scholarly journals Genetic Dissection of Complex Genetic Factor Involved in NIDDM of OLETF Rat

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Takahisa Yamada ◽  
Hiroyuki Kose ◽  
Takeshi Ohta ◽  
Kozo Matsumoto
Keyword(s):  
Body Weight ◽  
Dependent Diabetes Mellitus ◽  
Genetic Dissection ◽  
Glucose Levels ◽  
Genome Wide ◽  
A Genome ◽  
Interesting Candidate ◽  
Genome Search ◽  
Genomic Regions ◽  
Oletf Rat

The Otsuka Long-Evans Tokushima Fatty (OLETF) rat is an animal model for obese-type, noninsulin-dependent diabetes mellitus (NIDDM) in humans. NIDDM in this rat model was shown to be regulated by multiple genes. We have identified 14 quantitative trait loci (QTLs) responsible for NIDDM (Nidd1-14/of) on chromosomes 1, 5, 7, 8, 9, 11, 12, 14, 16, and 17 by a whole genome search in 160 F2 progenies obtained by mating the OLETF and the F344 rats. Among these loci, two QTLs,Nidd1and2/of, were declared significant loci at a genome-wide level.Nidd3, 8, 9,and13/ofexhibited heterosis: heterozygotes showing significantly higher glucose levels than OLETF or F344 homozygotes. We also found evidence for interaction (epistasis) betweenNidd1/ofandNidd2/of, betweenNidd1/ofandNidd10/of, betweenNidd2/ofandNidd8/of, and betweenNidd2/ofandNidd14/of. Furthermore,Nidd6and11/ofshowed linkage with body weight, andNidd1, 2, 8, 9, 10,and12/ofhad an interaction with body weight. These indicated that NIDDM in the OLETF would have a higher degree of genetic complexity. We suggest several interesting candidate genes located in rat genomic regions forNidd1-14/ofor the syntenic regions in human genome.

scholarly journals Identification of possible quantitative trait loci responsible for hyperglycaemia after 70% pancreatectomy using a spontaneously diabetogenic rat

1999 ◽  
Vol 73 (1) ◽  
pp. 29-36 ◽  
Author(s):  
T. OGINO ◽  
D. H. MORALEJO ◽  
M. ZHU ◽  
K. TOIDE ◽  
S. WEI ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Insulin Dependent Diabetes Mellitus ◽  
Dependent Diabetes Mellitus ◽  
Partial Pancreatectomy ◽  
Glucose Levels ◽  
Fischer 344 ◽  
A Genome ◽  
Trait Loci ◽  
Oletf Rat

The Otsuka Long-Evans Tokushima Fatty (OLETF) rat is an animal model for obese-type non-insulin-dependent diabetes mellitus (NIDDM) in humans. The OLETF rat exhibits sustained hyperglycaemia after partial pancreatectomy, while the normal control rat does not. This difference is thought to be genetically determined and to be caused by impairment of β-cell regrowth, a possible event involved in the pathogenesis of NIDDM. Our investigation was designed to identify quantitative trait loci (QTL) responsible for post-pancreatectomy hyperglycaemia by performing a genome-wide scan in an F2 intercross obtained by mating the OLETF and Fischer-344 (F344) rats. We have identified three possible QTL on rat chromosomes (Chrs) 3, 14 and 19 that account for a total of approximately 75% of the genetic variance in the F2. For the QTL on Chr 14, the OLETF allele corresponds with increased glucose levels, as expected. Surprisingly, for the QTL on Chr 19, the F344 allele corresponds with increased glucose levels. The Chr 3 QTL exhibits heterosis, heterozygotes showing significantly higher glucose levels than OLETF or F344 homozygotes. We also found evidence for interaction (epistasis) between the QTL on Chrs 14 and 19.

scholarly journals Genomic prediction for growth using a low-density SNP panel in dromedary camels

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Morteza Bitaraf Sani ◽  
Javad Zare Harofte ◽  
Mohammad Hossein Banabazi ◽  
Saeid Esmaeilkhanian ◽  
Ali Shafei Naderi ◽  
...  
Keyword(s):  
Body Weight ◽  
Birth Weight ◽  
Sample Size ◽  
Genetic Improvement ◽  
Growth Traits ◽  
P Value ◽  
Dromedary Camels ◽  
Genome Wide ◽  
A Genome ◽  
Daily Gain

AbstractFor thousands of years, camels have produced meat, milk, and fiber in harsh desert conditions. For a sustainable development to provide protein resources from desert areas, it is necessary to pay attention to genetic improvement in camel breeding. By using genotyping-by-sequencing (GBS) method we produced over 14,500 genome wide markers to conduct a genome- wide association study (GWAS) for investigating the birth weight, daily gain, and body weight of 96 dromedaries in the Iranian central desert. A total of 99 SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.002). Genomic breeding values (GEBVs) were estimated with the BGLR package using (i) all 14,522 SNPs and (ii) the 99 SNPs by GWAS. Twenty-eight SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.001). Annotation of the genomic region (s) within ± 100 kb of the associated SNPs facilitated prediction of 36 candidate genes. The accuracy of GEBVs was more than 0.65 based on all 14,522 SNPs, but the regression coefficients for birth weight, daily gain, and body weight were 0.39, 0.20, and 0.23, respectively. Because of low sample size, the GEBVs were predicted using the associated SNPs from GWAS. The accuracy of GEBVs based on the 99 associated SNPs was 0.62, 0.82, and 0.57 for birth weight, daily gain, and body weight. This report is the first GWAS using GBS on dromedary camels and identifies markers associated with growth traits that could help to plan breeding program to genetic improvement. Further researches using larger sample size and collaboration of the camel farmers and more profound understanding will permit verification of the associated SNPs identified in this project. The preliminary results of study show that genomic selection could be the appropriate way to genetic improvement of body weight in dromedary camels, which is challenging due to a long generation interval, seasonal reproduction, and lack of records and pedigrees.

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.

Loci of intestinal distress in cystic fibrosis knockout mice

2003 ◽  
Vol 12 (2) ◽  
pp. 79-84 ◽  
Author(s):  
Christina K. Haston ◽  
Lap-Chee Tsui
Keyword(s):  
Cystic Fibrosis ◽  
X Chromosome ◽  
Knockout Mice ◽  
Mendelian Inheritance ◽  
Genetic Dissection ◽  
Male Mice ◽  
Female Mice ◽  
Genome Wide ◽  
A Genome ◽  
Strain Dependent

The strain-dependent survival of cystic fibrosis (CF) knockout mice has been used to map a modifier of CF, Cfm1, in mice and, subsequently, in humans. To identify additional modifiers of the CF phenotype, in this study, the survival of F2 CF mice derived from a cross between congenic C57BL/6J CF and BALB/cJ CF heterozygotes was followed up to 12 wk of age. A genome-wide linkage scan completed in F2 CF mice revealed a chromosome 10 locus ( P = 1.2 × 10−4) to predict for intestinal distress in CF male mice. An X chromosome locus for which non-Mendelian inheritance favoring B6 alleles in the surviving CF mice and BALB alleles in mice of a control population, was identified. The survival of female mice, both F2 CF and F2 control, was linked to loci on chromosomes 3 and 5. The identification of additional putative CF modifier loci may permit further genetic dissection of the complex CF phenotype.

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.

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