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 An explainable model of host genetic interactions linked to COVID-19 severity

2022 ◽  
Author(s):  
Anthony Onoja ◽  
Nicola Picchiotti ◽  
Chiara Fallerini ◽  
Margherita Baldassarri ◽  
Francesca Fava ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Genetic Factors ◽  
Association Studies ◽  
Principal Component ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Lectin Receptor ◽  
Increased Risk ◽  
Importance Analysis ◽  
Host Genetic

Abstract We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with training of multiple supervised classifiers, to predict severity on the basis of screened features. Feature importance analysis from tree-based models allowed to identify a handful of 16 variants with highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with good accuracy (ACC=81.88%; ROC_AUC=96%; MCC=61.55%). Principal Component Analysis (PCA) and clustering of patients on important variants orthogonally identified two groups of individuals with a higher fraction of severe cases. Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response, such as JAK-STAT, Cytokine, Interleukin, and C-type lectin receptor signaling. It also identified additional processes cross-talking with immune pathways, such as GPCR signalling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as “Respiratory or thoracic disease”, confirming their link with COVID-19 severity outcome. Taken together, our analysis suggests that curated genetic information can be effectively integrated along with other patient clinical covariates to forecast COVID-19 disease severity and dissect the underlying host genetic mechanisms for personalized medicine treatments.

scholarly journals Assessing the potential for assisted gene flow using past introduction of Norway spruce in Southern Sweden: Local adaptation and genetic basis of quantitative traits in trees

2018 ◽  
Author(s):  
Pascal Milesi ◽  
Mats Berlin ◽  
Jun Chen ◽  
Marion Orsucci ◽  
Lili Li ◽  
...  
Keyword(s):  
Gene Flow ◽  
Local Adaptation ◽  
Norway Spruce ◽  
Quantitative Traits ◽  
Genetic Basis ◽  
Association Studies ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Southern Sweden ◽  
Breeding Programs

AbstractNorway spruce (Picea abies) is a dominant conifer species of major economic importance in Northern Europe. Extensive breeding programs were established to improve phenotypic traits of interest. In southern Sweden seeds used to create progeny tests were collected on about 3000 trees of outstanding phenotype (“plus” trees) across the region. Some were of local origin but many were recent introductions from the rest of the natural range. The mixed origin of the trees together with partial sequencing of the exome of >1,500 of these trees and phenotypic data retrieved from the Swedish breeding program offered us a unique opportunity to dissect the genetic basis of local adaptation of three quantitative traits (height, diameter and budburst). Through a combination of multivariate analyses and genome-wide association studies, we showed that there was a very strong effect of geographical origin on growth (height and diameter) and phenology (budburst) with trees from southern origins outperforming local provenances. Association studies also indicated that growth traits were highly polygenic and budburst somewhat less. Hence, our results suggest that assisted gene flow and genomic selection approaches could help alleviating the effect of climate change on P. abies breeding programs in Sweden.

scholarly journals An explainable model of host genetic interactions linked to COVID-19 severity

2021 ◽  
Author(s):  
Anthony Onoja ◽  
Nicola Picchiotti ◽  
Chiara Fallerini ◽  
Margherita Baldassarri ◽  
Francesca Fava ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Genetic Factors ◽  
Association Studies ◽  
Principal Component ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Lectin Receptor ◽  
Increased Risk ◽  
Importance Analysis ◽  
Host Genetic

Abstract We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with training of multiple supervised classifiers, to predict severity on the basis of screened features. Feature importance analysis from decision-tree models allowed to identify a handful of 16 variants with highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with good accuracy (ACC=81.88%; ROC_AUC=96%; MCC=61.55%). Principal Component Analysis (PCA) and clustering of patients on important variants orthogonally identified two groups of individuals with a higher fraction of severe cases. Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response, such as JAK-STAT, Cytokine, Interleukin, and C-type lectin receptor signaling. It also identified additional processes cross-talking with immune pathways, such as GPCR signalling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits (e.g. “Respiratory or thoracic disease”), confirming their link with COVID-19 severity outcome. Taken together, our analysis suggests that curated genetic information can be effectively integrated along with other patient clinical covariates to forecast COVID-19 disease severity and dissect the underlying host genetic mechanisms for personalized medicine treatments.

TLR1 and PRKAA1 Gene Polymorphisms in the Development of Atrophic Gastritis and Gastric Cancer

2018 ◽  
Vol 27 (4) ◽  
pp. 363-369 ◽  
Author(s):  
Gintare Dargiene ◽  
Greta Streleckiene ◽  
Jurgita Skieceviciene ◽  
Marcis Leja ◽  
Alexander Link ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Atrophic Gastritis ◽  
Genetic Polymorphisms ◽  
Association Studies ◽  
Control Group ◽  
Similar Distribution ◽  
Genome Wide Association Studies ◽  
Increased Risk ◽  
Infection Susceptibility ◽  
H Pylori

Background & Aims: Previous genome-wide association studies showed that genetic polymorphisms in toll-like receptor 1 (TLR1) and protein kinase AMP-activated alpha 1 catalytic subunit (PRKAA1) genes were associated with gastric cancer (GC) or increased Helicobacter pylori (H. pylori) infection susceptibility. The aim of this study was to evaluate the association between TLR1 and PRKAA1 genes polymorphisms and H.pylori infection, atrophic gastritis (AG) or GC in the European population.Methods: Single-nucleotide polymorphisms (SNPs) were analysed in 511 controls, 340 AG patients and 327 GC patients. TLR1 C>T (rs4833095) and PRKAA1 C>T (rs13361707) were genotyped by the real-time polymerase chain reaction. H. pylori status was determined by testing for anti-H. pylori IgG antibodies in the serum.Results: The study included 697 (59.2%) H. pylori positive and 481 (40.8%) H. pylori negative cases. We observed similar distribution of TLR1 and PRKAA1 alleles and genotypes in H. pylori positive and negative cases. TLR1 and PRKAA1 SNPs were not linked with the risk of AG. TC genotype of TLR1 gene was more prevalent in GC patients compared to the control group (29.7% and 22.3% respectively, p=0.002). Carriers of TC genotype had a higher risk of GC (aOR=1.89, 95% CI: 1.26–2.83, p=0.002). A similar association was observed in a dominant inheritance model for TLR1 gene SNP, where comparison of CC+TC vs. TT genotypes showed an increased risk of GC (aOR=1.86, 95% CI: 1.26–2.75, p=0.002). No association between genetic polymorphism in PRKAA1 gene and GC was observed.Conclusions: TLR1 rs4833095 SNP was associated with an increased risk of GC in a European population, while PRKAA1 rs13361707 genetic variant was not linked with GC. Both genetic polymorphisms were not associated with H. pylori infection susceptibility or the risk of AG.

scholarly journals GWAS of serum ALT and AST reveals an association of SLC30A10 Thr95Ile with hypermanganesemia symptoms

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lucas D. Ward ◽  
Ho-Chou Tu ◽  
Chelsea B. Quenneville ◽  
Shira Tsour ◽  
Alexander O. Flynn-Carroll ◽  
...  
Keyword(s):  
Bile Duct ◽  
Extrahepatic Bile Duct ◽  
Association Studies ◽  
Missense Variant ◽  
Deficiency Anemia ◽  
Genome Wide Association Studies ◽  
Loss Of Function ◽  
Extrahepatic Bile Duct Cancer ◽  
Hepatocellular Damage ◽  
Increased Risk

AbstractUnderstanding mechanisms of hepatocellular damage may lead to new treatments for liver disease, and genome-wide association studies (GWAS) of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) serum activities have proven useful for investigating liver biology. Here we report 100 loci associating with both enzymes, using GWAS across 411,048 subjects in the UK Biobank. The rare missense variant SLC30A10 Thr95Ile (rs188273166) associates with the largest elevation of both enzymes, and this association replicates in the DiscovEHR study. SLC30A10 excretes manganese from the liver to the bile duct, and rare homozygous loss of function causes the syndrome hypermanganesemia with dystonia-1 (HMNDYT1) which involves cirrhosis. Consistent with hematological symptoms of hypermanganesemia, SLC30A10 Thr95Ile carriers have increased hematocrit and risk of iron deficiency anemia. Carriers also have increased risk of extrahepatic bile duct cancer. These results suggest that genetic variation in SLC30A10 adversely affects more individuals than patients with diagnosed HMNDYT1.

scholarly journals The Genetic Basis of Hypertriglyceridemia

2021 ◽  
Vol 23 (8) ◽  
Author(s):  
Germán D. Carrasquilla ◽  
Malene Revsbech Christiansen ◽  
Tuomas O. Kilpeläinen
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Cumulative Effect ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Risk Variants ◽  
Genome Wide ◽  
Severe Hypertriglyceridemia ◽  
Increased Risk ◽  
Polygenic Scores

Abstract Purpose of Review Hypertriglyceridemia is a common dyslipidemia associated with an increased risk of cardiovascular disease and pancreatitis. Severe hypertriglyceridemia may sometimes be a monogenic condition. However, in the vast majority of patients, hypertriglyceridemia is due to the cumulative effect of multiple genetic risk variants along with lifestyle factors, medications, and disease conditions that elevate triglyceride levels. In this review, we will summarize recent progress in the understanding of the genetic basis of hypertriglyceridemia. Recent Findings More than 300 genetic loci have been identified for association with triglyceride levels in large genome-wide association studies. Studies combining the loci into polygenic scores have demonstrated that some hypertriglyceridemia phenotypes previously attributed to monogenic inheritance have a polygenic basis. The new genetic discoveries have opened avenues for the development of more effective triglyceride-lowering treatments and raised interest towards genetic screening and tailored treatments against hypertriglyceridemia. Summary The discovery of multiple genetic loci associated with elevated triglyceride levels has led to improved understanding of the genetic basis of hypertriglyceridemia and opened new translational opportunities.

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.

Abstract 288: Novel Mechanisms of Non-coding Genomic Regulation Identified in Cardiac Disease-in-a-dish Models

2016 ◽  
Vol 119 (suppl_1) ◽  
Author(s):  
Aditya Kumar ◽  
Stephanie Thomas ◽  
Kirsten Wong ◽  
Kevin Tenerelli ◽  
Valentina Lo Sardo ◽  
...  
Keyword(s):  
Heart Attack ◽  
Connexin 43 ◽  
Disease Risk ◽  
Association Studies ◽  
Correlation Coefficients ◽  
Induced Pluripotent Stem Cell ◽  
Genome Wide Association Studies ◽  
Isogenic Line ◽  
Nucleotide Polymorphisms ◽  
Increased Risk

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) at gene loci that affect cardiovascular function, and while mechanisms in protein-coding loci are obvious, those in non-coding loci are difficult to determine. 9p21 is a recently identified locus associated with increased risk of coronary artery disease (CAD) and myocardial infarction. Associations have implicated SNPs in altering smooth muscle and endothelial cell properties but have not identified adverse effects in cardiomyocytes (CMs) despite enhanced disease risk. Using induced pluripotent stem cell-derived CMs from patients that are homozygous risk/risk (R/R) and non-risk/non-risk (N/N) for 9p21 SNPs and either CAD positive or negative, we assessed CM function when cultured on hydrogels capable of mimicking the fibrotic stiffening associated with disease post-heart attack, i.e. “heart attack-in-a-dish” stiffening from 11 kiloPascals (kPa) to 50 kPa. While all CMs independent of genotype and disease beat synchronously on soft matrices, R/R CMs cultured on dynamically stiffened hydrogels exhibited asynchronous contractions and had significantly lower correlation coefficients versus N/N CMs in the same conditions. Dynamic stiffening reduced connexin 43 expression and gap junction assembly in R/R CMs but not N/N CMs. To eliminate patient-to-patient variability, we created an isogenic line by deleting the 9p21 gene locus from a R/R patient using TALEN-mediated gene editing, i.e. R/R KO. Deletion of the 9p21 locus restored synchronous contractility and organized connexin 43 junctions. As a non-coding locus, 9p21 appears to repress connexin transcription, leading to the phenotypes we observe, but only when the niche is stiffened as in disease. These data are the first to demonstrate that disease-specific niche remodeling, e.g. a “heart attack-in-a-dish” model, can differentially affect CM function depending on SNPs within a non-coding locus.

scholarly journals HAPPI GWAS: Holistic Analysis with Pre and Post Integration GWAS

2020 ◽  
Author(s):  
Marianne L. Slaten ◽  
Yen On Chan ◽  
Vivek Shrestha ◽  
Alexander E. Lipka ◽  
Ruthie Angelovici
Keyword(s):  
Association Studies ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Gwas Analysis ◽  
Genome Wide ◽  
Large Populations ◽  
Unbiased Estimates ◽  
Best Linear Unbiased ◽  
Automated Pipeline

AbstractMotivationAdvanced publicly available sequencing data from large populations have enabled in-formative genome-wide association studies (GWAS) that associate SNPs with phenotypic traits of interest. Many publicly available tools able to perform GWAS have been developed in response to increased demand. However, these tools lack a comprehensive pipeline that includes both pre-GWAS analysis such as outlier removal, data transformation, and calculation of Best Linear Unbiased Predictions (BLUPs) or Best Linear Unbiased Estimates (BLUEs). In addition, post-GWAS analysis such as haploblock analysis and candidate gene identification are lacking.ResultsHere, we present HAPPI GWAS, an open-source GWAS tool able to perform pre-GWAS, GWAS, and post-GWAS analysis in an automated pipeline using the command-line interface.AvailabilityHAPPI GWAS is written in R for any Unix-like operating systems and is available on GitHub (https://github.com/Angelovici-Lab/HAPPI.GWAS.git)[email protected]

scholarly journals Genetic Variability in Molecular Pathways Implicated in Alzheimer's Disease: A Comprehensive Review

2021 ◽  
Vol 13 ◽  
Author(s):  
David Vogrinc ◽  
Katja Goričar ◽  
Vita Dolžan
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Age Of Onset ◽  
Association Studies ◽  
The Elderly ◽  
Gene Clustering ◽  
Molecular Pathways ◽  
Genome Wide Association Studies ◽  
Cellular Processes ◽  
Increased Risk

Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting a significant part of the population. The majority of AD cases occur in the elderly with a typical age of onset of the disease above 65 years. AD presents a major burden for the healthcare system and since population is rapidly aging, the burden of the disease will increase in the future. However, no effective drug treatment for a full-blown disease has been developed to date. The genetic background of AD is extensively studied; numerous genome-wide association studies (GWAS) identified significant genes associated with increased risk of AD development. This review summarizes more than 100 risk loci. Many of them may serve as biomarkers of AD progression, even in the preclinical stage of the disease. Furthermore, we used GWAS data to identify key pathways of AD pathogenesis: cellular processes, metabolic processes, biological regulation, localization, transport, regulation of cellular processes, and neurological system processes. Gene clustering into molecular pathways can provide background for identification of novel molecular targets and may support the development of tailored and personalized treatment of AD.

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