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PubMed2004

Conditional probability methods for haplotyping in pedigrees.

Efficient haplotyping in pedigrees is important for the fine mapping of quantitative trait locus (QTL) or complex disease genes. To reconstruct haplotypes efficiently for a large pedigree with a large number of linked loci, two algorithms based on conditional probabilities and likelihood computations are presented. The first algorithm (the conditional probability method) produces a single, approximately optimal haplotype configuration, with computing time increasing linearly in the number of linked loci and the pedigree size. The other algorithm (the conditional enumeration method) identifies a set of haplotype configurations with high probabilities conditional on the observed genotype data for a pedigree. Its computing time increases less than exponentially with the size of a subset of the set of person-loci with unordered genotypes and linearly with its complement. The size of the subset is controlled by a threshold parameter. The set of identified haplotype configurations can be used to estimate the identity-by-descent (IBD) matrix at a map position for a pedigree. The algorithms have been tested on published and simulated data sets. The new haplotyping methods are much faster and provide more information than several existing stochastic and rule-based methods. The accuracies of the new methods are equivalent to or better than those of these existing methods.

Animals↗
PubMed2026

Exploring genomic regions regulating the liver transcriptome and energy homeostasis in pigs.

In pigs, energy homeostasis has an impact on meat quality and health. In a Duroc pig population, 30 quantitative trait locus (QTL) regions associated with fatty acid (FA) composition in adipose tissue, plasma, liver and muscle were previously identified. Mapping of expression quantitative trait locus (eQTL) regions will provide a molecular hypothesis for genotype-phenotype interactions and may allow the identification of shared causal variants, key to increasing our understanding of the genetic regulation of FA composition and energy homeostasis. However, gene expression is impacted by environmental factors, while individual-level allelic imbalance (AI) can be more reliable and can be surveyed via allelic-specific expression (ASE) analysis. Furthermore, treatment of ASE as a quantitative trait allows the identification of allele-specific expression quantitative trait loci (aseQTLs), which are variants whose heterozygosity is linked to the AI of a nearby single-nucleotide polymorphism (SNP), pointing to regulatory elements. In this study, liver was selected as a key metabolic hub with an important role in the regulation of energy homeostasis, and 310 liver RNA sequencing samples were analysed using a combination of (1) eQTL mapping, (2) ASE analysis, and (3) aseQTL mapping methods. A total of 2 188 eQTL regions were identified, mostly cis-eQTL regions (73.17%). ASE analysis reported 1 964 ASE SNPs, associated with 633 genes. Finally, aseQTL mapping reported 64 172 aseQTL, associated with the AI of 31 genes. Colocalisation analysis combined with ASE analysis showed that the expression of FADS1 and FADS2 genes is associated with the polyunsaturated FA composition in several tissues, where microRNA regulation may be present. Finally, in the DGAT2 gene, annotated in a QTL region associated with multiple FAs in adipose tissue, ASE revealed allelic imbalance in the 3' untranslated region (UTR) of this gene. Allelic differential expression can be caused by a 13-bp insertion affecting messenger RNA stability, previously described, exemplifying how allelic imbalance is caused by a post-transcriptional regulatory mechanism undetectable by eQTL mapping. Furthermore, aseQTLs were associated with this gene, linked to a previously identified copy number variant not yet associated with DGAT2 expression. These results demonstrate how ASE analysis and aseQTL mapping can complement eQTL mapping, as they resolved a complex region affected by allelic heterogeneity, a main confounding effect of QTL mapping. In conclusion, the combination of eQTL mapping, ASE analysis and aseQTL mapping allowed the characterisation of the regulation of liver gene expression, improving our understanding of the genetic determinism of energy homeostasis.

Allele-specific expression↗
PubMed1994

Localization of genes affecting alcohol drinking in mice.

The genomic map locations of specific genes controlling behaviors can be identified by studying a panel of recombinant inbred (RI) mouse strains. The progenitor C57BL/6J (B6) and DBA/2J (D2) strains, and 19 of the BXD RI strains derived from an F2 cross of these progenitors, were tested for 3% and 10% ethanol (EtOH) intake. The test sequence began with two-bottle free choice between tap water and unsweetened ethanol, and ended with free choice between water and saccharin-sweetened ethanol. Saccharin preference was also measured. Correlational analyses indicated that 59% of the genetic variance in 10% ethanol and sweetened 10% ethanol consumption was held in common, 24% of the genetic variance in saccharin and sweetened 10% ethanol consumption was held in common, and only 7% of the genetic variance in saccharin and unsweetened 10% ethanol consumption was held in common. These percentages for 3% ethanol solutions were 21%, 36%, and 14%. In addition, the severity of handling-induced convulsions during ethanol withdrawal was found to be significantly associated with the amount of ethanol consumed from the sweetened ethanol drinking tubes, suggesting that genetic differences in avidity for ethanol could lead to the development of physical dependence. Quantitative trait loci (QTL) analyses revealed that several genetic markers were associated with ethanol consumption levels, including markers for the D2 dopamine receptor. QTL analyses of saccharin and sweetened ethanol consumption identified the sac locus, thought to determine the ability to detect saccharin. In general, our results suggest that saccharin and ethanol consumption are determined by the actions of multiple genes (QTL), some in common, and suggest specific map locations of several such QTL on the mouse genome.

Alcohol Drinking↗
PubMed2006

The genetic control of milling yield, dough rheology and baking quality of wheat.

Improving the end-use quality of wheat is a key target for many breeding programmes. With the exception of the relationship between glutenin alleles and some dough rheological characters, knowledge concerning the genetic control of wheat quality traits is somewhat limited. A doubled haploid population produced from a cross between two Australian cultivars 'Trident' and 'Molineux' has been used to construct a linkage map based largely on microsatellite molecular makers. 'Molineux' is superior to 'Trident' for a number of milling, dough rheology and baking quality characteristics, although by international standards 'Trident' would still be regarded as possessing moderately good end-use quality. This population was therefore deemed useful for investigation of wheat end-use quality. A number of significant QTL identified for dough rheological traits mapped to HMW and LMW glutenin loci on chromosomes 1A and 1B. However, QTL associated with dough strength and loaf volume were also identified on chromosome 2A and a significant QTL associated with loaf volume and crumb quality was identified on chromosome 3A. A QTL for flour protein content and milling yield was identified on chromosome 6A and a QTL associated with flour colour reported previously on chromosome 7B was confirmed in this population. The detection of loci affecting dough strength, loaf volume and flour protein content may provide fresh opportunities for the application of marker-assisted selection to improve bread-making quality.

Alleles↗
PubMed2005

High-resolution association mapping of quantitative trait loci: a population-based approach.

In this article, population-based regression models are proposed for high-resolution linkage disequilibrium mapping of quantitative trait loci (QTL). Two regression models, the "genotype effect model" and the "additive effect model," are proposed to model the association between the markers and the trait locus. The marker can be either diallelic or multiallelic. If only one marker is used, the method is similar to a classical setting by Nielsen and Weir, and the additive effect model is equivalent to the haplotype trend regression (HTR) method by Zaykin et al. If two/multiple marker data with phase ambiguity are used in the analysis, the proposed models can be used to analyze the data directly. By analytical formulas, we show that the genotype effect model can be used to model the additive and dominance effects simultaneously; the additive effect model takes care of the additive effect only. On the basis of the two models, F-test statistics are proposed to test association between the QTL and markers. By a simulation study, we show that the two models have reasonable type I error rates for a data set of moderate sample size. The noncentrality parameter approximations of F-test statistics are derived to make power calculation and comparison. By a simulation study, it is found that the noncentrality parameter approximations of F-test statistics work very well. Using the noncentrality parameter approximations, we compare the power of the two models with that of the HTR. In addition, a simulation study is performed to make a comparison on the basis of the haplotype frequencies of 10 SNPs of angiotensin-1 converting enzyme (ACE) genes.

Alleles↗
PubMed2006

Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.).

Development of high-yielding wheat varieties with good end-use quality has always been a major concern for wheat breeders. To genetically dissect quantitative trait loci (QTLs) for yield-related traits such as grain yield, plant height, maturity, lodging, test weight and thousand-grain weight, and for quality traits such as grain and flour protein content, gluten strength as evaluated by mixograph and SDS sedimentation volume, an F1-derived doubled haploid (DH) population of 185 individuals was developed from a cross between a Canadian wheat variety "AC Karma" and a breeding line 87E03-S2B1. A genetic map was constructed based on 167 marker loci, consisting of 160 microsatellite loci, three HMW glutenin subunit loci: Glu-A1, Glu-B1 and Glu-D1, and four STS-PCR markers. Data for investigated traits were collected from three to four environments in Manitoba, Canada. QTL analyses were performed using composite interval mapping. A total of 50 QTLs were detected, 24 for agronomic traits and 26 for quality-related traits. Many QTLs for correlated traits were mapped in the same genomic regions forming QTL clusters. The largest QTL clusters, consisting of up to nine QTLs, were found on chromosomes 1D and 4D. HMW glutenin subunits at Glu-1 loci had the largest effect on breadmaking quality; however, other genomic regions also contributed genetically to breadmaking quality. QTLs detected in the present study are compared with other QTL analyses in wheat.

Analysis of Variance↗
PubMed2006

Prediction of IBD based on population history for fine gene mapping.

A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDL probabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDL are used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM.

Alleles↗
PubMedDate not supplied

An efficient variance component approach implementing an average information REML suitable for combined LD and linkage mapping with a general complex pedigree.

Variance component (VC) approaches based on restricted maximum likelihood (REML) have been used as an attractive method for positioning of quantitative trait loci (QTL). Linkage disequilibrium (LD) information can be easily implemented in the covariance structure among QTL effects (e.g. genotype relationship matrix) and mapping resolution appears to be high. Because of the use of LD information, the covariance structure becomes much richer and denser compared to the use of linkage information alone. This makes an average information (AI) REML algorithm based on mixed model equations and sparse matrix techniques less useful. In addition, (near-) singularity problems often occur with high marker densities, which is common in fine-mapping, causing numerical problems in AIREML based on mixed model equations. The present study investigates the direct use of the variance covariance matrix of all observations in AIREML for LD mapping with a general complex pedigree. The method presented is more efficient than the usual approach based on mixed model equations and robust to numerical problems caused by near-singularity due to closely linked markers. It is also feasible to fit multiple QTL simultaneously in the proposed method whereas this would drastically increase computing time when using mixed model equation-based methods.

Algorithms↗
PubMed2002

A penalized likelihood method for mapping epistatic quantitative trait Loci with one-dimensional genome searches.

Epistasis is a common and important phenomenon, as indicated by results from a number of recent experiments. Unfortunately, the discovery of epistatic quantitative trait loci (QTL) is difficult since one must search for multiple QTL simultaneously in two or more dimensions. Such a multidimensional search necessitates many statistical tests, and a high statistical threshold must be adopted to avoid false positives. Furthermore, the large number of (interaction) parameters in comparison with the number of observations results in a serious danger of overfitting and overinterpretation of the data. In this article we present a new statistical framework for mapping epistasis in inbred line crosses. It is based on reducing the high dimensionality of the problem in two ways. First, epistatic QTL are mapped in a one-dimensional genome scan for high interactions between QTL and the genetic background. Second, the dimension of the search is bounded by penalized likelihood methods. We use simulated backcross data to illustrate the new approach.

Chromosome Mapping↗
PubMed1999

Mapping of post-flowering drought resistance traits in grain sorghum: association between QTLs influencing premature senescence and maturity.

The identification of genetic factors underlying the complex responses of plants to drought stress provides a solid basis for improving drought resistance. The staygreen character in sorghum (Sorghum bicolor L. Moench) is a post-flowering drought resistance trait, which makes plants resistant to premature senescence under drought stress during the grainfilling stage. The objective of this study was to identify quantitative trait loci (QTLs) that control premature senescence and maturity traits, and to investigate their association under post-flowering drought stress in grain sorghum. A genetic linkage map was developed using a set of recombinant inbred lines (RILs) obtained from the cross B35 x Tx430, which were scored for 142 restriction fragment length polymorphism (RFLP) markers. The RILs and their parental lines were evaluated for post-flowering drought resistance and maturity in four environments. Simple interval mapping identified seven stay-green QTLs and two maturity QTLs. Three major stay-green QTLs (SGA, SGD and SGG) contributed to 42% of the phenotypic variability (LOD 9.0) and four minor QTLs (SGB, SGI. 1, SGI.2, and SGJ) significantly contributed to an additional 25% of the phenotypic variability in stay-green ratings. One maturity QTL (DFB) alone contributed to 40% of the phenotypic variability (LOD 10.0), while the second QTL (DFG) significantly contributed to an additional 17% of the phenotypic variability (LOD 4.9). Composite interval mapping confirmed the above results with an additional analysis of the QTL x Environment interaction. With heritability estimates of 0.72 for stay-green and 0.90 for maturity, the identified QTLs explained about 90% and 63% of genetic variability for stay-green and maturity traits, respectively. Although stay-green ratings were significantly correlated (r = 0.22, P< or =0.05) with maturity, six of the seven stay-green QTLs were independent of the QTLs influencing maturity. Similarly, one maturity QTL (DFB) was independent of the staygreen QTLs. One stay-green QTL (SGG), however, mapped in the vicinity of a maturity QTL (DFG), and all markers in the vicinity of the independent maturity QTL (DFB) were significantly (P< or =0.1) correlated with stay-green ratings, confounding the phenotyping of stay-green. The molecular genetic analysis of the QTLs influencing stay-green and maturity, together with the association between these two inversely related traits, provides a basis for further study of the underlying physiological mechanisms and demonstrates the possibility of improving drought resistance in plants by pyramiding the favorable QTLs.

Agriculture↗
PubMed2002

Interacting quantitative trait loci control loss of peripheral tolerance and susceptibility to autoimmune ovarian dysgenesis after day 3 thymectomy in mice.

Day 3 thymectomy (D3Tx) results in a loss of peripheral tolerance mediated by CD4(+)CD25(+) T cells and the development of autoimmune ovarian dysgenesis (AOD) in A/J and (C57BL/6J x A/J)F(1) (B6AF(1)) hybrids but not in C57BL/6J mice. Quantitative trait loci (QTL) linkage analysis using a B6AF(1) x C57BL/6J backcross population verified Aod1 and Aod2 that were previously mapped as qualitative traits. Additionally, three new QTL intervals, Aod3, Aod4, and Aod5, on chromosomes 1, 2, and 7, respectively, influencing specific subphenotypes of AOD were identified. QTL linkage analysis using the A x B and B x A recombinant inbred lines verified Aod3 and confirmed linkage to H2. Aod5 colocalized with Mater, an ovarian-specific autoantigen recognized by anti-ovarian autoantibodies in the sera of D3Tx mice. Sequence analysis of Mater identified allelic, strain-specific splice variants between A/J and C57BL/6J mice making it an attractive candidate gene for Aod5. Interaction analysis revealed significant epistatic effects between Aod1-5 and Gasa2, a locus associated with susceptibility to D3Tx-induced autoimmune gastritis, as well as with H2. These results indicate that the QTL controlling D3Tx-induced autoimmune phenomenon are both organ specific and more generalized in their effects with respect to the genesis and activity of the immunoregulatory mechanisms maintaining peripheral tolerance.

Amino Acid Sequence↗
PubMed2004

Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome.

Genetic architecture of flowering time in maize was addressed by synthesizing a total of 313 quantitative trait loci (QTL) available for this trait. These were analyzed first with an overview statistic that highlighted regions of key importance and then with a meta-analysis method that yielded a synthetic genetic model with 62 consensus QTL. Six of these displayed a major effect. Meta-analysis led in this case to a twofold increase in the precision in QTL position estimation, when compared to the most precise initial QTL position within the corresponding region. The 62 consensus QTL were compared first to the positions of the few flowering-time candidate genes that have been mapped in maize. We then projected rice candidate genes onto the maize genome using a synteny conservation approach based on comparative mapping between the maize genetic map and japonica rice physical map. This yielded 19 associations between maize QTL and genes involved in flowering time in rice and in Arabidopsis. Results suggest that the combination of meta-analysis within a species of interest and synteny-based projections from a related model plant can be an efficient strategy for identifying new candidate genes for trait variation.

Chromosome Mapping↗
PubMed2004

QTL analysis of fertility restoration in cytoplasmic male sterile pepper.

Fertility restoration of Peterson's cytoplasmic male-sterility in pepper (Capsicum annuum L.) is quantitative and environment-dependent. QTL analysis of fertility restoration was performed based on the test-cross progeny of 77013A (a strict cytoplasmic-genetic male sterile line) and a doubled haploid population of 114 lines obtained from an F1 hybrid between Yolo wonder (a sterility maintainer line) and Perennial (a fertility-restorer line). The fertility of the test-crossed lines was assessed under greenhouse and open field conditions using three criteria related to pollen or seed production. One major QTL for fertility restoration was mapped to chromosome P6. It was significant in all the environments and for all the traits, accounting for 20-69% of the phenotypic variation, depending on the trait. Four additional minor QTLs were also detected on chromosomes P5, P2, and linkage groups PY3 and PY1, accounting for 7-17% of the phenotypic variation. Most of the alleles increasing fertility originated from the restorer parent, except for two alleles at minor QTLs. Phenotypic analysis and genetic dissection indicated that breeding pepper for complete sterility of female lines and high hybrid fertility requires complex combinations of alleles from both parents and a strict control of the environment.

Breeding↗
PubMed2025

Genetic basis and role of exotic accessions in cultivated cotton fiber quality improvement.

Exotic Gossypium accessions still harbor QTL&#x2011;validated alleles that, combined with CRISPR pyramiding and genomic selection, can break the entrenched fiber length-strength trade&#x2011;off. Cotton's four independent domestications twice in diploids and twice in allotetraploids offer a natural experiment in fiber improvement. Synthesizing three decades of data, we chart how polyploidy, selection and modern breeding have repeatedly reshaped the Gossypium genome. More than 15,000 quantitative trait locus (QTL) and genome wide association mapping studies (GWAS) hits converge on a handful of chromosomal "hotspots"; new MAGIC, NAM, NIL and long-read resources now narrow these peaks to&#x2009;<&#x2009;200&#xa0;kb, resolving causal genes such as GhHOX3, GhZF14 and GhMYB7. Multi-omics evidence links auxin, ethylene, gibberellin, brassinosteroid and strigolactone signaling to HDZIP IV, MYB, bHLH/HLH and ERF networks that drive fiber initiation, extreme cell elongation and cellulose deposition. Population genomics shows that&#x2009;~&#x2009;40% of favorable fiber alleles are fixed in elite Gossypium hirsutum, yet wild diploids and landraces still harbor variants that could break the length strength trade-off. We propose a three-step roadmap genomic selection, CRISPR gene pyramiding and accelerated introgression to expand cotton's genetic base and deliver fibers suited to sustainable textile demands.

Gossypium↗
PubMed2006

Shrinkage estimation method for mapping multiple quantitative trait loci.

In this article, shrinkage estimation method for multiple-marker analysis and for mapping multiple quantitative trait loci (QTL) was reviewed. For multiple-marker analysis, Xu (Genetics, 2003, 163:789-801) developed a Bayesian shrinkage estimation (BSE) method. The key to the success of this method is to allow each marker effect have its own variance parameter, which in turn has its own prior distribution so that the variance can be estimated from the data. Under this hierarchical model, a large number of markers can be handled although most of them may have negligible effects. Under epistatic genetic model, however, the running time is very long. To overcome this problem, a novel method of incorporating the idea described above into maximum likelihood, known as penalized likelihood method, was proposed. A simulated study showed that this method can handle a model with multiple effects, which are ten times larger than the sample size. For multiple QTL analysis, two modified versions for the BSE method were introduced: one is the fixed-interval method and another is the variable-interval method. The former deals with markers with intermediate density, and the latter can handle markers with extremely high density as well as model with epistatic effects. For the detection of epistatic effects, penalized likelihood method and the variable-interval approach of the BSE method are available.

Bayes Theorem↗
PubMed2001

A microsatellite polymorphism in the gamma interferon gene is associated with resistance to gastrointestinal nematodes in a naturally-parasitized population of Soay sheep.

Free-living Soay sheep (Ovis aries) on the island of Hirta, St Kilda, Scotland, are naturally parasitized by gastrointestinal nematodes, predominantly Teladorsagia circumcincta. In this paper we show that reduced faecal egg counts (FEC) are associated with an allele at a microsatellite locus located in the first intron of the interferon gamma gene (o(IFN)-gamma) in Soay sheep lambs and yearlings, measured at approximately 4 and 16 months of age, respectively. The same allele was also associated with increased T. circumcincta-specific antibody (IgA) in lambs, but not associated significantly in yearlings. Flanking control markers failed to show a significant association with either FEC or IgA. These results suggest that a polymorphic gene conferring increased resistance to gastrointestinal nematode parasites is located at or near the interferon gamma gene, and support previous reports which have mapped a quantitative trait locus (QTL) for resistance to this region in domestic sheep. Our data are consistent with the idea that a functional polymorphism leading to reduced expression or efficacy of (IFN)-gamma could enhance the immune response to gastrointestinal nematodes by favouring the activity of the Th2 cell subset and antibody associated immune mechanisms.

Animals↗
PubMed2026

Genetic diversity of Collaborative Cross mice implicates FFAR3 as a target for ILC2 anti-inflammatory reprogramming.

Pulmonary group 2 innate lymphoid cells (ILC2s) are key drivers of Type 2 inflammation in diseases like asthma, yet the molecular mechanisms regulating their function are incompletely understood. Using the genetically diverse Collaborative Cross (CC) mouse panel, we mapped a quantitative trait locus (QTL) that governs ILC2 prevalence in the lung after aeroallergen exposure. This QTL induces a large population of ILC2s in the lung that are resistant to activation and have diminished Type 2 effector function. We identified free-fatty acid receptor 3 (Ffar3) as a gene responsible for this effect and demonstrated that FFAR3 signaling reprograms ILC2s to an anti-inflammatory state by promoting their survival, reducing Type 2 cytokine production, and enhancing IL-10 expression. This anti-inflammatory state is dependent on IL-2 signaling, is characterized by decreased ST2 expression, and is distinct from previously described IL-10-producing ILC2 phenotypes. FFAR3-dependent reprogramming is mediated by epidermal growth factor receptor (EGFR) upregulation, and FFAR3's anti-inflammatory effect is partially conserved in human ILC2s.

Animals↗
PubMed2005

Pedigree linkage disequilibrium mapping of quantitative trait loci.

In this paper, we propose to use pedigrees of any size and any types of relatives in joint high-resolution linkage disequilibrium (LD) and linkage mapping of quantitative trait loci (QTL) by variance component models. Two or multiple markers can be simultaneously used in modeling association with the trait locus, instead of using one marker a time in the analysis. The proposed method can provide a unified result by using two or multiple markers in the modeling. This may avoid the complications of different results obtained from the separate analysis of marker by marker. The models simultaneously incorporate both linkage and LD information. The measures of LD are modeled by mean coefficients, and linkage information is modeled by variance-covariance matrix. Using analytical formulas to calculate the regression coefficients, the genetic effects are shown to be decomposed into additive and dominance components. The noncentrality parameter approximations of test statistics of LD are provided to make power calculations. Power and type I error rates are explored to investigate the merit of the proposed method by both the analytical formulas and simulations. Comparing with the association between-family and association within-family ('AbAw') approach of Fulker and Abecasis et al, it is evident that the method proposed in this article is more powerful. The method is applied to investigate the relation between polymorphisms in the angiotensin 1-converting enzyme (ACE) genes and circulating ACE levels, with a better result than that of the 'AbAw' approach. Moreover, two markers I/D and 4656(CT)3/2 can fully interpret association with the trait locus at a 0.01 significance level, which provides a unique result for the ACE data.

Animals↗