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G3 (Bethesda, Md.) Apr 2021Quantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of...
Quantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of biological studies. The QTL hotspots are important and attractive since they are highly informative and may harbor genes for the quantitative traits. So far, the current statistical methods for QTL hotspot detection use either the individual-level data from the genetical genomics experiments or the summarized data from public QTL databases to proceed with the detection analysis. These methods may suffer from the problems of ignoring the correlation structure among traits, neglecting the magnitude of LOD scores for the QTL, or paying a very high computational cost, which often lead to the detection of excessive spurious hotspots, failure to discover biologically interesting hotspots composed of a small-to-moderate number of QTL with strong LOD scores, and computational intractability, respectively, during the detection process. In this article, we describe a statistical framework that can handle both types of data as well as address all the problems at a time for QTL hotspot detection. Our statistical framework directly operates on the QTL matrix and hence has a very cheap computational cost and is deployed to take advantage of the QTL mapping results for assisting the detection analysis. Two special devices, trait grouping and top γn,α profile, are introduced into the framework. The trait grouping attempts to group the traits controlled by closely linked or pleiotropic QTL together into the same trait groups and randomly allocates these QTL together across the genomic positions separately by trait group to account for the correlation structure among traits, so as to have the ability to obtain much stricter thresholds and dismiss spurious hotspots. The top γn,α profile is designed to outline the LOD-score pattern of QTL in a hotspot across the different hotspot architectures, so that it can serve to identify and characterize the types of QTL hotspots with varying sizes and LOD-score distributions. Real examples, numerical analysis, and simulation study are performed to validate our statistical framework, investigate the detection properties, and also compare with the current methods in QTL hotspot detection. The results demonstrate that the proposed statistical framework can effectively accommodate the correlation structure among traits, identify the types of hotspots, and still keep the notable features of easy implementation and fast computation for practical QTL hotspot detection.
Topics: Chromosome Mapping; Computer Simulation; Lod Score; Phenotype; Quantitative Trait Loci
PubMed: 33638985
DOI: 10.1093/g3journal/jkab056 -
Annals of Human Genetics Jul 2008The maximum LOD score statistic is extremely powerful for gene mapping when calculated using the correct genetic parameter value. When the mode of genetic transmission... (Comparative Study)
Comparative Study
The maximum LOD score statistic is extremely powerful for gene mapping when calculated using the correct genetic parameter value. When the mode of genetic transmission is unknown, the maximum of the LOD scores obtained using several genetic parameter values is reported. This latter statistic requires higher critical value than the maximum LOD score statistic calculated from a single genetic parameter value. In this paper, we compare the power of maximum LOD scores based on three fixed sets of genetic parameter values with the power of the LOD score obtained after maximizing over the entire range of genetic parameter values. We simulate family data under nine generating models. For generating models with non-zero phenocopy rates, LOD scores maximized over the entire range of genetic parameters yielded greater power than maximum LOD scores for fixed sets of parameter values with zero phenocopy rates. No maximum LOD score was consistently more powerful than the others for generating models with a zero phenocopy rate. The power loss of the LOD score maximized over the entire range of genetic parameters, relative to the maximum LOD score calculated using the correct genetic parameter value, appeared to be robust to the generating models.
Topics: Computer Simulation; Family; Genotype; Humans; Lod Score; Models, Genetic; Models, Statistical; Population Groups
PubMed: 18410472
DOI: 10.1111/j.1469-1809.2008.00442.x -
American Journal of Human Genetics Aug 2000
Topics: Alleles; Chromosome Mapping; Female; Humans; Likelihood Functions; Lod Score; Male; Models, Genetic; Nuclear Family; Pedigree; Software
PubMed: 10884360
DOI: 10.1086/303029 -
Journal of Genetics Jun 2019Panicle traits are the most important agronomic characters which directly relate to yield in rice. Panicle length (PL) being one of the major components of rice panicle...
Panicle traits are the most important agronomic characters which directly relate to yield in rice. Panicle length (PL) being one of the major components of rice panicle structure is controlled by quantitative trait loci (QTLs). In our research, conducted at Research Farm of SKUAST-J, crosses of parental lines K343 and DHMAS were made for generating F mapping population, which were then transplanted into the field using augmented design-I. The F population was used for phenotypic evaluation, development of linkage map and identification of QTLs on the chromosomes by using SSR markers. A total of 450 SSR markers were used for screening both the parents of which 53 highly polymorphic markers were selected and used for genotyping of 233 genotypes of Fpopulation. Linkage map was generated using MAPMAKER/EXP3.0 software, seven linkage groups were found distributed on 11 chromosomes of rice. QTLs were detected using QTL Cartographer (v2.5) software. Based on 1000 permutation tests, a logarithm of odds (LOD) threshold value 2.0 and 3.0 was set. Composite interval mapping was used to map QTLs in populations derived from bi-parental crosses. The phenotypic data, genotypic data and the genetic linkage map generated identified total three QTLs of which one was identified for PL qPL2, located at 85.01 cM position with 2.1 LOD value and in between the marker intervals RM324-RM208, this QTL explained the phenotype variation by 4.36%. The other two QTLs were identified for spikelet density (SD) qSD3.1 and qSD3.2, located at 28.91 and 39.51 cM, respectively, both with a flanking marker RM6832 on chromosome 3. The LOD value and phenotypic variation explained for qSD3.1 and qSD3.2 was 3.00 and 3.25; 9.70 and 12.34% respectively. The reported QTLs identified in the study suggested a less diversity in the parents used and also the rejection of not so useful markers from the used set of markers for PL and SD.
Topics: Chromosome Mapping; Genetic Linkage; Genetics, Population; Genotype; Lod Score; Oryza; Phenotype; Polymorphism, Genetic; Quantitative Trait Loci; Repetitive Sequences, Nucleic Acid
PubMed: 31204700
DOI: No ID Found -
Archives of Sexual Behavior Nov 2021Male sexual orientation is a scientifically and socially important trait shown by family and twin studies to be influenced by environmental and complex genetic factors.... (Meta-Analysis)
Meta-Analysis
Male sexual orientation is a scientifically and socially important trait shown by family and twin studies to be influenced by environmental and complex genetic factors. Individual genome-wide linkage studies (GWLS) have been conducted, but not jointly analyzed. Two main datasets account for > 90% of the published GWLS concordant sibling pairs on the trait and are jointly analyzed here: MGSOSO (Molecular Genetic Study of Sexual Orientation; 409 concordant sibling pairs in 384 families, Sanders et al. (2015)) and Hamer (155 concordant sibling pairs in 145 families, Mustanski et al. (2005)). We conducted multipoint linkage analyses with Merlin on the datasets separately since they were genotyped differently, integrated genetic marker positions, and combined the resultant LOD (logarithm of the odds) scores at each 1 cM grid position. We continue to find the strongest linkage support at pericentromeric chromosome 8 and chromosome Xq28. We also incorporated the remaining published GWLS dataset (on 55 families) by using meta-analytic approaches on published summary statistics. The meta-analysis has maximized the positional information from GWLS of currently available family resources and can help prioritize findings from genome-wide association studies (GWAS) and other approaches. Although increasing evidence highlights genetic contributions to male sexual orientation, our current understanding of contributory loci is still limited, consistent with the complexity of the trait. Further increasing genetic knowledge about male sexual orientation, especially via large GWAS, should help advance our understanding of the biology of this important trait.
Topics: Female; Genetic Linkage; Genome, Human; Genome-Wide Association Study; Humans; Lod Score; Male; Sexual Behavior
PubMed: 34080073
DOI: 10.1007/s10508-021-02035-3 -
Journal of Genetics Dec 2009Age-related macular degeneration (AMD) is a complex disorder of the eye and the third leading cause of blindness worldwide. With a multifactorial etiology, AMD results... (Review)
Review
Age-related macular degeneration (AMD) is a complex disorder of the eye and the third leading cause of blindness worldwide. With a multifactorial etiology, AMD results in progressive loss of central vision affecting the macular region of the eye in elderly. While the prevalence is relatively higher in the Caucasian populations, it has gradually become a major public health issue among the non-Caucasian populations (including Indians) as well due to senescence, rapidly changing demographics and life-style factors. Recent genome-wide association studies (GWAS) on large case-control cohorts have helped in mapping genes in the complement cascade that are involved in the regulation of innate immunity with AMD susceptibility. Genes involved with mitochondrial oxidative stress and extracellular matrix regulation also play a role in AMD pathogenesis. Majority of the associations observed in complement (CFH, CFB, C2 and C3) and other (ARMS2 and HTRA1) genes have been replicated in diverse populations worldwide. Gene-gene (CFH with ARMS2 and HTRA1) interactions and correlations with environmental traits (smoking and body mass index) have been established as significant covariates in AMD pathology. In this review, we have provided an overview on the underlying molecular genetic mechanisms in AMD worldwide and highlight the AMD-associated-candidate genes and their potential role in disease pathogenesis.
Topics: Chromosome Mapping; Genetic Predisposition to Disease; Genome, Human; Genome-Wide Association Study; Humans; Lod Score; Macular Degeneration; Polymorphism, Single Nucleotide
PubMed: 20090206
DOI: 10.1007/s12041-009-0064-4 -
American Journal of Human Genetics Oct 1994Determining the mode of inheritance is often difficult under the best of circumstances, but when segregation analysis is used, the problems of ambiguous ascertainment...
Determining the mode of inheritance is often difficult under the best of circumstances, but when segregation analysis is used, the problems of ambiguous ascertainment procedures, reduced penetrance, heterogeneity, and misdiagnosis make mode-of-inheritance determinations even more unreliable. The mode of inheritance can also be determined using a linkage-based method (maximized maximum lod score or mod score) and association-based methods, which can overcome many of these problems. In this work, we determined how much information is necessary to reliably determine the mode of inheritance from linkage data when heterogeneity and reduced penetrance are present in the data set. We generated data sets under both dominant and recessive inheritance with reduced penetrance and with varying fractions of linked and unlinked families. We then analyzed those data sets, assuming reduced penetrance, both dominant and recessive inheritance, and no heterogeneity. We investigated the reliability of two methods for determining the mode of inheritance from the linkage data. The first method examined the difference (delta) between the maximum lod scores calculated under the two mode-of-inheritance assumptions. We found that if delta was > 1.5, then the higher of the two maximum lod scores reflected the correct mode of inheritance with high reliability and that a delta of 2.5 appeared to practically guarantee a correct mode-of-inheritance inference. Furthermore, this reliability appeared to be virtually independent of alpha, the fraction of linked families in the data set, although the reliability decreased slightly as alpha fell below .50.(ABSTRACT TRUNCATED AT 250 WORDS)
Topics: Female; Genetics, Medical; Humans; Lod Score; Male; Models, Genetic; Models, Statistical; Nuclear Family; Probability
PubMed: 7942860
DOI: No ID Found -
American Journal of Human Genetics Mar 1998A LOD score >=3 is necessary but not sufficient to make a linkage test reliable, and this applies to complex inheritance as well as to major loci. Factors that affect...
A LOD score >=3 is necessary but not sufficient to make a linkage test reliable, and this applies to complex inheritance as well as to major loci. Factors that affect this threshold are considered here. A LOD score as small as 2 is suggestive but is unreliable except as confirmation of either a significant linkage or a strong candidate locus. A threshold as great as 4 is unnecessarily conservative if multipoint tests are used sensibly. Marker density is not a major factor, and biases in the evaluation of LOD scores-especially inadequate allowance for estimation of nuisance parameters in multiple models-are paramount. Allelic association increases resolution for oligogenes within a candidate region and remains the only practical method to locate polygenes. The method sketched here combines multipoint linkage and allelic association to test efficiently for a regional candidate locus.
Topics: Alleles; Genetic Linkage; Genetic Markers; Humans; Lod Score
PubMed: 9497238
DOI: 10.1086/301741 -
Human Genomics Nov 2003There is now a wide choice of software available for linkage analysis. The most well known packages are briefly reviewed here. The package with the most extensive range... (Review)
Review
There is now a wide choice of software available for linkage analysis. The most well known packages are briefly reviewed here. The package with the most extensive range of analyses is GENEHUNTER, but for many of its functions there are other programs with better performance. These include FASTLINK and VITESSE for parametric analysis ALLEGRO and MERLIN for non-parametric analysis and SOLAR for variance components analysis. The computational limits of current approaches can be improved with SIMWALK2 and the promising new SUPERLINK program. Directions for future work include improved user interfaces and consensus formats for data input and exchange.
Topics: Algorithms; Computer Systems; Data Collection; Genes, Recessive; Genetic Linkage; Genetic Markers; Haplotypes; Humans; Lod Score; Microsatellite Repeats; Pedigree; Polymorphism, Single Nucleotide; Quantitative Trait, Heritable; Regression Analysis; Software
PubMed: 15601534
DOI: 10.1186/1479-7364-1-1-63 -
Methods (San Diego, Calif.) Feb 2011In 1999 a meeting took place at the Jackson Laboratory, a large mouse research centre in Bar Harbor, Maine, to consider the value of systematically collecting phenotypes... (Review)
Review
In 1999 a meeting took place at the Jackson Laboratory, a large mouse research centre in Bar Harbor, Maine, to consider the value of systematically collecting phenotypes on inbred strains of mice (Paigen and Eppig (2000) [1]). The group concluded that cataloguing the extensive phenotypic diversity present among laboratory mice, and in particular providing the research community with data from cohorts of animals, phenotyped according to standardized protocols, was essential if we were to take advantage of the possibilities of mouse genetics. Beginning with the collection of basic physiological, biochemical and behavioral data on nine commonly used inbred strains, the project has expanded so that by the beginning of 2010 data for 178 strains had been collected, with 105 phenotype projects yielding over 2000 different measurements (Bogue et al. (2007) [2].
Topics: Animals; Chromosome Mapping; Crosses, Genetic; Genome; Inbreeding; Lod Score; Mice; Mice, Inbred Strains; Phenotype; Quantitative Trait Loci
PubMed: 20643209
DOI: 10.1016/j.ymeth.2010.07.007