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PubMed2005

The canine genome.

The dog has emerged as a premier species for the study of morphology, behavior, and disease. The recent availability of a high-quality draft sequence lifts the dog system to a new threshold. We provide a primer to use the dog genome by first focusing on its evolutionary history. We overview the relationship of dogs to wild canids and discuss their origin and domestication. Dogs clearly originated from a substantial number of gray wolves and dog breeds define distinct genetic units that can be divided into at least four hierarchical groupings. We review evidence showing that dogs have high levels of linkage disequilibrium. Consequently, given that dog breeds express specific phenotypic traits and vary in behavior and the incidence of genetic disease, genomic-wide scans for linkage disequilibrium may allow the discovery of genes influencing breed-specific characteristics. Finally, we review studies that have utilized the dog to understand the genetic underpinning of several traits, and we summarize genomic resources that can be used to advance such studies. We suggest that given these resources and the unique characteristics of breeds, that the dog is a uniquely valuable resource for studying the genetic basis of complex traits.

Animals↗

PubMed2026

Spectral Transforms as a Tool to Optimize Digital Phenotyping in Biological Images.

Modern livestock breeding has mastered genotyping. Genome-wide association studies, genomic selection, and SNP arrays enable genetic merit prediction at lower cost. However, phenotyping remains the bottleneck, as manual measurement is slow, expensive, subjective, and unable to capture spatial or temporal trait organization. Digital phenotyping via artificial intelligence could resolve this, but deep learning requires thousands of labelled examples, impractical when phenotyping cost itself limits datasets to hundreds of individuals. This creates a paradox: AI could accelerate phenotyping but requires large numbers of samples to train the models. Here, we demonstrate that integrating computer vision with machine learning offers sample-efficient digital phenotyping using eggshell colour as a model system. Rather than learning features from scratch (deep learning), we engineer physically motivated features via Wavelet transforms that decompose images into multi-scale spatial components. Wavelet features captured 14.2 percentage points more variance (R2 = 0.976 vs. 0.834, p < 0.001) than standard colorimetry, with 50% better sample efficiency (achieving at n = 60 what colorimetry required n = 120). Variance decomposition revealed 77% of discriminative capacity derives from spatial patterns (bands, spots, gradients) invisible to scalar averages. Additionally, we identified "cryptic phenotypes" (3.3%) where spatial patterns contradicted average colour, cases where colorimeters failed but Wavelets succeeded. The underlying principle-that spatial decomposition can recover organizational information lost by scalar averaging-may be applicable to other traits with spatial or temporal structure, such as marbling, dermatitis, or pigmentation rhythms, although whether comparable performance gains would be observed remains to be tested empirically. Hence, for breeding programs implementing genomic selection, computer vision-based digital phenotyping captures complex trait variation without massive training datasets, addressing the bottleneck that increasingly limits genetic progress as genotyping becomes trivial.

Wavelet transform↗

PubMed2001

The genetic architecture of quantitative traits.

Phenotypic variation for quantitative traits results from the segregation of alleles at multiple quantitative trait loci (QTL) with effects that are sensitive to the genetic, sexual, and external environments. Major challenges for biology in the post-genome era are to map the molecular polymorphisms responsible for variation in medically, agriculturally, and evolutionarily important complex traits; and to determine their gene frequencies and their homozygous, heterozygous, epistatic, and pleiotropic effects in multiple environments. The ease with which QTL can be mapped to genomic intervals bounded by molecular markers belies the difficulty in matching the QTL to a genetic locus. The latter requires high-resolution recombination or linkage disequilibrium mapping to nominate putative candidate genes, followed by genetic and/or functional complementation and gene expression analyses. Complete genome sequences and improved technologies for polymorphism detection will greatly advance the genetic dissection of quantitative traits in model organisms, which will open avenues for exploration of homologous QTL in related taxa.

Animals↗

PubMed1996

Genetic regulation of cholesterol homeostasis: chromosomal organization of candidate genes.

As part of an effort to dissect the genetic factors involved in cholesterol homeostasis in the mouse model, we report the mapping of 12 new candidate genes using linkage analysis. The genes include: cytoplasmic HMG-CoA synthase (Hmgcs 1, Chr 13), mitochondrial synthase (Hmgcs 2, Chr 3), a synthase-related sequence (Hmgcs 1-rs, Chr 12), mevalonate kinase (Mvk, Chr 5), farnesyl diphosphate synthase (Fdps, Chr 3), squalene synthase (Fdft 1, Chr 14), acyl-CoA:cholesterol acyltransferase (Acact, Chr 1), sterol regulatory element binding protein-1 (Srebf1, Chr 8) and -2 (Srebf2, Chr 15), apolipoprotein A-I regulatory protein (Tcfcoup2, Chr 7), low density receptor-related protein-related sequence (Lrp-rs, Chr 10), and Lrp-associated protein (Lrpap 1, Chr 5). In addition, the map positions for several lipoprotein receptor genes were refined. These genes include: low density lipoprotein receptor (Ldlr, Chr 9), very low density lipoprotein receptor (Vldlr, Chr 19), and glycoprotein 330 (Gp330, Chr 2). Some of these candidate genes are located within previously defined chromosomal regions (quantitative trait loci, QTLs) contributing to plasma lipoprotein levels, and Acact maps near a mouse mutation, ald, resulting in depletion of cholesteryl esters in the adrenals. The combined use of QTL and candidate gene mapping provides a powerful means of dissecting complex traits such as cholesterol homeostasis.

Animals↗

PubMed1996

[Epidemiologic and molecular genetic of suicidal behavior].

The current understanding of suicidal behaviors is that such behaviors are multidetermined and mental state and trait related. Genetic factors appear to be of great importance, as suggested by the findings of family, twin, and adoption studies. Whether these genetic factors are similar to those involved in the susceptibility to psychiatric disorders closely related to suicidal behavior (eg, manic depressive illness, schizophrenia or substance use disorders) is yet unknown. However, a genetic factor of susceptibility to suicide, independent or additive to the genetic transmission of the psychiatric disorders that are related to suicidal behavior, is strongly suggested by the data of the Copenhagen adoption study and a study of Amish families. Recently, new approaches have been proposed to identify the genetic component of such complex traits. Association studies between genetic markers and a disease phenotype has been successfully applied to several complex disease such as essential hypertension. One candidate gene for suicidal behaviors is the tryptophane hydroxylase (TPH) gene which is the first and possibly rate-limiting enzyme of the metabolic pathway for serotonin. Indeed, altered serotoninergic function in both completed suicide and suicide attempt has been one of the most replicated findings in modern biological psychiatry. In our knowledge, only two studies have tested the association between suicide attempt and the TPH gene and their authors found negative results. Despite these negative results, association studies that use candidate gene remain one of the methods of choice for studying the genetic component of suicidal behaviors.

Depressive Disorder↗

PubMed1997

Modeling the phenotype in parametric linkage analysis of bipolar disorder.

The definition of phenotype is a major problem in genetic studies of psychiatric disorders. Most linkage studies in bipolar disorder have defined the phenotype as a dichotomous trait and have usually employed different hierarchical classifications in order to overcome uncertainty resulting from phenotypic variability. In this study we explored the advantages of maximizing the evidence for linkage over different phenotypic definitions when conducting parametric linkage analysis of a complex trait. The GAW10 Problem 1 was used, focusing on chromosome 18 data sets. Three major phenotypic models were analyzed: quasi-quantitative, liability-based and affection-status models. Overall, no single phenotypic model performed consistently better than the others (i.e., lod scores greater than 1.0). Each model yielded higher lod scores than the others in particular instances, suggesting that it might be useful in exploratory data analysis, where the phenotype is variable, to maximize evidence for linkage over different phenotypic models.

Bipolar Disorder↗

PubMed2004

Problems and solutions in the genetic analysis of late-onset Alzheimer's disease.

The identification of the apolipoprotein E gene as a risk factor for late-onset Alzheimer's disease was a spectacularly successful application of genetic analysis to a complex trait, and it led to the hope and expectation that other risk loci for the disease would soon be forthcoming. Twelve years later, despite a huge amount of work, no other loci have been identified. In this article, we discuss the complexity of the problem and the pitfalls in the analytical methods that have been used and how we are approaching this problem.

Age of Onset↗

PubMed2005

The self-incompatibility locus (S) and quantitative trait loci for self-pollination and seed dormancy in sunflower.

Wild populations of common sunflower (Helianthus annuus L.) are self-incompatible and have deep seed dormancy, whereas modern cultivars, inbreds, and hybrids are self-compatible and partially-to-strongly self-pollinated, and have shallow seed dormancy. Self-pollination (SP) and seed dormancy are genetically complex traits, the number of self-compatibility (S) loci has been disputed, and none of the putative S loci have been genetically mapped in sunflower. We genetically mapped quantitative trait loci (QTL) for self-incompatibility (SI), SP, and seed dormancy in a backcross population produced from a cross between an elite, self-pollinated, nondormant inbred line (NMS373) and a wild, self-incompatible, dormant population (ANN1811). A population consisting of 212 BC(1) progeny was subsequently produced by backcrossing a single hybrid individual to NMS373. BC(1) progeny produced 0-838 seeds per primary capitula when naturally selfed and 0-518 seeds per secondary capitula when manually selfed and segregated for a single S locus. The S locus mapped to linkage group 17 and was tightly linked to a cluster of previously identified QTL for several domestication and postdomestication traits. Two synergistically interacting QTL were identified for SP among self-compatible (ss) BC(1) progeny (R(2)=34.6%). NMS373 homozygotes produced 271.5 more seeds per secondary capitulum than heterozygotes. Germination percentages of seeds after-ripened for 4 weeks ranged from 0% to 100% among self-compatible BC(1)S(1) families. Three QTL for seed dormancy were identified (R(2)=38.3%). QTL effects were in the predicted direction (wild alleles decreased self-pollination and seed germination). The present analysis differentiated between loci governing SI and SP and identified DNA markers for bypassing SI and seed dormancy in elite x wild crosses through marker-assisted selection.

Chromosome Mapping↗

PubMedDate not supplied

Genetic dissection of age-related changes of immune function in mice.

Understanding of the genetic basis of normal and abnormal development of the immune response is an enormous undertaking. The immune response, at the most minimal level, involves interactions of antigen presenting cells (APCs), T and B cells. Each of these cells produce cell surface and soluble factors (cytokines) that affect both autocrine and paracrine functions. A second level of complexity needs to consider the development of the macrophage/monocyte lineage as well as the production of the common lymphoid precursor which undergoes distinct maturation steps in the thymus and periphery to form mature T cells as well as in BM (BM) and lymphoid organs to form mature B cells. A third level of complexity involves the immune response to infectious agents including viruses and also the response to tumour antigens. In addition, there are imbalances that predispose to decreased responses (immunodeficiencies) or increased responses (autoimmunity). A fourth level of complexity involves attempts to understand the differences in the immune response that occurs at a very young age, in adults, and at a very old age. This review will focus on the use of C57BL/6 J X DBA/2 J (BXD) recombinant inbred (RI) strains of mice to map genetic loci associated with the production of lymphoid precursors in the BM, development of T cells in the thymus, and T-cell responses to stimulation in the peripheral lymphoid organs in adult and in aged mice. Strategies to improve the power and precision in which complex traits such as the age-related immune response can be mapped is limited with the current set of 35 strains of BXD mice. Strategies to increase these strains by generating recombinant intercross (RIX) strains of mice are being developed to enable this large set of lines to detect quantitative trait loci (QTLs) with a much higher consistency and statistical power. More importantly, the resolution with which these QTLs can be mapped would be greatly improved and, in many cases, adequate to carry out direct identification of candidate genes. It is likely that, given the complexity of the immune system development, the number of cells involved in an immune response, and especially the changes in the immune system with ageing, mapping hundreds of genes will be required to fully understand age-related changes in the immune response. This review outlines ongoing and future strategies that will enable the mapping and identification of these genes.

Aging↗

PubMed2006

Admixture in Mexico City: implications for admixture mapping of type 2 diabetes genetic risk factors.

Admixture mapping is a recently developed method for identifying genetic risk factors involved in complex traits or diseases showing prevalence differences between major continental groups. Type 2 diabetes (T2D) is at least twice as prevalent in Native American populations as in populations of European ancestry, so admixture mapping is well suited to study the genetic basis of this complex disease. We have characterized the admixture proportions in a sample of 286 unrelated T2D patients and 275 controls from Mexico City and we discuss the implications of the results for admixture mapping studies. Admixture proportions were estimated using 69 autosomal ancestry-informative markers (AIMs). Maternal and paternal contributions were estimated from geographically informative mtDNA and Y-specific polymorphisms. The average proportions of Native American, European and, West African admixture were estimated as 65, 30, and 5%, respectively. The contributions of Native American ancestors to maternal and paternal lineages were estimated as 90 and 40%, respectively. In a logistic model with higher educational status as dependent variable, the odds ratio for higher educational status associated with an increase from 0 to 1 in European admixture proportions was 9.4 (95%, credible interval 3.8-22.6). This association of socioeconomic status with individual admixture proportion shows that genetic stratification in this population is paralleled, and possibly maintained, by socioeconomic stratification. The effective number of generations back to unadmixed ancestors was 6.7 (95% CI 5.7-8.0), from which we can estimate that genome-wide admixture mapping will require typing about 1,400 evenly distributed AIMs to localize genes underlying disease risk between populations of European and Native American ancestry. Sample sizes of about 2,000 cases will be required to detect any locus that contributes an ancestry risk ratio of at least 1.5.

Africa, Western↗

PubMed2005

Novel integrative approaches to the identification of candidate genes in hypertension.

Hypertension, diabetes, and obesity are common diseases that are genetically expressed as complex traits. The clinical expression of these diseases, which run in families but have no clear pattern of inheritance, has been attributed to the interaction between multiple genes and the environment. Identifying the underlying genes, a crucial step in understanding the molecular pathogenesis of complex diseases, has had limited success so far, stressing the need for novel strategies to move this process forward. Innovative integrative genetic-genomic approaches have been proposed recently for the identification of new high-priority candidate genes. These strategies, which combine expression profiling with genetic linkage in different ways, may represent a breakthrough in the search for the genes involved in complex diseases.

Animals↗

PubMed2006

A high-resolution map of segmental DNA copy number variation in the mouse genome.

Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome. We demonstrate that this technique can identify copy number differences associated with known polymorphic traits. The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci. Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource that will help define the genetic basis of complex traits.

Animals↗

PubMedDate not supplied

[Influence of selection forms on genetic structure of domestic animals].

Analysis of genetic structure of pure and crossbred sheep and cattle with the use of genetic-biochemical markers was carried out. Data on breed- and locus-specific genetic traits, stable in the time, were obtained. In sheep, breed-specific peculiarities of genetic structure partly related with the belonging of breeds to breed groups with fine-, semi-fine and coarse wool. The preferable influence of artificial selection at the phenotype complex traits in comparison with natural selection and animal origin on the genetic structure of crossbred sheep was revealed. However, the more profound effects of natural selection on the genetic structure of crossbred cattle were observed.

Alleles↗

PubMed2001

Quantitative trait analysis of nickel-induced acute lung injury in mice.

The genetic determinants underlying susceptibility to acute lung injury have not been identified. Recently, we found that the strain distribution pattern for mean survival time (MST) to three irritants-ozone, ultrafine Teflon, and nickel sulfate- was shared between inbred mouse strains. For ozone-induced acute lung injury, survival was found to be a complex trait controlled by at least three quantitative trait loci (QTLs), designated Aliq1, Aliq2, and Aliq3. To explore whether similar genes might be involved in survival to acute lung injury induced by nickel sulfate, we took advantage of the 2-fold difference in MSTs between the sensitive A/J and resistant C57BL/6J mice. QTL analysis of 307 backcross mice generated from these strains identified significant linkage to chromosome 6 (proposed as Aliq4) and suggestive linkage on chromosomes 1 and 12. Loci on chromosomes 9 and 16 had lod scores (log of the odds ratio, which equals the log of the "likelihood of linkage divided by the likelihood of no linkage") below significance, but contributed to the overall response. Comparing MSTs of backcross mice with similar haplotypes identified an allelic combination of four QTLs that could account for the survival time difference between the parental strains. Similar QTL intervals on chromosomes 6 and 12 were previously identified with ozone, suggesting that the interplay between different combinations of relatively few genes might be important for irritant-induced acute lung injury survival.

Administration, Inhalation↗

PubMed2026

Genome-wide variation analysis of two Salvia hispanica L. genotypes and implication for associations with metabolic and adaptive traits.

BACKGROUND: Advances in next-generation sequencing have accelerated genome-wide exploration of genetic diversity in underutilized oilseed crops. Salvia hispanica L. (chia), a high-nutrient pseudocereal rich in omega-3 fatty acids, is increasingly valued for its health benefits and commercial potential, yet it remains poorly characterized at the genomic level. Understanding the scale and nature of genomic variation is essential for improving complex traits such as oil yield, stress tolerance, and seed quality. METHODS: Two contrasting chia genotypes, Black-chia (CACH-B) and White- chia (CACH-W), were resequenced using the Bio-Resequencing Toolkit (BRT) pipeline. High-coverage sequencing, with a mapping rate exceeding 99% and an average depth of approximately 28×, facilitated the detection and annotation of single-nucleotide polymorphisms (SNPs), insertions and deletions (InDels), copy-number variations (CNVs), and structural variants (SVs). The functional classification of variant impacts enabled the identification of genes potentially linked to metabolic and adaptive traits. RESULTS: A total of 1.97 million SNPs, 401,493 InDels, 836 CNVs, and 15,288 SVs were identified across the chia genome. Notably, approximately 53% of exonic SNPs were non-synonymous (dN/dS ≈ 1.28), predominantly affecting lipid metabolism, transcriptional regulation, and stress response pathways, potentially altering key agronomic traits. In addition, CNV hotspots were concentrated in chromosomes 3 and 6, overlapping MYB, WRKY, and bZIP transcription factor loci, may potentially be involved in stress tolerance and yield. Furthermore, structural rearrangements, including inversions and duplications within the FAD2, FAD3, and CYP450 gene clusters, were potentially associated with seed pigmentation and omega-3 biosynthesis, pointing to their potential breeding relevance. Observed heterozygosity (Hₒ ≈ 0.71) and nucleotide diversity (π ≈ 7 × 10-3) indicated moderate to high allelic richness. In addition, the low FST value (0.038) indicates substantial genomic similarity between the two genotypes. CONCLUSION: This study presents the first comprehensive map integrating SNPs, CNVs, and SVs in S. hispanica L. The results reveal a structurally dynamic genome characterized by substantial sequence and structural variation, providing valuable insights into genomic diversity and potential adaptive mechanisms in chia. The coexistence of high SNP diversity and abundant structural variation underpins chia's nutritional specialization and environmental resilience. These results deliver a foundational genomic resource for marker-assisted breeding, genome-wide association studies, and the development of climate-resilient chia cultivars.

Copy-number variation, structural variation↗

PubMed2002

Genetic sources of individual differences in the cerebellum.

The highly regular anatomy of the cerebellum that results from myriad genetic, environmental, and stochastic events during pre- and postnatal development is nonetheless quantitatively very different among individuals. Understanding the sources of these individual differences represents an immense challenge to those interested in the cerebellum. Here we highlight the use of new methods to dissect individual differences to their genetic sources by reviewing quantitative trait locus mapping efforts in the mouse model system. We further suggest and illustrate how to combine these methods with other modern genetic techniques to accelerate our understanding. Finally, we embed these methods in a hypothetical line of cerebellar research to illustrate the vast potential of combining complex trait analysis with a systems neuroscience perspective.

Animals↗

PubMed1999

Induction and characterization of Ph1 wheat mutants.

The cloning of genes for complex traits in polyploid plants that possess large genomes, such as hexaploid wheat, requires an efficient strategy. We present here one such strategy focusing on the homologous pairing suppressor (Ph1) locus of wheat. This locus has been shown to affect both premeiotic and meiotic processes, possibly suggesting a complex control. The strategy combined the identification of lines carrying specific deletions using multiplex PCR screening of fast-neutron irradiated wheat populations with the approach of physically mapping the region in the rice genome equivalent to the deletion to reveal its gene content. As a result, we have located the Ph1 factor controlling the euploid-like level of homologous chromosome pairing to the region between two loci (Xrgc846 and Xpsr150A). These loci are located within 400 kb of each other in the rice genome. By sequencing this region of the rice genome, it should now be possible to define the nature of this factor.

Base Sequence↗

PubMed2004

Quantitative trait locus analysis of growth-related traits in a new Arabidopsis recombinant inbred population.

Arabidopsis natural variation was used to analyze the genetics of plant growth rate. Screening of 22 accessions revealed a large variation for seed weight, plant dry weight and relative growth rate but not for water content. A positive correlation was observed between seed weight and plant area 10 d after planting, suggesting that seed weight affects plant growth during early phases of development. During later stages of plant growth this correlation was not significant, indicating that other factors determine growth rate during this phase. Quantitative trait locus (QTL) analysis, using 114 (F9 generation) recombinant inbred lines derived from the cross between Landsberg erecta (Ler, from Poland) and Shakdara (Sha, from Tadjikistan), revealed QTLs for seed weight, plant area, dry weight, relative growth rate, chlorophyll fluorescence, flowering time, and flowering-related traits. Growth traits (plant area, dry weight, and relative growth rate) colocated at five genomic regions. At the bottom of chromosome 5, colocation was found of QTLs for leaf area, leaf initiation speed, specific leaf area, and chlorophyll fluorescence but not for dry weight, indicating that this locus might be involved in leaf development. No consistent relation between growth traits and flowering time was observed despite some colocations. Some of the QTLs detected for flowering time overlapped with loci detected in other recombinant inbred line populations, but also new loci were identified. This study shows that Arabidopsis can successfully be used to study the genetic basis of complex traits like plant growth rate.

Arabidopsis↗