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 A Genome Scan for Quantitative Trait Loci in a Wild Population of Red Deer (Cervus elaphus)

Genetics ◽  
2002 ◽  
Vol 162 (4) ◽  
pp. 1863-1873 ◽  
Author(s):  
J Slate ◽  
P M Visscher ◽  
S MacGregor ◽  
D Stevens ◽  
M L Tate ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Cervus Elaphus ◽  
Quantitative Trait ◽  
Red Deer ◽  
Wild Population ◽  
Additive Genetic Variance ◽  
Model Organisms ◽  
A Genome ◽  
Trait Loci ◽  
In The Wild

Abstract Recent empirical evidence indicates that although fitness and fitness components tend to have low heritability in natural populations, they may nonetheless have relatively large components of additive genetic variance. The molecular basis of additive genetic variation has been investigated in model organisms but never in the wild. In this article we describe an attempt to map quantitative trait loci (QTL) for birth weight (a trait positively associated with overall fitness) in an unmanipulated, wild population of red deer (Cervus elaphus). Two approaches were used: interval mapping by linear regression within half-sib families and a variance components analysis of a six-generation pedigree of >350 animals. Evidence for segregating QTL was found on three linkage groups, one of which was significant at the genome-wide suggestive linkage threshold. To our knowledge this is the first time that a QTL for any trait has been mapped in a wild mammal population. It is hoped that this study will stimulate further investigations of the genetic architecture of fitness traits in the wild.

scholarly journals A Genome-Wide Association Study Identifies Protein Quantitative Trait Loci (pQTLs)

PLoS Genetics ◽  
2008 ◽  
Vol 4 (5) ◽  
pp. e1000072 ◽  
Author(s):  
David Melzer ◽  
John R. B. Perry ◽  
Dena Hernandez ◽  
Anna-Maria Corsi ◽  
Kara Stevens ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Association Study ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome ◽  
Trait Loci

scholarly journals Meta-Analysis of Quantitative Trait Loci Associated with Seedling-Stage Salt Tolerance in Rice (Oryza sativa L.)

Plants ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 33 ◽  
Author(s):  
Md. Islam ◽  
John Ontoy ◽  
Prasanta Subudhi
Keyword(s):  
Quantitative Trait Loci ◽  
Salt Tolerance ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Oryza Sativa L ◽  
Meta Analysis ◽  
Seedling Stage ◽  
Phenotypic Variance ◽  
A Genome ◽  
Trait Loci

Soil and water salinity is one of the major abiotic stresses that reduce growth and productivity in major food crops including rice. The lack of congruence of salt tolerance quantitative trait loci (QTLs) in multiple genetic backgrounds and multiple environments is a major hindrance for undertaking marker-assisted selection (MAS). A genome-wide meta-analysis of QTLs controlling seedling-stage salt tolerance was conducted in rice using QTL information from 12 studies. Using a consensus map, 11 meta-QTLs for three traits with smaller confidence intervals were localized on chromosomes 1 and 2. The phenotypic variance of 3 meta-QTLs was ≥20%. Based on phenotyping of 56 diverse genotypes and breeding lines, six salt-tolerant genotypes (Bharathy, I Kung Ban 4-2 Mutant, Langmanbi, Fatehpur 3, CT-329, and IARI 5823) were identified. The perusal of the meta-QTL regions revealed several candidate genes associated with salt-tolerance attributes. The lack of association between meta-QTL linked markers and the level of salt tolerance could be due to the low resolution of meta-QTL regions and the genetic complexity of salt tolerance. The meta-QTLs identified in this study will be useful not only for MAS and pyramiding, but will also accelerate the fine mapping and cloning of candidate genes associated with salt-tolerance mechanisms in rice.

A genome-wide scan for quantitative trait loci affecting serum glucose and lipids in a White Duroc × Erhualian intercross F2 population

2009 ◽  
Vol 20 (6) ◽  
pp. 386-392 ◽  
Author(s):  
Rongrong Chen ◽  
Jun Ren ◽  
Wanbo Li ◽  
Xiang Huang ◽  
Xueming Yan ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Serum Glucose ◽  
F2 Population ◽  
Genome Wide ◽  
A Genome ◽  
Trait Loci ◽  
Genome Wide Scan

Quantitative Trait Loci For Lipid Metabolism In The Study Of Oletf x (Oletf x Fischer 344) Backcross Rats

2000 ◽  
Vol 27 (11) ◽  
pp. 881-886 ◽  
Author(s):  
Yuki Yamasaki ◽  
Takeshi K Watanabe ◽  
Shiro Okuno ◽  
Toshihide Ono ◽  
Keiko Oga ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Fischer 344 ◽  
Trait Loci

ADDO: a comprehensive toolkit to detect, classify and visualize additive and non-additive quantitative trait loci

2019 ◽  
Vol 36 (5) ◽  
pp. 1517-1521
Author(s):  
Leilei Cui ◽  
Bin Yang ◽  
Nikolas Pontikos ◽  
Richard Mott ◽  
Lusheng Huang
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Association Studies ◽  
Genetic Effects ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Additive Effects ◽  
A Genome ◽  
Trait Loci ◽  
Additive Genetic Effects

Abstract Motivation During the past decade, genome-wide association studies (GWAS) have been used to map quantitative trait loci (QTLs) underlying complex traits. However, most GWAS focus on additive genetic effects while ignoring non-additive effects, on the assumption that most QTL act additively. Consequently, QTLs driven by dominance and other non-additive effects could be overlooked. Results We developed ADDO, a highly efficient tool to detect, classify and visualize QTLs with additive and non-additive effects. ADDO implements a mixed-model transformation to control for population structure and unequal relatedness that accounts for both additive and dominant genetic covariance among individuals, and decomposes single-nucleotide polymorphism effects as either additive, partial dominant, dominant or over-dominant. A matrix multiplication approach is used to accelerate the computation: a genome scan on 13 million markers from 900 individuals takes about 5 h with 10 CPUs. Analysis of simulated data confirms ADDO’s performance on traits with different additive and dominance genetic variance components. We showed two real examples in outbred rat where ADDO identified significant dominant QTL that were not detectable by an additive model. ADDO provides a systematic pipeline to characterize additive and non-additive QTL in whole genome sequence data, which complements current mainstream GWAS software for additive genetic effects. Availability and implementation ADDO is customizable and convenient to install and provides extensive analytics and visualizations. The package is freely available online at https://github.com/LeileiCui/ADDO. Supplementary information Supplementary data are available at Bioinformatics online.

Detection of quantitative trait loci for locomotion and osteochondrosis-related traits in Large White ✕ Meishan pigs

2003 ◽  
Vol 76 (2) ◽  
pp. 155-165 ◽  
Author(s):  
G.J. Lee ◽  
A.L. Archibald ◽  
G.B. Garth ◽  
A.S. Law ◽  
D. Nicholson ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Chromosome 1 ◽  
Chromosome 15 ◽  
Large White ◽  
Chromosome 13 ◽  
Genome Wide ◽  
A Genome ◽  
Trait Loci ◽  
Gait Score

AbstractData from the F2 generation of a Large White (LW) ✕ Meishan (MS) crossbred population were analysed to detect quantitative trait loci (QTL) for leg and gait scores, osteochondrosis and physis scores. Legs, feet and gait score were assessed in 308 F2 animals at 85 ( + 5) kg and osteochondrosis and physis scores were recorded for the right foreleg after slaughter. A genome scan was performed using 111 genetic markers chosen to span the genome that were genotyped on the F2 animals and their F1 parents and purebred grandparents. A QTL on chromosome 1 affecting gait score was significant at the genome-wide significance level. Additional QTL significant at the chromosome-wide 5% threshold level (approx. equivalent to the genome-wide suggestive level) were detected on chromosome 1 for front feet and back legs scores, on chromosome 13 for front legs and front feet scores, on chromosome 14 for front legs, front feet and back legs scores and on chromosome 15 for back feet score. None of the QTL for osteochondrosis score exceeded the chromosome-wide suggestive level, but one chromosome-wide QTL for physis score was found on chromosome 7. On chromosome 1, gait and front feet scores mapped to the middle of the chromosome and showed additive effects in favour of the LW alleles and no dominance effects. The QTL for back legs score mapped to the distal end of the chromosome and showed a dominant effect and no additive effect. On chromosomes 14 and 15, the LW allele was again superior to the MS allele. On chromosome 13, there were both additive and dominance effects in favour of the MS allele. The MS alleles on chromosome 13 may have potential for introgression into a commercial LW population. The other putative QTLs identified may have value in marker-assisted selection in LW or MS-synthetic populations.

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