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Background: Disparities in the genetic risk of cancer among various ancestry groups and populations remain poorly defined. This challenge is even more acute for Middle Eastern populations, where the paucity of genomic data could affect the clinical potential of cancer genetic risk profiling. We used data from the phase 1 cohort of the Qatar Genome Programme to investigate genetic variation in cancer-susceptibility genes in the Qatari population. Methods: The Qatar Genome Programme generated high-coverage genome sequencing on DNA samples collected from 6142 native Qataris, stratified into six distinct ancestry groups: general Arab, Persian, Arabian Peninsula, Admixture Arab, African, and South Asian. In this population-based, cohort study, we evaluated the performance of polygenic risk scores for the most common cancers in Qatar (breast, prostate, and colorectal cancers). Polygenic risk scores were trained in The Cancer Genome Atlas (TCGA) dataset, and their distributions were subsequently applied to the six different genetic ancestry groups of the Qatari population. Rare deleterious variants within 1218 cancer susceptibility genes were analysed, and their clinical pathogenicity was assessed by ClinVar and the CharGer computational tools. Findings: The cohort included in this study was recruited by the Qatar Biobank between Dec 11, 2012, and June 9, 2016. The initial dataset comprised 6218 cohort participants, and whole genome sequencing quality control filtering led to a final dataset of 6142 samples. Polygenic risk score analyses of the most common cancers in Qatar showed significant differences between the six ancestry groups (p

In October 2020, 62 scientists from nine nations worked together remotely in the Second Baylor College of Medicine & DNAnexus hackathon, focusing on different related topics on Structural Variation, Pan-genomes, and SARS-CoV-2 related research. The overarching focus was to assess the current status of the field and identify the remaining challenges. Furthermore, how to combine the strengths of the different interests to drive research and method development forward. Over the four days, eight groups each designed and developed new open-source methods to improve the identification and analysis of variations among species, including humans and SARS-CoV-2. These included improvements in SV calling, genotyping, annotations and filtering. Together with advancements in benchmarking existing methods. Furthermore, groups focused on the diversity of SARS-CoV-2. Daily discussion summary and methods are available publicly at https://github.com/collaborativebioinformatics provides valuable insights for both participants and the research community.

To describe the clinical features, epidemiology, autoantibody status, HLA haplotypes and genetic mechanisms of type 1 diabetes mellitus (T1DM). Patients (0–18 years) with diabetes were recruited. Clinical data was collected, autoantibodies and c-peptide were measured. Whole Genome Sequencing was performed. Genomic data analysis was compared with the known genes linked with T1DM and HLA alleles were studied. 1096 patients had one or more antibody positivity. The incidence of T1DM in 2020 was 38.05 per 100,000 children and prevalence was 249.73. GADA was the most common autoantibody followed by IAA. Variants in GSTCD, SKAP2, SLC9B1, BANK1 were most prevalent. An association of HLA haplotypes DQA1*03:01:01G (OR = 2.46, p value = 0.011) and DQB1*03:02:01G (OR = 2.43, p value = 0.022) was identified. The incidence of T1DM in Qatar is the fourth highest in the world, IA2 autoantibody was the most specific with some patients only having ZnT8 or IA2 autoantibodies thus underlining the necessity of profiling all 4 autoantibodies. The genes associated with T1DM in the Arab population were different from those that are common in the Caucasian population. HLA-DQ was enriched in the Qatari patients suggesting that it can be considered a major risk factor at an early age.

Background Neonatal diabetes mellitus (NDM) is a rare condition that occurs within the first six months of life. Permanent NDM (PNDM) is caused by mutations in specific genes that are known for their expression at early and/or late stages of pancreatic beta‐ cell development, and are either involved in beta‐cell survival, insulin processing, regulation, and release. The native population in Qatar continues to practice consanguineous marriages that lead to a high level of homozygosity. To our knowledge, there is no previous report on the genomics of NDM among the Qatari population. The aims of the current study are to identify patients with NDM diagnosed between 2001 and 2016, and examine their clinical and genetic characteristics. Methods To calculate the incidence of PNDM, all patients with PNDM diagnosed between 2001 and 2016 were compared to the total number of live births over the 16‐year‐period. Whole Genome Sequencing (WGS) was used to investigate the genetic etiology in the PNDM cohort. Results PNDM was diagnosed in nine (n = 9) patients with an estimated incidence rate of 1:22,938 live births among the indigenous Qatari. Seven different mutations in six genes (PTF1A, GCK, SLC2A2, EIF2AK3, INS, and HNF1B) were identified. In the majority of cases, the genetic etiology was part of a previously identified autosomal recessive disorder. Two novel de novo mutations were identified in INS and HNF1B. Conclusion Qatar has the second highest reported incidence of PNDM worldwide. A majority of PNDM cases present as rare familial autosomal recessive disorders. Pancreas associated transcription factor 1a (PTF1A) enhancer deletions are the most common cause of PNDM in Qatar, with only a few previous cases reported in the literature.

Essential hypertension (EH) is a leading risk condition for cardiovascular and renal com-plications. While multiple genes are associated with EH, little is known about its genetic etiology. Therefore, this study aimed to screen for variants that are associated with EH in 100 hypertensive/100 control patients comprising Qatari individuals using GWASs of whole-genome sequencing and compare these findings with genetic data obtained from more than 10,000 published peer-reviewed studies on EH. The GWAS analysis performed with 21,096 SNPs revealed 38 SNPs with a significant ?4 log-pval association with EH. The two highest EH-associated SNPs (rs921932379 and rs113688672) revealed a significance score of ?5 log-pval. These SNPs are located within the inter-genic region of GMPS-SETP14 and ISCA1P6-AC012451.1, respectively. Text mining yielded 3748 genes and 3078 SNPs, where 51 genes and 24 SNPs were mentioned in more than 30 and 10 different articles, respectively. Comparing our GWAS results to previously published articles revealed 194 that are unique to our patient cohort; of these, 13 genes that have 26 SNPs are the most significant with ?4 log-pval. Of these genes, C2orf47-SPATS2L contains nine EH-associated SNPs. Most of EH-associated genes are related to ion gate channel activity and cardiac conduction. The disease-gene analysis revealed that a large number of EH-associated genes are associated with a variety of cardiovascular disorders. The clustering analysis using EH-associated SNPs across different ethnic groups showed high frequency for the minor allele in different ethnic groups, including Africans, East Asians, and South Asians. The combination of GWAS and text mining helped in identifying the unique genetic susceptibility profile of Qatari patients with EH. To our knowledge, this is the first small study that searched for genetic factors associated with EH in Qatari patients. 2022 by the authors. Licensee MDPI, Basel, Switzerland. Funding: This work was supported by the Qatar university grants QUST-1-CHS-2019-11 and QUST-1-CHS-2019-12. Scopus

Next generation sequencing (NGS) data analysis is highly compute intensive. In-memory computing, vectorization, bulk data transfer, CPU frequency scaling are some of the hardware features in the modern computing architectures. To get the best execution time and utilize these hardware features, it is necessary to tune the system level parameters before running the application. We studied the GATK-HaplotypeCaller which is part of common NGS workflows, that consume more than 43% of the total execution time. Multiple GATK 3.x versions were benchmarked and the execution time of HaplotypeCaller was optimized by various system level parameters which included: (i) tuning the parallel garbage collection and kernel shared memory to simulate in-memory computing, (ii) architecture-specific tuning in the PairHMM library for vectorization, (iii) including Java 1.8 features through GATK source code compilation and building a runtime environment for parallel sorting and bulk data transfer (iv) the default ’on-demand’ mode of CPU frequency is over-clocked by using ’performance-mode’ to accelerate the Java multi-threads. As a result, the HaplotypeCaller execution time was reduced by 82.66% in GATK 3.3 and 42.61% in GATK 3.7. Overall, the execution time of NGS pipeline was reduced to 70.60% and 34.14% for GATK 3.3 and GATK 3.7 respectively.

BackgroundMonoallelic expression (MAE) is a frequent genomic phenomenon in normal tissues, however its role in cancer is yet to be fully understood. MAE is defined as the expression of a gene that is restricted to one allele in the presence of a diploid heterozygous genome. Constitutive MAE occur for imprinted genes, odorant receptors and random X inactivation. Several studies in normal tissues have showed MAE in about 5–20% of the cases. However, little information exists on the MAE rate in cancer. In this study we assessed the presence and rate of MAE in melanoma. The genetic basis of melanoma has been studied in depth over the past decades, leading to the identification of mutations/genetic alterations responsible for melanoma development. To examine the role of MAE in melanoma we used 15 melanoma cell lines and compared their RNA-seq data with genotyping data obtained by the parental TIL (tumor infiltrating lymphocytes).MethodsGenotyping was performed by Illumina HumanOmni1 beadchip. For the RNA-seq experiment, library preparation and sequencing was performed using the Illumina TruSeq Stranded Total RNA Human Kit and subsequently sequenced using a HiSeq 2500 according to manufacturer's guidelines. Genotype calling and subsequent quality filtering was performed in Illumina's Genome Studio software. IMPUTE2 (University of Oxford) was used for imputation of the genotyped data. RNA-Seq analysis was performed using the Broad Best Practice Workflows for RNA-Seq with the exception that a genotype was created for every available base pair in order to compare to the genotyped array data. In house custom perl scripts were then created to compare the genotyping data to the processed RNA-Seq data. The genotype and the B-allele frequency were calculated the latter creating a range of expression to evaluate.By comparing genotyping data with RNA-seq data, we identified SNPs in which DNA genotypes were heterozygous and corresponding RNA genotypes were homozygous. All homozygous DNA genotypes were removed prior to the analysis. To confirm the validity to detect MAE, we examined heterozygous DNA genotypes from X chromosome of female samples as well as for imprinted and olfactory receptor genes and confirmed MAE.ResultsMAE was detected in all 15 cell lines although to a different rate (spanning from approximately 17% to 75% MAE). When looking at the B-allele frequencies we found a preferential pattern of complete monoallelic expression rather then differential monoallelic expression across the 15 melanoma cell lines. As some samples showed high differences in the homozygous and heterozygous call rate, we looked at the single chromosomes and showed that MAE may be explained by underlying large copy number imbalances and isodisomy in some instances. Nevertheless, some chromosome regions showed MAE without CN imbalances suggesting that additional mechanisms (including epigenetic silencing) may explain MAE in melanoma.ConclusionThe biological implications of MAE are yet to be realized. Nevertheless our findings suggest that MAE is a common phenomenon in melanoma cell lines. Further analyses are currently being undertaken to evaluate whether MAE is gene/pathway specific and to understand whether MAE can be employed by cancers to achieve a more aggressive phenotype.

When searching for disease-causing mutations with polymerase chain reaction (PCR)-based methods, candidate genes are usually screened in their entirety, exon by exon. Genomic resources (i.e. www.ncbi.nih.gov, www.ensembl.org, and genome.ucsc.edu) largely support this paradigm for mutation screening by making it easy to view and access sequence data associated with genes in their genomic context. However, the administrative burden of conducting mutation screening in potentially hundreds of genes and thousands of exons in thousands of patients is significant, even with the use of public genome resources. For example, the manual design of oligonucleotide primers for all exons of the 10 Leber's congenital amaurosis (LCA) genes (149 exons) represents a significant information management challenge. The Transcript Annotation Prioritization and Screening System (TrAPSS) is designed to accelerate mutation screening by (1) providing a gene-based local cache of candidate disease genes in a genomic context, (2) automating tasks associated with optimizing candidate disease gene screening and information management, and (3) providing the implementation of an algorithmic technique to utilize large amounts of heterogeneous genome annotation (e.g. conserved protein functional domains) so as to prioritize candidate genes.

Mechanisms for controlling symbiont populations are critical for maintaining the associations that exist between a host and its microbial partners. We describe here the transcriptional, metabolic, and ultrastructural characteristics of a diel rhythm that occurs in the symbiosis between the squid Euprymna scolopes and the luminous bacterium Vibrio fischeri. The rhythm is driven by the host’s expulsion from its light-emitting organ of most of the symbiont population each day at dawn. The transcriptomes of both the host epithelium that supports the symbionts and the symbiont population itself were characterized and compared at four times over this daily cycle. The greatest fluctuation in gene expression of both partners occurred as the day began. Most notable was an up-regulation in the host of >50 cytoskeleton-related genes just before dawn and their subsequent down-regulation within 6 h. Examination of the epithelium by TEM revealed a corresponding restructuring, characterized by effacement and blebbing of its apical surface. After the dawn expulsion, the epithelium reestablished its polarity, and the residual symbionts began growing, repopulating the light organ. Analysis of the symbiont transcriptome suggested that the bacteria respond to the effacement by up-regulating genes associated with anaerobic respiration of glycerol; supporting this finding, lipid analysis of the symbionts’ membranes indicated a direct incorporation of host-derived fatty acids. After 12 h, the metabolic signature of the symbiont population shifted to one characteristic of chitin fermentation, which continued until the following dawn. Thus, the persistent maintenance of the squid–vibrio symbiosis is tied to a dynamic diel rhythm that involves both partners.

The light–organ symbiosis between the squid Euprymna scolopes and the luminous bacterium Vibrio fischeri offers the opportunity to decipher the hour-by-hour events that occur during the natural colonization of an animal's epithelial surface by its microbial partners. To determine the genetic basis of these events, a glass-slide microarray was used to characterize the light-organ transcriptome of juvenile squid in response to the initiation of symbiosis. Patterns of gene expression were compared between animals not exposed to the symbiont, exposed to the wild-type symbiont, or exposed to a mutant symbiont defective in either of two key characters of this association: bacterial luminescence or autoinducer (AI) production. Hundreds of genes were differentially regulated as a result of symbiosis initiation, and a hierarchy existed in the magnitude of the host's response to three symbiont features: bacterial presence > luminescence > AI production. Putative host receptors for bacterial surface molecules known to induce squid development are up-regulated by symbiont light production, suggesting that bioluminescence plays a key role in preparing the host for bacteria-induced development. Further, because the transcriptional response of tissues exposed to AI in the natural context (i.e., with the symbionts) differed from that to AI alone, the presence of the bacteria potentiates the role of quorum signals in symbiosis. Comparison of these microarray data with those from other symbioses, such as germ-free/conventionalized mice and zebrafish, revealed a set of shared genes that may represent a core set of ancient host responses conserved throughout animal evolution.

Zabner, Joseph, Todd E. Scheetz, Hakeem G. Almabrazi, Thomas L. Casavant, Jian Huang, Shaf Keshavjee, and Paul B. McCray, Jr. CFTR F508 mutation has minimal effect on the gene expression profile of differentiated human airway epithelia. Am J Physiol Lung Cell Mol Physiol 289: L545–L553, 2005. First published June 3, 2005; doi:10.1152/ajplung.00065.2005.—Cystic fibrosis (CF) is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR), an epithelial chloride channel regulated by phosphorylation. Most of the disease-associated morbidity is the consequence of chronic lung infection with progressive tissue destruction. As an approach to investigate the cellular effects of CFTR mutations, we used large-scale microarray hybridization to contrast the gene expression profiles of well-differentiated primary cultures of human CF and non-CF airway epithelia grown under resting culture conditions. We surveyed the expression profiles for 10 non-CF and 10 F508 homozygote samples. Of the 22,283 genes represented on the Affymetrix U133A GeneChip, we found evidence of significant changes in expression in 24 genes by two-sample t-test (P 0.00001). A second, three-filter method of comparative analysis found no significant differences between the groups. The levels of CFTR mRNA were comparable in both groups. There were no significant differences in the gene expression patterns between male and female CF specimens. There were 18 genes with significant increases and 6 genes with decreases in CF relative to non-CF samples. Although the function of many of the differentially expressed genes is unknown, one transcript that was elevated in CF, the KCl cotransporter (KCC4), is a candidate for further study. Overall, the results indicate that CFTR dysfunction has little direct impact on airway epithelial gene expression in samples grown under these conditions.