GWAS Methods Research Articles

Shared genetic architecture between COVID-19 and irritable bowel syndrome: a large-scale genome-wide cross-trait analysis

BackgroundIt has been reported that COVID-19 patients have an increased risk of developing IBS; however, the underlying genetic mechanisms of these associations remain largely unknown. The aim of this study was to investigate potential shared SNPs, genes, proteins, and biological pathways between COVID-19 and IBS by assessing pairwise genetic correlations and cross-trait genetic analysis.Materials and methodsWe assessed the genetic correlation between three COVID-19 phenotypes and IBS using linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL) methods. Two different sources of IBS data were combined using METAL, and the Multi-trait analysis of GWAS (MTAG) method was applied for multi-trait analysis to enhance statistical robustness and discover new genetic associations. Independent risk loci were examined using genome-wide complex trait analysis (GCTA)-conditional and joint analysis (COJO), multi-marker analysis of genomic annotation (MAGMA), and functional mapping and annotation (FUMA), integrating various QTL information and methods to further identify risk genes and proteins. Gene set variation analysis (GSVA) was employed to compute pleiotropic gene scores, and combined with immune infiltration algorithms, IBS patients were categorized into high and low immune infiltration groups.ResultsWe found a positive genetic correlation between COVID-19 infection, COVID-19 hospitalization, and IBS. Subsequent multi-trait analysis identified nine significantly associated genomic loci. Among these, eight genetic variants were closely related to the comorbidity of IBS and COVID-19. The study also highlighted four genes and 231 proteins associated with the susceptibility to IBS identified through various analytical strategies and a stratification approach for IBS risk populations.ConclusionsOur study reveals a shared genetic architecture between these two diseases, providing new insights into potential biological mechanisms and laying the groundwork for more effective interventions.

Genetic architecture of meat traits in Large White sows

Currently, genome-wide association analysis is a modern and reliable method for analyzing genomic information about animals, as well as determining the “genotype — phenotype” relationship. This study aims to use the GWAS method to identify significant SNPs located within or linked to genes for meat traits in Large White pigs — backfat thickness over the 6–7th and 10–12th vertebrae, and loin muscle depth. The conducted GWA analysis revealed 60 genes, of which 17 are associated with biological functionality, annotated using the DAVID program. Three genes were found to have codification in the Pig QTL database. The genes were divided into 10 groups based on gene ontology (GO). Of all the genes, the AUTS2 gene, located on chromosome 3 and predicting the number of corpora lutea in sows, is of greatest interest. The results of this scientific work will contribute to the development of a genetic evaluation system and improvement of meat qualities in pigs.

Comparison of genomic prediction accuracy using different models for egg production traits in Taiwan country chicken

In local chickens targeted for niche markets, genotyping costs are relatively high due to the small population size and diverse breeding goals. The single-step genomic best linear unbiased prediction (ssGBLUP) model, which combines pedigree and genomic information, has been introduced to increase the accuracy of genomic estimated breeding value (GEBV). Therefore, this model may be more beneficial than the genomic BLUP (GBLUP) model for genomic selection in local chickens. Additionally, the single-step genome-wide association study (ssGWAS) can be used to extend the ssGBLUP model results to animals with available phenotypic information but without genotypic data. In this study, we compared the accuracy of (G)EBVs using the pedigree-based BLUP (PBLUP), GBLUP, and ssGBLUP models. Moreover, we conducted single-SNP GWAS (SNP-GWAS), GBLUP-GWAS, and ssGWAS methods to identify genes associated with egg production traits in the NCHU-G101 chicken to understand the feasibility of using genomic selection in a small population. The average prediction accuracy of (G)EBV for egg production traits using the PBLUP, GBLUP, and ssGBLUP models is 0.536, 0.531, and 0.555, respectively. In total, 22 suggestive- and 5% Bonferroni genome-wide significant-level SNPs for total egg number (EN), average laying rate (LR), average clutch length, and total clutch number are detected using 3 GWAS methods. These SNPs are mapped onto Gallus gallus chromosomes (GGA) 4, 6, 10, 18, and 25 in NCHU-G101 chicken. Furthermore, through SNP-GWAS and ssGWAS methods, we identify 2 genes on GGA4 associated with EN and LR: ENSGALG00000023172 and PPARGC1A. In conclusion, the ssGBLUP model demonstrates superior prediction accuracy, performing on average 3.41% than the PBLUP model. The implications of our gene results may guide future selection strategies for Taiwan Country chickens. Our results highlight the applicability of the ssGBLUP model for egg production traits selection in a small population, specifically NCHU-G101 chicken in Taiwan.

Chromosome-level genome assembly and population genomics reveals crucial selection for subgynoecy development in chieh-qua.

Chieh-qua is an important cucurbit crop and very popular in South China and Southeast Asia. Despite its significance, its genetic basis and domestication history are unclear. In this study, we have successfully generated a chromosome-level reference genome assembly for the chieh-qua 'A36' using a hybrid assembly strategy that combines PacBio long reads and Illumina short reads. The assembled genome of chieh-qua is approximately 953.3Mb in size and is organized into 12 chromosomes, with contig N50 of 6.9Mb and scaffold N50 of 68.2Mb. Notably, the chieh-qua genome is comparable in size to the wax gourd genome. Through gene prediction analysis, we have identified a total of 24 593 protein-coding genes in the A36 genome. Additionally, approximately 56.6% (539.3Mb) of the chieh-qua genome consists of repetitive sequences. Comparative genome analysis revealed that chieh-qua and wax gourd are closely related, indicating a close evolutionary relationship between the two species. Population genomic analysis, employing 129 chieh-qua accessions and 146 wax gourd accessions, demonstrated that chieh-qua exhibits greater genetic diversity compared to wax gourd. We also employed the GWAS method to identify related QTLs associated with subgynoecy, an interested and important trait in chieh-qua. The MYB59 (BhiCQ0880026447) exhibited relatively high expression levels in the shoot apex of four subgynoecious varieties compared with monoecious varieties. Overall, this research provides insights into the domestication history of chieh-qua and offers valuable genomic resources for further molecular research.

Screening of Litter-Size-Associated SNPs in NOX4, PDE11A and GHR Genes of Sheep.

In previous studies, NOX4, PDE11A and GHR genes have been screened as important candidate genes for litter size in sheep by using the GWAS method; however, neither their effects on litter size nor the loci associated with litter size have been identified. In this study, three candidate loci (c.1057-4C > T in NOX4, c.1983C > T in PDE11A and c.1618C > T in GHR) were first screened based on our previous resequencing data of 10 sheep breeds. After the three loci were genotyped using Sequenom MassARRAY technology, we carried out population genetics analysis on the three loci and performed association analysis between the polymorphism of the three loci and the litter size of sheep. The results of population genetics analysis suggested that c.1057-4C > T in NOX4 and c.1983C > T in PDE11A may be subject to natural or artificial selection. The results of association analysis indicated that litter size was significantly associated with c.1057-4C > T in NOX4 and c.1983C > T in PDE11A (p < 0.05) in Small Tail Han sheep, and there was no significant interaction effect between the two loci on the litter size. In summary, c.1057-4C > T in NOX4 and c.1983 C > T in PDE11A can be considered candidate molecular markers for improving litter size in sheep.

Multi-model genome-wide association studies for appearance quality in rice.

Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and FASTmrMLM) genome-wide association studies were conducted in a subset of 3K-RGP consisting of 198 rice accessions with 553,831 SNP markers. A total of 594 SNP markers were identified using the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by the ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grains with chalkiness (PGC, %). Finally, 39 QTNs were identified using single- and multi-locus GWAS methods. Among the 39 reliable QTNs, 20 novel QTNs were identified for the above-mentioned three quality-related traits. Based on annotation and previous studies, four functional candidate genes (LOC_Os01g66110, LOC_Os01g66140, LOC_Os07g44910, and LOC_Os02g14120) were found to influence AR, HRR (%), and PGC (%), which could be utilized in rice breeding to improve grain quality traits.

Genetic study on heritability and novel SNP loci of temperament in Chinese Kunming Dog

Chinese Kunming dog (CKD) is a working breed widely used by army, customs and police across the country. To better evaluate a breeding population's potential working performance and implement selective breeding for future offspring, a temperament test with five subsets, including following to trainer (FO), reaction to stranger (RS), tease by towel (TT), chase and fetch (CF) and tug of war (TW), was annually operated by the Kunming Police Dog Base since 2019. To fully utilize this behavioral data, 92 breeding animals of CKDs were genotyped by a 50K SNP chip, and a GWAS method supporting repeated measurement was adopted to estimate heritabilities and explore genetic variants associated with the five subsets. The heritabilities estimated for the five subsets ranged from 0,03 to 0.14, which showed a possibility for genetic improvement. Meanwhile, in total seven novel SNPs were identified associated with subsets FO, TT, CF and TW. In addition to that five of the seven loci are separately located within ACOT11, PRDM16, SAMD12, CPA1 and ENSCAFG00000023173 genes. Nevertheless, genetic effects of these novel loci on dog temperament should be further validated by a larger dataset in the future.

Comparative Application of Terminal Restriction Fragment Analysis Tools to Large-Scale Genomic Assays.

The analysis of telomere length is an important component of many studies aiming to characterize the role of telomere maintenance mechanisms in cellular lifespan, disease, or in general chromosome protection and DNA replication pathways. Several powerful methods to accurately measure the telomere length from Southern blots have been developed, but their utility for large-scale genomic studies has not been previously evaluated. Here, we performed a comparative analysis of two recently developed programs, TeloTool and WALTER, for the extraction of mean telomere length values from Southern blots. Using both software packages, we measured the telomere length in two extensive experimental datasets for the model plant Arabidopsis thaliana, consisting of 537 natural accessions and 65 T-DNA (transfer DNA for insertion mutagenesis) mutant lines in the reference Columbia (Col-0) genotype background. We report that TeloTool substantially overestimates the telomere length in comparison to WALTER, especially for values over 4500 bp. Importantly, the TeloTool- and WALTER-calculated telomere length values correlate the most in the 2100-3500 bp range, suggesting that telomeres in this size interval can be estimated by both programs equally well. We further show that genome-wide association studies using datasets from both telomere length analysis tools can detect the most significant SNP candidates equally well. However, GWAS analysis with the WALTER dataset consistently detects fewer significant SNPs than analysis with the TeloTool dataset, regardless of the GWAS method used. These results imply that the telomere length data generated by WALTER may represent a more stringent approach to GWAS and SNP selection for the downstream molecular screening of candidate genes. Overall, our work reveals the unanticipated impact of the telomere length analysis method on the outcomes of large-scale genomic screens.

Marker-Trait Associations of Agronomic Traits in Barley (Hordeum vulgare L.) under Semi-Arid Conditions

Heading date, plant height, and spike-related phenotypes are key traits that affect the yield potential and adaptation of barley to Mediterranean environments. These traits are controlled by a complex network of genes as well as environmental effects. Marker-trait associations (MTAs) were performed using a set of 361 barley genotypes, evaluated phenotypically for three years under semi-arid conditions. In total, 24 MTAs were detected using the recently developed GWAS method (BLINK) at –log p ≥ 5. These included one MTA with awn length (Awl) on chromosome 2H; twelve MTAs with heading date (HD) distributed over all chromosomes except 4H; three MTAs with grains per spike (GPS) on chromosomes 1H, 2H, and 6H; six MTAs were detected for plant height (PH) on 2H (2), 3H, 4H, 6H, and 7H; and two MTAs with spike length (SL) on 3H and 7H. The results showed novel and known associations between specific SNP markers and heading date, plant height, and spike-related traits, suggesting that these markers can be used in breeding programs to improve these traits in barley. This study provides valuable information for breeders and geneticists working to develop new barley varieties that are better adapted to semi-arid climates and have improved yield and quality characteristics.

Identification of southern corn rust resistance QTNs in Chinese summer maize germplasm via multi-locus GWAS and post-GWAS analysis.

Southern corn rust (SCR) caused by Puccinia polysora Underw is a major disease leading to severe yield losses in China Summer Corn Belt. Using six multi-locus GWAS methods, we identified a set of SCR resistance QTNs from a diversity panel of 140 inbred lines collected from China Summer Corn Belt. Thirteen QTNs on chromosomes 1, 2, 4, 5, 6, and 8 were grouped into three types of allele effects and their associations with SCR phenotypes were verified by post-GWAS case-control sampling, allele/haplotype effect analysis. Relative resistance (RRR) and relative susceptibility (RRs) catering to its inbred carrier were estimated from single QTN and QTN-QTN combos and epistatitic effects were estimated for QTN-QTN combos. By transcriptomic annotation, a set of candidate genes were predicted to be involved in transcriptional regulation (S5_145, Zm00001d01613, transcription factor GTE4), phosphorylation (S8_123, Zm00001d010672, Pgk2- phosphoglycerate kinase 2), and temperature stress response (S6_164a/S6_164b, Zm00001d038806, hsp101, and S5_211, Zm00001d017978, cellulase25). The breeding implications of the above findings were discussed.

Genetic architecture of reproductive traits in Russian Landrace pigs

Relevance. Currently, the development of molecular and population genetics is a relevant task. The need to identify reliable candidate genes is associated with increase in pig population and quality improvement of both breeding and meat products. In this regard, the whole-genome analysis method solves issues of the genetic determination in quantitative and economically important traits.Methods. In this study, the GWAS method was applied to reproductive traits of Landrace sows.Results. 35 reliable candidate genes with biological functionality were identified and described, located near or within the identified significant SNP, responsible for various reproductive traits of sow organisms. Genes were classified into two clusters — 20 genes belonged to Cluster 1, which was responsible for mitochondrial and coupled electron transport, ATP synthesis, as well as binding of fatty acids and tryptophan (AFF4, IL13, IL4, IRF1, SHROOM1, IL-5, UQCRQ, MRPL13, TTR, ENPEP, NOL4, PCDH7, DSG3, RASSF6, ALB, AFP, ANKRD17, SOX9), and 15 genes belonged to Cluster 2, which was associated with response to bacterial and viral infections (YTHDC2, KIF3A, EYA1, DSG2, DSG4, PPIH, RNF125, TRAPPC8, PITX2, KIAA1462, MTPAP, JMJD6, METTL23, SRSF2, and U2AF1).

E-GWAS: an ensemble-like GWAS strategy that provides effective control over false positive rates without decreasing true positives

BackgroundGenome-wide association studies (GWAS) are an effective way to explore genotype–phenotype associations in humans, animals, and plants. Various GWAS methods have been developed based on different genetic or statistical assumptions. However, no single method is optimal for all traits and, for many traits, the putative single nucleotide polymorphisms (SNPs) that are detected by the different methods do not entirely overlap due to the diversity of the genetic architecture of complex traits. Therefore, multi-tool-based GWAS strategies that combine different methods have been increasingly employed. To take this one step further, we propose an ensemble-like GWAS strategy (E-GWAS) that statistically integrates GWAS results from different single GWAS methods.ResultsE-GWAS was compared with various single GWAS methods using simulated phenotype traits with different genetic architectures. E-GWAS performed stably across traits with different genetic architectures and effectively controlled the number of false positive genetic variants detected without decreasing the number of true positive variants. In addition, its performance could be further improved by using a bin-merged strategy and the addition of more distinct single GWAS methods. Our results show that the numbers of true and false positive SNPs detected by the E-GWAS strategy slightly increased and decreased, respectively, with increasing bin size and when the number and the diversity of individual GWAS methods that were integrated in E-GWAS increased, the latter being more effective than the bin-merged strategy. The E-GWAS strategy was also applied to a real dataset to study backfat thickness in a pig population, and 10 candidate genes related to this trait and expressed in adipose-associated tissues were identified.ConclusionsUsing both simulated and real datasets, we show that E-GWAS is a reliable and robust strategy that effectively integrates the GWAS results of different methods and reduces the number of false positive SNPs without decreasing that of true positive SNPs.

QT–GWAS: A novel method for unveiling biosynthetic loci affecting qualitative metabolic traits

AbstractAlthough the plant kingdom provides an enormous diversity of metabolites with potentially beneficial applications for humankind, a large fraction of these metabolites and their biosynthetic pathways remain unknown. Resolving metabolite structures and their biosynthetic pathways is key to gaining biological understanding and to allow metabolic engineering. In order to retrieve novel biosynthetic genes involved in specialized metabolism, we developed a novel untargeted method designated as qualitative trait GWAS (QT–GWAS) that subjects qualitative metabolic traits to a genome-wide association study, while the conventional metabolite GWAS (mGWAS) mainly considers the quantitative variation of metabolites. As a proof of the validity of QT-GWAS, 23 and 15 of the retrieved associations identified in Arabidopsis thaliana by QT-GWAS and mGWAS, respectively, were supported by previous research. Furthermore, seven gene-metabolite associations retrieved by QT–GWAS were confirmed in this study through reverse genetics combined with metabolomics and/or in vitro enzyme assays. As such, we established that CYTOCHROME P450 706A5 (CYP706A5) is involved in the biosynthesis of chroman derivatives, UDP-GLYCOSYLTRANSFERASE 76C3 (UGT76C3) is able to hexosylate guanine in vitro and in planta, and SULFOTRANSFERASE 202B1 (SULT202B1) catalyzes the sulfation of neolignans in vitro. Collectively, our study demonstrates that the untargeted QT–GWAS method can retrieve valid gene–metabolite associations at the level of enzyme-encoding genes, even new associations that cannot be found by the conventional mGWAS, providing a new approach for dissecting qualitative metabolic traits.

Comparative study of candidate sex determination regions in snakeheads (Channa argus and C. maculata) and development of novel sex markers

Belonging to the Channidae family, Channa argus and C. maculata are the main cultured snakehead species in China and have important economic value. Both species show distinct sexual dimorphism in growth, with males growing much faster than females. Therefore, the production of all males will majorly improve the efficiency of aquaculture. However, the sex-determination (SD) mechanism of snakeheads remains unclear. Herein, we used whole-genome resequencing data of C. maculata and C. argus to analyse sex-linked genomic regions in these two species. By using GWAS and Pool-seq analysis methods, their potential SD regions were refined to fewer than 200 kb, containing two protein-coding genes (rnf144a and id2) without known sex-related function. The gene content on the sex chromosomes of the two snakehead species was basically consistent, and gonadal transcriptome analysis results showed that the mRNA expression level of id2 in the testis was significantly lower than that in the ovary in both species, whereas rnf144a showed inconsistent expression trends in the two species. Moreover, we assembled the male reference genomes and identified a 4–5 kb male-specific noncoding fragment for both species, allowing us to design universal sex-specific markers for C. argus, C. maculata, and their hybrids (C. maculata ♀ × C. argus ♂). Our findings will facilitate the understanding of the molecular basis of the SD mechanism in snakeheads, and further promote their all-male breeding progress in the industry.

Genetic risk of asthma: a review of reports on the effect of single nucleotide polymorphisms detected by genome-wide association study on the development and course of asthma using the genes: ORMDL3, ADAM33, DENND1B as examples

Asthma, an inflammatory disease of the lower and upper airways, is one of the most common diseases in society. Depending on the source and the population studied, the percentage of asthma patients ranges from 5% to as high as 15%. The development of asthma is believed to be caused by an overlap between the body's personal propensity to develop the disease and environmental factors. For years, scientists have been studying the genetic basis of asthma. For several years they have had a new weapon in their arsenal - the GWAS method. The use of this method has enabled researchers to discover the relationship between gene variants found in patients and an increased risk of developing asthma.

Multi-locus genome-wide association study of chickpea reference set identifies genetic determinants of Pratylenchus thornei resistance.

Pratylenchus thornei is an economically important species of root-lesion nematode adversely affecting chickpea (Cicer arietinum) yields globally. Integration of resistant crops in farming systems is recognised as the most effective and sustainable management strategy for plant-parasitic nematodes. However, breeding for P. thornei resistance in chickpea is limited by the lack of genetic diversity. We deployed a genome-wide association approach to identify genomic regions and candidate genes associated with P. thornei resistance in 285 genetically diverse chickpea accessions. Chickpea accessions were phenotyped for P. thornei resistance in replicated glasshouse experiments performed for two years (2018 and 2020). Whole genome sequencing data comprising 492,849 SNPs were used to implement six multi-locus GWAS models. Fourteen chickpea genotypes were found to be resistant to P. thornei. Of the six multi-locus GWAS methods deployed, FASTmrMLM was found to be the best performing model. In all, 24 significant quantitative trait nucleotides (QTNs) were identified, of which 13 QTNs were associated with lower nematode population density and 11 QTNs with higher nematode population density. These QTNs were distributed across all of the chickpea chromosomes, except chromosome 8. We identified, receptor-linked kinases (RLKs) on chromosomes 1, 4 and 6, GDSL-like Lipase/Acylhydrolase on chromosome 3, Aspartic proteinase-like and Thaumatin-like protein on chromosome 4, AT-hook DNA-binding and HSPRO2 on chromosome 6 as candidate genes for P. thornei resistance in the chickpea reference set. New sources of P. thornei resistant genotypes were identified that can be harnessed into breeding programs and putative candidate P. thornei resistant genes were identified that can be explored further to develop molecular markers and accelerate the incorporation of improved P. thornei resistance into elite chickpea cultivars.

Meta-Analysis and Multivariate GWAS Analyses in 80,950 Individuals of African Ancestry Identify Novel Variants Associated with Blood Pressure Traits.

High blood pressure (HBP) has been implicated as a major risk factor for cardiovascular diseases in several populations, including individuals of African ancestry. Despite the elevated burden of HBP-induced cardiovascular diseases in Africa and other populations of African descent, limited genetic studies have been carried out to explore the genetic mechanism driving this phenomenon. We performed genome-wide association univariate and multivariate analyses of both systolic (SBP) and diastolic blood pressure (DBP) traits in 80,950 individuals of African ancestry. We used summary statistics data from six independent cohorts, including the African Partnership for Chronic Disease Research (APCDR), the UK Biobank, and the Million Veteran Program (MVP). FUMA was used to annotate, prioritize, visualize, and interpret our findings to gain a better understanding of the molecular mechanism(s) underlying the genetics of BP traits. Finally, we undertook a Bayesian fine-mapping analysis to identify potential causal variants. Our meta-analysis identified 10 independent variants associated with SBP and 9 with DBP traits. Whilst our multivariate GWAS method identified 21 independent signals, 18 of these SNPs have been previously identified. SBP was linked to gene sets involved in biological processes such as synapse assembly and cell-cell adhesion via plasma membrane adhesion. Of the 19 independent SNPs identified in the BP meta-analysis, only 11 variants had posterior probability (PP) of > 50%, including one novel variant: rs562545 (MOBP, PP = 77%). To facilitate further research and fine-mapping of high-risk loci/variants in highly susceptible groups for cardiovascular disease and other related traits, large-scale genomic datasets are needed. Our findings highlight the importance of including ancestrally diverse populations in large GWASs and the need for diversity in genetic research.

Genome-wide association study reveals the candidate genes for reproduction traits in Yunong black pigs.

Enhancing pig reproductive efficiency has the potential to have a significant positive economic impact on the pig business. We collected four reproduction records of 734 Yunong black pigs in this study, including the total number of piglets born (TNB), the number born alive (NBA), the average birth interval of piglets (ABI) and the average birth weight (ABW). A total of 453 Yunong black pigs were genotyped with Porcine 50K SNP BeadChip. Twenty-five SNPs and 35 genomic areas were found to have a substantial impact on the reproductive performance of Yunong black pigs by single-locus GWAS and single-step GWAS (ssGWAS). For the ssGWAS, we found that the two genomic regions (12.67-13.85 and 14.26-15.01Mb) on Sus scrofa chromosome X were associated with TNB, NBA and ABI. It is worth noting that CNC10110530 and CNC100141254 significantly affected the TNB by both GWAS methods. Finally, we further determined the gene functions by enrichment analysis and a literature search, and identified 28 of them as candidate genes affecting the reproductive performance of Yunong black pigs, including RET, EIF1AX, NELL2, CTPS2, S100G, RBBP7 and PDHA1. This study further promotes understanding of the genetic mechanism of porcine reproductive performance, and also provides more molecular markers for pig breeding.

Current Trends and Approaches to the Search for Genetic Determinants of Aging and Longevity.

The online version contains supplementary material available at 10.1134/S1022795422120067.

Abstract 11587: Intriguing Genetic Overlap Between SCAD and TAD

Importance: Thoracic aortic dissections (TAD) are a well-known vascular cause of sudden death. Spontaneous coronary artery dissections (SCAD) are emerging as an important cause of early-onset myocardial infarction and sudden death. Genetic variants in multiple connective tissue genes have been recognized to underlie TAD; other genetic variants have similarly been recognized to underlie SCAD. Little data is available regarding any genetic commonality between TAD and SCAD. Objective: To determine any genetic overlap between genes coding for TAD and SCAD. Methods: Extensive review of 17 various retrospective and prospective clinical studies published between 2016 and 2022 exploring genetic studies of TAD and SCAD was performed using PubMed and Orbis. Articles highlighting the significant plausible triggers for TAD or SCAD were analyzed. Separate lists of causative genes were constructed for TAD and SCAD—and then commonalities sought. A Venn diagram was constructed to display the genetic overlap and common physiological pathways involved. Results: We identified a definite, meaningful overlap of fourteen independent genes based on GWAS or other genetic methods. Associated genetic pathways involved various biological processes including: Elastin degradation, smooth muscle cell function and the TGF-pathway. Overlapping genes included the following: COL3A1, TGFB2, SMAD3, MYLK, TGFBR2, TGFBR1, LOX, FBN1, NOTCH1, ELN, COL5A1, COL5A2, COL1A2, MYH11. Corresponding molecular pathways were investigated and correlated for both diseases. Conclusions and relevance: We are not aware of other studies searching for genetic commonalities between TAD and SCAD. We have successfully identified overlapping genes—and their corresponding molecular pathways—for TAD and SCAD. We hope these insights will lead to further clinical and scientific understanding of each disease via study of their fundamental commonalities.