Multiple Trait Analysis of Genetic Mapping for Quantitative Trait Loci

We present in this paper models and statistical methods for performing multiple trait analysis on mapping quantitative trait loci (QTL) based on the composite interval mapping method. By taking into account the correlated structure of multiple traits, this joint analysis has several advantages, compared with separate analyses, for mapping QTL, including the expected improvement on the statistical power of the test for QTL and on the precision of parameter estimation. Also this joint analysis provides formal procedures to test a number of biologically interesting hypotheses concerning the nature of genetic correlations between different traits. Among the testing procedures considered are those for joint mapping, pleiotropy, QTL by environment interaction, and pleiotropy vs. close linkage. The test of pleiotropy (one pleiotropic QTL at a genome position) vs. close linkage (multiple nearby nonpleiotropic QTL) can have important implications for our understanding of the nature of genetic correlations between different traits in certain regions of a genome and also for practical applications in animal and plant breeding because one of the major goals in breeding is to break unfavorable linkage. Results of extensive simulation studies are presented to illustrate various properties of the analyses.     

Optogenetic Rescue of a Patterning Mutant

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Ontogenetic Patterning of Skeletal Fluctuating Asymmetry in Rhesus Macaques and Humans: Evolutionary and Developmental Implications

I address the question of how fluctuating asymmetry (FA)—the distribution of random deviations from bilateral symmetry—varies ontogenetically in the mammalian skeleton. This question is significant because of the light that such patterns can shed on the causes of variation in developmental stability in bone as well as other structures. Based on large ontogenetic skeletal series of Macaca mulatta and Homo sapiens, I report that the FA variances of skeletal metric traits increase ontogenetically. Coupled with the finding that FA variances also accumulate to greater magnitudes in slower growing mammals, this result is consistent with the hypotheses that FA in bone is primarily caused by (a) cumulative effects of asymmetrical mechanical factors, (b) accumulation of variation in the (local) regulation of growth, or (c) a tendency for bone morphology to drift through undirected remodeling. I discuss the implications of these optional explanations for primate evolution and bone development.     

遗传标记与数量性状基因间连锁关系的分析

本文讨论标记基因与数量性状主基因连锁关系的一般分析方法,包括重组值的估计和有关遗传假设的测验。并以我们水稻遗传试验中两个具有互补和重叠作用的卷叶基因和一个矮秆基因试验结果的分析为例作了较详细的示范。     

Effects of Genetic and Environmental Factors on Trait Network Predictions From Quantitative Trait Locus Data

The use of high-throughput genomic techniques to map gene expression quantitative trait loci has spurred the development of path analysis approaches for predicting functional networks linking genes and natural trait variation. The goal of this study was to test whether potentially confounding factors, including effects of common environment and genes not included in path models, affect predictions of cause–effect relationships among traits generated by QTL path analyses. Structural equation modeling (SEM) was used to test simple QTL-trait networks under different regulatory scenarios involving direct and indirect effects. SEM identified the correct models under simple scenarios, but when common-environment effects were simulated in conjunction with direct QTL effects on traits, they were poorly distinguished from indirect effects, leading to false support for indirect models. Application of SEM to loblolly pine QTL data provided support for biologically plausible a priori hypotheses of QTL mechanisms affecting height and diameter growth. However, some biologically implausible models were also well supported. The results emphasize the need to include any available functional information, including predictions for genetic and environmental correlations, to develop plausible models if biologically useful trait network predictions are to be made.     

The Genetic Analysis of Quantitative Trait Differences between Two Homozygous Lines

Previous maximum likelihood methods to analyze quantitative data on two inbred parental strains, their F₁ and backcross generations are extended in three directions: (1) a method is suggested to transform the data to better satisfy the assumptions of normality and homoscedasticity; (2) the likelihoods are modified to allow for litter correlations and heteroscedasticity and (3) allowance is made for the incorporation of F₂ data. The problem of making a choice among a set of simple genetic hypotheses is further discussed.     

Relating Mutant Genotype to Phenotype via Quantitative Behavior of the NADPH Redox Cycle in Human Erythrocytes

Background

The NADPH redox cycle plays a key role in antioxidant protection of human erythrocytes. It consists of two enzymes: glucose-6-phosphate dehydrogenase (G6PD) and glutathione reductase. Over 160 G6PD variants have been characterized and associated with several distinct clinical manifestations. However, the mechanistic link between the genotype and the phenotype remains poorly understood.

Methodology/Principal Findings

We address this issue through a novel framework (design space) that integrates information at the genetic, biochemical and clinical levels. Our analysis predicts three qualitatively-distinct phenotypic regions that can be ranked according to fitness. When G6PD variants are analyzed in design space, a correlation is revealed between the phenotypic region and the clinical manifestation: the best region with normal physiology, the second best region with a pathology, and the worst region with a potential lethality. We also show that Plasmodium falciparum, by induction of its own G6PD gene in G6PD-deficient erythrocytes, moves the operation of the cycle to a region of the design space that yields robust performance.

Conclusions/Significance

In conclusion, the design space for the NADPH redox cycle, which includes relationships among genotype, phenotype and environment, illuminates the function, design and fitness of the cycle, and its phenotypic regions correlate with the organism''s clinical status.     

Genetic Interactions between Naturally Occurring Alleles at Quantitative Trait Loci and Mutant Alleles at Candidate Loci Affecting Bristle Number in Drosophila Melanogaster

Previously, we mapped quantitative trait loci (QTL) affecting response to short-term selection for abdominal bristle number to seven suggestive regions that contain loci involved in bristle development and/or that have adult bristle number mutant phenotypes, and are thus candidates for bristle number QTL in natural populations. To test the hypothesis that the factors contributing to selection response genetically interact with these candidate loci, high and low chromosomes from selection lines were crossed to chromosomes containing wild-type or mutant alleles at the candidate loci, and the numbers of bristles were recorded in trans heterozygotes. Quantitative failure to complement, detected as a significant selection line*cross effect by analysis of variance, can be interpreted as evidence for allelism or epistasis between the factors on selected chromosomes and the candidate loci. Mutations at some candidate loci (bb, emc, h, Dl, Hairless) showed strong interactions with selected chromosomes, whereas others interacted weakly (ASC, abd, Scr) or not at all (N, mab, E(spl)). These results support the hypothesis that some candidate loci, initially identified through mutations of large effect on bristle number, either harbor or are close members in the same genetic pathway as variants that contribute to standing variation in bristle number.     

A Genetic Map of Quantitative Trait Loci for Body Weight in the Mouse

The genetic basis of body weight in the mouse was investigated by measuring frequency changes of microsatellite marker alleles in lines divergently selected for body weight from a base population of a cross between two inbred strains. In several regions of the genome, sharp peaks of frequency change at linked markers were detected, which suggested the presence of single genes of moderate effect, although in several other regions, significant frequency changes occurred over large portions of chromosomes. A method based on maximum likelihood was used to infer effects and map positions of quantitative trait loci (QTLs) based on genotype frequencies at one or more marker loci. Eleven QTLs with effects in the range 0.17-0.28 phenotypic standard deviations were detected; but under an additive model, these did not fully account for the observed selection response. Tests for the presence of more than one QTL in regions where there were large changes of marker allele frequency were mostly inconclusive.     

Multiple-Interval Mapping for Quantitative Trait Loci With a Spike in the Trait Distribution

For phenotypic distributions where many individuals share a common value—such as survival time following a pathogenic infection—a spike occurs at that common value. This spike affects quantitative trait loci (QTL) mapping methodologies and causes standard approaches to perform suboptimally. In this article, we develop a multiple-interval mapping (MIM) procedure based on mixture generalized linear models (GLIMs). An extended Bayesian information criterion (EBIC) is used for model selection. To demonstrate its utility, this new approach is compared to single-QTL models that appropriately handle the phenotypic distribution. The method is applied to data from Listeria infection as well as data from simulation studies. Compared to the single-QTL model, the findings demonstrate that the MIM procedure greatly improves the efficiency in terms of positive selection rate and false discovery rate. The method developed has been implemented using functions in R and is freely available to download and use.     

Quantitative Trait Loci for Metabolic Syndrome in the Hypertension Genetic Epidemiology Network Study

As part of the Hypertension Genetic Epidemiology Network study, genome scans were performed in two ethnicities on the categorical metabolic syndrome (MetS). Genome scans were performed also on the factor scores produced by factor analysis (quantitative MetS). Heritabilities were highest for the obesity‐insulin (INS) factor and lowest for blood pressure (BP) and central obesity. Seventeen unique putative quantitative trait loci (QTLs) yielded logarithm of the odds ratio (LOD) scores in excess of 1.7, 8 for blacks and 9 for whites. Important QTL findings in whites included an LOD score of 3.19 on chromosome 15q15 for the BP factor, 3.08 on chromosome 8p23 for the lipids‐INS factor, and 3.07 on chromosome 3p26 for the obesity‐INS factor. In blacks, after excluding type 2 diabetics, important QTLs were identified, including an LOD score of 2.77 on 13p12 for the obesity‐INS factor and 2.63 on chromosome 11q24 for the lipids‐INS factor. Categorical MetS had lower results than quantitative MetS. Notably, several loci identified overlap with those identified in other studies for a single or group of traits. The most promising candidate loci on 11q24 for lipids‐INS and 13p12 for obesity‐INS in blacks, 8p23 for lipids‐INS, 14q24 for obesity‐INS, and 15q15 for BP in whites warrant further investigation.     

Ecotype-Specific Expression of a Flowering Mutant Phenotype in Arabidopsis thaliana

The majority of mutations that delay flowering in Arabidopsis thaliana have been identified in studies of the Landsberg erecta (Ler) ecotype. In this report we describe a gene (referred to as FLD) that, when mutated, delays flowering in the Columbia ecotype but has a minimal phenotype in the Ler genetic background. The late-flowering phenotype of fld mutants requires a non-Ler allele of another gene involved in the control of flowering time, Flowering Locus C. fld mutants retain a photoperiod response, and the flowering time of fld mutants can be reduced by cold treatment and low red/far-red light ratios.     

Quantitative Trait Loci Identification by Estimating the Genetic Model based on the Extremal Samples

Background In genetic association studies with quantitative trait loci (QTL), the association between a candidate genetic marker and the trait of interest is commonly examined by the omnibus F test or by the t-test corresponding to a given genetic model or mode of inheritance. It is known that the t-test with a correct model specification is more powerful than the F test. However, since the underlying genetic model is rarely known in practice, the use of a model-specific t-test may incur substantial power loss. Robust-efficient tests, such as the Maximin Efficiency Robust Test (MERT) and MAX3 have been proposed in the literature.Methods In this paper, we propose a novel two-step robust-efficient approach, namely, the genetic model selection (GMS) method for quantitative trait analysis. GMS selects a genetic model by testing Hardy-Weinberg disequilibrium (HWD) with extremal samples of the population in the first step and then applies the corresponding genetic model-specific t-test in the second step.Results Simulations show that GMS is not only more efficient than MERT and MAX3, but also has comparable power to the optimal t-test when the genetic model is known.Conclusion Application to the data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort demonstrates that the proposed approach can identify meaningful biological SNPs on chromosome 19.     

The SNP rs3128965 of HLA-DPB1 as a Genetic Marker of the AERD Phenotype

Background

Two common clinical syndromes of acetylsalicylic acid (aspirin) hypersensitivity, aspirin-exacerbated respiratory disease (AERD) and aspirin-exacerbated cutaneous disease (AECD), were subjected to a genome-wide association study to identify strong genetic markers for aspirin hypersensitivity in a Korean population.

Methods

A comparison of SNP genotype frequencies on an Affymetrix Genome-Wide Human SNP array of 179 AERD patients and 1989 healthy normal control subjects (NC) revealed SNPs on chromosome 6 that were associated with AERD, but not AECD. To validate the association, we enrolled a second cohort comprising AERD (n = 264), NC (n = 238) and disease-control (aspirin tolerant asthma; ATA, n = 387) groups.

Results

The minor genotype frequency (AG or AA) of a particular SNP, rs3128965, in the HLA-DPB1 region was higher in the AERD group compared to the ATA or NC group (P = 0.001, P = 0.002, in a co-dominant analysis model, respectively). Comparison of rs3128965 alleles with the clinical features of asthmatics revealed that patients harboring the A allele had increased bronchial hyperresponsiveness to inhaled aspirin and methacholine, and higher 15-HETE levels, than those without the A allele (P = 0.039, 0.037, and 0.004, respectively).

Conclusions

This implies the potential of rs3128965 as a genetic marker for diagnosis and prediction of the AERD phenotype.     

水产养殖动物遗传连锁图谱及QTL定位研究进展

自1997年美国农业部启动5种水产养殖动物基因组计划以来,在不到10年的时间里,世界各国都相继开展了本国主要水产养殖动物基因组研究。截至2005年底,有近17种海淡水养殖动物公布了遗传连锁图谱：属于高密度连锁图谱的有虹鳟和大西洋鲑（标记数超过1000）;属于中密度遗传连锁图谱的有罗非鱼、沟鲶、黑虎虾、日本牙鲆和欧洲海鲈（标记数为400-1000）;属于低密度遗传连锁图谱的有泰国的胡鲶,中国的栉孔扇贝、鲤鱼,日本的黄尾鲕,美国的牡蛎等近10种养殖种类（标记数少于400）。水产养殖动物遗传连锁图谱的构建和发展,促进了一些与经济性状（如生长、抗逆、发育等）相关的数量性状位点（QTL）的定位研究。然而,QTL定位研究目前只在具有中高密度遗传连锁图谱的鲑科鱼类（虹鳟、大西洋鲑和北极嘉鱼）、罗非鱼、沟鲶和日本牙鲆等种类中开展,而且定位研究仍处在初级水平。遗传连锁图谱的高分辨率和QTL在图谱上的精确定位,是今后能否实现对主要水产养殖动物的经济性状进行遗传操作的技术保证,同时也是实现分子标记或基因辅助育种在水产养殖动物中成功运用的制胜法宝。     

水稻粒长QTL定位与主效基因的遗传分析

该研究利用短粒普通野生稻矮杆突变体和长粒栽培稻品种KJ01组配杂交组合F_1,构建分离群体F_2;并对该群体粒长进行性状遗传分析,利用平均分布于水稻的12条染色体上的132对多态分子标记对该群体进行QTL定位及主效QTLs遗传分析,为进一步克隆新的主效粒长基因奠定基础,并为水稻粒形育种提供理论依据。结果表明:(1)所构建的水稻杂交组合分离群体F_2的粒长性状为多基因控制的数量性状。(2)对543株F_2分离群体进行QTL连锁分析,构建了控制水稻粒长的连锁遗传图谱,总长为1 713.94 cM,共检测出24个QTLs,只有3个表现为加性遗传效应,其余位点均表现为遗传负效应。(3)检测到的3个主效QTLs分别位于3号染色体的分子标记PSM379～RID24455、RID24455～RM15689和RM571～RM16238之间,且三者对表型的贡献率分别为54.85%、31.02%和7.62%。(4)在标记PSM379～RID24455之间已克隆到的粒长基因为该研究新发现的主效QTL位点。     

拟南芥表皮毛发育突变体abt3-1的基因定位及表型分析

在发掘和鉴定调控植物表皮毛发育的新因子过程中,获得了一个表皮毛发育异常的拟南芥隐性突变体abt3-1(aberrantly branched trichome 3-1)。与野生型拟南芥(Col-0)相比,其表皮毛分支数目明显增加。另外,abt3-1还表现出植株小、叶形宽、叶色发灰、主根短等发育缺陷。利用图位克隆技术将该突变基因ABT3定位在1号染色体上,分子标记在F28G11#3与F4N21#1之间,物理距离为134kb。该研究将为进一步克隆ABT3基因及研究其在调控植物生长发育过程中的作用奠定基础。