scholarly journals How Cardiac Embryology Translates into Clinical Arrhythmias

2021 ◽  
Vol 8 (6) ◽  
pp. 70
Author(s):  
Mathilde R. Rivaud ◽  
Michiel Blok ◽  
Monique R. M. Jongbloed ◽  
Bastiaan J. Boukens
Keyword(s):  
Transcription Factors ◽  
Association Studies ◽  
Pulmonary Veins ◽  
Atrioventricular Node ◽  
Right Ventricular Outflow Tract ◽  
Ventricular Outflow Tract ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Congenital Atrioventricular Block ◽  
The Right

The electrophysiological signatures of the myocardium in cardiac structures, such as the atrioventricular node, pulmonary veins or the right ventricular outflow tract, are established during development by the spatial and temporal expression of transcription factors that guide expression of specific ion channels. Genome-wide association studies have shown that small variations in genetic regions are key to the expression of these transcription factors and thereby modulate the electrical function of the heart. Moreover, mutations in these factors are found in arrhythmogenic pathologies such as congenital atrioventricular block, as well as in specific forms of atrial fibrillation and ventricular tachycardia. In this review, we discuss the developmental origin of distinct electrophysiological structures in the heart and their involvement in cardiac arrhythmias.

The need to shift pharmacogenetic research from candidate gene to genome-wide association studies

2021 ◽  
Author(s):  
Derek W Linskey ◽  
David C Linskey ◽  
Howard L McLeod ◽  
Jasmine A Luzum
Keyword(s):  
Candidate Gene ◽  
Association Studies ◽  
Genome Wide Association ◽  
Research Approach ◽  
Genome Wide Association Studies ◽  
Pharmacogenetic Research ◽  
Candidate Gene Association ◽  
Genome Wide ◽  
The Right ◽  
Gwas Catalog

The primary research approach in pharmacogenetics has been candidate gene association studies (CGAS), but pharmacogenomic genome-wide association studies (GWAS) are becoming more common. We are now at a critical juncture when the results of those two research approaches, CGAS and GWAS, can be compared in pharmacogenetics. We analyzed publicly available databases of pharmacogenetic CGAS and GWAS (i.e., the Pharmacogenomics Knowledgebase [PharmGKB®] and the NHGRI-EBI GWAS catalog) and the vast majority of variants (98%) and genes (94%) discovered in pharmacogenomic GWAS were novel (i.e., not previously studied CGAS). Therefore, pharmacogenetic researchers are not selecting the right candidate genes in the vast majority of CGAS, highlighting a need to shift pharmacogenetic research efforts from CGAS to GWAS.

scholarly journals Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data Across 27 Tissue Types

2018 ◽  
Author(s):  
Cory C. Funk ◽  
Alex M. Casella ◽  
Segun Jung ◽  
Matthew A. Richards ◽  
Alex Rodriguez ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Human Genome ◽  
Binding Sites ◽  
Regulatory Networks ◽  
Specific Binding ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Sequence Motifs ◽  
Link Type ◽  
Genome Wide

AbstractThere is intense interest in mapping the tissue-specific binding sites of transcription factors in the human genome to reconstruct gene regulatory networks and predict functions for non-coding genetic variation. DNase-seq footprinting provides a means to predict genome-wide binding sites for hundreds of transcription factors (TFs) simultaneously. However, despite the public availability of DNase-seq data for hundreds of samples, there is neither a unified analytical workflow nor a publicly accessible database providing the locations of footprints across all available samples. Here, we implemented a workflow for uniform processing of footprints using two state-of-the-art footprinting algorithms: Wellington and HINT. Our workflow scans the footprints generated by these algorithms for 1,530 sequence motifs to predict binding sites for 1,515 human transcription factors. We applied our workflow to detect footprints in 192 DNase-seq experiments from ENCODE spanning 27 human tissues. This collection of footprints describes an expansive landscape of potential TF occupancy. At thresholds optimized through machine learning, we report high-quality footprints covering 9.8% of the human genome. These footprints were enriched for true positive TF binding sites as defined by ChIP-seq peaks, as well as for genetic variants associated with changes in gene expression. Integrating our footprint atlas with summary statistics from genome-wide association studies revealed that risk for neuropsychiatric traits was enriched specifically at highly-scoring footprints in human brain, while risk for immune traits was enriched specifically at highly-scoring footprints in human lymphoblasts. Our cloud-based workflow is available at github.com/globusgenomics/genomics-footprint and a database with all footprints and TF binding site predictions are publicly available at http://data.nemoarchive.org/other/grant/sament/sament/footprint_atlas.

scholarly journals Revealing New Candidate Genes for Teat Number Relevant Traits in Duroc Pigs Using Genome-Wide Association Studies

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 806
Author(s):  
Yang Li ◽  
Lei Pu ◽  
Liangyu Shi ◽  
Hongding Gao ◽  
Pengfei Zhang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Association Studies ◽  
Significant Snps ◽  
Genomic Region ◽  
Genome Wide Association ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Teat Number ◽  
The Right

The number of teats is related to the nursing ability of sows. In the present study, we conducted genome-wide association studies (GWAS) for traits related to teat number in Duroc pig population. Two mixed models, one for counted and another for binary phenotypic traits, were employed to analyze seven traits: the right (RTN), left (LTN), and total (TTN) teat numbers; maximum teat number on a side (MAX); left minus right side teat number (LR); the absolute value of LR (ALR); and the presence of symmetry between left and right teat numbers (SLR). We identified 11, 1, 4, 13, and 9 significant SNPs associated with traits RTN, LTN, MAX, TTN, and SLR, respectively. One significant SNP (MARC0038565) was found to be simultaneous associated with RTN, LTN, MAX and TTN. Two annotated genes (VRTN and SYNDIG1L) were located in genomic region around this SNP. Three significant SNPs were shown to be associated with TTN, RTN and MAX traits. Seven significant SNPs were simultaneously detected in two traits of TTN and RTN. Other two SNPs were only identified in TTN. These 13 SNPs were clustered in the genomic region between 96.10—98.09 Mb on chromosome 7. Moreover, nine significant SNPs were shown to be significantly associated with SLR. In total, four and 22 SNPs surpassed genome-wide significance and suggestive significance levels, respectively. Among candidate genes annotated, eight genes have documented association with the teat number relevant traits. Out of them, DPF3 genes on Sus scrofa chromosome (SSC) 7 and the NRP1 gene on SSC 10 were new candidate genes identified in this study. Our findings demonstrate the genetic mechanism of teat number relevant traits and provide a reference to further improve reproductive performances in practical pig breeding programs.

scholarly journals Genetic factors influencing risk to orofacial clefts: today’s challenges and tomorrow’s opportunities

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2800 ◽  
Author(s):  
Terri H. Beaty ◽  
Mary L. Marazita ◽  
Elizabeth J. Leslie
Keyword(s):  
Birth Defects ◽  
Cleft Lip ◽  
Cleft Lip And Palate ◽  
Familial Aggregation ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Orofacial Clefts ◽  
Craniofacial Malformations ◽  
Genome Wide ◽  
The Right

Orofacial clefts include cleft lip (CL), cleft palate (CP), and cleft lip and palate (CLP), which combined represent the largest group of craniofacial malformations in humans with an overall prevalence of one per 1,000 live births. Each of these birth defects shows strong familial aggregation, suggesting a major genetic component to their etiology. Genetic studies of orofacial clefts extend back centuries, but it has proven difficult to define any single etiologic mechanism because many genes appear to influence risk. Both linkage and association studies have identified several genes influencing risk, but these differ across families and across populations. Genome-wide association studies have identified almost two dozen different genes achieving genome-wide significance, and there are broad classes of ‘causal genes’ for orofacial clefts: a few genes strongly associated with risk and possibly directly responsible for Mendelian syndromes which include orofacial clefts as a key phenotypic feature of the syndrome, and multiple genes with modest individual effects on risk but capable of disrupting normal craniofacial development under the right circumstances (which may include exposure to environmental risk factors). Genomic sequencing studies are now underway which will no doubt reveal additional genes/regions where variants (sequence and structural) can play a role in controlling risk to orofacial clefts. The real challenge to medicine and public health is twofold: to identify specific genes and other etiologic factors in families with affected members and then to devise effective interventions for these different biological mechanisms controlling risk to complex and heterogeneous birth defects such as orofacial clefts.

scholarly journals Erythro-megakaryocytic transcription factors associated with hereditary anemia

Blood ◽  
2014 ◽  
Vol 123 (20) ◽  
pp. 3080-3088 ◽  
Author(s):  
John D. Crispino ◽  
Mitchell J. Weiss
Keyword(s):  
Transcription Factors ◽  
Association Studies ◽  
Fetal Hemoglobin ◽  
Genome Wide Association Studies ◽  
Mutant Proteins ◽  
Rbc Membrane ◽  
Genome Wide ◽  
Disease Mutations ◽  
Genes Encoding ◽  
Altered Proteins

Abstract Most heritable anemias are caused by mutations in genes encoding globins, red blood cell (RBC) membrane proteins, or enzymes in the glycolytic and hexose monophosphate shunt pathways. A less common class of genetic anemia is caused by mutations that alter the functions of erythroid transcription factors (TFs). Many TF mutations associated with heritable anemia cause truncations or amino acid substitutions, resulting in the production of functionally altered proteins. Characterization of these mutant proteins has provided insights into mechanisms of gene expression, hematopoietic development, and human disease. Mutations within promoter or enhancer regions that disrupt TF binding to essential erythroid genes also cause anemia and heritable variations in RBC traits, such as fetal hemoglobin content. Defining the latter may have important clinical implications for de-repressing fetal hemoglobin synthesis to treat sickle cell anemia and β thalassemia. Functionally important alterations in genes encoding TFs or their cognate cis elements are likely to occur more frequently than currently appreciated, a hypothesis that will soon be tested through ongoing genome-wide association studies and the rapidly expanding use of global genome sequencing for human diagnostics. Findings obtained through such studies of RBCs and associated diseases are likely generalizable to many human diseases and quantitative traits.

scholarly journals Epigenetic and Transcriptional Networks Underlying Atrial Fibrillation

2020 ◽  
Vol 127 (1) ◽  
pp. 34-50 ◽  
Author(s):  
Antoinette F. van Ouwerkerk ◽  
Amelia W. Hall ◽  
Zachary A. Kadow ◽  
Sonja Lazarevic ◽  
Jasmeet S. Reyat ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Transcription Factors ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association ◽  
Transcriptional Networks ◽  
Genome Wide Association Studies ◽  
Genome Wide

Genome-wide association studies have uncovered over a 100 genetic loci associated with atrial fibrillation (AF), the most common arrhythmia. Many of the top AF-associated loci harbor key cardiac transcription factors, including PITX2, TBX5, PRRX1, and ZFHX3. Moreover, the vast majority of the AF-associated variants lie within noncoding regions of the genome where causal variants affect gene expression by altering the activity of transcription factors and the epigenetic state of chromatin. In this review, we discuss a transcriptional regulatory network model for AF defined by effector genes in Genome-wide association studies loci. We describe the current state of the field regarding the identification and function of AF-relevant gene regulatory networks, including variant regulatory elements, dose-sensitive transcription factor functionality, target genes, and epigenetic states. We illustrate how altered transcriptional networks may impact cardiomyocyte function and ionic currents that impact AF risk. Last, we identify the need for improved tools to identify and functionally test transcriptional components to define the links between genetic variation, epigenetic gene regulation, and atrial function.

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