The Analysis of Association Between Traits When Differences Between Trait States Matter

Because of their elementary significance in almost all fields of science, measures of association between two variables or traits are abundant and multiform. One aspect of association that is of considerable interest, especially in population genetics and ecology, seems to be widely ignored. This aspect concerns association between complex traits that show variable and arbitrarily defined state differences. Among such traits are genetic characters controlled by many and potentially polyploid loci, species characteristics, and environmental variables, all of which may be mutually and asymmetrically associated. A concept of directed association of one trait with another is developed here that relies solely on difference measures between the states of a trait. Associations are considered at three levels: between individual states of two variables, between an individual state of one variable and the totality of the other variable, and between two variables. Relations to known concepts of association are identified. In particular, measures at the latter two levels turn out to be interpretable as measures of differentiation. Examples are given for areas of application (search for functional relationships, distribution of variation over populations, genomic associations, spatiogenetic structure).     

Comparison of Photosynthetic Traits Between Two Typical Shrubs: Legume and Non-Legume in Hunshandak Sandland

In Huanshandak Sandland, China, net photosynthetic rate (P _N), transpiration rate (E), stomatal conductance (g _s), intercellular CO₂ concentration (C _i), water use efficiency (WUE), photochemical efficiency of photosystem 2 (F_v/F_m), and leaf nitrogen content were compared for Hedysarum fruticosum var. mongolicum (H.f.m.), a nitrogen fixing shrub, and Salix gordejevii (S.g.), a nitrogen non-fixing shrub. P _N, E, and g _s of the two shrubs were similar in trends, i.e. two peaks were observed in diurnal courses. However, except C _i, other parameters of H.f.m. were higher during the measured days than those of S.g. The midday depression of P _N was mainly due to decrease in stomata conductance and to reduction of F_v/F_m at midday. The higher P _N of H.f.m. was consistent with the higher leaf N content and there was a positive relation between them. In addition, several C₄ traits were found in H.f.m., i.e. high saturation irradiance and WUE, low dark respiration rate, and C _i, which partly resulted in higher P _N. This seems to indicate that the C₃ plant H.f.m. may have C₄ photosynthesis pathway or C₄ enzymes.     

Negative Association Between Conspicuous Visual Display and Chemosensory Behavior in Two Phrynosomatid Lizards

Communication in one sensory modality can influence communication in others. Lizards in many phrynosomatid species use primarily visual but also chemical signals. The striped plateau lizard, Sceloporus virgatus , exhibits evolutionary loss of a male color signal that in many species is used during aggressive postural displays towards conspecific males. These patches are used similarly in Urosaurus , the sister genus to Sceloporus . We compared a species in which a color signal has been lost, S. virgatus , to a species retaining the ancestral character state of blue abdominal display patches, Urosaurus ornatus , the common tree lizard, to test two hypotheses: (i) conspicuous postural displays that reveal the abdominal patch location are used less in the species that has lost the color patches; and (ii) potential chemical signals are used more in the species with the color loss. We analyzed both visual display behavior (push-up, full-show) and chemosensory behavior (tongue flick and nose tap) of male lizards following their introduction to a resident conspecific male in his home terrarium. Resident males performed very low rates of all behaviors, but intruders exhibited sufficient behavior for analysis.
Supporting the first hypothesis, S. virgatus were less likely than U. ornatus to perform full-show, a display that reveals abdominal skin. Male S. virgatus were more likely to perform push-up than U. ornatus , although S. virgatus performed push-up infrequently. Push-up is a postural display that does not specifically reveal the abdominal patch location. Supporting the second hypothesis, S . virgatus were more likely to perform chemosensory behaviors and performed them at a greater rate than did U. ornatus . Work comparing more closely related species is warranted to determine whether a negative association between conspicuous visual displays and chemosensory behavior is a general pattern.     

雌激素受体基因和长白猪繁殖性能相关研究

通过检测612头长白母猪共2 239窝ESR基因的PvuⅡ酶切多态性,分析了不同ESR基因型和长白母猪繁殖性状的相关,以确定ESR基因在猪育种应用的可能性.头胎母猪、第2胎母猪和3胎以上母猪的资料分开统计.群体中B等位基因的频率很低,但似然比检验结果显示群体的基因频率处于哈代-温伯格连锁平衡状态.第1胎BB基因型母猪的总产仔数显著高于AA型母猪(12.05±0.82 vs 10.19±0.24)(P＜0.05),但BB基因型母猪的初生仔猪重显著低于AA型母猪(1.23±0.07vs 1.42±0.02)(P＜0.05).第3胎以上资料合并,BB基因型母猪的总产仔数显著多于AA和AB基因型母猪(11.98±0.63 vs10.90±0.48/10.92±0.51)(P＜0.05),产活仔数显著高于AA型母猪(10.31±0.58 vs 9.43±0.45)(P＜0.05);AB基因型母猪初生仔猪重显著低于AA型母猪(1.44±0.04 vs 1.48±0.04)(P＜0.05).所有资料合并,BB基因型母猪的总产仔数极显著高于AB型母猪(11.63±0.52 VS 10.63±0.42)(P＜0.01),显著高于AA型母猪(11.63±0.52 vs 10.70±0.40)(P＜0.05);BB基因型母猪的产活仔数显著高于AB和AA基因型母猪(10.15±0.50 vs 9.33±0.39/9.41±0.41)(P＜0.05).其余情况下各基因型母猪间繁殖性状间差异不显著(P＞0.05).总之,BB基因型母猪的总产仔数和产活仔数优于其他基因型母猪,但仔猪初生重较低.ESR基因可以作为遗传标记,用于本群长白猪产仔数的选择.     

山羊FGF5基因组织表达及其变异与羊绒性状的关联性分析

为了研究山羊FGF5基因的遗传变异和组织表达等分子特征及其变异对山羊羊绒性状的影响,本试验应用PCR-SSCP与测序相结合的方法检测FGF5基因第1外显子在陇东绒山羊、柴达木绒山羊和中卫山羊中的多态性,并分析该基因变异对羊绒性状的影响;采用RT-qPCR技术研究FGF5基因在陇东绒山羊和辽宁绒山羊组织中的表达.结果 表明,在山羊FGF5基因的第1外显子区检测到一个同义突变位点c.272C＞T,表现为MM、MN和NN3种基因型,其中NN型仅在陇东绒山羊中有极少量分布.3个山羊品种的优势基因型均为MM,优势等位基因均为M.c.272C＞T位点在3种山羊品种中均处于Hardy-Weinberg平衡状态,且均为低度多态.c.272C＞T位点与陇东绒山羊的羊绒性状关联性分析表明,该位点对羊绒纤维直径的影响显著.携带等位基因N的个体的羊绒纤维直径显著低于不含等位基因N的个体的(P＜0.05);基因型MN个体的羊绒纤维直径显著低于基因型MM个体的(P＜0.05).FGF5基因在陇东绒山羊和辽宁绒山羊的心、肝、脾、肺、肾、骨骼肌和皮肤中均有表达;在陇东绒山羊的心、脾、肺、肾和皮肤中的表达量显著或极显著高于辽宁绒山羊的.本研究结果提示,若以改善羊绒细度为选育目标,山羊FGF5基因可作为羊绒性状改良的候选基因.     

A Generalized Family-Based Association Test for Dichotomous Traits

Recent advances in genotyping technology make it possible to utilize large-scale association analysis for disease-gene mapping. Powerful and robust family-based association methods are crucial for successful gene mapping. We propose a family-based association method, the generalized disequilibrium test (GDT), in which the genotype differences of all discordant relative pairs are utilized in assessing association within a family. The improvement of the GDT over existing methods is threefold: (1) information beyond first-degree relatives is incorporated efficiently, yielding substantial gains in power in comparison to existing tests; (2) the GDT statistic is implemented via a robust technique that does not rely on large sample theory, resulting in further power gains, especially at high levels of significance; and (3) covariates and weights based on family size are incorporated. Advantages of the GDT over existing methods are demonstrated by extensive computer simulations and by application to recently published large-scale genome-wide linkage data from the Type 1 Diabetes Genetics Consortium (T1DGC). In our simulations, the GDT consistently outperforms other tests for a common disease and frequently outperforms other tests for a rare disease; the power improvement is > 13% in 6 out of 8 extended pedigree scenarios. All of the six strongest associations identified by the GDT have been reported by other studies, whereas only three or four of these associations can be identified by existing methods. For the T1D association at gene UBASH3A, the GDT resulted in a genome-wide significance (p = 4.3 × 10⁻⁶), much stronger than the published significance (p = 10⁻⁴).     

Study on the Association Between Estrogen Receptor Gene (ESR) and Reproduction Traits in Landrace Pigs

To study the potential use of estrogen receptor gene (ESR) as a genetic marker to improve the reproductive traits of pigs, the genotypes of the ESR PCR product digested by Pvu II were determined in 2 239 litters from 612 Landrace sows. The data of the first, second, and later parities were separately evaluated. Although the frequency of the B allele was much lower than that of the A allele, likelihood ratio test showed that the gene frequencies were in Hardy-Weinberg equilibrium. The effects of ESR of different parities were not equal. In summary, the sows with the BB genotype showed better performance for total number of piglets born (TNB) and number of piglets born alive (NBA), but had a lower average piglet weight at birth (AWB). It was concluded that ESR could be used as a marker for the selection of litter size in the Landrace population.     

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.     

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness

BackgroundIncreasing our understanding of the genetic architecture of complex traits, through analyses of genotype-phenotype associations and of the genes/polymorphisms accounting for trait variation, is crucial, to improve the integration of molecular markers into forest tree breeding. In this study, two full-sib families and one breeding population of maritime pine were used to identify quantitative trait loci (QTLs) for height growth and stem straightness, through linkage analysis (LA) and linkage disequilibrium (LD) mapping approaches.ResultsThe populations used for LA consisted of two unrelated three-generation full-sib families (n = 197 and n = 477). These populations were assessed for height growth or stem straightness and genotyped for 248 and 217 markers, respectively. The population used for LD mapping consisted of 661 founders of the first and second generations of the breeding program. This population was phenotyped for the same traits and genotyped for 2,498 single-nucleotide polymorphism (SNP) markers corresponding to 1,652 gene loci. The gene-based reference genetic map of maritime pine was used to localize and compare the QTLs detected by the two approaches, for both traits. LA identified three QTLs for stem straightness and two QTLs for height growth. The LD study yielded seven significant associations (P ≤ 0.001): four for stem straightness and three for height growth. No colocalisation was found between QTLs identified by LA and SNPs detected by LD mapping for the same trait.ConclusionsThis study provides the first comparison of LA and LD mapping approaches in maritime pine, highlighting the complementary nature of these two approaches for deciphering the genetic architecture of two mandatory traits of the breeding program.     

Region-Based Association Analysis of Human Quantitative Traits in Related Individuals

Regional-based association analysis instead of individual testing of each SNP was introduced in genome-wide association studies to increase the power of gene mapping, especially for rare genetic variants. For regional association tests, the kernel machine-based regression approach was recently proposed as a more powerful alternative to collapsing-based methods. However, the vast majority of existing algorithms and software for the kernel machine-based regression are applicable only to unrelated samples. In this paper, we present a new method for the kernel machine-based regression association analysis of quantitative traits in samples of related individuals. The method is based on the GRAMMAR+ transformation of phenotypes of related individuals, followed by use of existing kernel machine-based regression software for unrelated samples. We compared the performance of kernel-based association analysis on the material of the Genetic Analysis Workshop 17 family sample and real human data by using our transformation, the original untransformed trait, and environmental residuals. We demonstrated that only the GRAMMAR+ transformation produced type I errors close to the nominal value and that this method had the highest empirical power. The new method can be applied to analysis of related samples by using existing software for kernel-based association analysis developed for unrelated samples.     

Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links

Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on ¹H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10⁻⁸) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10⁻⁴⁴) and lysine (rs8101881, P = 1.2×10⁻³³), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn''s disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.     

小麦耐低磷相关性状的全基因组关联分析

通过对小麦耐低磷相关性状进行全基因组关联分析(GWAS,genome-wide association study),挖掘与小麦耐低磷性显著相关的单核苷酸多态性标记(SNP,single nucleotide polymorphism)位点及候选基因,为小麦耐低磷性状的遗传基础和分子机制研究提供理论参考。本试验以198份黄淮麦区小麦品种(系)为试验材料,设置低磷和正常磷营养液水培试验,利用小麦35K芯片对分布于小麦全基因组的11896个SNP,采用Q+K关联模型对小麦耐低磷性相关性状进行关联分析。结果表明,小麦耐低磷性状表现出广泛的表型变异,变异系数为15.65%~26.59%,多态性信息含量(PIC,polymorphic information content)为0.095~0.500。群体结构分析表明,试验所用自然群体可分为2个亚群,GWAS共检测到67个与小麦耐低磷相关性状显著关联的SNP位点(P≤0.001),这些位点分布在除3A、3B和3D以外的18条染色体上,单个SNP位点可解释5.826%~9.552%的表型变异。在这些显著位点中有4个SNP位点同时关联到了2个不同的耐低磷性状。对67个SNP位点进行发掘,筛选到7个可能与小麦耐低磷性有关的候选基因。TraesCS6A02G001000和TraesCS6A02G001100在锌指合成中有重要作用;TraesCS6A02G118100可能为低磷胁迫诱导基因;TraesCS5D02G536400、TraesCS1B02G154200和TraesCS5D02G536500与低磷胁迫相关酶类基因家族有关;TraesCS1D02G231200与植物DUF 538结构域蛋白有关,是植物胁迫相关调控蛋白候选基因。     

Robust Rare-Variant Association Tests for Quantitative Traits in General Pedigrees

Next-generation sequencing technology has propelled the development of statistical methods to identify rare polygenetic variation associated with complex traits. The majority of these statistical methods are designed for case–control or population-based studies, with few methods that are applicable to family-based studies. Moreover, existing methods for family-based studies mainly focus on trios or nuclear families; there are far fewer existing methods available for analyzing larger pedigrees of arbitrary size and structure. To fill this gap, we propose a method for rare-variant analysis in large pedigree studies that can utilize information from all available relatives. Our approach is based on a kernel machine regression (KMR) framework, which has the advantages of high power, as well as fast and easy calculation of p-values using the asymptotic distribution. Our method is also robust to population stratification due to integration of a QTDT framework (Abecasis et al., Eur J Hum Genet 8(7):545–551, 2000b) with the KMR framework. In our method, we first calculate the expected genotype (between-family component) of a non-founder using all founders’ information and then calculate the deviates (within-family component) of observed genotype from the expectation, where the deviates are robust to population stratification by design. The test statistic, which is constructed using within-family component, is thus robust to population stratification. We illustrate and evaluate our method using simulated data and sequence data from Genetic Analysis Workshop 18.     

Exploring Potential of Pearl Millet Germplasm Association Panel for Association Mapping of Drought Tolerance Traits

A pearl millet inbred germplasm association panel (PMiGAP) comprising 250 inbred lines, representative of cultivated germplasm from Africa and Asia, elite improved open-pollinated cultivars, hybrid parental inbreds and inbred mapping population parents, was recently established. This study presents the first report of genetic diversity in PMiGAP and its exploitation for association mapping of drought tolerance traits. For diversity and genetic structure analysis, PMiGAP was genotyped with 37 SSR and CISP markers representing all seven linkage groups. For association analysis, it was phenotyped for yield and yield components and morpho-physiological traits under both well-watered and drought conditions, and genotyped with SNPs and InDels from seventeen genes underlying a major validated drought tolerance (DT) QTL. The average gene diversity in PMiGAP was 0.54. The STRUCTURE analysis revealed six subpopulations within PMiGAP. Significant associations were obtained for 22 SNPs and 3 InDels from 13 genes under different treatments. Seven SNPs associations from 5 genes were common under irrigated and one of the drought stress treatments. Most significantly, an important SNP in putative acetyl CoA carboxylase gene showed constitutive association with grain yield, grain harvest index and panicle yield under all treatments. An InDel in putative chlorophyll a/b binding protein gene was significantly associated with both stay-green and grain yield traits under drought stress. This can be used as a functional marker for selecting high yielding genotypes with ‘stay green’ phenotype under drought stress. The present study identified useful marker-trait associations of important agronomics traits under irrigated and drought stress conditions with genes underlying a major validated DT-QTL in pearl millet. Results suggest that PMiGAP is a useful panel for association mapping. Expression patterns of genes also shed light on some physiological mechanisms underlying pearl millet drought tolerance.     

Conjugation Between Two Strains of Blepharisma

SYNOPSIS. Conjugation involving two Japanese strains of Blepharisma , Niigata and Nara, which are considerably different from each other in external morphology, but are rather similar in nuclear configuration, was induced experimentally. Compared with normal conjugations of the two strains, both the Niigata- and Nara-interbred exconjugants show a strikingly high mortality. The possibilities of the occurrence of autogamy and cross-fertilization are discussed on the basis of the results obtained from observations on living and fixed material.     

小麦根部耐盐性状全基因组关联分析

为了解小麦耐盐相关性状的遗传机理,挖掘与小麦耐盐性显著相关的SNP位点及候选基因,本研究利用浓度200 mmol/L的NaCl溶液和正常营养液对全国300份小麦品种(系)进行耐盐性试验,并利用小麦90 K芯片对分布于小麦全基因组的16650个SNP,采用Q+K关联混合模型对小麦最长根长、根干重、根鲜重、根平均直径、根尖...     

Genome-Wide Association Mapping of Root Traits in a Japonica Rice Panel

Rice is a crop prone to drought stress in upland and rainfed lowland ecosystems. A deep root system is recognized as the best drought avoidance mechanism. Genome-wide association mapping offers higher resolution for locating quantitative trait loci (QTLs) than QTL mapping in biparental populations. We performed an association mapping study for root traits using a panel of 167 japonica accessions, mostly of tropical origin. The panel was genotyped at an average density of one marker per 22.5 kb using genotyping by sequencing technology. The linkage disequilibrium in the panel was high (r²>0.6, on average, for 20 kb mean distances between markers). The plants were grown in transparent 50 cm × 20 cm × 2 cm Plexiglas nailboard sandwiches filled with 1.5 mm glass beads through which a nutrient solution was circulated. Root system architecture and biomass traits were measured in 30-day-old plants. The panel showed a moderate to high diversity in the various traits, particularly for deep (below 30 cm depth) root mass and the number of deep roots. Association analyses were conducted using a mixed model involving both population structure and kinship to control for false positives. Nineteen associations were significant at P<1e-05, and 78 were significant at P<1e-04. The greatest numbers of significant associations were detected for deep root mass and the number of deep roots, whereas no significant associations were found for total root biomass or deep root proportion. Because several QTLs for different traits were co-localized, 51 unique loci were detected; several co-localized with meta-QTLs for root traits, but none co-localized with rice genes known to be involved in root growth. Several likely candidate genes were found in close proximity to these loci. Additional work is necessary to assess whether these markers are relevant in other backgrounds and whether the genes identified are robust candidates.     

Impact of Measurement Error on Testing Genetic Association with Quantitative Traits

Measurement error of a phenotypic trait reduces the power to detect genetic associations. We examined the impact of sample size, allele frequency and effect size in presence of measurement error for quantitative traits. The statistical power to detect genetic association with phenotype mean and variability was investigated analytically. The non-centrality parameter for a non-central F distribution was derived and verified using computer simulations. We obtained equivalent formulas for the cost of phenotype measurement error. Effects of differences in measurements were examined in a genome-wide association study (GWAS) of two grading scales for cataract and a replication study of genetic variants influencing blood pressure. The mean absolute difference between the analytic power and simulation power for comparison of phenotypic means and variances was less than 0.005, and the absolute difference did not exceed 0.02. To maintain the same power, a one standard deviation (SD) in measurement error of a standard normal distributed trait required a one-fold increase in sample size for comparison of means, and a three-fold increase in sample size for comparison of variances. GWAS results revealed almost no overlap in the significant SNPs (p<10⁻⁵) for the two cataract grading scales while replication results in genetic variants of blood pressure displayed no significant differences between averaged blood pressure measurements and single blood pressure measurements. We have developed a framework for researchers to quantify power in the presence of measurement error, which will be applicable to studies of phenotypes in which the measurement is highly variable.     

Association between Personality Traits and Sleep Quality in Young Korean Women

Personality is a trait that affects behavior and lifestyle, and sleep quality is an important component of a healthy life. We analyzed the association between personality traits and sleep quality in a cross-section of 1,406 young women (from 18 to 40 years of age) who were not reporting clinically meaningful depression symptoms. Surveys were carried out from December 2011 to February 2012, using the Revised NEO Personality Inventory and the Pittsburgh Sleep Quality Index (PSQI). All analyses were adjusted for demographic and behavioral variables. We considered beta weights, structure coefficients, unique effects, and common effects when evaluating the importance of sleep quality predictors in multiple linear regression models. Neuroticism was the most important contributor to PSQI global scores in the multiple regression models. By contrast, despite being strongly correlated with sleep quality, conscientiousness had a near-zero beta weight in linear regression models, because most variance was shared with other personality traits. However, conscientiousness was the most noteworthy predictor of poor sleep quality status (PSQI≥6) in logistic regression models and individuals high in conscientiousness were least likely to have poor sleep quality, which is consistent with an OR of 0.813, with conscientiousness being protective against poor sleep quality. Personality may be a factor in poor sleep quality and should be considered in sleep interventions targeting young women.