PSVIII-24 Inbreeding levels of the Line 4 Hereford cattle population

Abstract Inbreeding is an increasing issue in the beef cattle industry due to increased use of artificial insemination (AI) and embryo transfer (ET). Inbreeding, or increased relatedness between animals, results in inbreeding depression and its effects have been well documented; reduced performance, reproduction, and profitability. However, there is a lack of understanding the molecular mechanisms involved in inbreeding depression. Long-term linebred populations offer a unique opportunity to better understand this, more specifically the Line 4 Hereford population. The population was established from the Line 1 Hereford population in 1962 and has been maintained by the Montana State University (MSU) Northern Agricultural Research Center (NARC) near Havre, MT since its establishment. Inbreeding was estimated using a complete pedigree (FPED) and genomic information on a subset of the population. A pedigree containing 3,453 animals was constructed covering years 1962 – 2018 and was used to calculate FCPED. Animals were selected for genotyping based on genetic contributions and availability. 241 semen, tissue, and blood samples were collected and genotyped with the Illumina Bovine GGP 50K BeadChip. Genomic inbreeding (FG) and pedigree inbreeding (FGPED) were evaluated for the 241 genotyped animals. Average rate of change in inbreeding per year was also evaluated. Runs of Homozygosity (ROH) analysis was performed in Golden Helix SVS v8.8.3. ROH were defined as a minimum run length of 500 kb with a minimum of 20 SNP. Inbreeding ranges were 0 – 34%, 0 – 98%, and 0 – 27% and the average inbreeding was 10.0%, 11.4%, and 15.3% for FPED, FG, and FGPED, respectively. The average rate of change in inbreeding per year was 0.3% over 57 years. Initial analysis found 30 regions identified by ROH, indicating that we can use ROH analysis and potentially Genome-Wide Association Studies (GWAS) to identify regions of the genome being impacted by inbreeding depression.

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44 Inbreeding levels of the Line 1 and Line 4 Hereford cattle populations

Journal of Animal Science ◽

10.1093/jas/skaa278.034 ◽

2020 ◽

Vol 98 (Supplement_4) ◽

pp. 18-18

Author(s):

Jordan K Hieber ◽

Julia M Dafoe ◽

Cory T Parsons ◽

Don C Anderson ◽

Darrin L Boss ◽

...

Keyword(s):

Inbreeding Depression ◽

Molecular Mechanisms ◽

Average Rate ◽

Rate Of Change ◽

Minimum Length ◽

Association Analyses ◽

Hereford Cattle ◽

Negative Impacts ◽

Significant Line ◽

Genomic Inbreeding

Abstract The Line 1 and Line 4 Hereford populations have been linebred for decades. Since these populations share origins but have been managed differently, they offer a unique opportunity to understand molecular mechanisms contributing to inbreeding depression. The study attempted to identify areas of the genome impacting inbreeding depression. Inbreeding was estimated using a complete pedigree (FPED), genomic inbreeding (FG), and genomic pedigree inbreeding (FGPED). Average rate of change in inbreeding per year was evaluated. Runs of homozygosity (ROH) analyses were performed in Golden Helix SVS software, and ROH were defined as a minimum length of 2,500 kb, 250 single nucleotide polymorphism (SNP) appearing in 20 samples. Expected phenotypes for five traits were calculated by adjusting each animal’s individual phenotype with published negative impacts of inbreeding depression. Regression association analyses were performed (Golden Helix) on phenotype and genotype data. Markers above 5 x 10–4 genome-wide significance were considered strongly significant. Line 1 FPED, FG, and FGPED average inbreeding was 42.1% (range 0–71%), 14.4% (range 0–46%), and 31.0% (range 0–63%), respectively. Line 4 FPED, FG, and FGPED average inbreeding was 12.6% (range 0–36%), 12.3% (range 0–49%), and 17.7% (range 0–29%), respectively. Average rate of change in inbreeding per year for Line 1 was -0.03% over 83 yr and 0.03% over 55 yr for Line 4. Fifty ROH regions, 93 strongly significant SNP, three strongly significant SNP within ROH, and some significant SNP within 11 previously identified genes were identified for Line 1. Forty-five ROH regions, 35 strongly significant SNP, three strongly significant SNP within ROH, and some significant SNP within 12 previously identified genes were identified for Line 4. Variation in identified regions of the genome of both lines indicate management is impacting results of inbreeding and the expressed inbreeding depression.

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Molecular Mechanisms of ZC3H12C/Reg-3 Biological Activity and Its Involvement in Psoriasis Pathology

International Journal of Molecular Sciences ◽

10.3390/ijms22147311 ◽

2021 ◽

Vol 22 (14) ◽

pp. 7311

Author(s):

Mateusz Wawro ◽

Jakub Kochan ◽

Weronika Sowinska ◽

Aleksandra Solecka ◽

Karolina Wawro ◽

...

Keyword(s):

Family Member ◽

Cellular Localization ◽

Molecular Mechanisms ◽

Inflammatory Diseases ◽

Association Studies ◽

Psoriasis Patient ◽

Genome Wide Association Studies ◽

Mrna Levels ◽

Transcript Levels

The members of the ZC3H12/MCPIP/Regnase family of RNases have emerged as important regulators of inflammation. In contrast to Regnase-1, -2 and -4, a thorough characterization of Regnase-3 (Reg-3) has not yet been explored. Here we demonstrate that Reg-3 differs from other family members in terms of NYN/PIN domain features, cellular localization pattern and substrate specificity. Together with Reg-1, the most comprehensively characterized family member, Reg-3 shared IL-6, IER-3 and Reg-1 mRNAs, but not IL-1β mRNA, as substrates. In addition, Reg-3 was found to be the only family member which regulates transcript levels of TNF, a cytokine implicated in chronic inflammatory diseases including psoriasis. Previous meta-analysis of genome-wide association studies revealed Reg-3 to be among new psoriasis susceptibility loci. Here we demonstrate that Reg-3 transcript levels are increased in psoriasis patient skin tissue and in an experimental model of psoriasis, supporting the immunomodulatory role of Reg-3 in psoriasis, possibly through degradation of mRNA for TNF and other factors such as Reg-1. On the other hand, Reg-1 was found to destabilize Reg-3 transcripts, suggesting reciprocal regulation between Reg-3 and Reg-1 in the skin. We found that either Reg-1 or Reg-3 were expressed in human keratinocytes in vitro. However, in contrast to robustly upregulated Reg-1 mRNA levels, Reg-3 expression was not affected in the epidermis of psoriasis patients. Taken together, these data suggest that epidermal levels of Reg-3 are negatively regulated by Reg-1 in psoriasis, and that Reg-1 and Reg-3 are both involved in psoriasis pathophysiology through controlling, at least in part different transcripts.

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Polygenic Risk Score of Longevity Predicts Longer Survival Across an Age Continuum

The Journals of Gerontology Series A ◽

10.1093/gerona/glaa289 ◽

2020 ◽

Author(s):

Niccolo’ Tesi ◽

Sven J van der Lee ◽

Marc Hulsman ◽

Iris E Jansen ◽

Najada Stringa ◽

...

Keyword(s):

Older Adults ◽

Cellular Response ◽

Molecular Mechanisms ◽

Association Studies ◽

Risk Scores ◽

Human Longevity ◽

Polygenic Risk Score ◽

Genome Wide Association Studies ◽

Polygenic Risk ◽

Age Related

Abstract Studying the genome of centenarians may give insights into the molecular mechanisms underlying extreme human longevity and the escape of age-related diseases. Here, we set out to construct polygenic risk scores (PRSs) for longevity and to investigate the functions of longevity-associated variants. Using a cohort of centenarians with maintained cognitive health (N = 343), a population-matched cohort of older adults from 5 cohorts (N = 2905), and summary statistics data from genome-wide association studies on parental longevity, we constructed a PRS including 330 variants that significantly discriminated between centenarians and older adults. This PRS was also associated with longer survival in an independent sample of younger individuals (p = .02), leading up to a 4-year difference in survival based on common genetic factors only. We show that this PRS was, in part, able to compensate for the deleterious effect of the APOE-ε4 allele. Using an integrative framework, we annotated the 330 variants included in this PRS by the genes they associate with. We find that they are enriched with genes associated with cellular differentiation, developmental processes, and cellular response to stress. Together, our results indicate that an extended human life span is, in part, the result of a constellation of variants each exerting small advantageous effects on aging-related biological mechanisms that maintain overall health and decrease the risk of age-related diseases.

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The migraine–stroke connection: A genetic perspective

Cephalalgia ◽

10.1177/0333102415621055 ◽

2015 ◽

Vol 36 (7) ◽

pp. 658-668 ◽

Cited By ~ 12

Author(s):

Rainer Malik ◽

Bendik Winsvold ◽

Eva Auffenberg ◽

Martin Dichgans ◽

Tobias Freilinger

Keyword(s):

Ischemic Stroke ◽

Vascular Disease ◽

Molecular Mechanisms ◽

Association Studies ◽

Familial Hemiplegic Migraine ◽

Artery Dissection ◽

Cervical Artery Dissection ◽

Data Sets ◽

Genome Wide Association Studies ◽

Disease Manifestation

Background A complex relationship between migraine and vascular disease has long been recognized. The pathophysiological basis underlying this correlation is incompletely understood. Aim The aim of this review is to focus on the migraine–vascular disorders connection from a genetic perspective, illustrating potentially shared (molecular) mechanisms. Results We first summarize the clinical presentation and genetic basis of CADASIL and other monogenic vascular syndromes with migraine as a prominent disease manifestation. Based on data from transgenic mouse models for familial hemiplegic migraine, we then discuss cortical spreading depression as a potential mechanistic link between migraine and ischemic stroke. Finally, we review data from genome-wide association studies, with a focus on overlapping findings with cervical artery dissection, ischemic stroke in general and cardiovascular disease. Conclusion A wealth of data supports a genetic link between migraine and vascular disease. Based on growing high-throughput data-sets, new genotyping techniques and in-depth phenotyping, further insights are expected for the future.

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Enriching human interactome with functional mutations to detect high-impact network modules underlying complex diseases

10.1101/786798 ◽

2019 ◽

Author(s):

Hongzhu Cui ◽

Suhas Srinivasan ◽

Dmitry Korkin

Keyword(s):

Biological Networks ◽

Molecular Mechanisms ◽

Association Studies ◽

Genetic Diseases ◽

Detection Methods ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Human Interactome ◽

Module Detection ◽

Disease Module

AbstractProgress in high-throughput -omics technologies moves us one step closer to the datacalypse in life sciences. In spite of the already generated volumes of data, our knowledge of the molecular mechanisms underlying complex genetic diseases remains limited. Increasing evidence shows that biological networks are essential, albeit not sufficient, for the better understanding of these mechanisms. The identification of disease-specific functional modules in the human interactome can provide a more focused insight into the mechanistic nature of the disease. However, carving a disease network module from the whole interactome is a difficult task. In this paper, we propose a computational framework, DIMSUM, which enables the integration of genome-wide association studies (GWAS), functional effects of mutations, and protein-protein interaction (PPI) network to improve disease module detection. Specifically, our approach incorporates and propagates the functional impact of non-synonymous single nucleotide polymorphisms (nsSNPs) on PPIs to implicate the genes that are most likely influenced by the disruptive mutations, and to identify the module with the greatest impact. Comparison against state-of-the-art seed-based module detection methods shows that our approach could yield modules that are biologically more relevant and have stronger association with the studied disease. We expect for our method to become a part of the common toolbox for disease module analysis, facilitating discovery of new disease markers.

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Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

eLife ◽

10.7554/elife.31977 ◽

2018 ◽

Vol 7 ◽

Cited By ~ 60

Author(s):

Matthias Thurner ◽

Martijn van de Bunt ◽

Jason M Torres ◽

Anubha Mahajan ◽

Vibe Nylander ◽

...

Keyword(s):

Type 2 Diabetes ◽

Pancreatic Islet ◽

Molecular Mechanisms ◽

Association Studies ◽

Human Islets ◽

Chromatin Accessibility ◽

Chromatin State ◽

Open Chromatin ◽

Genome Wide Association Studies

Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

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A Pathway and Network Oriented Approach to Enlighten Molecular Mechanisms of Type 2 Diabetes Using Multiple Association Studies

10.1101/2020.01.14.905547 ◽

2020 ◽

Author(s):

Burcu Bakir-Gungor ◽

Miray Unlu Yazici ◽

Gokhan Goy ◽

Mustafa Temiz

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Protein Interaction ◽

Molecular Mechanisms ◽

Association Studies ◽

Genome Wide Association Studies ◽

Protein Protein Interaction ◽

Ppi Networks ◽

Oriented Approach

AbstractDiabetes Mellitus (DM) is a group of metabolic disorder that is characterized by pancreatic dysfunction in insulin producing beta cells, glucagon secreting alpha cells, and insulin resistance or insulin in-functionality related hyperglycemia. Type 2 Diabetes Mellitus (T2D), which constitutes 90% of the diabetes cases, is a complex multifactorial disease. In the last decade, genome-wide association studies (GWASs) for type 2 diabetes (T2D) successfully pinpointed the genetic variants (typically single nucleotide polymorphisms, SNPs) that associate with disease risk. However, traditional GWASs focus on the ‘the tip of the iceberg’ SNPs, and the SNPs with mild effects are discarded. In order to diminish the burden of multiple testing in GWAS, researchers attempted to evaluate the collective effects of interesting variants. In this regard, pathway-based analyses of GWAS became popular to discover novel multi-genic functional associations. Still, to reveal the unaccounted 85 to 90% of T2D variation, which lies hidden in GWAS datasets, new post-GWAS strategies need to be developed. In this respect, here we reanalyze three meta-analysis data of GWAS in T2D, using the methodology that we have developed to identify disease-associated pathways by combining nominally significant evidence of genetic association with the known biochemical pathways, protein-protein interaction (PPI) networks, and the functional information of selected SNPs. In this research effort, to enlighten the molecular mechanisms underlying T2D development and progress, we integrated different in-silico approaches that proceed in top-down manner and bottom-up manner, and hence presented a comprehensive analysis at protein subnetwork, pathway, and pathway subnetwork levels. Our network and pathway-oriented approach is based on both the significance level of an affected pathway and its topological relationship with its neighbor pathways. Using the mutual information based on the shared genes, the identified protein subnetworks and the affected pathways of each dataset were compared. While, most of the identified pathways recapitulate the pathophysiology of T2D, our results show that incorporating SNP functional properties, protein-protein interaction networks into GWAS can dissect leading molecular pathways, which cannot be picked up using traditional analyses. We hope to bridge the knowledge gap from sequence to consequence.

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Genetic basis of intracranial aneurysm formation and rupture: clinical implications in the postgenomic era

Neurosurgical FOCUS ◽

10.3171/2019.4.focus19204 ◽

2019 ◽

Vol 47 (1) ◽

pp. E10 ◽

Cited By ~ 6

Author(s):

Nardin Samuel ◽

Ivan Radovanovic

Keyword(s):

Intracranial Aneurysm ◽

Genetic Basis ◽

Molecular Mechanisms ◽

Aneurysmal Subarachnoid Hemorrhage ◽

Association Studies ◽

Genome Wide Association Studies ◽

Genetic Aberrations ◽

Aneurysm Formation ◽

Genome Wide ◽

Risk Of Rupture

OBJECTIVEDespite the prevalence and impact of intracranial aneurysms (IAs), the molecular basis of their pathogenesis remains largely unknown. Moreover, there is a dearth of clinically validated biomarkers to efficiently screen patients with IAs and prognosticate risk for rupture. The aim of this study was to survey the literature to systematically identify the spectrum of genetic aberrations that have been identified in IA formation and risk of rupture.METHODSA literature search was performed using the Medical Subject Headings (MeSH) system of databases including PubMed, EMBASE, and Google Scholar. Relevant studies that reported on genetic analyses of IAs, rupture risk, and long-term outcomes were included in the qualitative analysis.RESULTSA total of 114 studies were reviewed and 65 were included in the qualitative synthesis. There are several well-established mendelian syndromes that confer risk to IAs, with variable frequency. Linkage analyses, genome-wide association studies, candidate gene studies, and exome sequencing identify several recurrent polymorphic variants at candidate loci, and genes associated with the risk of aneurysm formation and rupture, including ANRIL (CDKN2B-AS1, 9p21), ARGHEF17 (11q13), ELN (7q11), SERPINA3 (14q32), and SOX17 (8q11). In addition, polymorphisms in eNOS/NOS3 (7q36) may serve as predictive markers for outcomes following intracranial aneurysm rupture. Genetic aberrations identified to date converge on posited molecular mechanisms involved in vascular remodeling, with strong implications for an associated immune-mediated inflammatory response.CONCLUSIONSComprehensive studies of IA formation and rupture have identified candidate risk variants and loci; however, further genome-wide analyses are needed to identify high-confidence genetic aberrations. The literature supports a role for several risk loci in aneurysm formation and rupture with putative candidate genes. A thorough understanding of the genetic basis governing risk of IA development and the resultant aneurysmal subarachnoid hemorrhage may aid in screening, clinical management, and risk stratification of these patients, and it may also enable identification of putative mechanisms for future drug development.

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Diagnosis of Human Axillary Osmidrosis by Genotyping of the HumanABCC11Gene: Clinical Practice and Basic Scientific Evidence

BioMed Research International ◽

10.1155/2016/7670483 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 12

Author(s):

Yu Toyoda ◽

Tsuneaki Gomi ◽

Hiroshi Nakagawa ◽

Makoto Nagakura ◽

Toshihisa Ishikawa

Keyword(s):

Genetic Polymorphisms ◽

Molecular Mechanisms ◽

New Technologies ◽

Disease Risk ◽

Association Studies ◽

Diagnostic Strategy ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Drug Induced ◽

Axillary Osmidrosis

The importance of personalized medicine and healthcare is becoming increasingly recognized. Genetic polymorphisms associated with potential risks of various human genetic diseases as well as drug-induced adverse reactions have recently been well studied, and their underlying molecular mechanisms are being uncovered by functional genomics as well as genome-wide association studies. Knowledge of certain genetic polymorphisms is clinically important for our understanding of interindividual differences in drug response and/or disease risk. As such evidence accumulates, new clinical applications and practices are needed. In this context, the development of new technologies for simple, fast, accurate, and cost-effective genotyping is imperative. Here, we describe a simple isothermal genotyping method capable of detecting single nucleotide polymorphisms (SNPs) in the human ATP-binding cassette (ABC) transporterABCC11gene and its application to the clinical diagnosis of axillary osmidrosis. We have recently reported that axillary osmidrosis is linked with one SNP 538G>A in theABCC11gene. Our molecular biological and biochemical studies have revealed that this SNP greatly affects the protein expression level and the function of ABCC11. In this review, we highlight the clinical relevance and importance of this diagnostic strategy in axillary osmidrosis therapy.

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Challenges and progress in interpretation of non-coding genetic variants associated with human disease

Experimental Biology and Medicine ◽

10.1177/1535370217713750 ◽

2017 ◽

Vol 242 (13) ◽

pp. 1325-1334 ◽

Cited By ~ 19

Author(s):

Yizhou Zhu ◽

Cagdas Tazearslan ◽

Yousin Suh

Keyword(s):

Molecular Mechanisms ◽

Target Genes ◽

Disease Risk ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genetic Associations ◽

Functional Interpretation ◽

Genome Wide ◽

Coding Variants

Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants.

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