scholarly journals Genetic Basis of Mastitis Resistance in Dairy Cattle – A Review / Podstawy Genetyczne Odporności Krów Mlecznych Na Zapalenie Wymienia – Artykuł Przeglądowy

2013 ◽  
Vol 13 (4) ◽  
pp. 663-673 ◽  
Author(s):  
Grażyna Sender ◽  
Agnieszka Korwin-Kossakowska ◽  
Adrianna Pawlik ◽  
Karima Galal Abdel Hameed ◽  
Jolanta Oprządek
Keyword(s):  
Dairy Cattle ◽  
Association Studies ◽  
Genetic Resistance ◽  
Clinical Mastitis ◽  
Future Research ◽  
Complex Nature ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies ◽  
Polygenic Control ◽  
Breeding Programmes

Abstract Mastitis is one of the most important mammary gland diseases impacting lactating animals. Resistance to this disease could be improved by breeding. There are several selection methods for mastitis resistance. To improve the natural genetic resistance of cows in succeeding generations, current breeding programmes use somatic cell count and clinical mastitis cases as resistance traits. However, these methods of selection have met with limited success. This is partly due to the complex nature of the disease. The limited progress in improving udder health by conventional selection procedures requires applying information on molecular markers of mastitis susceptibility in marker-assisted selection schemes. Mastitis is under polygenic control, so there are many genes that control this trait in many loci. This review briefly describes genome-wide association studies which have been carried out to identify quantitative trait loci associated with mastitis resistance in dairy cattle worldwide. It also characterizes the candidate gene approach focus on identifying genes that are strong candidates for the mastitis resistance trait. In the conclusion of the paper we focus our attention on future research which should be conducted in the field of the resistance to mastitis.

scholarly journals Genetic Markers of Differential Vulnerability to Sleep Loss in Adults

Genes ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1317
Author(s):  
Courtney E. Casale ◽  
Namni Goel
Keyword(s):  
Sleep Deprivation ◽  
Genetic Markers ◽  
Clock Genes ◽  
Association Studies ◽  
Sleep Loss ◽  
Future Research ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies ◽  
Recovery Sleep ◽  
Differential Vulnerability

In this review, we discuss reports of genotype-dependent interindividual differences in phenotypic neurobehavioral responses to total sleep deprivation or sleep restriction. We highlight the importance of using the candidate gene approach to further elucidate differential resilience and vulnerability to sleep deprivation in humans, although we acknowledge that other omics techniques and genome-wide association studies can also offer insights into biomarkers of such vulnerability. Specifically, we discuss polymorphisms in adenosinergic genes (ADA and ADORA2A), core circadian clock genes (BHLHE41/DEC2 and PER3), genes related to cognitive development and functioning (BDNF and COMT), dopaminergic genes (DRD2 and DAT), and immune and clearance genes (AQP4, DQB1*0602, and TNFα) as potential genetic indicators of differential vulnerability to deficits induced by sleep loss. Additionally, we review the efficacy of several countermeasures for the neurobehavioral impairments induced by sleep loss, including banking sleep, recovery sleep, caffeine, and naps. The discovery of reliable, novel genetic markers of differential vulnerability to sleep loss has critical implications for future research involving predictors, countermeasures, and treatments in the field of sleep and circadian science.

scholarly journals Genetic basis of depressive disorders

2019 ◽  
Vol 23 (4) ◽  
pp. 465-472
Author(s):  
Yu. D. Davydova ◽  
R. F. Enikeeva ◽  
A. V. Kazantseva ◽  
R. N. Mustafin ◽  
A. R. Romanova ◽  
...  
Keyword(s):  
Depressive Disorders ◽  
Hormone Receptors ◽  
Methylenetetrahydrofolate Reductase ◽  
Association Studies ◽  
Common Mental Disorder ◽  
Future Research ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Whole Exome

Depression is a common mental disorder being one of the main causes of disability and mortality worldwide. Despite an intensive research during the past decades, the etiology of depressive disorders (DDs) remains incompletely understood; however, genetic factors are significantly involved in the liability to depression. The present review is focused on the studies based on a candidate gene approach, genome-wide association studies (GWAS) and whole exome sequencing (WES), which previously demonstrated associations between gene polymorphisms and DDs. According to the first approach, DD development is affected by serotonergic (TPH1, TPH2, HTR1A, HTR2A, and SLC6A4), dopaminergic (DRD4, SLC6A3) and noradrenergic (SLC6A2) system genes, and genes of enzymatic degradation (MAOA, COMT). In addition, there is evidence of the involvement of HPA-axis genes (OXTR, AVPR1A, and AVPR1B), sex hormone receptors genes (ESR1, ESR2, and AR), neurotrophin (BDNF) and methylenetetrahydrofolate reductase (MTHFR) genes, neuronal apoptosis (CASP3, BCL-XL, BAX, NPY, APP, and GRIN1) and inflammatory system (TNF, CRP, IL6, IL1B, PSMB4, PSMD9, and STAT3) genes in DD development. The results of the second approach (GWAS and WES) revealed that the PCLO, SIRT1, GNL3, GLT8D1, ITIH3, MTNR1A, BMP5, FHIT, KSR2, PCDH9, and AUTS2 genes predominantly responsible for neurogenesis and cell adhesion are involved in liability to depression. Therefore, the findings discussed suggest that genetic liability to DD is a complex process, which assumes simultaneous functioning of multiple genes including those reported previously, and requires future research in this field. 

scholarly journals Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 599
Author(s):  
Miguel A. Gutierrez-Reinoso ◽  
Pedro M. Aponte ◽  
Manuel Garcia-Herreros
Keyword(s):  
Dairy Cattle ◽  
Production Efficiency ◽  
Association Studies ◽  
Phenotypic Traits ◽  
Progeny Testing ◽  
Genome Wide Association Studies ◽  
Genetic Progress ◽  
Breeding Programs ◽  
Increased Risk ◽  
Selection Of

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

scholarly journals Host Genetics and Gut Microbiome: Perspectives for Multiple Sclerosis

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1181
Author(s):  
Alessandro Maglione ◽  
Miriam Zuccalà ◽  
Martina Tosi ◽  
Marinella Clerico ◽  
Simona Rolla
Keyword(s):  
Multiple Sclerosis ◽  
Environmental Factors ◽  
Lupus Erythematosus ◽  
Gut Microbiome ◽  
Complex Disease ◽  
Current Knowledge ◽  
Association Studies ◽  
Future Research ◽  
Genome Wide Association Studies ◽  
Host Genetics

As a complex disease, Multiple Sclerosis (MS)’s etiology is determined by both genetic and environmental factors. In the last decade, the gut microbiome has emerged as an important environmental factor, but its interaction with host genetics is still unknown. In this review, we focus on these dual aspects of MS pathogenesis: we describe the current knowledge on genetic factors related to MS, based on genome-wide association studies, and then illustrate the interactions between the immune system, gut microbiome and central nervous system in MS, summarizing the evidence available from Experimental Autoimmune Encephalomyelitis mouse models and studies in patients. Finally, as the understanding of influence of host genetics on the gut microbiome composition in MS is in its infancy, we explore this issue based on the evidence currently available from other autoimmune diseases that share with MS the interplay of genetic with environmental factors (Inflammatory Bowel Disease, Rheumatoid Arthritis and Systemic Lupus Erythematosus), and discuss avenues for future research.

scholarly journals Four Loci Are Associated with Cardiorespiratory Fitness and Endurance Performance in Young Chinese Females

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ying Zhao ◽  
Guoyuan Huang ◽  
Zuosong Chen ◽  
Xiang Fan ◽  
Tao Huang ◽  
...  
Keyword(s):  
Cardiorespiratory Fitness ◽  
Association Studies ◽  
Endurance Performance ◽  
Young Female ◽  
Future Research ◽  
Genome Wide Association Studies ◽  
Genetic Trait ◽  
Young Females ◽  
Genome Wide ◽  
Fixed Model

AbstractCardiorespiratory fitness (CRF) and endurance performance are characterized by a complex genetic trait with high heritability. Although research has identified many physiological and environmental correlates with CRF, the genetic architecture contributing to CRF remains unclear, especially in non-athlete population. A total of 762 Chinese young female participants were recruited and an endurance run test was used to determine CRF. We used a fixed model of genome-wide association studies (GWAS) for CRF. Genotyping was performed using the Affymetrix Axiom and illumina 1 M arrays. After quality control and imputation, a linear regression-based association analysis was conducted using a total of 5,149,327 variants. Four loci associated with CRF were identified to reach genome-wide significance (P < 5.0 × 10-8), which located in 15q21.3 (rs17240160, P = 1.73 × 10-9, GCOM1), 3q25.31 (rs819865, P = 8.56 × 10-9, GMPS), 21q22.3 (rs117828698, P = 9.59 × 10-9, COL18A1), and 17q24.2 (rs79806428, P = 3.85 × 10-8, PRKCA). These loci (GCOM1, GMPS, COL18A1 and PRKCA) associated with cardiorespiratory fitness and endurance performance in Chinese non-athlete young females. Our results suggest that these gene polymorphisms provide further genetic evidence for the polygenetic nature of cardiorespiratory endurance and be used as genetic biomarkers for future research.

scholarly journals Confirmed effects of candidate variants for milk production, udder health, and udder morphology in dairy cattle

2020 ◽  
Vol 52 (1) ◽  
Author(s):  
Thierry Tribout ◽  
Pascal Croiseau ◽  
Rachel Lefebvre ◽  
Anne Barbat ◽  
Mekki Boussaha ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Candidate Genes ◽  
Milk Production ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Production Traits ◽  
Milk Production Traits ◽  
Udder Health ◽  
Gwas Approach

Abstract Background Over the last years, genome-wide association studies (GWAS) based on imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci (QTL) and highlight candidate genes for important traits. However, in general this approach does not allow to validate the effects of candidate mutations or determine if they are truly causative for the trait(s) in question. To address these questions, we applied a two-step, within-breed GWAS approach on 15 traits (5 linked with milk production, 2 with udder health, and 8 with udder morphology) in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) cattle. We detected the most-promising candidate variants (CV) using imputed WGS of 2515 MON, 2203 NOR, and 6321 HOL bulls, and validated their effects in three younger populations of 23,926 MON, 9400 NOR, and 51,977 HOL cows. Results Bull sequence-based GWAS detected 84 QTL: 13, 10, and 30 for milk production traits; 3, 0, and 2 for somatic cell score (SCS); and 8, 2 and 16 for udder morphology traits, in MON, NOR, and HOL respectively. Five genomic regions with effects on milk production traits were shared among the three breeds whereas six (2 for production and 4 for udder morphology and health traits) had effects in two breeds. In 80 of these QTL, 855 CV were highlighted based on the significance of their effects and functional annotation. The subsequent GWAS on MON, NOR, and HOL cows validated 8, 9, and 23 QTL for production traits; 0, 0, and 1 for SCS; and 4, 1, and 8 for udder morphology traits, respectively. In 47 of the 54 confirmed QTL, the CV identified in bulls had more significant effects than single nucleotide polymorphisms (SNPs) from the standard 50K chip. The best CV for each validated QTL was located in a gene that was functionally related to production (36 QTL) or udder (9 QTL) traits. Conclusions Using this two-step GWAS approach, we identified and validated 54 QTL that included CV mostly located within functional candidate genes and explained up to 6.3% (udder traits) and 37% (production traits) of the genetic variance of economically important dairy traits. These CV are now included in the chip used to evaluate French dairy cattle and can be integrated into routine genomic evaluation.

Pathophysiology and genetic factors in moyamoya disease

2009 ◽  
Vol 26 (4) ◽  
pp. E4 ◽  
Author(s):  
Achal S. Achrol ◽  
Raphael Guzman ◽  
Marco Lee ◽  
Gary K. Steinberg
Keyword(s):  
Moyamoya Disease ◽  
Genetic Factors ◽  
Association Studies ◽  
Vascular Anomalies ◽  
Future Research ◽  
Incomplete Penetrance ◽  
Genome Wide Association Studies ◽  
Research Directions ◽  
Genome Wide ◽  
Future Research Directions

Moyamoya disease is an uncommon cerebrovascular condition characterized by progressive stenosis of the bilateral internal carotid arteries with compensatory formation of an abnormal network of perforating blood vessels providing collateral circulation. The etiology and pathogenesis of moyamoya disease remain unclear. Evidence from histological studies, proteomics, and endothelial progenitor cell analyses suggests new theories underlying the cause of vascular anomalies, including moyamoya disease. Familial moyamoya disease has been noted in as many as 15% of patients, indicating an autosomal dominant inheritance pattern with incomplete penetrance. Genetic analyses in familial moyamoya disease and genome-wide association studies represent promising strategies for elucidating the pathophysiology of this condition. In this review, the authors discuss recent studies that have investigated possible mechanisms underlying the etiology of moyamoya disease, including stem cell involvement and genetic factors. They also discuss future research directions that promise not only to offer new insights into the origin of moyamoya disease but to enhance our understanding of new vessel formation in the CNS as it relates to stroke, vascular anomalies, and tumor growth.

scholarly journals Genome-Wide Association Study of Coronary Artery Disease

2010 ◽  
Vol 2010 ◽  
pp. 1-8 ◽  
Author(s):  
Naomi Ogawa ◽  
Yasushi Imai ◽  
Hiroyuki Morita ◽  
Ryozo Nagai
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Association Studies ◽  
Genome Wide Association ◽  
Candidate Gene Approach ◽  
International Hapmap Project ◽  
Genome Wide Association Studies ◽  
Genetic Determinants ◽  
Genome Wide ◽  
Artery Disease

Coronary artery disease (CAD) is a multifactorial disease with environmental and genetic determinants. The genetic determinants of CAD have previously been explored by the candidate gene approach. Recently, the data from the International HapMap Project and the development of dense genotyping chips have enabled us to perform genome-wide association studies (GWAS) on a large number of subjects without bias towards any particular candidate genes. In 2007, three chip-based GWAS simultaneously revealed the significant association between common variants on chromosome 9p21 and CAD. This association was replicated among other ethnic groups and also in a meta-analysis. Further investigations have detected several other candidate loci associated with CAD. The chip-based GWAS approach has identified novel and unbiased genetic determinants of CAD and these insights provide the important direction to better understand the pathogenesis of CAD and to develop new and improved preventive measures and treatments for CAD.

scholarly journals Accounting for Population Structure and Phenotypes From Relatives in Association Mapping for Farm Animals: A Simulation Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Enrico Mancin ◽  
Daniela Lourenco ◽  
Matias Bermann ◽  
Roberto Mantovani ◽  
Ignacy Misztal
Keyword(s):  
Population Structure ◽  
Beef Cattle ◽  
Dairy Cattle ◽  
Genetic Relatedness ◽  
Association Studies ◽  
Single Step ◽  
Structured Populations ◽  
Farm Animals ◽  
Snp Analysis ◽  
Genome Wide Association Studies

Population structure or genetic relatedness should be considered in genome association studies to avoid spurious association. The most used methods for genome-wide association studies (GWAS) account for population structure but are limited to genotyped individuals with phenotypes. Single-step GWAS (ssGWAS) can use phenotypes from non-genotyped relatives; however, its ability to account for population structure has not been explored. Here we investigate the equivalence among ssGWAS, efficient mixed-model association expedited (EMMAX), and genomic best linear unbiased prediction GWAS (GBLUP-GWAS), and how they differ from the single-SNP analysis without correction for population structure (SSA-NoCor). We used simulated, structured populations that mimicked fish, beef cattle, and dairy cattle populations with 1040, 5525, and 1,400 genotyped individuals, respectively. Larger populations were also simulated that had up to 10-fold more genotyped animals. The genomes were composed by 29 chromosomes, each harboring one QTN, and the number of simulated SNPs was 35,000 for the fish and 65,000 for the beef and dairy cattle populations. Males and females were genotyped in the fish and beef cattle populations, whereas only males had genotypes in the dairy population. Phenotypes for a trait with heritability varying from 0.25 to 0.35 were available in both sexes for the fish population, but only for females in the beef and dairy cattle populations. In the latter, phenotypes of daughters were projected into genotyped sires (i.e., deregressed proofs) before applying EMMAX and SSA-NoCor. Although SSA-NoCor had the largest number of true positive SNPs among the four methods, the number of false negatives was two–fivefold that of true positives. GBLUP-GWAS and EMMAX had a similar number of true positives, which was slightly smaller than in ssGWAS, although the difference was not significant. Additionally, no significant differences were observed when deregressed proofs were used as pseudo-phenotypes in EMMAX compared to daughter phenotypes in ssGWAS for the dairy cattle population. Single-step GWAS accounts for population structure and is a straightforward method for association analysis when only a fraction of the population is genotyped and/or when phenotypes are available on non-genotyped relatives.

scholarly journals MOLECULAR EPIDEMIOLOGY OF RENAL CANCER

2018 ◽  
Vol 14 (3) ◽  
pp. 107-119 ◽  
Author(s):  
D. G. Zaridze ◽  
A. F. Mukeriya ◽  
O. V. Shan’gina ◽  
V. B. Matveev
Keyword(s):  
Risk Factors ◽  
Molecular Epidemiology ◽  
Genetic Susceptibility ◽  
Association Studies ◽  
Cell Cancer ◽  
Transitional Cell ◽  
Occupational Exposures ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies ◽  
Very High

Kidney cancer consists of renal cell cancer (RCC) accounting for over 90 % of all kidney carcinomas and the transitional cell cancer. Clear cell cancer is a predominant type (80–85 %) of RCC. Smoking, overweight, obesity, hypertension, occupational exposures to pesticides, specifically to trichloroethylene are considered causal risk factors for sporadic i.e. non-hereditary RCC. The majority of sporadic RCC have polygenic etiology. They develop as a result of combined effect of large number of low penetrance genetic susceptibility genes (genetic polymorphism). The interplay of exposures to environmental risk factors and genetic susceptibility of exposed individuals is believed to influence the risk of developing sporadic RCC. Inheritance of high penetrance genes is associated with very high risk of the RCC. To these genes belongs, for example, VHL (von Hippel–Lindau). Germline mutations in VHL are causing VHL syndrome and hereditary type of RCC. Risk of RCC in individuals with germ-line mutations is very high however the proportion RCC associated with these events is very low (>5–7 %). Environmental factors virtually do not influence the risk of these cancers.The studies in molecular epidemiology based on candidate gene approach have shown that certain types (variants) of polymorphisms of GST, MTHFR, TYMS, VHL genes are associated with RCC. The genome wide association studies identified over twenty locus with single nucleotide polymorphism affecting the risk of RCC. The risk loci so far identified for RCC account for only about 10 % of the familial risk of RCC. Thus more studies with larger sample size are needed. As more RCC susceptibility alleles are discovered, deciphering the biological basis of risk variants should provide new insights into the biology of RCC that may lead to new approaches to prevention, early detection and therapeutic intervention.

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