Journal articles: 'Quantitative trait locis'

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Qin, Hongtao, Zhangxiong Liu, Yuyang Wang, Mingyue Xu, Xinrui Mao, Huidong Qi, Zhengong Yin, et al. "Meta-analysis and overview analysis of quantitative trait locis associated with fatty acid content in soybean for candidate gene mining." Plant Breeding 137, no. 2 (February 14, 2018): 181–93. http://dx.doi.org/10.1111/pbr.12562.

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Seifi Moroudi, R., S. Ansari Mahyari, R. Vaez Torshizi, H. Lanjanian, and A. Masoudi‐Nejad. "Identification of new genes and quantitative trait locis associated with growth curve parameters in F2 chicken population using genome‐wide association study." Animal Genetics 52, no. 2 (January 11, 2021): 171–84. http://dx.doi.org/10.1111/age.13038.

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Gimelfarb, A. "Pleiotropy as a factor maintaining genetic variation in quantitative characters under stabilizing selection." Genetical Research 68, no. 1 (August 1996): 65–73. http://dx.doi.org/10.1017/s0016672300033899.

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SummaryA model of pleiotropy with N diallelic loci contributing additively to N quantitative traits and stabilizing selection acting on each of the traits is considered. Every locus has a major contribution to one trait and a minor contribution to the rest of them, while every trait is controlled by one major locus and N−1 minor loci. It is demonstrated that a stable equilibrium with the allelic frequency equal to 0·5 in all N loci can be maintained in such a model for a wide range of parameters. Such a ‘totally polymorphic’ equilibrium is maintained for practically any strength of selection and any recombination, if the relative contribution by a minor locus to a trait is less than 20 % of the contribution by a major locus. The dynamic behaviour of the model is shown to be quite complex with a possibility under sufficiently strong selection of multiple stable equilibria and positive linkage disequilibria between loci. It is also suggested that pleiotropy among loci controlling traits experiencing direct selection can be responsible for apparent selection on neutral traits also controlled by these loci.

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Tsilo, T. J., J. B. Ohm, G. A. Hareland, S. Chao, and J. A. Anderson. "Quantitative trait loci influencing end-use quality traits of hard red spring wheat breeding lines." Czech Journal of Genetics and Plant Breeding 47, Special Issue (October 20, 2011): S190—S195. http://dx.doi.org/10.17221/3279-cjgpb.

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Wheat bread-making quality is influenced by a complex group of traits including dough visco-elastic characteristics. In this study, quantitative trait locus/loci (QTL) mapping and analysis were conducted for endosperm polymeric proteins together with dough mixing strength and bread-making properties in a population of 139 (MN98550 × MN99394) recombinant inbred lines that was evaluated at three environments in 2006. Eleven chromosome regions were associated with endosperm polymeric proteins, explaining 4.2–31.8% of the phenotypic variation. Most of these polymeric proteins QTL coincided with several QTL for dough-mixing strength and bread-making properties. Major QTL clusters were associated with the low-molecular weight glutenin gene Glu-A3, the two high-molecular weight glutenin genes Glu-B1 and Glu-D1, and two regions on chromosome 6D. Alleles at these QTL clusters have previously been proven useful for wheat quality except one of the 6D QTL clusters.

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Xu, Shizhong, and William R. Atchley. "Mapping Quantitative Trait Loci for Complex Binary Diseases Using Line Crosses." Genetics 143, no. 3 (July 1, 1996): 1417–24. http://dx.doi.org/10.1093/genetics/143.3.1417.

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Abstract A composite interval gene mapping procedure for complex binary disease traits is proposed in this paper. The binary trait of interest is assumed to be controlled by an underlying liability that is normally distributed. The liability is treated as a typical quantitative character and thus described by the usual quantitative genetics model. Translation from the liability into a binary (disease) phenotype is through the physiological threshold model. Logistic regression analysis is employed to estimate the effects and locations of putative quantitative trait loci (our terminology for a single quantitative trait locus is QTL while multiple loci are referred to as QTLs). Simulation studies show that properties of this mapping procedure mimic those of the composite interval mapping for normally distributed data. Potential utilization of the QTL mapping procedure for resolving alternative genetic models (e.g., single- or two-trait-locus model) is discussed.

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Edwards, M. D., C. W. Stuber, and J. F. Wendel. "Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action." Genetics 116, no. 1 (May 1, 1987): 113–25. http://dx.doi.org/10.1093/genetics/116.1.113.

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ABSTRACT Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17–20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800–1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.

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Paran, I., I. L. Goldman, and D. Zamir. "Morphological Trait QTL Mapping in Tomato Recombinant Inbred Line Population." HortScience 30, no. 4 (July 1995): 788D—788. http://dx.doi.org/10.21273/hortsci.30.4.788d.

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Quantitative trait loci influencing morphological traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RIL) derived from a cross of the cultivated tomato (Lycopersicon esculentum) with a related wild species (L. cheesmanii). One-hundred-thirty-two polymorphic RFLP loci spaced throughout the tomato genome were scored for 97 RIL families. Morphological traits, including plant height, fresh weight, node number, first flower-bearing node, leaf length at nodes three and four, and number of branches, were measured in replicated trials during 1991, 1992, and 1993. Significant (P ≤ 0.01 level) quantitative trait locus (QTL) associations of marker loci were identified for each trait. Lower plant height, more branches, and shorter internode length were generally associated with RFLP alleles from the L. cheesmanii parent. QTL with large effects on a majority of the morphological traits measured were detected at chromosomes 2, 3, and 4. Large additive effects were measured at significant marker loci for many of the traits measured. Several marker loci exhibited significant associations with numerous morphological traits, suggesting their possible linkage to genes controlling growth and development processes in Lycopersicon.

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Linder, Robert A., Fabian Seidl, Kimberly Ha, and Ian M. Ehrenreich. "The complex genetic and molecular basis of a model quantitative trait." Molecular Biology of the Cell 27, no. 1 (January 2016): 209–18. http://dx.doi.org/10.1091/mbc.e15-06-0408.

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Quantitative traits are often influenced by many loci with small effects. Identifying most of these loci and resolving them to specific genes or genetic variants is challenging. Yet, achieving such a detailed understanding of quantitative traits is important, as it can improve our knowledge of the genetic and molecular basis of heritable phenotypic variation. In this study, we use a genetic mapping strategy that involves recurrent backcrossing with phenotypic selection to obtain new insights into an ecologically, industrially, and medically relevant quantitative trait—tolerance of oxidative stress, as measured based on resistance to hydrogen peroxide. We examine the genetic basis of hydrogen peroxide resistance in three related yeast crosses and detect 64 distinct genomic loci that likely influence the trait. By precisely resolving or cloning a number of these loci, we demonstrate that a broad spectrum of cellular processes contribute to hydrogen peroxide resistance, including DNA repair, scavenging of reactive oxygen species, stress-induced MAPK signaling, translation, and water transport. Consistent with the complex genetic and molecular basis of hydrogen peroxide resistance, we show two examples where multiple distinct causal genetic variants underlie what appears to be a single locus. Our results improve understanding of the genetic and molecular basis of a highly complex, model quantitative trait.

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Peters, Luanne L., Amy J. Lambert, Weidong Zhang, Gary A. Churchill, Carlo Brugnara, and Orah S. Platt. "Quantitative trait loci for baseline erythroid traits." Mammalian Genome 17, no. 4 (April 2006): 298–309. http://dx.doi.org/10.1007/s00335-005-0147-3.

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McINTYRE, LAUREN M., CYNTHIA J. COFFMAN, and R. W. DOERGE. "Detection and localization of a single binary trait locus in experimental populations." Genetical Research 78, no. 1 (August 2001): 79–92. http://dx.doi.org/10.1017/s0016672301005092.

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The advancements made in molecular technology coupled with statistical methodology have led to the successful detection and location of genomic regions (quantitative trait loci; QTL) associated with quantitative traits. Binary traits (e.g. susceptibility/resistance), while not quantitative in nature, are equally important for the purpose of detecting and locating significant associations with genomic regions. Existing interval regression methods used in binary trait analysis are adapted from quantitative trait analysis and the tests for regression coefficients are tests of effect, not detection. Additionally, estimates of recombination that fail to take into account varying penetrance perform poorly when penetrance is incomplete. In this work a complete probability model for binary trait data is developed allowing for unbiased estimation of both penetrance and recombination between a genetic marker locus and a binary trait locus for backcross and F2 experimental designs. The regression model is reparameterized allowing for tests of detection. Extensive simulations were conducted to assess the performance of estimation and testing in the proposed parameterization. The proposed parameterization was compared with interval regression via simulation. The results indicate that our parameterization shows equivalent estimation capabilities, requires less computational effort and works well with only a single marker.

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Marzougui, Salem, Mohamed Kharrat, and Mongi ben Younes. "Marker-trait associations of yield related traits in bread wheat (Triticum aestivum L.) under a semi-arid climate." Czech Journal of Genetics and Plant Breeding 55, No. 4 (September 23, 2019): 138–45. http://dx.doi.org/10.17221/154/2018-cjgpb.

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Identifying QTLs (quantitative trait loci) that control yield related traits under a stressed environment is very useful for marker-assisted selection (MAS). Marker-trait associations (MTA) for several agro-morphological traits were performed with 130 Tunisian and exotic spring bread wheat (Triticum aestivum L.) accessions under a semi-arid climate in El Kef, Tunisia. Grain yield and other important traits were evaluated. A population structural analysis identified two sub populations. In total, 29 MTAs were detected at –log P ≥ 3 using an MLM (mixed linear model), and only 5 MTAs with –log P ≥ 4. The locus on chromosome 4A was detected to control the heading date accounting for up to 22% of the trait variance. Two other loci located on chromosomes 3B and 7B were found to be stable during the two cropping seasons and have a pleiotropic effect on the heading date, yield, internodes length and grain per spike. These two regions are candidates for further genetic analysis.

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Nelson, James C., Cristina Andreescu, Flavio Breseghello, Patrick L. Finney, Daisy G. Gualberto, Christine J. Bergman, Roberto J. Peña, et al. "Quantitative trait locus analysis of wheat quality traits." Euphytica 149, no. 1-2 (June 2, 2006): 145–59. http://dx.doi.org/10.1007/s10681-005-9062-7.

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Zhang, Fei, Jiafu Jiang, Sumei Chen, Fadi Chen, and Weimin Fang. "Mapping single-locus and epistatic quantitative trait loci for plant architectural traits in chrysanthemum." Molecular Breeding 30, no. 2 (December 22, 2011): 1027–36. http://dx.doi.org/10.1007/s11032-011-9686-3.

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Bürger, Reinhard, and Alexander Gimelfarb. "Genetic Variation Maintained in Multilocus Models of Additive Quantitative Traits Under Stabilizing Selection." Genetics 152, no. 2 (June 1, 1999): 807–20. http://dx.doi.org/10.1093/genetics/152.2.807.

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Abstract Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright’s two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination.

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Rajon, Etienne, and Joshua B. Plotkin. "The evolution of genetic architectures underlying quantitative traits." Proceedings of the Royal Society B: Biological Sciences 280, no. 1769 (October 22, 2013): 20131552. http://dx.doi.org/10.1098/rspb.2013.1552.

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In the classic view introduced by R. A. Fisher, a quantitative trait is encoded by many loci with small, additive effects. Recent advances in quantitative trait loci mapping have begun to elucidate the genetic architectures underlying vast numbers of phenotypes across diverse taxa, producing observations that sometimes contrast with Fisher's blueprint. Despite these considerable empirical efforts to map the genetic determinants of traits, it remains poorly understood how the genetic architecture of a trait should evolve, or how it depends on the selection pressures on the trait. Here, we develop a simple, population-genetic model for the evolution of genetic architectures. Our model predicts that traits under moderate selection should be encoded by many loci with highly variable effects, whereas traits under either weak or strong selection should be encoded by relatively few loci. We compare these theoretical predictions with qualitative trends in the genetics of human traits, and with systematic data on the genetics of gene expression levels in yeast. Our analysis provides an evolutionary explanation for broad empirical patterns in the genetic basis for traits, and it introduces a single framework that unifies the diversity of observed genetic architectures, ranging from Mendelian to Fisherian.

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Berke, T. G., and T. R. Rocheford. "Quantitative Trait Loci for Tassel Traits in Maize." Crop Science 39, no. 5 (September 1999): 1439–43. http://dx.doi.org/10.2135/cropsci1999.3951439x.

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Banerjee, Samprit, Brian S. Yandell, and Nengjun Yi. "Bayesian Quantitative Trait Loci Mapping for Multiple Traits." Genetics 179, no. 4 (August 2008): 2275–89. http://dx.doi.org/10.1534/genetics.108.088427.

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Yi, Nengjun, Shizhong Xu, Varghese George, and David B. Allison. "Mapping Multiple Quantitative Trait Loci for Ordinal Traits." Behavior Genetics 34, no. 1 (January 2004): 3–15. http://dx.doi.org/10.1023/b:bege.0000009473.43185.43.

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Xu, C., X. He, and S. Xu. "Mapping quantitative trait loci underlying triploid endosperm traits." Heredity 90, no. 3 (March 2003): 228–35. http://dx.doi.org/10.1038/sj.hdy.6800217.

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Buitenhuis, A. J., T. B. Rodenburg, M. Siwek, S. J. B. Cornelissen, M. G. B. Nieuwland, R. P. M. A. Crooijmans, M. A. M. Groenen, P. Koene, H. Bovenhuis, and J. J. van der Poel. "Quantitative trait loci for behavioural traits in chickens." Livestock Production Science 93, no. 1 (April 2005): 95–103. http://dx.doi.org/10.1016/j.livprodsci.2004.11.010.

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Panthee, D. R., V. R. Pantalone, A. M. Saxton, D. R. West, and C. E. Sams. "Quantitative trait loci for agronomic traits in soybean." Plant Breeding 126, no. 1 (February 2007): 51–57. http://dx.doi.org/10.1111/j.1439-0523.2006.01305.x.

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Sato, S., C. Ohnishi, Y. Uemoto, and E. Kobayashi. "Haplotype analysis within quantitative trait locus affecting intramuscular fat content on porcine chromosome." Czech Journal of Animal Science 56, No. 12 (December 22, 2011): 521–28. http://dx.doi.org/10.17221/4414-cjas.

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Previous results of fine mapping for quantitative trait loci affecting intramuscular fat content identified a 3.0-Mb chromosome interval on porcine chromosome 7, which contains at least 9 genes, based on the pig genome assembly. Therefore, we proposed these nine genes (LOC100154481, LOC100155711, LOC100155276, SPATA7, PTPN21, ZCH14, EML5, TTC8, and FOXN3) as positional candidate genes. The coding exons of the nine genes were characterized, and 45 polymorphisms were detected in F<sub>2</sub> Duroc × Meishan population. Within the nine genes, 10 non-synonymous substitutions and 1 insertion were genotyped among three European breeds (Landrace, Large White, and Duroc) and 1 Chinese breed (Meishan). Genotyping data was used to perform the haplotype analysis. Polymorphisms were found in all the studied genes, except ZCH14. We surveyed the frequency of 33 haplotypes that formed non-synonymous substitutions in four breeds. One of them was distributed widely in the Landrace, Large White, and Meishan breeds, but not in Duroc. Each breed had different major haplotypes.  

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Corsi, Beatrice, Lia Obinu, Camila M. Zanella, Saverio Cutrupi, Rob Day, Manuel Geyer, Morten Lillemo, et al. "Identification of eight QTL controlling multiple yield components in a German multi-parental wheat population, including Rht24, WAPO-A1, WAPO-B1 and genetic loci on chromosomes 5A and 6A." Theoretical and Applied Genetics 134, no. 5 (March 12, 2021): 1435–54. http://dx.doi.org/10.1007/s00122-021-03781-7.

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Abstract Key message Quantitative trait locus (QTL) mapping of 15 yield component traits in a German multi-founder population identified eight QTL each controlling ≥2 phenotypes, including the genetic loci Rht24, WAPO-A1 and WAPO-B1. Abstract Grain yield in wheat (Triticum aestivum L.) is a polygenic trait representing the culmination of many developmental processes and their interactions with the environment. Toward maintaining genetic gains in yield potential, ‘reductionist approaches’ are commonly undertaken by which the genetic control of yield components, that collectively determine yield, are established. Here we use an eight-founder German multi-parental wheat population to investigate the genetic control and phenotypic trade-offs between 15 yield components. Increased grains per ear was significantly positively correlated with the number of fertile spikelets per ear and negatively correlated with the number of infertile spikelets. However, as increased grain number and fertile spikelet number per ear were significantly negatively correlated with thousand grain weight, sink strength limitations were evident. Genetic mapping identified 34 replicated quantitative trait loci (QTL) at two or more test environments, of which 24 resolved into eight loci each controlling two or more traits—termed here ‘multi-trait QTL’ (MT-QTL). These included MT-QTL associated with previously cloned genes controlling semi-dwarf plant stature, and with the genetic locus Reduced height 24 (Rht24) that further modulates plant height. Additionally, MT-QTL controlling spikelet number traits were located to chromosome 7A encompassing the gene WHEAT ORTHOLOG OF APO1 (WAPO-A1), and to its homoeologous location on chromosome 7B containing WAPO-B1. The genetic loci identified in this study, particularly those that potentially control multiple yield components, provide future opportunities for the targeted investigation of their underlying genes, gene networks and phenotypic trade-offs, in order to underpin further genetic gains in yield.

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Comuzzie, Anthony G., Tohru Funahashi, Gabriele Sonnenberg, Lisa J. Martin, Howard J. Jacob, Anne E. Kwitek Black, Diana Maas, et al. "The Genetic Basis of Plasma Variation in Adiponectin, a Global Endophenotype for Obesity and the Metabolic Syndrome." Journal of Clinical Endocrinology & Metabolism 86, no. 9 (September 1, 2001): 4321–25. http://dx.doi.org/10.1210/jcem.86.9.7878.

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Here we present the first genetic analysis of adiponectin levels, a newly identified adipocyte-derived protein. Recent work has suggested that adiponectin may play a role in mediating the effects of body weight as a risk factor for coronary artery disease. For this analysis we assayed serum levels of adiponectin in 1100 adults of predominantly northern European ancestry distributed across 170 families. Quantitative genetic analysis of adiponectin levels detected an additive genetic heritability of 46%. The maximum LOD score detected in a genome wide scan for adiponectin levels was 4.06 (P = 7.7 × 10−6), 35 cM from pter on chromosome 5. The second largest LOD score (LOD = 3.2; P = 6.2 × 10−5) was detected on chromosome 14, 29 cM from pter. The detection of a significant linkage with a quantitative trait locus on chromosome 5 provides strong evidence for a replication of a previously reported quantitative trait locus for obesity-related phenotypes. In addition, several secondary signals offer potential evidence of replications for additional previously reported obesity-related quantitative trait loci on chromosomes 2 and 10. Not only do these results identify quantitative trait loci with significant effects on a newly described, and potentially very important, adipocyte-derived protein, they also reveal the emergence of a consistent pattern of linkage results for obesity-related traits across a number of human populations.

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Xi, Zhang-Ying, Feng-Hua He, Rui-Zhen Zeng, Ze-Min Zhang, Xiao-Hua Ding, Wen-Tao Li, and Gui-Quan Zhang. "Development of a wide population of chromosome single-segment substitution lines in the genetic background of an elite cultivar of rice (Oryza sativa L.)." Genome 49, no. 5 (May 1, 2006): 476–84. http://dx.doi.org/10.1139/g06-005.

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Naturally occurring allelic variations underlying complex traits are useful resources for the functional analysis of plant genes. To facilitate the genetic analysis of complex traits and the use of marker-assisted breeding in rice, we developed a wide population consisting of 217 chromosome single-segment substitution lines (SSSLs) using Oryza sativa L. 'Hua-Jing-Xian74' (HJX74), an elite Indica cultivar, as recipient, and 6 other accessions, including 2 Indica and 4 Japonica, as donors. Each SSSL contains a single substituted chromosome segment derived from 1 of the 6 donors in the genetic background of HJX74. The total size of the substituted segments in the SSSL population was 4695.0 cM, which was 3.1 times that of rice genome. To evaluate the potential application of these SSSLs for quantitative trait loci detection, phenotypic variations of the quantitative traits of days to heading and grain length in the population consisting of 210 SSSLs were observed under natural environmental conditions. The results demonstrated that there was a wide range of phenotypic variation in the traits in the SSSL population. These genetic materials will be powerful tools to dissect complex traits into a set of monogenic loci and to assign phenotypic values to different alleles at the locus of interest.Key words: rice, mapping population, single segment substitution lines, marker-assisted selection, quantitative trait loci.

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Gonzalez-Segovia, Eric, Sergio Pérez-Limon, G. Carolina Cíntora-Martínez, Alejandro Guerrero-Zavala, Garrett M. Janzen, Matthew B. Hufford, Jeffrey Ross-Ibarra, and Ruairidh J. H. Sawers. "Characterization of introgression from the teosinte Zea mays ssp. mexicana to Mexican highland maize." PeerJ 7 (May 3, 2019): e6815. http://dx.doi.org/10.7717/peerj.6815.

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Background The spread of maize cultivation to the highlands of central Mexico was accompanied by substantial introgression from the endemic wild teosinte Zea mays ssp. mexicana, prompting the hypothesis that the transfer of beneficial variation facilitated local adaptation. Methods We used whole-genome sequence data to map regions of Zea mays ssp. mexicana introgression in three Mexican highland maize individuals. We generated a genetic linkage map and performed Quantitative Trait Locus mapping in an F2 population derived from a cross between lowland and highland maize individuals. Results Introgression regions ranged in size from several hundred base pairs to Megabase-scale events. Gene density within introgression regions was comparable to the genome as a whole, and over 1,000 annotated genes were located within introgression events. Quantitative Trait Locus mapping identified a small number of loci linked to traits characteristic of Mexican highland maize. Discussion Although there was no strong evidence to associate quantitative trait loci with regions of introgression, we nonetheless identified many Mexican highland alleles of introgressed origin that carry potentially functional sequence variants. The impact of introgression on stress tolerance and yield in the highland environment remains to be fully characterized.

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Hashimoto, Takuma, Nakao Kubo, Kanako Nishimura, Atsushi J. Nagano, Azusa Sasaki, Yasushi Nakamura, and Yutaka Mimura. "Quantitative Trait Locus Analysis in Squash (Cucurbita moschata) Based on Simple Sequence Repeat Markers and Restriction Site-Associated DNA Sequencing Analysis." Horticulturae 6, no. 4 (October 22, 2020): 71. http://dx.doi.org/10.3390/horticulturae6040071.

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Squash (Cucurbita moschata) displays wide morphological and genetic variations; however, limited information is available regarding the genetic loci of squash that control its agronomic traits. To obtain basic genetic information for C. moschata, an F2 population was prepared derived from a cross between the Vietnamese cultivar ‘Bí Hồ Lô TN 6 (TN 6)’ and the Japanese cultivar ‘Shishigatani’, and flowering and fruit traits were examined. Overall, the traits showed a continuous distribution in the F2 population, suggesting that they were quantitative traits. A linkage map was constructed based on simple sequence repeat and restriction site-associated DNA (RAD) markers to detect quantitative trait loci (QTLs). Twelve QTLs for flowering and fruit traits, as well as one phenotypic trait locus, were successfully localized on the map. The present QTLs explained the phenotypic variations at a moderate to relatively high level (16.0%–47.3%). RAD markers linked to the QTLs were converted to codominant cleaved amplified polymorphic sequence (CAPS) and derived CAPS markers for the easy detection of alleles. The information reported here provides useful information for understanding the genetics of Cucurbita and other cucurbit species, and for the selection of individuals with ideal traits during the breeding of Cucurbita vegetables.

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Baes, C., and N. Reinsch. "TIGER: A software system for fine-mapping quantitative trait loci." Archives Animal Breeding 51, no. 4 (October 10, 2008): 402–12. http://dx.doi.org/10.5194/aab-51-402-2008.

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Abstract. The localisation of quantitative trait loci which contribute significantly to phenotype variation of economically important traits in domestic species has become an important goal in animal genomics. Several such loci have been roughly identified using linkage analyses; however the focus has now shifted towards fine mapping and pinpointing causal mutations. In the context of a cooperative national research project, the software system TIGER was developed. TIGER is a UNIX script linking several individual Fortran programmes and is used for comprehensive variance component analysis of fine mapping data. Starting with raw genotype data, pedigree and marker map information and ending with a residual maximum likelihood-based test for each putative quantitative trait locus position, the software provides the user with an "all in one" package capable of linkage analysis, linkage disequilibrium analysis and combined linkage/linkage disequilibrium analysis. The software system has been employed in 4 fine mapping projects on 4 distinct cattle chromosomes.

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Gahlaut, Vijay, Gaurav Zinta, Vandana Jaiswal, and Sanjay Kumar. "Quantitative Epigenetics: A New Avenue for Crop Improvement." Epigenomes 4, no. 4 (November 7, 2020): 25. http://dx.doi.org/10.3390/epigenomes4040025.

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Plant breeding conventionally depends on genetic variability available in a species to improve a particular trait in the crop. However, epigenetic diversity may provide an additional tier of variation. The recent advent of epigenome technologies has elucidated the role of epigenetic variation in shaping phenotype. Furthermore, the development of epigenetic recombinant inbred lines (epi-RILs) in model species such as Arabidopsis has enabled accurate genetic analysis of epigenetic variation. Subsequently, mapping of epigenetic quantitative trait loci (epiQTL) allowed association between epialleles and phenotypic traits. Likewise, epigenome-wide association study (EWAS) and epi-genotyping by sequencing (epi-GBS) have revolutionized the field of epigenetics research in plants. Thus, quantitative epigenetics provides ample opportunities to dissect the role of epigenetic variation in trait regulation, which can be eventually utilized in crop improvement programs. Moreover, locus-specific manipulation of DNA methylation by epigenome-editing tools such as clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) can potentially facilitate epigenetic based molecular breeding of important crop plants.

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Jackson, Anne U., Alison Fornés, Andrzej Galecki, Richard A. Miller, and David T. Burke. "Multiple-Trait Quantitative Trait Loci Analysis Using a Large Mouse Sibship." Genetics 151, no. 2 (February 1, 1999): 785–95. http://dx.doi.org/10.1093/genetics/151.2.785.

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Abstract Quantitative trait loci influencing several phenotypes were assessed using a genetically heterogeneous mouse population. The 145 individuals were produced by a cross between (BALB/cJ × C57BL/6J)F1 females and (C3H/HeJ × DBA/2J)F1 males. The population is genetically equivalent to full siblings derived from heterozygous parents, with known linkage phase. Each individual in the population represents a unique combination of alleles from the inbred grandparents. Quantitative phenotypes for eight T cell measures were obtained at 8 and 18 mo of age. Single-marker locus, repeated measures analysis of variance identified nine marker-phenotype associations with an experimentwise significance level of P < 0.05. Six of the eight quantitative phenotypes could be associated with at least one locus having experiment-wide significance. Composite interval, repeated measures analysis of variance identified 13 chromosomal regions with comparisonwise (nominal) significance associations of P < 0.001. The heterozygous-parent cross provides a reproducible, general method for identification of loci associated with quantitative trait phenotypes or repeated phenotypic measures.

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31

Mayo, O. "Interaction and quantitative trait loci." Australian Journal of Experimental Agriculture 44, no. 11 (2004): 1135. http://dx.doi.org/10.1071/ea03240.

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Parallel searches for quantitative trait loci (QTL) for growth-related traits in different populations frequently detect sets of QTL that hardly overlap. Thus, many QTL potentially exist. Tools for the detection of QTL that interact are available and are currently being tested. Initial results suggest that epistasis is widespread. Modelling of the first recognised interaction, dominance, continues to be developed. Multigenic interaction appears to be a necessary part of any explanation. This paper covers an attempt to link some of these studies and to draw inferences about useful approaches to understanding and using the genes that influence quantitative traits.

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Hua, J. P., Y. Z. Xing, C. G. Xu, X. L. Sun, S. B. Yu, and Qifa Zhang. "Genetic Dissection of an Elite Rice Hybrid Revealed That Heterozygotes Are Not Always Advantageous for Performance." Genetics 162, no. 4 (December 1, 2002): 1885–95. http://dx.doi.org/10.1093/genetics/162.4.1885.

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Abstract We introduced an experimental design that produced an “immortalized F2” population allowing for complete dissection of genetic components underlying quantitative traits. Data for yield and three component traits of the immortalized F2 were collected from replicated field trials over 2 years. Using 231 marker loci, we resolved the genetic effects into individual components and assessed relative performance of all the genotypes at both single- and two-locus levels. Single-locus analysis detected 40 QTL for the four traits. Dominance effects for about one-half of the QTL were negative, resulting in little “net” positive dominance effect. Correlation between genotype heterozygosity and trait performance was low. Large numbers of digenic interactions, including AA, AD, and DD, were detected for all the traits, with AA as the most prevalent interaction. Complementary two-locus homozygotes frequently performed the best among the nine genotypes of many two-locus combinations. While cumulative small advantages over two-locus combinations may partly explain the genetic basis of heterosis of the hybrid as double heterozygotes frequently demonstrated marginal advantages, double heterozygotes were never the best genotypes in any of the two-locus combinations. It was concluded that heterozygotes were not necessarily advantageous for trait performance even among genotypes derived from such a highly heterotic hybrid.

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Korol, A. B., Y. I. Ronin, and V. M. Kirzhner. "Interval mapping of quantitative trait loci employing correlated trait complexes." Genetics 140, no. 3 (July 1, 1995): 1137–47. http://dx.doi.org/10.1093/genetics/140.3.1137.

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Abstract An approach to increase the resolution power of interval mapping of quantitative trait (QT) loci is proposed, based on analysis of correlated trait complexes. For a given set of QTs, the broad sense heritability attributed to a QT locus (QTL) (say, A/a) is an increasing function of the number of traits. Thus, for some traits x and y, H(xy)2(A/a) > or = H(x)2(A/a). The last inequality holds even if y does not depend on A/a at all, but x and y are correlated within the groups AA, Aa and aa due to nongenetic factors and segregation of genes from other chromosomes. A simple relationship connects H2 (both in single trait and two-trait analysis) with the expected LOD value, ELOD = -1/2N log(1-H2). Thus, situations could exist that from the inequality H(xy)2(A/a) > or = H(x)2(A/a) a higher resolution is provided by the two-trait analysis as compared to the single-trait analysis, in spite of the increased number of parameters. Employing LOD-score procedure to simulated backcross data, we showed that the resolution power of the QTL mapping model can be elevated if correlation between QTs is taken into account. The method allows us to test numerous biologically important hypotheses concerning manifold effects of genomic segments on the defined trait complex (means, variances and correlations).

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Korol, Abraham B., Yefim I. Ronin, Alexander M. Itskovich, Junhua Peng, and Eviatar Nevo. "Enhanced Efficiency of Quantitative Trait Loci Mapping Analysis Based on Multivariate Complexes of Quantitative Traits." Genetics 157, no. 4 (April 1, 2001): 1789–803. http://dx.doi.org/10.1093/genetics/157.4.1789.

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AbstractAn approach to increase the efficiency of mapping quantitative trait loci (QTL) was proposed earlier by the authors on the basis of bivariate analysis of correlated traits. The power of QTL detection using the log-likelihood ratio (LOD scores) grows proportionally to the broad sense heritability. We found that this relationship holds also for correlated traits, so that an increased bivariate heritability implicates a higher LOD score, higher detection power, and better mapping resolution. However, the increased number of parameters to be estimated complicates the application of this approach when a large number of traits are considered simultaneously. Here we present a multivariate generalization of our previous two-trait QTL analysis. The proposed multivariate analogue of QTL contribution to the broad-sense heritability based on interval-specific calculation of eigenvalues and eigenvectors of the residual covariance matrix allows prediction of the expected QTL detection power and mapping resolution for any subset of the initial multivariate trait complex. Permutation technique allows chromosome-wise testing of significance for the whole trait complex and the significance of the contribution of individual traits owing to: (a) their correlation with other traits, (b) dependence on the chromosome in question, and (c) both a and b. An example of application of the proposed method on a real data set of 11 traits from an experiment performed on an F2/F3 mapping population of tetraploid wheat (Triticum durum × T. dicoccoides) is provided.

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Strauss, S. H., R. Lande, and G. Namkoong. "Limitations of molecular-marker-aided selection in forest tree breeding." Canadian Journal of Forest Research 22, no. 7 (July 1, 1992): 1050–61. http://dx.doi.org/10.1139/x92-140.

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The advances to date with quantitative trait locus identification in agronomic crops, which have mostly been with studies of inter- and intra-specific hybrids, are of little relevance to assessing the potential for marker-aided selection in nonhybrid forest tree populations. Although molecular markers provide great opportunities for dissection of quantitative traits in experimental populations, we expect that their near-term usefulness in most operational tree breeding programs will be limited. In addition to cost, this limitation results from quantitative trait locus–marker associations being limited to specific genetic backgrounds as a result of linkage equilibrium, interactions of quantitative trait locus effects with genetic backgrounds, genotype by environment interaction, and changes of quantitative trait locus allele frequencies among generations. Marker-aided selection within individually mapped full-sib families can substantially aid phenotypic selection, but only where large restrictions of genetic base are tolerated, trait heritabilities are low, markers are able to explain much of the additive variance, selection intensities within families are high compared with that among families, and very large numbers of progeny are examined. Broad use of marker-aided selection in the longer term will require substantial technical advances in a number of areas, including means for precise quantitative trait locus identification; reduction of large-scale mapping and genotyping costs; and changes in breeding and propagation systems. Consideration of trait characteristics suggests that marker-aided selection will be most efficient in direct selection with high-value, low-heritability traits such as height and diameter growth. These traits, however, often show genotype by environment interaction and unfavorable genetic correlations with other desirable traits, and are likely to be controlled by a large number of minor genes rather than relatively few major ones. Traits with the most potential for marker-aided selection in nonhybrid tree populations will therefore be strongly inherited ones for which phenotypic assay is difficult; examples might include wood quality, resistance to biotrophic pathogens, and resistance to air pollutants. Because of the large disequilibrium generated during hybridization and the great phenotypic variance that segregates in F2 and backcross generations, interspecific hybrid programs lend themselves much more readily to marker-aideed selection. Segregation distortion and related meiotic aberrations, however, may substantially hamper precise estimation of quantitative trait locus locations and phenotypic effects. Nonadditive quantitative trait locus effects will likely be greater in hybrid populations than in intraspecific populations. Rapid decay of disequilibrium due to recombination, and allele frequency shifts due to selective breeding and natural selection during early generations after hybridization, are likely to cause instability for quantitative trait locus - marker associations and quantitative trait locus phenotypic effects. Finally, interspecific hybridization of highly heterozygous individuals from species in linkage equilibrium will impede marker-aided selection.

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Scoville, Alison G., Young Wha Lee, John H. Willis, and John K. Kelly. "Explaining the heritability of an ecologically significant trait in terms of individual quantitative trait loci." Biology Letters 7, no. 6 (June 8, 2011): 896–98. http://dx.doi.org/10.1098/rsbl.2011.0409.

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Most natural populations display substantial genetic variation in behaviour, morphology, physiology, life history and the susceptibility to disease. A major challenge is to determine the contributions of individual loci to variation in complex traits. Quantitative trait locus (QTL) mapping has identified genomic regions affecting ecologically significant traits of many species. In nearly all cases, however, the importance of these QTLs to population variation remains unclear. In this paper, we apply a novel experimental method to parse the genetic variance of floral traits of the annual plant Mimulus guttatus into contributions of individual QTLs. We first use QTL-mapping to identify nine loci and then conduct a population-based breeding experiment to estimate V Q , the genetic variance attributable to each QTL. We find that three QTLs with moderate effects explain up to one-third of the genetic variance in the natural population. Variation at these loci is probably maintained by some form of balancing selection. Notably, the largest effect QTLs were relatively minor in their contribution to heritability.

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Lin, Jing-Zhong, and Kermit Ritland. "Quantitative Trait Loci Differentiating the Outbreeding Mimulus guttatus From the Inbreeding M. platycalyx." Genetics 146, no. 3 (July 1, 1997): 1115–21. http://dx.doi.org/10.1093/genetics/146.3.1115.

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Theoretical predictions about the evolution of selfing depend on the genetic architecture of loci controlling selfing (monogenic vs. polygenic determination, large vs. small effect of alleles, dominance vs. recessiveness), and studies of such architecture are lacking. We inferred the genetic basis of mating system differences between the outbreeding Mimulus guttatus and the inbreeding M. platycalyx by quantitative trait locus (QTL) mapping using random amplified polymorphic DNA and isozyme markers. One to three QTL were detected for each of five mating system characters, and each QTL explained 7.6–28.6% of the phenotypic variance. Taken together, QTL accounted for up to 38% of the variation in mating system characters, and a large proportion of variation was unaccounted for. Inferred QTL often affected more than one trait, contributing to the genetic correlation between those traits. These results are consistent with the hypothesis that quantitative variation in plant mating system characters is primarily controlled by loci with small effect.

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Gutiérrez-Gil, B., M. F. El-Zarei, L. Alvarez, Y. Bayón, L. F. de la Fuente, F. San Primitivo, and J. J. Arranz. "Quantitative trait loci underlying milk production traits in sheep." Animal Genetics 40, no. 4 (August 2009): 423–34. http://dx.doi.org/10.1111/j.1365-2052.2009.01856.x.

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Gao, Y., Z. Q. Du, W. H. Wei, X. J. Yu, X. M. Deng, C. G. Feng, J. Fei, J. D. Feng, N. Li, and X. X. Hu. "Mapping quantitative trait loci regulating chicken body composition traits." Animal Genetics 40, no. 6 (December 2009): 952–54. http://dx.doi.org/10.1111/j.1365-2052.2009.01911.x.

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40

Song, Xianliang, and Tianzhen Zhang. "Quantitative trait loci controlling plant architectural traits in cotton." Plant Science 177, no. 4 (October 2009): 317–23. http://dx.doi.org/10.1016/j.plantsci.2009.05.015.

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41

Şahin-Çevik, Mehtap, and Gloria A. Moore. "Quantitative trait loci analysis of morphological traits in Citrus." Plant Biotechnology Reports 6, no. 1 (August 30, 2011): 47–57. http://dx.doi.org/10.1007/s11816-011-0194-z.

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42

Yang, Runqing, Jiahan Li, and Shizhong Xu. "Mapping quantitative trait loci for traits defined as ratios." Genetica 132, no. 3 (August 2, 2007): 323–29. http://dx.doi.org/10.1007/s10709-007-9175-0.

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Šimić, Domagoj, Snežana Mladenović Drinić, Zvonimir Zdunić, Antun Jambrović, Tatjana Ledenčan, Josip Brkić, Andrija Brkić, and Ivan Brkić. "Quantitative Trait Loci for Biofortification Traits in Maize Grain." Journal of Heredity 103, no. 1 (November 9, 2011): 47–54. http://dx.doi.org/10.1093/jhered/esr122.

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44

Lightfoot, J. Timothy, Michael J. Turner, Daniel Pomp, Steven R. Kleeberger, and Larry J. Leamy. "Quantitative trait loci for physical activity traits in mice." Physiological Genomics 32, no. 3 (February 2008): 401–8. http://dx.doi.org/10.1152/physiolgenomics.00241.2007.

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The genomic locations and identities of the genes that regulate voluntary physical activity are presently unknown. The purpose of this study was to search for quantitative trait loci (QTL) that are linked with daily mouse running wheel distance, duration, and speed of exercise. F2 animals ( n = 310) derived from high active C57L/J and low active C3H/HeJ inbred strains were phenotyped for 21 days. After phenotyping, genotyping with a fully informative single-nucleotide polymorphism panel with an average intermarker interval of 13.7 cM was used. On all three activity indexes, sex and strain were significant factors, with the F2 animals similar to the high active C57L/J mice in both daily exercise distance and duration of exercise. In the F2 cohort, female mice ran significantly farther, longer, and faster than male mice. QTL analysis revealed no sex-specific QTL but at the 5% experimentwise significance level did identify one QTL for duration, one QTL for distance, and two QTL for speed. The QTL for duration ( DUR13.1) and distance ( DIST13.1) colocalized with the QTL for speed ( SPD13.1). Each of these QTL accounted for ∼6% of the phenotypic variance, whereas SPD9.1 (chromosome 9, 7 cM) accounted for 11.3% of the phenotypic variation. DUR13.1, DIST13.1, SPD13.1, and SPD9.1 were subsequently replicated by haplotype association mapping. The results of this study suggest a genetic basis of voluntary activity in mice and provide a foundation for future candidate gene studies.

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45

Aminafshar, Mehdi, Mojtaba Hosseinpour Mashhadi, and Laleh jamsi. "Genetic evaluation of animals with and without using genotypic data of major gene loci." Proceedings of the British Society of Animal Science 2007 (April 2007): 153. http://dx.doi.org/10.1017/s1752756200020561.

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Now a days, scientists like to find about association of major genes and quantitative traits. In the first step, breeding value of quantitative trait should be predicted and genotype of animals for special major gene locus should be detected. Then, GLM analyses are used to compare all levels of genotypes and study about their association with quantitative traits. The accuracy of prediction of breeding value may influence the result of analyses. Different models with different accuracy of prediction may be utilized to predict breeding value. In this article, different models, with and without using the Genotypic Data of Major Genes Loci were used in order to identify the better model for genetic evaluation in this situation.

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46

NIELSEN, DAHLIA M., and B. S. WEIR. "A classical setting for associations between markers and loci affecting quantitative traits." Genetical Research 74, no. 3 (December 1999): 271–77. http://dx.doi.org/10.1017/s0016672399004231.

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We examine the relationships between a genetic marker and a locus affecting a quantitative trait by decomposing the genetic effects of the marker locus into additive and dominance effects under a classical genetic model. We discuss the structure of the associations between the marker and the trait locus, paying attention to non-random union of gametes, multiple alleles at the marker and trait loci, and non-additivity of allelic effects at the trait locus. We consider that this greater-than-usual level of generality leads to additional insights, in a way reminiscent of Cockerham's decomposition of genetic variance into five terms: three terms in addition to the usual additive and dominance terms. Using our framework, we examine several common tests of association between a marker and a trait.

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Mackinnon, M. J., and M. A. Georges. "The effects of selection on linkage analysis for quantitative traits." Genetics 132, no. 4 (December 1, 1992): 1177–85. http://dx.doi.org/10.1093/genetics/132.4.1177.

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Abstract The effects of within-sample selection on the outcome of analyses detecting linkage between genetic markers and quantitative traits were studied. It was found that selection by truncation for the trait of interest significantly reduces the differences between marker genotype means thus reducing the power to detect linked quantitative trait loci (QTL). The size of this reduction is a function of proportion selected, the magnitude of the QTL effect, recombination rate between the marker locus and the QTL, and the allele frequency of the QTL. Proportion selected was the most influential of these factors on bias, e.g., for an allele substitution effect of one standard deviation unit, selecting the top 80%, 50% or 20% of the population required 2, 6 or 24 times the number of progeny, respectively, to offset the loss of power caused by this selection. The effect on power was approximately linear with respect to the size of gene effect, almost invariant to recombination rate, and a complex function of QTL allele frequency. It was concluded that experimental samples from animal populations which have been subjected to even minor amounts of selection will be inefficient in yielding information on linkage between markers and loci influencing the quantitative trait under selection.

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Wang, Xingyi, Hui Liu, Md Sultan Mia, Kadambot H. M. Siddique, and Guijun Yan. "Development of near-isogenic lines targeting a major QTL on 3AL for pre-harvest sprouting resistance in bread wheat." Crop and Pasture Science 69, no. 9 (2018): 864. http://dx.doi.org/10.1071/cp17423.

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Resistance to pre-harvest sprouting (PHS) in wheat (Triticum aestivum L.) is one of the most valuable traits in many breeding programs. However, the quantitative nature of inheritance of PHS resistance challenges the study of this trait. Near-isogenic lines (NILs) can turn a complicated quantitative trait into a Mendelian factor (qualitative) and are, therefore, valuable materials for identification of the gene(s) responsible for a specific phenotypic trait and for functional studies of specific loci. Five pairs of NILs were developed and confirmed for a major quantitative trait locus (QTL) located on the long arm of chromosome 3A contributing to PHS resistance in wheat. These NILs were generated by using the heterogeneous inbred family method and a fast generation-cycling system. Significant differences in PHS resistance between the isolines were detected in the NILs. The presence of the PHS-resistance allele from the resistant parent increased resistance to sprouting on spikes by 26.7–96.8%, with an average of 73.8%, and increased seed dormancy by 36.9–87.2%, with an average of 59.9% across the NILs. These NILs are being used for the identification of candidate genes responsible for this major PHS-resistance locus on wheat chromosome arm 3AL.

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Allard, R. W. "Genetic Changes Associated with the Evolution of Adaptedness in Cultivated Plants and Their Wild Progenitors." Journal of Heredity 79, no. 4 (July 1, 1988): 225–38. http://dx.doi.org/10.1093/oxfordjournals.jhered.a110503.

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Abstract The results of long-term studies of changes in adaptedness in a number of experimental populations of annual plants are summarized. Measurements made of quantitative traits showed that cumulative increases in reproductive capacity continued in these experimental populations for more than 50 generations. Highly significant allelic frequency changes also occurred for marker loci governing morphological variants, disease resistance, allozymes, and rDNA restriction fragments. Individual effects of the marker loci on quantitative traits were determined by extensive progeny testing of selfed families descended from single plants isolated from various generations of the experimental populations. Comparisons between homozygotes and heterozygotes of marker loci for quantitative trait expression revealed that all the marker loci studied had statistically significant additive effects on several to many quantitative traits; thus, each Mendelian locus, in addition to being a locus for its discrete descriptive effect, was also a locus for several quantitative traits. Consistent associations were found between superior reproductive capacity (e.g., larger numbers of kernels per plant) and the alleles of marker loci that Increased in frequency over generations; no other quantitative traits measured were clearly and consistently associated with alleles that increased in frequency. Multilocus analyses based on canonical correlation, log linear, and cluster analysis procedures showed that highly significant associations developed in early generations among alleles of different loci in all the predominantly selfing populations studied. Dynamic changes featuring amalgamations of alleles into fewer clusters involving larger numbers of loci continued into the late generations. Patterns of ecogenetic differentiation that developed under predominant selling were found to be fine-scaled overlays of environmental heterogeneity. The picture of evolutionary change that emerges is one in which the incorporation of Increasing numbers of favorably interacting alleles into large synergistic complexes was accompanied in inbreeding populations by increases in adaptedness to the local environment and also by striking ecogenetic differentiation among local populations that occupy unlike habitats, including differentiation between cultivated plants and their wild progenitors. Selfing appears to promote the development and maintenance of adaptedness within populations and at the same time to facilitate the development of spatial differentiation by retarding gene flow between populations. Patterns of adaptive change in outbreeding populations, although similar to those of inbreeders in most particulars, featured less distinct multilocus structural organization within, as well as much less distinct ecogeographical differentiation among, populations.

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Jermstad, Kathleen D., Daniel L. Bassoni, Keith S. Jech, Gary A. Ritchie, Nicholas C. Wheeler, and David B. Neale. "Mapping of Quantitative Trait Loci Controlling Adaptive Traits in Coastal Douglas Fir. III. Quantitative Trait Loci-by-Environment Interactions." Genetics 165, no. 3 (November 1, 2003): 1489–506. http://dx.doi.org/10.1093/genetics/165.3.1489.

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Abstract Quantitative trait loci (QTL) were mapped in the woody perennial Douglas fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) for complex traits controlling the timing of growth initiation and growth cessation. QTL were estimated under controlled environmental conditions to identify QTL interactions with photoperiod, moisture stress, winter chilling, and spring temperatures. A three-generation mapping population of 460 cloned progeny was used for genetic mapping and phenotypic evaluations. An all-marker interval mapping method was used for scanning the genome for the presence of QTL and single-factor ANOVA was used for estimating QTL-by-environment interactions. A modest number of QTL were detected per trait, with individual QTL explaining up to 9.5% of the phenotypic variation. Two QTL-by-treatment interactions were found for growth initiation, whereas several QTL-by-treatment interactions were detected among growth cessation traits. This is the first report of QTL interactions with specific environmental signals in forest trees and will assist in the identification of candidate genes controlling these important adaptive traits in perennial plants.

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Journal articles on the topic 'Quantitative trait locis'

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