Analysis of Quantitative Trait Loci for Behavioral Laterality in Mice

Abstract Laterality is believed to have genetic components, as has been deduced from family studies in humans and responses to artificial selection in mice, but these genetic components are unknown and the underlying physiological mechanisms are still a subject of dispute. We measured direction of laterality (preferential use of left or right paws) and degree of laterality (absolute difference between the use of left and right paws) in C57BL/6ByJ (B) and NZB/BlNJ (N) mice and in their F1 and F2 intercrosses. Measurements were taken of both forepaws and hind paws. Quantitative trait loci (QTL) did not emerge for direction but did for degree of laterality. One QTL for forepaw (LOD score = 5.6) and the second QTL for hind paw (LOD score = 7.2) were both located on chromosome 4 and their peaks were within the same confidence interval. A QTL for plasma luteinizing hormone concentration was also found in the confidence interval of these two QTL. These results suggest that the physiological mechanisms underlying degree of laterality react to gonadal steroids.

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Empirical Nonparametric Bootstrap Strategies in Quantitative Trait Loci Mapping: Conditioning on the Genetic Model

Genetics ◽

10.1093/genetics/148.1.525 ◽

1998 ◽

Vol 148 (1) ◽

pp. 525-535

Author(s):

Claude M Lebreton ◽

Peter M Visscher

Keyword(s):

Quantitative Trait Loci ◽

Confidence Interval ◽

Confidence Intervals ◽

Quantitative Trait ◽

Genetic Factors ◽

Genetic Model ◽

Original Data ◽

Nonparametric Bootstrap ◽

Test Protocol ◽

Trait Loci

AbstractSeveral nonparametric bootstrap methods are tested to obtain better confidence intervals for the quantitative trait loci (QTL) positions, i.e., with minimal width and unbiased coverage probability. Two selective resampling schemes are proposed as a means of conditioning the bootstrap on the number of genetic factors in our model inferred from the original data. The selection is based on criteria related to the estimated number of genetic factors, and only the retained bootstrapped samples will contribute a value to the empirically estimated distribution of the QTL position estimate. These schemes are compared with a nonselective scheme across a range of simple configurations of one QTL on a one-chromosome genome. In particular, the effect of the chromosome length and the relative position of the QTL are examined for a given experimental power, which determines the confidence interval size. With the test protocol used, it appears that the selective resampling schemes are either unbiased or least biased when the QTL is situated near the middle of the chromosome. When the QTL is closer to one end, the likelihood curve of its position along the chromosome becomes truncated, and the nonselective scheme then performs better inasmuch as the percentage of estimated confidence intervals that actually contain the real QTL's position is closer to expectation. The nonselective method, however, produces larger confidence intervals. Hence, we advocate use of the selective methods, regardless of the QTL position along the chromosome (to reduce confidence interval sizes), but we leave the problem open as to how the method should be altered to take into account the bias of the original estimate of the QTL's position.

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Quantitative Trait Loci: A Meta-analysis

Genetics ◽

10.1093/genetics/155.1.463 ◽

2000 ◽

Vol 155 (1) ◽

pp. 463-473

Author(s):

Bruno Goffinet ◽

Sophie Gerber

Keyword(s):

Quantitative Trait Loci ◽

Confidence Interval ◽

Quantitative Trait ◽

Meta Analysis ◽

Trait Loci ◽

Akaike Criterion ◽

Using Data

Abstract This article presents a method to combine QTL results from different independent analyses. This method provides a modified Akaike criterion that can be used to decide how many QTL are actually represented by the QTL detected in different experiments. This criterion is computed to choose between models with one, two, three, etc., QTL. Simulations are carried out to investigate the quality of the model obtained with this method in various situations. It appears that the method allows the length of the confidence interval of QTL location to be consistently reduced when there are only very few “actual” QTL locations. An application of the method is given using data from the maize database available online at http://www.agron.missouri.edu/.

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Identification of Distinct Quantitative Trait Loci Affecting Length or Weight Variability at Birth in Humans

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/jc.2006-0529 ◽

2006 ◽

Vol 91 (10) ◽

pp. 4164-4170 ◽

Cited By ~ 13

Author(s):

Delphine Fradin ◽

Simon Heath ◽

Jacques Lepercq ◽

Mark Lathrop ◽

Pierre Bougnères

Keyword(s):

Birth Weight ◽

Quantitative Trait Loci ◽

Fetal Growth ◽

Quantitative Trait ◽

Close Correlation ◽

Birth Length ◽

Lod Score ◽

Sibling Pairs ◽

A Genome ◽

Trait Loci

Abstract Context: The variability of human fetal growth is multifactorial. Twin and family studies demonstrate that genetic determinants influence normal fetal growth, but the responsible genetic polymorphisms are unknown. Objective: The objective of the study was the mapping of quantitative trait loci (QTLs) for birth length and weight. Design and Methods: To approach the genetic factors implicated in the normal variation of birth length and weight, we conducted a genome-wide approach of these two quantitative traits in 220 French Caucasian pedigrees (412 sibling pairs) using a variance components method. Results: We observed evidence for several QTLs influencing birth length or birth weight independently. Whereas birth length and weight showed a close correlation (r = 0.76, P < 0.0001), their genetic variability appeared largely determined by distinct genomic loci. Birth length was influenced by two major QTLs located in 2p21 and 2q11 (LOD scores 2.69 and 3.57). The variability of birth weight was linked to another QTL on 7q35 (LOD score 3.1). Several other regions showed more modest evidence for linkage with LOD score values of 1–2 on chromosomes 7, 8, 10, 13, and 17 for birth length and chromosomes 1, 2, 6, 8, 10, 13, 14, 15, 17, and 20 for birth weight. Conclusion: These preliminary QTLs provide a first step toward the identification of the genomic variants involved in the variability of human fetal growth. Our results should, however, be considered preliminary until they are replicated in other studies.

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The Genetic Basis of Plasma Variation in Adiponectin, a Global Endophenotype for Obesity and the Metabolic Syndrome

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/jcem.86.9.7878 ◽

2001 ◽

Vol 86 (9) ◽

pp. 4321-4325 ◽

Cited By ~ 137

Author(s):

Anthony G. Comuzzie ◽

Tohru Funahashi ◽

Gabriele Sonnenberg ◽

Lisa J. Martin ◽

Howard J. Jacob ◽

...

Keyword(s):

Quantitative Trait Locus ◽

Quantitative Trait Loci ◽

Genetic Analysis ◽

Quantitative Trait ◽

European Ancestry ◽

Chromosome 5 ◽

Lod Score ◽

The Metabolic Syndrome ◽

Trait Loci ◽

Trait Locus

Here we present the first genetic analysis of adiponectin levels, a newly identified adipocyte-derived protein. Recent work has suggested that adiponectin may play a role in mediating the effects of body weight as a risk factor for coronary artery disease. For this analysis we assayed serum levels of adiponectin in 1100 adults of predominantly northern European ancestry distributed across 170 families. Quantitative genetic analysis of adiponectin levels detected an additive genetic heritability of 46%. The maximum LOD score detected in a genome wide scan for adiponectin levels was 4.06 (P = 7.7 × 10−6), 35 cM from pter on chromosome 5. The second largest LOD score (LOD = 3.2; P = 6.2 × 10−5) was detected on chromosome 14, 29 cM from pter. The detection of a significant linkage with a quantitative trait locus on chromosome 5 provides strong evidence for a replication of a previously reported quantitative trait locus for obesity-related phenotypes. In addition, several secondary signals offer potential evidence of replications for additional previously reported obesity-related quantitative trait loci on chromosomes 2 and 10. Not only do these results identify quantitative trait loci with significant effects on a newly described, and potentially very important, adipocyte-derived protein, they also reveal the emergence of a consistent pattern of linkage results for obesity-related traits across a number of human populations.

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AdjustedPValues for Genome-Wide Scans

Genetics ◽

10.1093/genetics/164.4.1683 ◽

2003 ◽

Vol 164 (4) ◽

pp. 1683-1687 ◽

Cited By ~ 2

Author(s):

Theodore C Lystig

Keyword(s):

Quantitative Trait Loci ◽

Quantitative Trait ◽

Vertical Axis ◽

Lod Score ◽

P Values ◽

Local Maxima ◽

Genome Wide ◽

Trait Loci ◽

Genome Wide Significance

AbstractGenome-wide scans for quantitative trait loci (QTL) have traditionally been summarized with plots of logarithm of odds (LOD) scores. A valuable modification is to supplement such plots with an additional vertical axis displaying quantiles of adjusted P values and labeling local maxima of the LOD scores with location-specific adjusted P values. This provides a visible gradation of genome-wide significance for the LOD score curve, instead of the stark dichotomy that a single threshold yields. Adjusted P values give genome-wide significance of individual LOD scores and are obtained through a straightforward modification of the familiar algorithm for generating permutation-based thresholds.

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Prediction of the Confidence Interval of Quantitative Trait Loci Location

Behavior Genetics ◽

10.1023/b:bege.0000023652.93162.e8 ◽

2004 ◽

Vol 34 (4) ◽

pp. 477-482 ◽

Cited By ~ 27

Author(s):

Peter M. Visscher ◽

Mike E. Goddard

Keyword(s):

Quantitative Trait Loci ◽

Confidence Interval ◽

Quantitative Trait ◽

Trait Loci

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A Whole-Genome Linkage Scan Suggests Several Genomic Regions Potentially Containing Quantitative Trait Loci for Osteoporosis

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/jc.2002-020474 ◽

2002 ◽

Vol 87 (11) ◽

pp. 5151-5159 ◽

Cited By ~ 105

Author(s):

Hong-Wen Deng ◽

Fu-Hua Xu ◽

Qing-Yang Huang ◽

Hui Shen ◽

Hongyi Deng ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Quantitative Trait ◽

Whole Genome ◽

Mineral Density ◽

Lod Score ◽

Multipoint Analysis ◽

Sibling Pairs ◽

Point Analysis ◽

Trait Loci ◽

Genomic Regions

Abstract Osteoporosis is an important health problem, particularly in the elderly women. Bone mineral density (BMD) is a major determinant of osteoporosis. For a sample of 53 pedigrees that contain 1249 sibling pairs, 1098 grandparent-grandchildren pairs, and 2589 first cousin pairs, we performed a whole- genome linkage scan using 380 microsatellite markers to identify genomic regions that may contain quantitative trait loci (QTL) of BMD. Each pedigree was ascertained through a proband with BMD values belonging to the bottom 10% of the population. We conducted two-point and multipoint linkage analyses. Several potentially important genomic regions were suggested. For example, the genomic region near the marker D10S1651 may contain a QTL for hip BMD variation (with two-point analysis LOD score of 1.97 and multipoint analysis LOD score of 2.29). The genomic regions near the markers D4S413 and D12S1723 may contain QTLs for spine BMD variation (with two-point analysis LOD score of 2.12 and 2.17 and multipoint analysis LOD score of 3.08 and 2.96, respectively). The genomic regions identified in this and some earlier reports are compared for exploration in extension studies with larger samples and/or denser markers for confirmation and fine mapping to eventually identify major functional genes involved in osteoporosis.

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