. mycetomatis using immunoinformatics approaches.
Methods and materials:
Fructose-bisphosphate aldolase of M. mycetomatis sequence was retrieved from NCBI. Different prediction tools were used to analyze the nominee’s epitopes in Immune Epitope Database for B-cell, T-cell MHC class II and class I. Then the proposed peptides were docked using Autodock 4.0 software program.
Results and conclusions:
The proposed and promising peptides KYLQ show a potent binding affinity to B-cell, FEYARKHAF with a very strong binding affinity to MHC I alleles and FFKEHGVPL that shows a very strong binding affinity to MHC II and MHC I alleles. This indicates a strong potential to formulate a new vaccine, especially with the peptide FFKEHGVPL which is likely to be the first proposed epitope-based vaccine against fructose-bisphosphate aldolase of M. mycetomatis. This study recommends an in vivo assessment for the most promising peptides especially FFKEHGVPL.


Computational Analysis of Functional Coding/Noncoding Single Nucleotide Polymorphisms (SNPs/Indels) in Human NEUROG1 gene

Computational Analysis of Functional Coding/Noncoding Single Nucleotide Polymorphisms (SNPs/Indels) in Human NEUROG1 gene


Shimaa M. Mahalah* , Zhoor A. A Hamid . Samah M Ibrahim. Shahazalia k babiker

Faculty of medicine, Sudan University of Science and Technology (Sudan).

Faculty of pharmacy, Al-Neelain University  (Sudan).

Faculty of medical laboratory, University of medical sciences and Technology  (Sudan).

Faculty of medical laboratory ,University of medical sciences and technology (Sudan).

*Corresponding author:


Human NEUROG1 gene encodes the protein neurogenin1 that has been demonstrated to have an essential role as a transcription factor in the process of neurogenesis and neuron repair. Mutations in this gene have been linked to many congenital diseases and to CNS diseases in adulthood. This study used bioinformatics tools to evaluate the effect of mutations along the sequence of the gene. Genomic data has been retrieved from databases in NCBI, GenBank and Ensembl; 617 SNPs and INDels were reported in the dbSNP spanning the coding and noncoding regions. There were 193 SNPs found in the coding region and only four of them have been predicted as deleterious. Modeling of the three-dimensional structure of NEUROG1 was generated through I-TASSER program and validated by different software. Analysis of 3’ UTR region showed that eight SNPs were found to have an effect on microRNA binding sites either by creating or disturbing them, and another three INDels were not observed to have any effect. This study is a proposed computational analysis for the possible effect of reported nonsynonymous SNPs on the functionality of NEUROG1 gene, and subsequently its protein, as an important cofactor in neuron formation. This gene has been suggested as a candidate for gene therapy at genetics and epigenetics levels and/or drug design of neurodevelopmental and neurodegenerative diseases.

Key words: Computational analysis, NEUROG1, Single Nucleotide Polymorphisms (SNPs), neurogenesis, gene therapy.



Sumaya Kambal



Sumaya Kambal1, Amna Alnazir2, Bashir Salim3


1Faculty of Animal Production Science & Technology, Sudan University of Science & Technology, 2Faculty of Veterinary Medicine, University of Khartoum, 3Department of Parasitology, Faculty of Veterinary Medicine, University of Khartoum




Background: Western Baggara cattle breed is naturally inhabiting the western regions of the Sudan, primarily raised by nomadic pastoralists in Darfur and Kurdofan states and ranked the best beef producing cattle breed in the country. This breed had structured phenotypically into three populations, Nyalawi, Rezaigi and Messairi. Decades to date, western Baggara cattle breed-Nyalawi population (WBCB-NP) is the most reputable beef cattle among the other types by its large size that contribute significantly to local meat consumption as well as to the export revenue.

Aims: This study was undertaken to investigate the maternal genetic diversity and the demography dynamic by addressing whether this population had undergone demographic expansion, decline or equilibrium.

Method: Genomic DNA was extracted from blood of 30 animals selected WBCB-NP and subjected to PCR targeting the entire mitochondrial DNA D-loop region and subsequently to DNA sequencing.

Results: This resulted in 43 polymorphic sites that defined 28 haplotypes of which 4 signatures of breed specific transition were detected when compared to bovine reference sequence. Genetic diversity indices revealed high level of haplotype diversity (1.000 ± 0.0091) and low level of nucleotide diversity (0.005 ± 0.0028) between these haplotypes that agreed with the Median Joining and Minimum Spanning networks’ pattern, and the Neighbor Joining phylogenetic tree. The revealed unimodal pattern of the mismatch distribution among the haplotypes was in a good accordance with both the negative values of Tajima’s D (-2.259; P= 0.000) and Fu’s Fs (-25.671; P= 0.000) results that are significantly deviated from the neutral model, suggesting population demographic expansion event.

Conclusion: It is concluded that WBCB-NP is highly divers and had experienced a demographic growth. This study has raised important queries about the nature and the factors of this demographic expansion that can be compared with other populations of cattle for historical dynamics tracing purpose.


The presenter: Sumaya Yousof Yassin Kambal

Teaching Assistant

Faculty of Animal Production Science and Technology, Sudan University of Science and Technology


Somia Mohamed



Somia Mohammed1, Mohssin H. Abdalla2, Alia Benkahla3, Faisal M. Fadlelmola1 1Centre for Bioinformatics & Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Bayan College for science and Technology, Sudan 2Faculty of Mathematical Sciences, University of Khartoum, Khartoum, Sudan 3Laboratory of BioInformatics, bioMathematics and bioStatistics (BIMS), Institute Pasteur of Tunis, Tunis

Cervical cancer is the second most common type of cancer in women worldwide. Due to poor access to screening and treatment services, more than 90% of deaths occur in women living in low- and middle-income countries. Although a diagnostic tool (PapTest) is widely available, cervical cancer incidence still remains high worldwide, and especially in developing countries, attributed to a large extent to sensitivities of the Pap test and unavailability of test in developing countries.

In this study, multi-omics data analysis was evaluated by integrating array-CGH,gene expression datasets in cervical cancer. meta-analysis approach was adopted whereby cervical cancer multi-omics datasets from Gene Expression Omnibus (GEO) to increase insurance of result and extract all passible in formation by reusing data sets, aCGH and  gene expression in early stages of cancer, were selected to set up the analysis. Each data set was analyzed separately by implementing R scripts. The dataset were subject to statistical tests (e.g. T-test and Other statistical  tests).

We get result in multi-layer of biological genomic transciptomics. Aberration chromosomal regions showed significant amplification or deletion  in most of samples in chromosomes  1,3 and 19  whereas deletion found in 11, 4 and 13. The aCGH data is searched for genes with a known regulatory role whose copy number is altered in the samples.

In genes level get gene list in We find that list of more significant genes its high expressed in  cancer stage. we tracing that gene in matched transcriptomics data is then examined to see if a gene’s altered  with a concurrent change in the gene’s expression, thus adding weight to the argument that the gene may be contributing to cervical cancer. The list of genes that show strong aCGH/expression is subjected to various public databases (e.g. OMIM) to perform further in silico analysis and validation.



The last 2 authors contributed equally to this work.





Oluwafemi A. Sarumi and Adebayo O.  Adetunmbi.

The Federal University of Technology, Akure, Ondo State, Nigeria.



This research is geared towards early identification of genes with inherent traits and potential to develop into cancerous tissues in Eukaryotic organisms.


Widespread of Deoxyribonucleic Acid (DNA) palindromes accentuates gene amplification in Eukaryotic organisms. Investigations from model systems have demonstrated that palindrome formation can be an early rate-limiting step in DNA amplification. Also, bioinformatics research has discovered that early detection of palindromes in organisms’ genome can aid the prediction of cancerous tissues growth in cell and also infertility in males. A palindrome sequence is a character sequence that reads the same frontwards and backward. DNA palindromes are words from the nucleotide base alphabets A, T, G, and C that are symmetrical in the sense that they read exactly the same as their complementary sequences in the reverse direction (inverted repeats).


In this research, we developed an algorithm using the Hidden Markov Models (HMM) to discover implicit, and previously unknown palindrome sequences from large volumes of eukaryotic organisms’ DNA sequences. HMMs are statistical models that can be used to describe the evolution of observable events that depend on internal factors, which are not directly observable. Also, our algorithm was implemented on the Spark parallel framework to provide for easy scalability as the volume of the datasets increases.


Experimental results show the effectiveness and high performance of our algorithm in mining hidden palindrome sequences from large volumes of genomic data.


Identification of palindrome sequences in genes of Eukaryotic organisms would initiate a treatment procedure that could prevent such genes from growing into cancerous tissues.






Najlaa Kharrat




Najla Kharrat1*, Sabrine Belmabrouk1, Rania Abdelhedi1, Amine Ben Ayed1, Riadh Benmarzoug1 and Ahmed Rebai1


1 : Centre de Biotechnologie de Sfax, laboratoire des procédés de criblage moléculaire er cellulaires, POBOX « 1177 » 3018, Sfax, Tunisie.

* : Correspondance :


Background: Studying genetic variation distribution in proteins containing charged regions, called charge clusters (CCs), is of great interest to unravel their functional role. Charge clusters are 20 to 75 residue segments with high net positive charge, high net negative charge, or high total charge relative to the overall charge composition of the protein. We previously developed a bioinformatics tool (FCCP) to detect charge clusters in proteomes and scanned the human proteome for the occurrence of CCs. In this paper we investigate the genetic variations in the human proteins harbouring CCs.

Results: We studied the coding regions of 317 positively charged clusters and 1020 negatively charged ones previously detected in human proteins. Results revealed that coding parts of CCs are richer in sequence variants than their corresponding genes, full mRNAs, and exonic + intronic sequences and that these variants are predominately rare (Minor allele frequency < 0.005). Furthermore, variants occurring in the coding parts of positively charged regions of proteins are more often pathogenic than those occurring in negatively charged ones. Classification of variants according to their types showed that substitution is the major type followed by Indels (Insertions-deletions). Concerning substitutions, it was found that within clusters of both charges, the charged amino acids were the greatest loser groups whereas polar residues were the greatest gainers.

Conclusions: Our findings highlight the prominent features of the human charged regions from the DNA up to the protein sequence which might provide potential clues to improve the current understanding of those charged regions and their implication in the emergence of diseases.


Faisal Koua


Rawia Mekki Hammad Mohammed1, Mona Ali Magrabi Mohammed1, Hajer Suleiman Hamdan Teia1, Sara Mohammed Ali Mohammed1, Faisal Hammad Mekky Koua2,3

1Department of Biology & Biotechnology, Faculty of Science & Technology, Al Neelain University, El-Baladiya Ave, PO Box 12702, Khartoum, Sudan. 2National University Research Institute-NURI, National University-Sudan, Air St, PO Box 3783, Khartoum, Sudan. 3Department of Biochemistry & Molecular Biology, Faculty of Science & Technology, Al Neelain University, El Baladiya Ave, PO Box 12702, Khartoum, Sudan.


Background and aim: Human oral microbiome is the total microbes and/or their genomic content that are harbored within a human mouth. They can be assessed by culture dependent and/or culture-independent methods. Here, we adopted a culture dependent method to unravel the cultivable firmicutes and the yeast Candida albicans of the human oral cavity. Methods: A comprehensive sampling method established during this study was used to collect samples from 11 donors and cultivated on selective media for firmicutes and C. albicans isolation followed by isolates identification using conventional microbiological techniques. Results: As a result, 24 bacteria isolates were identified and classified as firmicutes and related strains from actinobacteria with 96% and 4%, respectively. The assignments have resulted in 52.9% staphylococci, 41.2% bacilli and 4% clostridia, as well as micrococcus. On the other hand, 9 isolates of yeasts were identified as C. albicans. The majority of firmicutes were tolerant, while the staphylococci were mostly drug resistant especially toward tetracycline, lincomycin and cloxacillin. When co-cultured against each other, the B. mycoides isolates affected the growth of S. aureus, which is itself affected the growth of other staphylococci. Except the clostridium isolates, most of the isolates are salt tolerant up to 3.4 M NaCl. C. albicans growth was limited by >1.7 M NaCl as well as low temperature (<10 ºC). It exerts tolerance against clotrimazole and moderate susceptibility to nystatin antifungal drugs. Excessive phylogenetic analysis revealed more insights into the diversity of oral microbes. Conclusion: Further, genomic characterization for the B. mycoides and C. albicans will be considered in order to have a complete picture on these oral microbiome isolates and their interactions with other microbes residing the human oral cavity.


Azza Ahmed


 1,2Azza Ahmed, 3Gloria Rendon, 3,4Liudmila Sergeevna Mainzer, 4Victor Jongeneel, 1Faisal M. Fadlelmola

1Centre for Bioinformatics and Systems Biology, Faculty of Science, University of Khartoum, Sudan

2Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Khartoum, Sudan

3Institute for Genomic Biology, University of Illinois Urbana-Champaign, USA

4National Center for Supercomputing Applications, University of Illinois Urbana-Champaign, USA


The advent of massively parallel sequencing technologies (Next Generation Sequencing, NGS) had modified the landscape of human genetics. Whole Exome Sequencing (WES) is the NGS branch that focuses on the exonic regions of the eukaryotic genomes. Exomes are of interest as they are helping us understand high-penetrance allelic variation and its relationship to phenotype.

Variant calling is a study of genomic sequences differences, between some samples of interest and the reference genome; with the purpose of aiding understanding disease (or phenotype mechanism) and ultimately designing optimal treatment targets (i.e. personalized medicine). Typically, this involves many wet lab assays and procedures for preparing the biological samples and intensive computational processing via  many tools and software. Errors can creep into the analysis from any of these aspects.

When carried out in large cohorts, errors are exacerbated, and the variants observed at the level of the individual are lost in joint genotyping. Besides experimental wet lab errors, the called variants are subject to biases due to the choice of software, configuration of the analysis pipeline, and individual parameters of each tool used. Also intended as the pilot phase of a collaboration with Mayo Clinic in Florida, USA, this talk provides insights into the effect of the parameter configurations in a variant calling pipeline following GATK best practices from a mathematical point of view, along with experimental results, with the objective of identifying optimization targets in such a set up. Computational challenges relating to running the pipeline in this context are also highlighted.



Abubakr alayis poster


Abubaker, A. Elayis1; Yasir, A. Almofti2; Mohamed Ahmed Salih3 and Koubaeb4

1Department of Internal Medicine, College of Veterinary Medicine, University of Bahri, Sudan.

2Department of Biochemistry, College of Veterinary Medicine, University of Bahri, Sudan.

3Department of Biochemistry, College of Veterinary Medicine, University of Bahri Sudan.

4Department of Biochemistry, College of Veterinary Medicine, University of Bahri, Sudan.


This research aiming at designing new epitopes (Multiple Antigen Peptide) (MAP) vaccine by using Insilico software of Bioinformatics, because vaccines based on synthetic peptides would be safe and easy to produce. 22 capsid protein (VP2) amino acid residues of Canine Parvovirus (CPV) were retrieved from National Center of Biotechnology Information (NCBI). The retrieved sequences were aligned to obtain conserved regions using Multiple Sequence Alignment (MSA) software. Sequences aligned with the assist of Clustal W. as prelocate in the Bio Edit program. Chosen epitopeswre analyzed by different prediction tools from Immune Epitope Database (IEDB) which assist in the prediction and analysis of B cell and T cell epitopes. Bepired software from IEDB was used for linear B cell epitopes prediction from the conserved region with a dereliction threshold value of 0.306. By using Emini surface accessibility prediction tool of IBED. The surface accessibility of epitopes was predicted from the conserved region contract the default threshold value of 1.000 or higher. The Kolaskar and Tongaolsnkar antigenicity method was used to determine the antigenic sites with a threshold value of 1.033. Selected epitopes of MHC1 were turned into 3D models using PEP_FOLD online peptide modeling tool. Models were examined to obtain dog DLA by using Patchdock software. 6 peptides were suggested to form MAP vaccine. The selected peptides were: 157SATQPPTKV165 (peptide interacts with B cells), 336EVGYSAPYY344 (peptide interacts with B cells), 211YYFQWDRTL219 (peptide interacts with MHCI and T cells), 245YTIENSVPV253 (peptide interacts with MHCI and T cells), 16VRNERATGS24 (peptide interacts with MHCIIO and T cells) and 59WVEITANSS67 (peptide interacts with MHCII and T cells).