Common and Unique Susceptibility Loci in Graves and Hashimoto Diseases: Results of Whole-Genome Screening in a Data Set of 102 Multiplex Families

Abstract Background This report describes the design and methodology of the “Eyes of Africa: The Genetics of Blindness,” a collaborative study funded through the Human Heredity and Health in Africa (H3Africa) program of the National Institute of Health. Methods This is a case control study that is collecting a large well phenotyped data set among glaucoma patients and controls for a genome wide association study. (GWAS). Multiplex families segregating Mendelian forms of early-onset glaucoma will also be collected for exome sequencing. Discussion A total of 4500 cases/controls have been recruited into the study at the end of the 3rd funded year of the study. All these participants have been appropriately phenotyped and blood samples have been received from these participants. Recent GWAS of POAG in African individuals demonstrated genome-wide significant association with the APBB2 locus which is an association that is unique to individuals of African ancestry. This study will add to the existing knowledge and understanding of POAG in the African population.

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Whole genome transcriptome analysis of the stomach resected in human vertical sleeve gastrectomy: cutting more than calories

Physiological Genomics ◽

10.1152/physiolgenomics.00082.2020 ◽

2021 ◽

Author(s):

William C Dungan ◽

Michael R Garrett ◽

Bradley A. Welch ◽

William J Lawson ◽

Alexandra R Himel ◽

...

Keyword(s):

Body Weight ◽

Sleeve Gastrectomy ◽

Transcriptome Analysis ◽

Gene Signature ◽

Whole Genome ◽

Vertical Sleeve Gastrectomy ◽

Data Set ◽

Tissue Samples ◽

Highly Expressed Genes ◽

A Prospective Study

Background. Vertical sleeve gastrectomy (VSG) is a surgical weight loss procedure that resects 80% of the stomach, creating a tube linking the esophagus to the duodenum. Because of the efficacy and relative simplicity of VSG, it is preferred in the U.S with VSG currently at >61% of bariatric surgeries performed. Surprisingly, there has never been a complete molecular characterization of the human stomach fundus and corpus. Here we compare and contrast the molecular make-up of these regions. Methods. We performed a prospective study to obtain gastric tissue samples from patients undergoing VSG. Paired fundus and corpus samples were obtained Whole genome transcriptome analysis was performed by RNA sequencing, with key findings validated by qPCR. Results. Participants were primarily female (95.8%) and white (79.15%). Mean BMI, body weight, and age were 46.1 kg/m2, 121.6 kg, and 43.29 years, respectively. Overall, 432 gene transcripts were significantly different between the fundus and corpus (p<0.05). A significant correlation was found between the RNAseq data set and qPCR validation, demonstrating robust gene expression differences. Significant genes included: progastricsin, acid chitinase, gastokine 1 and 2 in both fundus and corpus. Of the very highly expressed genes in both regions, 87% were present in both the stomach's fundus and corpus, indicating substantial overlap. Conclusions. Despite significant overlap in the greater curvature gene signature, regional differences exist. Given that the mechanism of VSG is partly unresolved, the potential that the resected tissue may express genes that influence long-term body weight regulation is unknown and could influence VSG outcomes.

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Whole Genome Screening for Sick Newborns: Equity Now

Clinical OMICs ◽

10.1089/clinomi.08.06.02 ◽

2021 ◽

Vol 8 (6) ◽

pp. 3-3

Author(s):

Sharon F. Terry

Keyword(s):

Whole Genome ◽

Genome Screening

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The Whole-Genome Sequence of the Novel Yeast Species Metschnikowia persimmonesis Isolated from Medicinal Plant Diospyros kaki Thunb

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab246 ◽

2021 ◽

Author(s):

Endang Rahmat ◽

Inkyu Park ◽

Youngmin Kang

Keyword(s):

Gc Content ◽

Whole Genome Sequence ◽

Diospyros Kaki ◽

Whole Genome ◽

The Novel ◽

Data Set ◽

Draft Assembly ◽

Future Possibility ◽

Complete Set ◽

New Yeast

Abstract The new yeast Metschnikowia persimmonesis KCTC 12991BP (KIOM G15050 strain) exhibits strong antimicrobial activity against some pathogens. This activity may be related to the medicinal profile of secondary metabolites that could be found in the genome of this species. Therefore, to explore its future possibility of producing some beneficial activities, including medicinal ability, we report high quality whole-genome assembly of M. persimmonesis produced by PacBio RSII sequencer. The final draft assembly consisted of 16 scaffolds with GC content of 45.90% and comprised a fairly complete set (82.8%) of BUSCO result using Saccharomycetales lineage data set. The total length of the genome was 16.473 Mb, with a scaffold N50 of 1.982 Mb. Annotation of the M. persimmonesis genome revealed presence of 7,029 genes and 6,939 functionally annotated proteins. Based on the analysis of phylogenetic relationship and the average nucleotide identities (ANI), M. persimmonesis was proved to a novel species within the Metschnikowia genus. This finding is expected to significantly contribute to the discovery of high-value natural products from M. persimmonesis as well as for genome biology and evolution comparative analysis within Metschnikowia species.

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Whole-genome single nucleotide polymorphism-based linkage analysis in spondyloarthritis multiplex families reveals a new susceptibility locus in 13q13

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2015-207720 ◽

2015 ◽

Vol 75 (7) ◽

pp. 1380-1385 ◽

Cited By ~ 5

Author(s):

Félicie Costantino ◽

Emmanuel Chaplais ◽

Tifenn Leturcq ◽

Roula Said-Nahal ◽

Ariane Leboime ◽

...

Keyword(s):

Single Nucleotide Polymorphism ◽

Linkage Analysis ◽

Susceptibility Locus ◽

Whole Genome ◽

Nucleotide Polymorphism ◽

Single Nucleotide ◽

Multiplex Families

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Pancreatic cancer detection using EpiDetect signatures in plasma-derived cell free DNA in high-risk patients with new onset diabetes.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e16265 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e16265-e16265

Author(s):

Gulfem Guler ◽

Anna Bergamaschi ◽

David Haan ◽

Michael Kesling ◽

Yuhong Ning ◽

...

Keyword(s):

Pancreatic Cancer ◽

Early Stage ◽

Model Performance ◽

Training Data ◽

Diabetes Diagnosis ◽

Whole Genome ◽

Data Set ◽

Independent Validation ◽

Onset Diabetes ◽

New Onset

e16265 Background: Pancreatic cancer (PaCa) is the third leading cause of cancer death in the United States despite its low incidence rate, owing to a 5-year survival rate of 10%. It is often asymptomatic in early stage, resulting in the majority of diagnoses occurring when cancer has already metastasized to distant organs. Late diagnosis deprives patients of potentially curative treatments such as surgery and impacts survival rates. Diabetes can be an early symptom of PaCa. Indeed, 25% of PaCa patients had a preceding diabetes diagnosis. Among all people with new onset diabetes (NOD), 0.85% will be diagnosed with PaCa within 3 years, which represents 6-8 fold increased risk for PaCa compared to the general population. Surveillance of the NOD population for PaCa presents an opportunity to shift PaCa diagnosis to earlier stage by finding it sooner. Methods: Whole blood was obtained from a cohort of 117 PaCa patients as well as 800 non-cancer controls with and without NOD. Plasma was processed to isolate cfDNA and 5hmC and low pass whole genome libraries were generated and sequenced. The EpiDetect assay combines 5hmC and whole genome sequencing data and were generated using Bluestar Genomics’s technology platform. Results: To investigate whether PaCa can be detected in plasma, we interrogated plasma-derived cfDNA epigenomic and genomic signal from PaCa patients and non-cancer controls. We first trained stacked ensemble models on PaCa and non-cancer samples utilizing 5hmC, fragmentation and CNV-based biomarkers from cfDNA. These models performed stably with a median of 72.8% sensitivity and 90.1% specificity measured across 25 outer fold iterations using the training data set, which was composed of 50% early stage (Stages I & II) disease. The final binomial ensemble model was trained using all of the training data, yielding an area under the receiver operating characteristic curve (auROC) of 0.9, with 75% sensitivity and 89% specificity. This model was then tested on an independent validation data set from 33 PaCa patients (24 with diabetes, 15 of which was NOD) and 202 non-cancer control patients (76 with diabetes, 51 of which was NOD) and yielded a classification performance auROC of 0.9 with 67% sensitivity at 92% specificity. Lastly, model performance in the subset of patient cohort with NOD only had an auROC of 0.87 with 60% sensitivity at 88% specificity. Conclusions: Our results indicate that 5hmC profiles along with CNV and fragmentation patterns from cfDNA can be used to detect PaCa in plasma-derived cfDNA. Overall, model performance was stable and consistent between the training and independent validation datasets. A larger clinical study is under development to investigate the utility of the model described in this pilot study in identifying occult PaCa within the NOD population, with the aim of shifting diagnosis to early stage and potentially improving patient outcomes.

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Genome Screening for Graves’ Disease Susceptibility Loci in U.K. Families

The Genetics of Complex Thyroid Diseases ◽

10.1007/978-4-431-67885-4_2 ◽

2002 ◽

pp. 23-41

Author(s):

B. Vaidya ◽

H. Imrie ◽

P. Kendall-Taylor ◽

S. H. S. Pearce

Keyword(s):

Disease Susceptibility ◽

Graves Disease ◽

Susceptibility Loci ◽

Genome Screening

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A Method to Detect Differential Gene Expression in Cross-Species Hybridization Experiments at Gene and Probe Level

Biomedical Informatics Insights ◽

10.4137/bii.s3846 ◽

2010 ◽

Vol 3 ◽

pp. BII.S3846 ◽

Cited By ~ 1

Author(s):

Ying Chen ◽

Rebekah Wu ◽

James Felton ◽

David M. Rocke ◽

Anu Chakicherla

Keyword(s):

Gene Expression ◽

Gene Set Analysis ◽

Model Organisms ◽

Whole Genome ◽

Supplementary Data ◽

Genome Sequences ◽

Data Set ◽

Gene Set ◽

Level Data ◽

Species Hybridization

Motivation Whole genome microarrays are increasingly becoming the method of choice to study responses in model organisms to disease, stressors or other stimuli. However, whole genome sequences are available for only some model organisms, and there are still many species whose genome sequences are not yet available. Cross-species studies, where arrays developed for one species are used to study gene expression in a closely related species, have been used to address this gap, with some promising results. Current analytical methods have included filtration of some probes or genes that showed low hybridization activities. But consensus filtration schemes are still not available. Results A novel masking procedure is proposed based on currently available target species sequences to filter out probes and study a cross-species data set using this masking procedure and gene-set analysis. Gene-set analysis evaluates the association of some priori defined gene groups with a phenotype of interest. Two methods, Gene Set Enrichment Analysis (GSEA) and Test of Test Statistics (ToTS) were investigated. The results showed that masking procedure together with ToTS method worked well in our data set. The results from an alternative way to study cross-species hybridization experiments without masking are also presented. We hypothesize that the multi-probes structure of Affymetrix microarrays makes it possible to aggregate the effects of both well-hybridized and poorly-hybridized probes to study a group of genes. The principles of gene-set analysis were applied to the probe-level data instead of gene-level data. The results showed that ToTS can give valuable information and thus can be used as a powerful technique for analyzing cross-species hybridization experiments. Availability Software in the form of R code is available at http://anson.ucdavis.edu/~ychen/cross-species.html Supplementary Data Supplementary data are available at http://anson.ucdavis.edu/~ychen/cross-species.html

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Rapid construction of a whole-genome transposon insertion collection for Shewanella oneidensis by Knockout Sudoku

Nature Communications ◽

10.1038/ncomms13270 ◽

2016 ◽

Vol 7 (1) ◽

Cited By ~ 19

Author(s):

Michael Baym ◽

Lev Shaket ◽

Isao A. Anzai ◽

Oluwakemi Adesina ◽

Buz Barstow

Keyword(s):

Single Gene ◽

Shewanella Oneidensis ◽

Whole Genome ◽

Sequencing Data ◽

Kinetic Measurements ◽

Data Set ◽

Quinone Reduction ◽

Transposon Insertion ◽

Sequencing Library ◽

Technical Effort

Abstract Whole-genome knockout collections are invaluable for connecting gene sequence to function, yet traditionally, their construction has required an extraordinary technical effort. Here we report a method for the construction and purification of a curated whole-genome collection of single-gene transposon disruption mutants termed Knockout Sudoku. Using simple combinatorial pooling, a highly oversampled collection of mutants is condensed into a next-generation sequencing library in a single day, a 30- to 100-fold improvement over prior methods. The identities of the mutants in the collection are then solved by a probabilistic algorithm that uses internal self-consistency within the sequencing data set, followed by rapid algorithmically guided condensation to a minimal representative set of mutants, validation, and curation. Starting from a progenitor collection of 39,918 mutants, we compile a quality-controlled knockout collection of the electroactive microbe Shewanella oneidensis MR-1 containing representatives for 3,667 genes that is functionally validated by high-throughput kinetic measurements of quinone reduction.

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