Genotype and phenotype correlations in diabetic patients in Uruguay

ABSTRACT. To differentiate among different types of diabetes is becom-ing an increasingly challenging task. We investigated whether the patient’s genetic profile is useful to identify the particular type of diabetes, to deter-mine the corresponding hyperglycemia pathogenesis and treat accordingly. Three hundred and thirty-eight diabetic patients, diagnosed according to American Diabetes Association criteria, were recruited from 2004 to 2008 in diabetes health reference centers. We analyzed the major gene for type 1 diabetes susceptibility (HLA DQ/DR). In order to improve our understand-ing of the pathogenesis of the resulting hyperglycemia and to implement a more adequate treatment for the patients, we reclassified our sample ac-1353 ©FUNPEC-RP www.funpecrp.com.brGenetics and Molecular Research 8 (4): 1352-1358 (2009) Genotype and phenotype correlations in diabetic patients cording to the presence or absence of the genetic markers. We found that a higher percentage of people than expected have immunological disease, in

DecodeME Questionnaire

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic disease characterised by a substantial reduction of activity levels, estimated to affect approximately 250,000 people in the UK. ME/CFS is associated with high levels of disability and poor quality of life. DecodeME is a genetic study that aims to identify the genes, biological pathways or cell-types directly implicated in ME/CFS and to determine whether the genetics of ME/CFS overlaps with other diseases. We aim to generate strong scientific leads that researchers can pursue with future experiments, hoping in this way that our work will bring research one step closer to the development of diagnostic tests and treatments. All DecodeME participants are more than 16 years old, live in the UK and were diagnosed by a health professional with ME/CFS. Each participant was asked to provide their consent to participate in the study and to answer the DecodeME questionnaire before being considered (or not considered) for the GWAS part of the study. External references to the project can be found in the paper titled 'DecodeME: community recruitment for a large genetics study of myalgic encephalomyelitis / chronic fatigue syndrome' (https://bmcneurol.biomedcentral.com/articles/10.1186/s12883-022-02763-6). This deposit comprises documentation, namely the data dictionary and blank questionnaire

Dataset pertaining to the publication “Loci Associated with N-Glycosylation of Human Immunoglobulin G Show Pleiotropy with Autoimmune Diseases and Haematological Cancers”

The archive IgGGlycans_GWAMA_2013.tar.gz contains seventy-seven gzipped files corresponding to genome-wide association meta-analysis (GWAMA) of seventy-seven IgG glycans traits.Dataset pertaining to the publication “Loci Associated with N-Glycosylation of Human Immunoglobulin G Show Pleiotropy with Autoimmune Diseases and Haematological Cancers”. The files are comma separated and contain genome wide association meta-analysis data for the discovery studies. Summary data are given for the meta-analyses of over 2 million directly genotyped or imputed single variant polymorphisms corresponding to the HAPMAP2 release 22 reference panel : allele2, effallele, allele for which effect (beta) is reported, allele1, alternate allele. chromosome and position are position of the SNP on NCBI36/hg18 build. Meta-analysis mean effect size (beta) is the inverse-variance weighted estimate derived from individual discovery study; sebeta is its standard error. p is meta-analysis P-value; npops is the number of populations used for meta-analysis at that locus; n is the total number of samples used in individual level GWASs. Meta-analysis estimates are corrected for inflation of test statistics using genomic control at the individual study level. The archive IgGGlycans_GWAMA_2013.tar.gz contains seventy-seven gzipped files corresponding to genome-wide association meta-analysis (GWAMA) of seventy-seven IgG glycans traits.Huffman, Jennifer; Hayward, Caroline. (2016). Dataset pertaining to the publication “Loci Associated with N-Glycosylation of Human Immunoglobulin G Show Pleiotropy with Autoimmune Diseases and Haematological Cancers”, [dataset]. University of Edinburgh. Institute of Genetics and Molecular Medicine. http://dx.doi.org/10.7488/ds/1370

Supplementary files for study on modeling DSB with random forests

Structural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. The nonrandom distributions of these variants across tumour genomes are often assumed to reflect selective processes, but, as with single nucleotide variants, SV mutation rates often reflect the underlying chromatin and other features at a locus. Inferring which SVs may be under selection in tumourigenesis therefore remains challenging, though identifying such variants may lead to new diagnostic and therapeutic targets. Many SVs are thought to emerge via errors in the repair processes following DNA double strand breaks (DSBs) and a variety of studies have experimentally measured DSB frequencies across the genome in cell lines. Using these data we derive the first quantitative genome-wide models of DSB susceptibility, based upon underlying chromatin and sequence features. These models provide high predictive accuracy and novel insights into the mutational mechanisms generating DSBs. Models trained in one cell type can be successfully applied to others, but a substantial proportion of DSBs appear to reflect cell type specific processes. We also show that regions harboring unusually high tumour SV breakpoint frequencies occur within well modeled regions of the genome but often display DSB frequencies inconsistent with DSB model predictions. Using model predictions as a proxy for susceptibility to DSBs in tumours, many SV hotspots appear to be poorly explained by selectively neutral mutational bias alone. A substantial number of hotspots show unexpectedly high SV breakpoint frequencies given their predicted susceptibility to mutation, and are therefore credible targets of positive selection in tumours. These putatively positively selected hotspots are enriched for genes previously shown to be oncogenic. In contrast, several hundred regions across the genome show unexpectedly low levels of SVs, given their relatively high susceptibility to mutation. These novel ‘coldspot’ regions appear to be subject to purifying selection in tumours and are enriched for active promoters and enhancers. We conclude that models of DSB susceptibility offer a rigorous approach to the inference of SVs putatively subject to selection in tumours.Ballinger, Tracy. (2018). Supplementary files for study on modeling DSB with random forests, 2017-2018 [dataset]. University of Edinburgh. Institute of Genetics and Molecular Medicine. http://dx.doi.org/10.7488/ds/236

Lagging strand replication shapes the mutational landscape of the genome 

The origin of mutations is central to understanding evolution and of key relevance to health. Variation occurs non-randomly across the genome, and mechanisms for this remain to be defined. Here we report that the 5' ends of Okazaki fragments have significantly increased levels of nucleotide substitution, indicating a replicative origin for such mutations. Using a novel method, emRiboSeq, we map the genome-wide contribution of polymerases, and show that despite Okazaki fragment processing, DNA synthesized by error-prone polymerase-alpha (Pol-alpha) is retained in vivo, comprising ~1.5% of the mature genome. We propose that DNA-binding proteins that rapidly re-associate post-replication act as partial barriers to Pol-delta-mediated displacement of Pol-alpha-synthesized DNA, resulting in incorporation of such Pol-alpha tracts and increased mutation rates at specific sites. We observe a mutational cost to chromatin and regulatory protein binding, resulting in mutation hotspots at regulatory elements, with signatures of this process detectable in both yeast and humans.Taylor, Martin; Kemp, Harriet; Marion de Procé, Sophie; Reijns, Martin; Ding, James; Jackson, Andrew. (2015). Lagging strand replication shapes the mutational landscape of the genome, [dataset]. University of Edinburgh. MRC Institute of Genetics and Molecular Medicine. MRC Human Genetics Unit. http://dx.doi.org/10.7488/ds/204

Modulation of Genetic Associations with Serum Urate Levels by Body-Mass-Index in Humans 

Full lists of genome-wide association results for urate level as analysed in the PLOS-ONE manuscript "Modulation of Genetic Associations with Serum Urate Levels by Body-Mass-Index in Humans”. Please read the READ_DATASHARE.txt for full description.Vitart, Veronique. (2015). Modulation of Genetic Associations with Serum Urate Levels by Body-Mass-Index in Humans, [dataset]. University of Edinburgh. http://dx.doi.org/10.7488/ds/212

Dataset pertaining to the publication "Increased Level of Linkage Disequilibrium in Rural Compared with Urban Communities"

Vitart, Veronique. (2016). Dataset pertaining to the publication "Increased Level of Linkage Disequilibrium in Rural Compared with Urban Communities", 2001-2005 [dataset]. University of Edinburgh. MRC Human Genetics Unit. Quantitative Trait Locus (QTL) Identification.. http://dx.doi.org/10.7488/ds/1456

Fossilization processes have little impact on tip-calibrated divergence time analyses

The importance of palaeontological data in divergence time estimation has increased with the introduction of Bayesian Total-Evidence Dating methods which utilise fossil taxa directly for calibration, facilitated by the joint analysis of morphological and molecular data. Fossil taxa are invariably incompletely known as a consequence of taphonomic processes, resulting in the decidedly non-random distribution of missing data. The impact of non-random missing data on the accuracy and precision of clade age estimation is unknown. In an attempt to constrain the impact of taphonomy on tip-calibrated dating analyses, we compared clade ages estimated from a very complete morphological matrix to ages estimated from the same matrix permuted to simulate the progressive loss of anatomical information resulting from taphonomic processes. We demonstrate that systematically distributed missing data negatively influence clade age estimates, but that successive stages within the taphonomic process introduce greater differences in age estimates, when compared to estimates obtained from untreated data. Despite these effects, the general influence of missing data is weak, presumably due to the compensatory effect of extensive morphological data from extant taxa. We suggest that, in the absence of models that can explicitly account for taphonomic processes, morphological datasets should be constructed to minimise the impact of taphonomy on divergence time estimation.O'Reilly, Joseph (2021), Fossilization processes have little impact on tip-calibrated divergence time analyses, Dryad, Dataset, https://doi.org/10.5061/dryad.b2rbnzsd

Code and datasets for structural analyses in Natan et al, "Assembly in the translation milieu imposes evolutionary constraints on homomeric proteins"

This contains datasets and Perl scripts needed to reproduce the figures in Natan et al "Assembly in the translation milieu imposes evolutionary constraints on homomeric proteins". Specifically, it can be used to calculate the N- vs C-terminal interface enrichment for sets of homomeric or heteromeric structures, as in Figs 1B-C, and Figs S1-S3. The archive should only be extracted on a case-sensitive file system. The scripts have been tested on Mac and Linux systems.Marsh, Joseph. (2017). Code and datasets for structural analyses in Natan et al, "Assembly in the translation milieu imposes evolutionary constraints on homomeric proteins", [dataset]. University of Edinburgh. MRC Human Genetics Unit. http://dx.doi.org/10.7488/ds/2227

Zeng et al 2021 EBiomedicine modifiable POE

## Access ## This dataset is held in the Edinburgh DataVault, directly accessible only to authorised University of Edinburgh staff. External users may request access to a copy of the data by contacting the Principal Investigator, Contact Person or Data Manager named on this page. University of Edinburgh users who wish to have direct access should consult the information about retrieving data from the DataVault at: https://www.ed.ac.uk/is/research-support/datavault .Data relating to publication Lifestyle and Genetic Factors Modify Parent-of-Origin Effects on the Human Methylome... Zeng, Y., Amador, C., Gao, C., Walker, R. M., Morris, S. W., Campbell, A., Frkatović, A., Madden, R. A., Adams, M. J., He, S., Bretherick, A. D., Hayward, C., Porteous, D. J., Wilson, J. F., Evans, K. L., McIntosh, A. M., Navarro, P., & Haley, C. S. (2021). Lifestyle and Genetic Factors Modify Parent-of-Origin Effects on the Human Methylome. EBioMedicine, 74, [103730]. https://doi.org/10.1016/j.ebiom.2021.10373