Statistical methods for predicting genetic regulation

Transcriptional regulation of gene expression is essential for cellular differentiation and function, and defects in the process are associated with cancer. Transcription is regulated by the cis-acting regulatory regions and trans-acting regulatory elements. Transcription factors bind on enhancers and repressors and form complexes by interacting with each other to control the expression of the genes. Understanding the regulation of genes would help us to understand the biological system and can be helpful in identifying therapeutic targets for diseases such as cancer. The ENCODE project has mapped binding sites of many TFs in some important cell types and this project also has mapped DNase I hypersensitivity sites across the cell types. Predicting transcription factors mutual interactions would help us in finding the potential transcription regulatory networks. Here, we have developed two methods for prediction of transcription factors mutual interactions from ENCODE ChIP-seq data, and both methods generated similar results which tell us about the accuracy of the methods. It is known that functional regions of genome are conserved and here we identified that shared/overlapping transcription factor binding sites in multiple cell types and in transcription factors pairs are more conserved than their respective non-shared/non-overlapping binding sites. It has been also studied that co-binding sites influence the expression level of genes. Most of the genes mapped to the transcription factor co-binding sites have significantly higher level of expression than those genes which were mapped to the single transcription factor bound sites. The ENCODE data suggests a very large number of potential regulatory sites across the complete genome in many cell types and methods are needed to identify those that are most relevant and to connect them to the genes that they control. A penalized regression method, LASSO was used to build correlative models, and choose two regulatory regions that are predictive of gene expression, and link them to their respective gene. Here, we show that our identified regulatory regions accumulate significant number of somatic mutations that occur in cancer cells, suggesting that their effects may drive cancer initiation and development. Harboring of somatic mutations in these identified regulatory regions is an indication of positive selection, which has been also observed in cancer related genes

Oral Hygiene and Periodontal Health Status of Acute Coronary Syndrome Patients reported in PIMS Islamabad

Objective: To evaluate oral hygiene and periodontal health status of Acute Coronary Syndrome patients by using standardized oral hygiene and periodontal indices. Methodology: A cross sectional study conducted at the Cardiac center and OMFS Department of PIMS hospital Islamabad. The convenience sampling technique was used in which the sample size was calculated to be 300. Either gender, age in-between 40-75 years was included. Smokers, known diabetic, patients having any cardiac procedure <6 months, or Patients reporting periodontal treatment within 3 months were excluded. The data was analyzed by using SPSS software version 23.0. The frequencies and percentages were calculated for categorical variables and mean and standard deviation for continuous variables. Results: In this study 51% were male and 49% were female. The mean age was 54.55+9.605. It was found that 56% of included participants were living in urban areas and round about 40% belongs to the middle class socioeconomically. On the basis of oral hygiene 74% of participants had poor status. Periodontal health status was also poor as the 38.0% have gingivitis and pocket formation. Conclusion: In our study majority of acute coronary syndrome patients reported poor oral hygiene and periodontal health status although it is not clear how oral hygiene and poor periodontal health effects cardiovascular changes. To find out the association of cardiovascular disease and periodontal disease and further details of pathogenesis there is much need for clinical evidence based studies.

Drinking water quality in Rohri City, Sindh, Pakistan

Groundwater and surface water samples from Rohri city were analyzed for the presence of total coliform (TC), E. coli (Ec) and heterotrophic plate count (HPC). The samples were collected before and after storage. The bacteriological analysis was carried out by membrane filtration and spread plate count (SPC) technique. The pre-storage ground water samples were found to be contaminated with TC (25%), Ec (12.5%) and HPC (45%). All post-storage groundwater samples were found to be contaminated with TC (100%), Ec (41.6%) and with HPC (100%); the number of TC, Ec and HPC in post-storage groundwater samples was very high. The difference in number of colony forming units (cfu/100ml) between pre and post-storage groundwater samples was significant (p= 0.0001). The pre-storage surface water samples from main storage reservoirs and post-storage surface water samples from households were also found to be contaminated with TC (100%), Ec (100%) and HPC (100%). A significant (p= 0.002) difference in the number of cfu/ 100ml of ground water and in surface water samples was recorded. The quality of surface water was very poor as compared to groundwater in terms of microbial content and further declined after storage indicating lack of hygiene in the study  populationKey words: Groundwater, households, gastroenteritis and waterborne

Identification of gene specific cis-regulatory elements during differentiation of mouse embryonic stem cells: An integrative approach using high-throughput datasets.

Gene expression governs cell fate, and is regulated via a complex interplay of transcription factors and molecules that change chromatin structure. Advances in sequencing-based assays have enabled investigation of these processes genome-wide, leading to large datasets that combine information on the dynamics of gene expression, transcription factor binding and chromatin structure as cells differentiate. While numerous studies focus on the effects of these features on broader gene regulation, less work has been done on the mechanisms of gene-specific transcriptional control. In this study, we have focussed on the latter by integrating gene expression data for the in vitro differentiation of murine ES cells to macrophages and cardiomyocytes, with dynamic data on chromatin structure, epigenetics and transcription factor binding. Combining a novel strategy to identify communities of related control elements with a penalized regression approach, we developed individual models to identify the potential control elements predictive of the expression of each gene. Our models were compared to an existing method and evaluated using the existing literature and new experimental data from embryonic stem cell differentiation reporter assays. Our method is able to identify transcriptional control elements in a gene specific manner that reflect known regulatory relationships and to generate useful hypotheses for further testing.Wellcome Trust, BBSRC, CRU

Cancer somatic mutations cluster in a subset of regulatory sites predicted from the ENCODE data

Background: Transcriptional regulation of gene expression is essential for cellular differentiation and function, and defects in the process are associated with cancer. The ENCODE project has mapped potential regulatory sites across the complete genome in many cell types, and these regions have been shown to harbour many of the somatic mutations that occur in cancer cells, suggesting that their effects may drive cancer initiation and development. The ENCODE data suggests a very large number of regulatory sites, and methods are needed to identify those that are most relevant and to connect them to the genes that they control. Methods: Predictive models of gene expression were developed by integrating the ENCODE data for regulation, including transcription factor binding and DNase1 hypersensitivity, with RNA-seq data for gene expression. A penalized regression method was used to identify the most predictive potential regulatory sites for each transcript. Known cancer somatic mutations from the COSMIC database were mapped to potential regulatory sites, and we examined differences in the mapping frequencies associated with sites chosen in regulatory models and other (rejected) sites. The effects of potential confounders, for example replication timing, were considered. Results: Cancer somatic mutations preferentially occupy those regulatory regions chosen in our models as most predictive of gene expression. Conclusion: Our methods have identified a significantly reduced set of regulatory sites that are enriched in cancer somatic mutations and are more predictive of gene expression. This has significance for the mechanistic interpretation of cancer mutations, and the understanding of genetic regulation

Systematic identification of regulatory elements in Leukemia.

Abstract Background: Leukemia is a type of cancer that originates from the bone marrow's blood-forming stem cells. Cancer cells don't follow the usual cellular differentiation and function pathway, so they supersede the healthy cells. Depending on the population and maturity level of abnormal cells, leukemia can be classified as Acute or Chronic. Methodology: We mapped defined leukemia mutations from the COSMIC- The Catalogue of Somatic Mutations to perspective regulatory elements. GeneCards - Human Genes Database and Factorbook were utilized in this work to extract data to analyze gene-centric data related to AML and CML. The chromosomal location, Ensembl version, GRCh37 coordinates, and detailed examination of exons, introns, promoter binding regions, and enhancers were used to investigate co-expressed and differentially expressed genes. Downloaded from Factorbook, the expression levels of healthy and sick genes were compared to known transcription factor binding patterns. Results: When translational control genes become mutated, they begin performing their function excessively, leading to uncontrolled cell proliferation and an accumulation of immature cells in the blood that are unable to perform any function on the one hand and interfering with healthy cells' ability to function optimally due to overpopulation and growth on the other. There is a group of genes whose expression level declines as they are affected by the gene, suggesting that these genes should function as insulators or silencers under normal circumstances. The data for Myc and Max genes were extracted from the Human Genome database and sorted using different techniques to find the common regulatory regions (CRRs). These CRRs were then divided into distinct categories based on the degree to which they co-expressed or their level of expression. Conclusion: Regulatory elements have been identified depending on the values of their expression level and how they are changing concerning the control group. This work will help in understanding the guidelines of blood malignancy at the cellular level by recognizing administrative destinations and are, in this manner, possible focuses for the treatment plans and precession accuracy medication

Evaluation of Vibrio cholerae O1 El Tor variants circulating in Sindh Pakistan

Objective: To investigate the existence of genetically diverse vibrio cholerae variant strains in a rural Sindh district, and to find out the phylogenetic relationship of indigenous vibrio cholerae strains. Methods: The cross-sectional study was conducted from April 2014 to May 2016 in Khairpur, Pakistan, and comprised stool samples/rectal swabs collected from the main and city branches of the Khairpur Medical College Teaching Hospital, and the Pir Abdul Qadir Shah Jeelani Institute of Medical Sciences, Gambat. The samples were identified using standard microbiological, biochemical, serological techniques and polymerase chain reaction targeting the ompW gene. Whole genome sequencing and bioinformatics tool MUMmer 3.2.3 was used to compare indigenous and contemporary vibrio cholerae strains circulating in the province of Sindh. Neighbour-joining tree method was used to construct the phylogenic tree. Results: Of the 360 samples, 76(21.11%) were found positive for vibrio cholera strains. The species-specific ompW gene was amplified at the correct size of 588bp. The isolates belonged to serogroup Inaba, O1, biotype El Tor.  Unique sequences with same genomic coordinates showed that test strains were not similar to the reference sequence. Conserved genome sequences showed that 12 Out of 16 (75%) of the test strains were similar to each Other except the 3 strains isolated from Khairpur and 1 from Karachi. Multiple sequence alignment of the regions translated into protein showed that 13 out of 16 (81.25%) test strains were similar except 2 strains from Khairpur and 1 From Karachi. The phylogenetic tree showed that all isolated strains descended from the same ancestor along with the reference strain. Conclusions: Vibrio cholerae O1 El Tor variant existed in Khairpur. Key Words: Cholera, Vibrio cholerae, Variant, Khairpur, Phylogeny, MUMmer

Attitudes towards vaccines and intention to vaccinate against COVID-19: a cross-sectional analysis - implications for public health communications in Australia

Objective To examine SARS-CoV-2 vaccine confidence, attitudes and intentions in Australian adults as part of the iCARE Study. Design and setting Cross-sectional online survey conducted when free COVID-19 vaccinations first became available in Australia in February 2021. Participants Total of 1166 Australians from general population aged 18-90 years (mean 52, SD of 19). Main outcome measures Primary outcome: responses to question € If a vaccine for COVID-19 were available today, what is the likelihood that you would get vaccinated?'. Secondary outcome: analyses of putative drivers of uptake, including vaccine confidence, socioeconomic status and sources of trust, derived from multiple survey questions. Results Seventy-eight per cent reported being likely to receive a SARS-CoV-2 vaccine. Higher SARS-CoV-2 vaccine intentions were associated with: increasing age (OR: 2.01 (95% CI 1.77 to 2.77)), being male (1.37 (95% CI 1.08 to 1.72)), residing in least disadvantaged area quintile (2.27 (95% CI 1.53 to 3.37)) and a self-perceived high risk of getting COVID-19 (1.52 (95% CI 1.08 to 2.14)). However, 72% did not believe they were at a high risk of getting COVID-19. Findings regarding vaccines in general were similar except there were no sex differences. For both the SARS-CoV-2 vaccine and vaccines in general, there were no differences in intentions to vaccinate as a function of education level, perceived income level and rurality. Knowing that the vaccine is safe and effective and that getting vaccinated will protect others, trusting the company that made it and vaccination recommended by a doctor were reported to influence a large proportion of the study cohort to uptake the SARS-CoV-2 vaccine. Seventy-eight per cent reported the intent to continue engaging in virus-protecting behaviours (mask wearing, social distancing, etc) postvaccine. Conclusions Most Australians are likely to receive a SARS-CoV-2 vaccine. Key influencing factors identified (eg, knowing vaccine is safe and effective, and doctor's recommendation to get vaccinated) can inform public health messaging to enhance vaccination rates

How well do covariates perform when adjusting for sampling bias in online COVID-19 research? Insights from multiverse analyses

: COVID-19 research has relied heavily on convenience-based samples, which-though often necessary-are susceptible to important sampling biases. We begin with a theoretical overview and introduction to the dynamics that underlie sampling bias. We then empirically examine sampling bias in online COVID-19 surveys and evaluate the degree to which common statistical adjustments for demographic covariates successfully attenuate such bias. This registered study analysed responses to identical questions from three convenience and three largely representative samples (total N = 13,731) collected online in Canada within the International COVID-19 Awareness and Responses Evaluation Study ( www.icarestudy.com ). We compared samples on 11 behavioural and psychological outcomes (e.g., adherence to COVID-19 prevention measures, vaccine intentions) across three time points and employed multiverse-style analyses to examine how 512 combinations of demographic covariates (e.g., sex, age, education, income, ethnicity) impacted sampling discrepancies on these outcomes. Significant discrepancies emerged between samples on 73% of outcomes. Participants in the convenience samples held more positive thoughts towards and engaged in more COVID-19 prevention behaviours. Covariates attenuated sampling differences in only 55% of cases and increased differences in 45%. No covariate performed reliably well. Our results suggest that online convenience samples may display more positive dispositions towards COVID-19 prevention behaviours being studied than would samples drawn using more representative means. Adjusting results for demographic covariates frequently increased rather than decreased bias, suggesting that researchers should be cautious when interpreting adjusted findings. Using multiverse-style analyses as extended sensitivity analyses is recommended.COVID-19 research has relied heavily on convenience-based samples, which-though often necessary-are susceptible to important sampling biases. We begin with a theoretical overview and introduction to the dynamics that underlie sampling bias. We then empirically examine sampling bias in online COVID-19 surveys and evaluate the degree to which common statistical adjustments for demographic covariates successfully attenuate such bias. This registered study analysed responses to identical questions from three convenience and three largely representative samples (total N = 13,731) collected online in Canada within the International COVID-19 Awareness and Responses Evaluation Study (www.icarestudy.com). We compared samples on 11 behavioural and psychological outcomes (e.g., adherence to COVID-19 prevention measures, vaccine intentions) across three time points and employed multiverse-style analyses to examine how 512 combinations of demographic covariates (e.g., sex, age, education, income, ethnicity) impacted sampling discrepancies on these outcomes. Significant discrepancies emerged between samples on 73% of outcomes. Participants in the convenience samples held more positive thoughts towards and engaged in more COVID-19 prevention behaviours. Covariates attenuated sampling differences in only 55% of cases and increased differences in 45%. No covariate performed reliably well. Our results suggest that online convenience samples may display more positive dispositions towards COVID-19 prevention behaviours being studied than would samples drawn using more representative means. Adjusting results for demographic covariates frequently increased rather than decreased bias, suggesting that researchers should be cautious when interpreting adjusted findings. Using multiverse-style analyses as extended sensitivity analyses is recommended