scholarly journals Genomic Regions Associated with the Position and Number of Hair Whorls in Horses

Animals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 2925
Author(s):  
Diogo Felipe Pereira de Assis Lima ◽  
Valdecy Aparecida Rocha da Cruz ◽  
Guilherme Luís Pereira ◽  
Rogério Abdallah Curi ◽  
Raphael Bermal Costa ◽  
...  
Keyword(s):  
Physiological Activity ◽  
Pleiotropic Effect ◽  
Single Step ◽  
Vertical Position ◽  
Additive Variance ◽  
Genome Wide ◽  
Step Procedure ◽  
A Genome ◽  
Hair Follicle Growth ◽  
Genomic Regions

The position and number of hair whorls have been associated with the behavior, temperament, and laterality of horses. The easy observation of whorls assists in the prediction of reactivity, and thus permits the development of better measures of handling, training, mounting, and riding horses. However, little is known about the genetics involved in the formation of hair whorls. Therefore, the aim of this study was to perform a genome-wide association analysis to identify chromosome regions and candidate genes associated with hair whorl traits. Data from 342 Quarter Horses genotyped for approximately 53,000 SNPs were used in an association study using a single-step procedure. The following traits were analyzed: vertical position of hair whorl on the head, number of whorls on the head, and number of whorls on the left and right sides of the neck. The traits had between one and three genomic windows associated. Each of them explained at least 4% of the additive variance. The windows accounted for 20–80% of additive variance for each trait analyzed. Many of the prospected genes are related to hair follicle growth. Some of these genes exert a pleiotropic effect on neurological and behavioral traits. This is the first indication of biological and physiological activity that might explain the association of hair whorls and temperament.

scholarly journals Epigenome-Wide Study Identified Methylation Sites Associated with the Risk of Obesity

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1984
Author(s):  
Majid Nikpay ◽  
Sepehr Ravati ◽  
Robert Dent ◽  
Ruth McPherson
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait ◽  
Rare Variants ◽  
Genome Wide ◽  
A Genome ◽  
Genome Wide Search ◽  
Risk Snps ◽  
Trait Locus ◽  
Genomic Regions ◽  
Eqtl Data

Here, we performed a genome-wide search for methylation sites that contribute to the risk of obesity. We integrated methylation quantitative trait locus (mQTL) data with BMI GWAS information through a SNP-based multiomics approach to identify genomic regions where mQTLs for a methylation site co-localize with obesity risk SNPs. We then tested whether the identified site contributed to BMI through Mendelian randomization. We identified multiple methylation sites causally contributing to the risk of obesity. We validated these findings through a replication stage. By integrating expression quantitative trait locus (eQTL) data, we noted that lower methylation at cg21178254 site upstream of CCNL1 contributes to obesity by increasing the expression of this gene. Higher methylation at cg02814054 increases the risk of obesity by lowering the expression of MAST3, whereas lower methylation at cg06028605 contributes to obesity by decreasing the expression of SLC5A11. Finally, we noted that rare variants within 2p23.3 impact obesity by making the cg01884057 site more susceptible to methylation, which consequently lowers the expression of POMC, ADCY3 and DNAJC27. In this study, we identify methylation sites associated with the risk of obesity and reveal the mechanism whereby a number of these sites exert their effects. This study provides a framework to perform an omics-wide association study for a phenotype and to understand the mechanism whereby a rare variant causes a disease.

Drosophila Gain-of-Function Mutant RTK Torso Triggers Ectopic Dpp and STAT Signaling

Genetics ◽  
2003 ◽  
Vol 164 (1) ◽  
pp. 247-258 ◽  
Author(s):  
Jinghong Li ◽  
Willis X Li
Keyword(s):  
Tyrosine Kinases ◽  
Target Genes ◽  
Tor Signaling ◽  
Gain Of Function ◽  
Essential Requirement ◽  
Downstream Target ◽  
Rtk Signaling ◽  
Genome Wide ◽  
A Genome ◽  
Genomic Regions

Abstract Overactivation of receptor tyrosine kinases (RTKs) has been linked to tumorigenesis. To understand how a hyperactivated RTK functions differently from wild-type RTK, we conducted a genome-wide systematic survey for genes that are required for signaling by a gain-of-function mutant Drosophila RTK Torso (Tor). We screened chromosomal deficiencies for suppression of a gain-of-function mutation tor (torGOF), which led to the identification of 26 genomic regions that, when in half dosage, suppressed the defects caused by torGOF. Testing of candidate genes in these regions revealed many genes known to be involved in Tor signaling (such as those encoding the Ras-MAPK cassette, adaptor and structural molecules of RTK signaling, and downstream target genes of Tor), confirming the specificity of this genetic screen. Importantly, this screen also identified components of the TGFβ (Dpp) and JAK/STAT pathways as being required for TorGOF signaling. Specifically, we found that reducing the dosage of thickveins (tkv), Mothers against dpp (Mad), or STAT92E (aka marelle), respectively, suppressed torGOF phenotypes. Furthermore, we demonstrate that in torGOF embryos, dpp is ectopically expressed and thus may contribute to the patterning defects. These results demonstrate an essential requirement of noncanonical signaling pathways for a persistently activated RTK to cause pathological defects in an organism.

scholarly journals Learning a genome-wide score of human–mouse conservation at the functional genomics level

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Soo Bin Kwon ◽  
Jason Ernst
Keyword(s):  
Mouse Model ◽  
Functional Genomics ◽  
Functional Genomic ◽  
Transcriptomic Data ◽  
Model Studies ◽  
Genome Wide ◽  
A Genome ◽  
Important Challenge ◽  
Genomic Regions ◽  
Human And Mouse

AbstractIdentifying genomic regions with functional genomic properties that are conserved between human and mouse is an important challenge in the context of mouse model studies. To address this, we develop a method to learn a score of evidence of conservation at the functional genomics level by integrating information from a compendium of epigenomic, transcription factor binding, and transcriptomic data from human and mouse. The method, Learning Evidence of Conservation from Integrated Functional genomic annotations (LECIF), trains neural networks to generate this score for the human and mouse genomes. The resulting LECIF score highlights human and mouse regions with shared functional genomic properties and captures correspondence of biologically similar human and mouse annotations. Analysis with independent datasets shows the score also highlights loci associated with similar phenotypes in both species. LECIF will be a resource for mouse model studies by identifying loci whose functional genomic properties are likely conserved.

scholarly journals Genome-Wide Analyses Identifies Known and New Markers Responsible of Chicken Plumage Color

Animals ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 493
Author(s):  
Salvatore Mastrangelo ◽  
Filippo Cendron ◽  
Gianluca Sottile ◽  
Giovanni Niero ◽  
Baldassare Portolano ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Snp Array ◽  
Fixation Index ◽  
Phenotypic Traits ◽  
Plumage Color ◽  
Phenotypic Marker ◽  
Genome Wide ◽  
A Genome ◽  
The Difference ◽  
Genomic Regions

Through the development of the high-throughput genotyping arrays, molecular markers and genes related to phenotypic traits have been identified in livestock species. In poultry, plumage color is an important qualitative trait that can be used as phenotypic marker for breed identification. In order to assess sources of genetic variation related to the Polverara chicken breed plumage colour (black vs. white), we carried out a genome-wide association study (GWAS) and a genome-wide fixation index (FST) scan to uncover the genomic regions involved. A total of 37 animals (17 white and 20 black) were genotyped with the Affymetrix 600 K Chicken single nucleotide polymorphism (SNP) Array. The combination of results from GWAS and FST revealed a total of 40 significant markers distributed on GGA 01, 03, 08, 12 and 21, and located within or near known genes. In addition to the well-known TYR, other candidate genes have been identified in this study, such as GRM5, RAB38 and NOTCH2. All these genes could explain the difference between the two Polverara breeds. Therefore, this study provides the basis for further investigation of the genetic mechanisms involved in plumage color in chicken.

scholarly journals Emerging Technologies for Genome-Wide Profiling of DNA Breakage

2021 ◽  
Vol 11 ◽  
Author(s):  
Matthew J. Rybin ◽  
Melina Ramic ◽  
Natalie R. Ricciardi ◽  
Philipp Kapranov ◽  
Claes Wahlestedt ◽  
...  
Keyword(s):  
Genome Instability ◽  
Dna Double Strand Breaks ◽  
Single Nucleotide ◽  
Strand Breaks ◽  
Single Strand Breaks ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale ◽  
Nucleotide Resolution ◽  
Genomic Regions

Genome instability is associated with myriad human diseases and is a well-known feature of both cancer and neurodegenerative disease. Until recently, the ability to assess DNA damage—the principal driver of genome instability—was limited to relatively imprecise methods or restricted to studying predefined genomic regions. Recently, new techniques for detecting DNA double strand breaks (DSBs) and single strand breaks (SSBs) with next-generation sequencing on a genome-wide scale with single nucleotide resolution have emerged. With these new tools, efforts are underway to define the “breakome” in normal aging and disease. Here, we compare the relative strengths and weaknesses of these technologies and their potential application to studying neurodegenerative diseases.

scholarly journals SNP and Haplotype Regional Heritability Mapping (SNHap-RHM): joint mapping of common and rare variation affecting complex traits

2021 ◽  
Author(s):  
Richard F Oppong ◽  
Pau Navarro ◽  
Chris S Haley ◽  
Sara Knott
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Complex Traits ◽  
Health Study ◽  
P Value ◽  
Major Depressive ◽  
Genome Wide ◽  
A Genome ◽  
Joint Mapping ◽  
Genomic Regions

We describe a genome-wide analytical approach, SNP and Haplotype Regional Heritability Mapping (SNHap-RHM), that provides regional estimates of the heritability across locally defined regions in the genome. This approach utilises relationship matrices that are based on sharing of SNP and haplotype alleles at local haplotype blocks delimited by recombination boundaries in the genome. We implemented the approach on simulated data and show that the haplotype-based regional GRMs capture variation that is complementary to that captured by SNP-based regional GRMs, and thus justifying the fitting of the two GRMs jointly in a single analysis (SNHap-RHM). SNHap-RHM captures regions in the genome contributing to the phenotypic variation that existing genome-wide analysis methods may fail to capture. We further demonstrate that there are real benefits to be gained from this approach by applying it to real data from about 20,000 individuals from the Generation Scotland: Scottish Family Health Study. We analysed height and major depressive disorder (MDD). We identified seven genomic regions that are genome-wide significant for height, and three regions significant at a suggestive threshold (p-value <1x10^(-5) ) for MDD. These significant regions have genes mapped to within 400kb of them. The genes mapped for height have been reported to be associated with height in humans, whiles those mapped for MDD have been reported to be associated with major depressive disorder and other psychiatry phenotypes. The results show that SNHap-RHM presents an exciting new opportunity to analyse complex traits by allowing the joint mapping of novel genomic regions tagged by either SNPs or haplotypes, potentially leading to the recovery of some of the "missing" heritability.

scholarly journals Genetics of Germination and Seedling Traits under Drought Stress in a MAGIC Population of Maize

Plants ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1786
Author(s):  
Soumeya Rida ◽  
Oula Maafi ◽  
Ana López-Malvar ◽  
Pedro Revilla ◽  
Meriem Riache ◽  
...  
Keyword(s):  
Drought Tolerance ◽  
Genome Wide Association Study ◽  
Genetic Regulation ◽  
Breeding Programs ◽  
Seedling Traits ◽  
Genome Wide ◽  
A Genome ◽  
Positive Correlations ◽  
Genomic Regions ◽  
Magic Population

Drought is one of the most detrimental abiotic stresses hampering seed germination, development, and productivity. Maize is more sensitive to drought than other cereals, especially at seedling stage. Our objective was to study genetic regulation of drought tolerance at germination and during seedling growth in maize. We evaluated 420 RIL with their parents from a multi-parent advanced generation inter-cross (MAGIC) population with PEG-induced drought at germination and seedling establishment. A genome-wide association study (GWAS) was carried out to identify genomic regions associated with drought tolerance. GWAS identified 28 and 16 SNPs significantly associated with germination and seedling traits under stress and well-watered conditions, respectively. Among the SNPs detected, two SNPs had significant associations with several traits with high positive correlations, suggesting a pleiotropic genetic control. Other SNPs were located in regions that harbored major QTLs in previous studies, and co-located with QTLs for cold tolerance previously published for this MAGIC population. The genomic regions comprised several candidate genes related to stresses and plant development. These included numerous drought-responsive genes and transcription factors implicated in germination, seedling traits, and drought tolerance. The current analyses provide information and tools for subsequent studies and breeding programs for improving drought tolerance.

scholarly journals Genome-Wide Association Study and Selection Signatures Detect Genomic Regions Associated with Seed Yield and Oil Quality in Flax

2018 ◽  
Vol 19 (8) ◽  
pp. 2303 ◽  
Author(s):  
Frank You ◽  
Jin Xiao ◽  
Pingchuan Li ◽  
Zhen Yao ◽  
Gaofeng Jia ◽  
...  
Keyword(s):  
Association Study ◽  
Seed Yield ◽  
Phenotypic Variation ◽  
Genome Wide Association Study ◽  
Oil Quality ◽  
Genome Wide Association ◽  
Selection Signatures ◽  
Genome Wide ◽  
A Genome ◽  
Genomic Regions

A genome-wide association study (GWAS) was performed on a set of 260 lines which belong to three different bi-parental flax mapping populations. These lines were sequenced to an averaged genome coverage of 19× using the Illumina Hi-Seq platform. Phenotypic data for 11 seed yield and oil quality traits were collected in eight year/location environments. A total of 17,288 single nucleotide polymorphisms were identified, which explained more than 80% of the phenotypic variation for days to maturity (DTM), iodine value (IOD), palmitic (PAL), stearic, linoleic (LIO) and linolenic (LIN) acid contents. Twenty-three unique genomic regions associated with 33 quantitative trait loci (QTL) for the studied traits were detected, thereby validating four genomic regions previously identified. The 33 QTL explained 48–73% of the phenotypic variation for oil content, IOD, PAL, LIO and LIN but only 8–14% for plant height, DTM and seed yield. A genome-wide selective sweep scan for selection signatures detected 114 genomic regions that accounted for 7.82% of the flax pseudomolecule and overlapped with the 11 GWAS-detected genomic regions associated with 18 QTL for 11 traits. The results demonstrate the utility of GWAS combined with selection signatures for dissection of the genetic structure of traits and for pinpointing genomic regions for breeding improvement.

scholarly journals DNA methylation associated with postpartum depressive symptoms overlaps findings from a genome-wide association meta-analysis of depression

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Dana M. Lapato ◽  
Roxann Roberson-Nay ◽  
Robert M. Kirkpatrick ◽  
Bradley T. Webb ◽  
Timothy P. York ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Depressive Symptoms ◽  
Health Outcomes ◽  
Meta Analysis ◽  
Previous History ◽  
Depression Scale ◽  
Postpartum Depressive Symptoms ◽  
Genome Wide ◽  
A Genome ◽  
Genomic Regions

Abstract Background Perinatal depressive symptoms have been linked to adverse maternal and infant health outcomes. The etiology associated with perinatal depressive psychopathology is poorly understood, but accumulating evidence suggests that understanding inter-individual differences in DNA methylation (DNAm) patterning may provide insight regarding the genomic regions salient to the risk liability of perinatal depressive psychopathology. Results Genome-wide DNAm was measured in maternal peripheral blood using the Infinium MethylationEPIC microarray. Ninety-two participants (46% African-American) had DNAm samples that passed all quality control metrics, and all participants were within 7 months of delivery. Linear models were constructed to identify differentially methylated sites and regions, and permutation testing was utilized to assess significance. Differentially methylated regions (DMRs) were defined as genomic regions of consistent DNAm change with at least two probes within 1 kb of each other. Maternal age, current smoking status, estimated cell-type proportions, ancestry-relevant principal components, days since delivery, and chip position served as covariates to adjust for technical and biological factors. Current postpartum depressive symptoms were measured using the Edinburgh Postnatal Depression Scale. Ninety-eight DMRs were significant (false discovery rate < 5%) and overlapped 92 genes. Three of the regions overlap loci from the latest Psychiatric Genomics Consortium meta-analysis of depression. Conclusions Many of the genes identified in this analysis corroborate previous allelic, transcriptomic, and DNAm association results related to depressive phenotypes. Future work should integrate data from multi-omic platforms to understand the functional relevance of these DMRs and refine DNAm association results by limiting phenotypic heterogeneity and clarifying if DNAm differences relate to the timing of onset, severity, duration of perinatal mental health outcomes of the current pregnancy or to previous history of depressive psychopathology.

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