Journal articles: 'Quantitative trait analyses'

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Jiang, C., and Z. B. Zeng. "Multiple trait analysis of genetic mapping for quantitative trait loci." Genetics 140, no. 3 (July 1, 1995): 1111–27. http://dx.doi.org/10.1093/genetics/140.3.1111.

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Abstract We present in this paper models and statistical methods for performing multiple trait analysis on mapping quantitative trait loci (QTL) based on the composite interval mapping method. By taking into account the correlated structure of multiple traits, this joint analysis has several advantages, compared with separate analyses, for mapping QTL, including the expected improvement on the statistical power of the test for QTL and on the precision of parameter estimation. Also this joint analysis provides formal procedures to test a number of biologically interesting hypotheses concerning the nature of genetic correlations between different traits. Among the testing procedures considered are those for joint mapping, pleiotropy, QTL by environment interaction, and pleiotropy vs. close linkage. The test of pleiotropy (one pleiotropic QTL at a genome position) vs. close linkage (multiple nearby nonpleiotropic QTL) can have important implications for our understanding of the nature of genetic correlations between different traits in certain regions of a genome and also for practical applications in animal and plant breeding because one of the major goals in breeding is to break unfavorable linkage. Results of extensive simulation studies are presented to illustrate various properties of the analyses.

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Nichols, Krista M., Paul A. Wheeler, and Gary H. Thorgaard. "Quantitative Trait Loci Analyses for Meristic Traits in Oncorhynchus mykiss." Environmental Biology of Fishes 69, no. 1-4 (March 2004): 317–31. http://dx.doi.org/10.1023/b:ebfi.0000022905.72702.0e.

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Goffinet, Bruno, and Sophie Gerber. "Quantitative Trait Loci: A Meta-analysis." Genetics 155, no. 1 (May 1, 2000): 463–73. http://dx.doi.org/10.1093/genetics/155.1.463.

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Abstract This article presents a method to combine QTL results from different independent analyses. This method provides a modified Akaike criterion that can be used to decide how many QTL are actually represented by the QTL detected in different experiments. This criterion is computed to choose between models with one, two, three, etc., QTL. Simulations are carried out to investigate the quality of the model obtained with this method in various situations. It appears that the method allows the length of the confidence interval of QTL location to be consistently reduced when there are only very few “actual” QTL locations. An application of the method is given using data from the maize database available online at http://www.agron.missouri.edu/.

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Hardy, John, Danyah Trabzuni, and Mina Ryten. "Whole genome expression as a quantitative trait." Biochemical Society Transactions 37, no. 6 (November 19, 2009): 1276–77. http://dx.doi.org/10.1042/bst0371276.

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Surprisingly, whole genome analyses of complex human neurological and psychiatric disorders have revealed that many genetic risk factors are likely to influence gene expression rather than alter protein sequences. Previous analyses of neurological diseases have shown that genetic variability in gene expression levels of deposited proteins influence disease risk. With this background, we have embarked on a comprehensive project to determine the effects of common genetic variability on whole genome gene expression.

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Müller-Myhsok, B., and T. Grimm. "Linkage analysis and genetic models in dyslexia — considerations pertaining to discrete trait analysis and quantitative trait analyses." European Child & Adolescent Psychiatry 8, S3 (September 1999): S40—S42. http://dx.doi.org/10.1007/pl00010692.

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Wilcox, Marsha A., Diego F. Wyszynski, Carolien I. Panhuysen, Qianli Ma, Agustin Yip, John Farrell, and Lindsay A. Farrer. "Empirically derived phenotypic subgroups – qualitative and quantitative trait analyses." BMC Genetics 4, Suppl 1 (2003): S15. http://dx.doi.org/10.1186/1471-2156-4-s1-s15.

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Plomin, Robert, and Gerald E. McClearn. "Quantitative trait loci (QTL) analyses and alcohol-related behaviors." Behavior Genetics 23, no. 2 (March 1993): 197–211. http://dx.doi.org/10.1007/bf01067425.

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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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Xiong, Xinwei, Hui Yang, Bin Yang, Congying Chen, and Lusheng Huang. "Identification of quantitative trait transcripts for growth traits in the large scales of liver and muscle samples." Physiological Genomics 47, no. 7 (July 2015): 274–80. http://dx.doi.org/10.1152/physiolgenomics.00005.2015.

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Growth-related traits are economically important traits to the pig industry. Identification of causative gene and mutation responsible for growth-related QTL will facilitate the improvement of pig growth through marker-assisted selection. In this study, we applied whole genome gene expression and quantitative trait transcript (QTT) analyses in 497 liver and 586 longissimus dorsi muscle samples to identify candidate genes and dissect the genetic basis of pig growth in a white Duroc × Erhualian F2 resource population. A total of 20,108 transcripts in liver and 23,728 transcripts in muscle with expression values were used for association analysis between gene expression level and phenotypic value. At the significance threshold of P < 0.0005, we identified a total of 169 and 168 QTTs for nine growth-related traits in liver and muscle, respectively. We also found that some QTTs were correlated to more than one trait. The QTTs identified here showed high tissue specificity. We did not identify any QTTs that were associated with one trait in both liver and muscle. Through an integrative genomic approach, we identified SDR16C5 as the important candidate gene in pig growth trait. These findings contribute to further identification of the causative genes for porcine growth traits and facilitate improvement of pig breeding.

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HERNÁNDEZ-SÁNCHEZ, J., A. CHATZIPLI, D. BERALDI, J. GRATTEN, J. G. PILKINGTON, and J. M. PEMBERTON. "Mapping quantitative trait loci in a wild population using linkage and linkage disequilibrium analyses." Genetics Research 92, no. 4 (August 2010): 273–81. http://dx.doi.org/10.1017/s0016672310000340.

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SummaryHistorical information can be used, in addition to pedigree, traits and genotypes, to map quantitative trait locus (QTL) in general populations via maximum likelihood estimation of variance components. This analysis is known as linkage disequilibrium (LD) and linkage mapping, because it exploits both linkage in families and LD at the population level. The search for QTL in the wild population of Soay sheep on St. Kilda is a proof of principle. We analysed the data from a previous study and confirmed some of the QTLs reported. The most striking result was the confirmation of a QTL affecting birth weight that had been reported using association tests but not when using linkage-based analyses.

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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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ERICKSON, DAVID L., CHARLES B. FENSTER, HANS K. STENOIEN, and DONALD PRICE. "Quantitative trait locus analyses and the study of evolutionary process." Molecular Ecology 13, no. 9 (September 2004): 2505–22. http://dx.doi.org/10.1111/j.1365-294x.2004.02254.x.

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Seo, Ji-Heui, Qiyuan Li, Aquila Fatima, Aron Eklund, Zoltan Szallasi, Kornelia Polyak, Andrea L. Richardson, and Matthew L. Freedman. "Deconvoluting complex tissues for expression quantitative trait locus-based analyses." Philosophical Transactions of the Royal Society B: Biological Sciences 368, no. 1620 (June 19, 2013): 20120363. http://dx.doi.org/10.1098/rstb.2012.0363.

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Breast cancer genome-wide association studies have pinpointed dozens of variants associated with breast cancer pathogenesis. The majority of risk variants, however, are located outside of known protein-coding regions. Therefore, identifying which genes the risk variants are acting through presents an important challenge. Variants that are associated with mRNA transcript levels are referred to as expression quantitative trait loci (eQTLs). Many studies have demonstrated that eQTL-based strategies provide a direct way to connect a trait-associated locus with its candidate target gene. Performing eQTL-based analyses in human samples is complicated because of the heterogeneous nature of human tissue. We addressed this issue by devising a method to computationally infer the fraction of cell types in normal human breast tissues. We then applied this method to 13 known breast cancer risk loci, which we hypothesized were eQTLs. For each risk locus, we took all known transcripts within a 2 Mb interval and performed an eQTL analysis in 100 reduction mammoplasty cases. A total of 18 significant associations were discovered (eight in the epithelial compartment and 10 in the stromal compartment). This study highlights the ability to perform large-scale eQTL studies in heterogeneous tissues.

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HAO, J. J., S. X. YU, Z. D. DONG, S. L. FAN, Q. X. MA, M. Z. SONG, and J. W. YU. "Quantitative inheritance of leaf morphological traits in upland cotton." Journal of Agricultural Science 146, no. 5 (May 23, 2008): 561–69. http://dx.doi.org/10.1017/s0021859608007892.

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SUMMARYGenetic manipulation of leaf architecture may be a useful breeding objective in cotton (Gossypiumspp.). The present study reports quantitative genetic analysis of leaf traits from two intraspecific crosses of inbred lines in upland cotton (Gossypium hirsutumL.) viz. Kang3×Chaoji463 and Han109×Ji98. Six leaf morphological traits (leaf area (LA), leaf perimeter (LP), main lobe length (LL) and width (LW), petiole length (PL), and main LL/LW ratio) were recorded from multiple generations (P1, F1, P2, BC1, BC2, and F2) in the two crosses. Generation mean analyses were conducted to explain the inheritance of each leaf morphological trait. The six-parameter model showed a better fit to an additive-dominance model for LA, main LW, PL, and main LL/LW ratio in the two crosses, suggesting the relative importance of epistatic effects controlling leaf morphology. A simple additive-dominance model accounted for the genetic variation of the main LL in the Kang3×Chaoji463 cross. Different models were selected as appropriate to explain LP in the two crosses. The differences between broad- and narrow-sense heritability values for the same trait were not constant in the two crosses. The estimated minimum number of genes controlling each leaf morphological trait ranged from 0 to 2 for both the crosses. Moreover, the sums of the minimum number of genes controlling leaf morphology were 6 and 2 in the Kang3×Chaoji463 and Han109×Ji98 populations, respectively. Most data suggested that there existed a substantial opportunity to breed cottons that transgress the present range of leaf phenotypes found.

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Howe, Glenn T., Sally N. Aitken, David B. Neale, Kathleen D. Jermstad, Nicholas C. Wheeler, and Tony HH Chen. "From genotype to phenotype: unraveling the complexities of cold adaptation in forest trees." Canadian Journal of Botany 81, no. 12 (December 1, 2003): 1247–66. http://dx.doi.org/10.1139/b03-141.

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Adaptation to winter cold in temperate and boreal trees involves complex genetic, physiological, and developmental processes. Genecological studies demonstrate the existence of steep genetic clines for cold adaptation traits in relation to environmental (mostly temperature related) gradients. Population differentiation is generally stronger for cold adaptation traits than for other quantitative traits and allozymes. Therefore, these traits appear to be under strong natural selection. Nonetheless, high levels of genetic variation persist within populations. The genetic control of cold adaptation traits ranges from weak to strong, with phenological traits having the highest heritabilities. Within-population genetic correlations among traits range from negligible to moderate. Generally, bud phenology and cold hardiness in the fall are genetically uncorrelated with bud phenology and cold hardiness in the spring. Analyses of quantitative trait loci indicate that cold adaptation traits are mostly controlled by multiple genes with small effects and that quantitative trait loci × environment interactions are common. Given this inherent complexity, we suggest that future research should focus on identifying and developing markers for cold adaptation candidate genes, then using multilocus, multi allelic analytical techniques to uncover the relationships between genotype and phenotype at both the individual and population levels. Ultimately, these methods may be useful for predicting the performance of genotypes in breeding programs and for better understanding the evolutionary ecology of forest trees.Key words: association genetics, cold hardiness, dormancy, genecology, bud phenology, quantitative trait loci.

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Meyer, Karin, and Mark Kirkpatrick. "Up hill, down dale: quantitative genetics of curvaceous traits." Philosophical Transactions of the Royal Society B: Biological Sciences 360, no. 1459 (July 7, 2005): 1443–55. http://dx.doi.org/10.1098/rstb.2005.1681.

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‘Repeated’ measurements for a trait and individual, taken along some continuous scale such as time, can be thought of as representing points on a curve, where both means and covariances along the trajectory can change, gradually and continually. Such traits are commonly referred to as ‘function-valued’ (FV) traits. This review shows that standard quantitative genetic concepts extend readily to FV traits, with individual statistics, such as estimated breeding values and selection response, replaced by corresponding curves, modelled by respective functions. Covariance functions are introduced as the FV equivalent to matrices of covariances. Considering the class of functions represented by a regression on the continuous covariable, FV traits can be analysed within the linear mixed model framework commonly employed in quantitative genetics, giving rise to the so-called random regression model. Estimation of covariance functions, either indirectly from estimated covariances or directly from the data using restricted maximum likelihood or Bayesian analysis, is considered. It is shown that direct estimation of the leading principal components of covariance functions is feasible and advantageous. Extensions to multi-dimensional analyses are discussed.

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Knott, Sara A., and Chris S. Haley. "Multitrait Least Squares for Quantitative Trait Loci Detection." Genetics 156, no. 2 (October 1, 2000): 899–911. http://dx.doi.org/10.1093/genetics/156.2.899.

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Abstract A multiple-trait QTL mapping method using least squares is described. It is presented as an extension of a single-trait method for use with three-generation, outbred pedigrees. The multiple-trait framework allows formal testing of whether the same QTL affects more than one trait (i.e., a pleiotropic QTL) or whether more than one linked QTL are segregating. Several approaches to the testing procedure are presented and their suitability discussed. The performance of the method is investigated by simulation. As previously found, multitrait analyses increase the power to detect a pleiotropic QTL and the precision of its location estimate. With enough information, discrimination between alternative genetic models is possible.

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ABDALLAH, JIHAD M., BRIGITTE MANGIN, BRUNO GOFFINET, CHRISTINE CIERCO-AYROLLES, and MIGUEL PÉREZ-ENCISO. "A comparison between methods for linkage disequilibrium fine mapping of quantitative trait loci." Genetical Research 83, no. 1 (February 2004): 41–47. http://dx.doi.org/10.1017/s0016672303006554.

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We present a maximum likelihood method for mapping quantitative trait loci that uses linkage disequilibrium information from single and multiple markers. We made paired comparisons between analyses using a single marker, two markers and six markers. We also compared the method to single marker regression analysis under several scenarios using simulated data. In general, our method outperformed regression (smaller mean square error and confidence intervals of location estimate) for quantitative trait loci with dominance effects. In addition, the method provides estimates of the frequency and additive and dominance effects of the quantitative trait locus.

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Paran, I., I. Goldman, and D. Zamir. "QTL analysis of morphological traits in a tomato recombinant inbred line population." Genome 40, no. 2 (April 1, 1997): 242–48. http://dx.doi.org/10.1139/g97-034.

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Quantitative trait loci (QTLs) influencing morphological traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RILs) derived from a cross of the cultivated tomato Lycopersicon esculentum with a related wild species, Lycopersicon cheesmanii. One hundred and thirty-two RFLP loci spaced throughout the tomato genome were used as DNA probes on genomic DNA from 97 RIL families. Morphological traits, including plant height, plant fresh mass, number of branches, number of nodes, first flower-bearing node, and leaf length, were evaluated in two controlled environment trials in 1992 and 1993. QTLs were detected via regression analyses at multiple marker loci for each morphological trait. A total of 41 markers were significantly associated with the traits examined. Large additive effects were measured at many of these loci. QTLs for multiple traits were detected on chromosomes 3 (TG74) and 4 (CT188), suggesting the possible association of these chromosome segments with genes controlling growth and development in tomato. These chromosomal regions were also associated with multiple morphological traits in a L. esculentum × Lycopersicon pennellii cross. A total of 13% of the QTLs identified for traits common to both studies occupied similar map positions.Key words: Lycopersicon, quantitative trait, restriction fragment length polymorphism.

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Wang, Cheng, Huangai Li, Yan Long, Zhenying Dong, Jianhui Wang, Chang Liu, Xun Wei, and Xiangyuan Wan. "A Systemic Investigation of Genetic Architecture and Gene Resources Controlling Kernel Size-Related Traits in Maize." International Journal of Molecular Sciences 24, no. 2 (January 5, 2023): 1025. http://dx.doi.org/10.3390/ijms24021025.

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Grain yield is the most critical and complex quantitative trait in maize. Kernel length (KL), kernel width (KW), kernel thickness (KT) and hundred-kernel weight (HKW) associated with kernel size are essential components of yield-related traits in maize. With the extensive use of quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) analyses, thousands of QTLs and quantitative trait nucleotides (QTNs) have been discovered for controlling these traits. However, only some of them have been cloned and successfully utilized in breeding programs. In this study, we exhaustively collected reported genes, QTLs and QTNs associated with the four traits, performed cluster identification of QTLs and QTNs, then combined QTL and QTN clusters to detect consensus hotspot regions. In total, 31 hotspots were identified for kernel size-related traits. Their candidate genes were predicted to be related to well-known pathways regulating the kernel developmental process. The identified hotspots can be further explored for fine mapping and candidate gene validation. Finally, we provided a strategy for high yield and quality maize. This study will not only facilitate causal genes cloning, but also guide the breeding practice for maize.

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Gauderman, W. James, Cheryl L. Faucett, John L. Morrison, and Catherine L. Carpenter. "Joint segregation and linkage analysis of a quantitative trait compared to separate analyses." Genetic Epidemiology 14, no. 6 (1997): 993–98. http://dx.doi.org/10.1002/(sici)1098-2272(1997)14:6<993::aid-gepi72>3.0.co;2-f.

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Nalaila, Sungael, Paul Stothard, Stephen Moore, Zhiquan Wang, and Changxi Li. "Whole genome fine mapping of quantitative trait loci for ultrasound and carcass merit traits in beef cattle." Canadian Journal of Animal Science 91, no. 1 (March 2011): 61–73. http://dx.doi.org/10.4141/cjas10007.

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Nalaila, S. M., Stothard, P., Moore, S. S., Wang, Z. and Li, C. 2011. Whole genome fine mapping of quantitative trait loci for ultrasound and carcass merit traits in beef cattle. Can. J. Anim. Sci. 91: 61–73. Quantitative trait loci (QTL) mapped to large chromosomal regions have limited utility as DNA markers for marker-assisted selection (MAS) and are less informative as a reference for the identification of the underlying causative quantitative trait nucleotides (QTN). The objective of this study was to conduct a whole genome fine mapping of QTL for ultrasound and carcass merit traits in beef cattle using a greater density of single nucleotide polymorphism (SNP) markers, and to identify SNP markers within the QTL regions that are associated with the traits. A total of 418 steers from 28 sires were used in this study with nine ultrasound and seven carcass merit traits that were collected as part of a feedlot trial conducted from 2003 to 2005 at the University of Alberta Kinsella ranch. Sires and their progeny were genotyped for a total of 4592 SNP markers distributed across all 29 bovine autosomes (BTA). Across-family analyses detected 12 QTL for five ultrasound traits on nine chromosomes and 18 QTL for six carcass merit traits on 10 chromosomes (P<0.05). Within-family analyses identified 78 significant QTL for nine ultrasound and seven carcass merit traits (P<0.01). The use of a denser panel of SNP markers allowed fine mapping of QTL to smaller chromosomal regions ranging from 0.6 to 11 cM compared with relatively larger QTL regions of 4 to 24 cM reported in previous studies. Furthermore, single SNP marker association analyses identified 22 SNPs that were significantly associated with three ultrasound and four carcass merit traits under 12 QTL regions (P<0.05). These identified SNP markers significantly associated with the traits under the fine mapped QTL regions provide genomic tools for potential application of MAS and a reference to assist with the identification of QTN causing variations in ultrasound and carcass merit traits in beef cattle.

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Fu, Hao, R. L. Bohuslavskyi, and L. O. Atramentova. "Inheritance of quantitative traits in F1 hybrids of einkorn wheat." Faktori eksperimental'noi evolucii organizmiv 31 (September 1, 2022): 142–46. http://dx.doi.org/10.7124/feeo.v31.1501.

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Aim. Determine the type of quantitative traits inheritance in einkorn wheat F1 hybrids. Methods. Hybridological and morphometric analyses. Results. In the combination ♀T. urartu × ♂T. sinskajae, the hybrid caryopses did not set; in the reciprocal combination, the set rate was 28 %. In combinations involving T. boeoticum, T. monococcum, T. sinskajae the setting ranged from 37 % to 54 %. In different combinations, hybrids showed overdominance, hybrid depression, dominance of parental traits with a higher and lower trait value, rarely intermediate inheritance. The combinations in which T. sinskajae is involved are of interest due to heterosis in grain weight of per ear, spikelet number in ear, grain number in ear and less hullness. At the same time, the dominance degree for this trait correlates with the indicators of the dominance degree in length, width and area of flag leaf (r: 0.62–0.71). Conclusions. Einkorn hybrids with the participation of naked wheat T. sinskajae are promising in terms of spikelet number per ear, grain number per ear, ear weight, grain weight per ear, reduced hullness.

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Smith, A. B., B. R. Cullis, R. Appels, A. W. Campbell, G. B. Cornish, D. Martin, and H. M. Allen. "The statistical analysis of quality traits in plant improvement programs with application to the mapping of milling yield in wheat." Australian Journal of Agricultural Research 52, no. 12 (2001): 1207. http://dx.doi.org/10.1071/ar01058.

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It is well known that the response to selection for grain yield is improved with the use of appropriate experimental designs and statistical analyses. The issues are more complex for quality traits since the data are obtained from a 2-phase process in which samples are collected from the field then processed in the laboratory. This paper presents a method of analysis for quality trait data that allows for variation arising from both the field and laboratory phases. Initially, an analysis suitable for standard varietal selection is presented. This is extended to include molecular genetic marker information for the purpose of detecting quantitative trait loci. The technique is illustrated using two doubled haploid wheat (Triticum aestivum L.) populations in which the trait of interest is milling yield.

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SHEN, XIA, LARS RÖNNEGÅRD, and ÖRJAN CARLBORG. "How to deal with genotype uncertainty in variance component quantitative trait loci analyses." Genetics Research 93, no. 5 (July 18, 2011): 333–42. http://dx.doi.org/10.1017/s0016672311000152.

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SummaryDealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation–Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.

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Xiao-ping, Lu, Yun Jin-feng, Gao Cui-ping, and Surya Acharya. "Quantitative trait loci analysis of economically important traits in Sorghum bicolor × S. sudanense hybrid." Canadian Journal of Plant Science 91, no. 1 (January 2011): 81–90. http://dx.doi.org/10.4141/cjps09112.

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Lu, X-p., Yun, J-f., Gao, C-p. and Acharya, S. 2011. Quantitative trait loci analysis of economically important traits in Sorghum bicolor×S. sudanense hybrid. Can. J. Plant Sci. 91: 81–90. Many agronomic traits of Sorghum bicolor×S. sudanense hybrid are quantitatively inherited, and the gene mapping of these traits has important research and practical consequences. In this study, genetic mapping and quantitative trait loci (QTL) analyses were conducted using 248 F2:3 plants of a cross between sorghum 314A (female parent) and Sudan grass 2002GZ-1 (male parent). A total of 178 markers (170 amplified fragment length polymorphism and 8 random amplified polymorphic DNA) were employed to construct a linkage map with 10 linkage groups covering 836 cM of the genome. The two parents expressed polymorphism for 10 agronomic characters (plant height, stem diameter, leaf number, leaf length, leaf width, spike length, tiller number, ratio of stem and leaf weight, fresh plant weight and dry plant weight). When analyzed for possible QTLs a total of 98 QTLs were identified in two test sites, out of which 26 QTLs overlapped in both sites. The average number of QTLs per character was found to be 2.6 and the distributions of these QTLs were found to be uneven across linkage groups. This, and the fact that molecular marker densities were not proportional with QTL frequencies, indicates that the detectable QTLs correlated with the agronomic traits and the genetic map can be useful for improvement in relevant characters in Sorghum bicolor×S. sudanense hybrids.

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Ma, B., J. Huang, and L. Liang. "RTeQTL: Real-Time Online Engine for Expression Quantitative Trait Loci Analyses." Database 2014 (July 18, 2014): bau066. http://dx.doi.org/10.1093/database/bau066.

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JIA, ZHENYU, and SHIZHONG XU. "Clustering expressed genes on the basis of their association with a quantitative phenotype." Genetical Research 86, no. 3 (November 25, 2005): 193–207. http://dx.doi.org/10.1017/s0016672305007822.

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Cluster analyses of gene expression data are usually conducted based on their associations with the phenotype of a particular disease. Many disease traits have a clearly defined binary phenotype (presence or absence), so that genes can be clustered based on the differences of expression levels between the two contrasting phenotypic groups. For example, cluster analysis based on binary phenotype has been successfully used in tumour research. Some complex diseases have phenotypes that vary in a continuous manner and the method developed for a binary trait is not immediately applicable to a continuous trait. However, understanding the role of gene expression in these complex traits is of fundamental importance. Therefore, it is necessary to develop a new statistical method to cluster expressed genes based on their association with a quantitative trait phenotype. We developed a model-based clustering method to classify genes based on their association with a continuous phenotype. We used a linear model to describe the relationship between gene expression and the phenotypic value. The model effects of the linear model (linear regression coefficients) represent the strength of the association. We assumed that the model effects of each gene follow a mixture of several multivariate Gaussian distributions. Parameter estimation and cluster assignment were accomplished via an Expectation-Maximization (EM) algorithm. The method was verified by analysing two simulated datasets, and further demonstrated using real data generated in a microarray experiment for the study of gene expression associated with Alzheimer's disease.

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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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Tozlu, Ilhami, Charles L. Guy, and Gloria A. Moore. "QTL analysis of morphological traits in an intergeneric BC1 progeny of Citrus and Poncirus under saline and non-saline environments." Genome 42, no. 5 (October 1, 1999): 1020–29. http://dx.doi.org/10.1139/g99-035.

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The effects of salinization with 40 mM sodium chloride on Poncirus trifoliata (L.) Raf., Citrus grandis (L.) Osb., their F1, and a BC1 progeny population [C. grandis × (F1)] were investigated by measuring growth and dry mass production of different tissues and by QTL (quantitative trait locus) mapping. A total of 36 traits related to growth (six traits) and tissue or whole plant dry mass production (30 traits) in salinized and non-salinized BC1 progeny clones were evaluated. The comparison of the three parental types to the BC1 progeny under control and saline conditions showed that the BC1 progeny plants segregated transgressively for many of these traits. Mapping analyses of these quantitative traits resulted in a total of 70 potential quantitative trait loci (PQTL) with LOD scores greater than or equal to 3.0 located on a previously generated linkage map. Sixty-nine percent of the mapped PQTLs were for traits associated with salinity. The small progeny population size used made further analyses of these PQTLs necessary. By considering LOD scores, map locations, and correlation analyses of the traits, it was possible to identify 16 regions of the citrus genome of interest, six of which were involved in both growth and dry mass production. Correlation analyses and locations of PQTLs indicated that many of these regions may contain one or a few genuine QTLs of large effect. This is a first step in identifying QTLs that have a major impact on growth and dry mass production in Citrus under both optimum and stressful environments.Key words: Citrus grandis, Poncirus trifoliata, salinity stress, QTL mapping, morphological traits, transgressive segregation, NaCl, sodium, chloride, salt tolerance, citrus genetics, breeding.

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Han, Bing, Naomi S. Altman, Jessica A. Mong, Laura Cousino Klein, Donald W. Pfaff, and David J. Vandenbergh. "Comparing Quantitative Trait Loci and Gene Expression Data." Advances in Bioinformatics 2008 (September 16, 2008): 1–6. http://dx.doi.org/10.1155/2008/719818.

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We develop methods to compare the positions of quantitative trait loci (QTL) with a set of genes selected by other methods, such as microarray experiments, from a sequenced genome. We apply our methods to QTL for addictive behavior in mouse, and a set of genes upregulated in a region of the brain associated with addictive behavior, the nucleus accumbens (NA). The association between the QTL and NA genes is not significantly stronger than expected by chance. However, chromosomes 2 and 16 do show strong associations suggesting that genes on these chromosomes might be associated with addictive behavior. The statistical methodology developed for this study can be applied to similar studies to assess the mutual information in microarray and QTL analyses.

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Hibbins, Mark S., and Matthew W. Hahn. "The effects of introgression across thousands of quantitative traits revealed by gene expression in wild tomatoes." PLOS Genetics 17, no. 11 (November 8, 2021): e1009892. http://dx.doi.org/10.1371/journal.pgen.1009892.

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It is now understood that introgression can serve as powerful evolutionary force, providing genetic variation that can shape the course of trait evolution. Introgression also induces a shared evolutionary history that is not captured by the species phylogeny, potentially complicating evolutionary analyses that use a species tree. Such analyses are often carried out on gene expression data across species, where the measurement of thousands of trait values allows for powerful inferences while controlling for shared phylogeny. Here, we present a Brownian motion model for quantitative trait evolution under the multispecies network coalescent framework, demonstrating that introgression can generate apparently convergent patterns of evolution when averaged across thousands of quantitative traits. We test our theoretical predictions using whole-transcriptome expression data from ovules in the wild tomato genus Solanum. Examining two sub-clades that both have evidence for post-speciation introgression, but that differ substantially in its magnitude, we find patterns of evolution that are consistent with histories of introgression in both the sign and magnitude of ovule gene expression. Additionally, in the sub-clade with a higher rate of introgression, we observe a correlation between local gene tree topology and expression similarity, implicating a role for introgressed cis-regulatory variation in generating these broad-scale patterns. Our results reveal a general role for introgression in shaping patterns of variation across many thousands of quantitative traits, and provide a framework for testing for these effects using simple model-informed predictions.

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Solomon, Charles U., David G. McVey, Catherine Andreadi, Peng Gong, Lenka Turner, Paulina J. Stanczyk, Sonja Khemiri, et al. "Effects of Coronary Artery Disease–Associated Variants on Vascular Smooth Muscle Cells." Circulation 146, no. 12 (September 20, 2022): 917–29. http://dx.doi.org/10.1161/circulationaha.121.058389.

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Background: Genome-wide association studies have identified many genetic loci that are robustly associated with coronary artery disease (CAD). However, the underlying biological mechanisms are still unknown for most of these loci, hindering the progress to medical translation. Evidence suggests that the genetic influence on CAD susceptibility may act partly through vascular smooth muscle cells (VSMCs). Methods: We undertook genotyping, RNA sequencing, and cell behavior assays on a large bank of VSMCs (n>1499). Expression quantitative trait locus and splicing quantitative trait locus analyses were performed to identify genes with an expression that was influenced by CAD-associated variants. To identify candidate causal genes for CAD, we ascertained colocalizations of VSMC expression quantitative trait locus signals with CAD association signals by performing causal variants identification in associated regions analysis and the summary data–based mendelian randomization test. Druggability analysis was then performed on the candidate causal genes. CAD risk variants were tested for associations with VSMC proliferation, migration, and apoptosis. Collective effects of multiple CAD-associated variants on VSMC behavior were estimated by polygenic scores. Results: Approximately 60% of the known CAD-associated variants showed statistically significant expression quantitative trait locus or splicing quantitative trait locus effects in VSMCs. Colocalization analyses identified 84 genes with expression quantitative trait locus signals that significantly colocalized with CAD association signals, identifying them as candidate causal genes. Druggability analysis indicated that 38 of the candidate causal genes were druggable, and 13 had evidence of drug-gene interactions. Of the CAD-associated variants tested, 139 showed suggestive associations with VSMC proliferation, migration, or apoptosis. A polygenic score model explained up to 5.94% of variation in several VSMC behavior parameters, consistent with polygenic influences on VSMC behavior. Conclusions: This comprehensive analysis shows that a large percentage of CAD loci can modulate gene expression in VSMCs and influence VSMC behavior. Several candidate causal genes identified are likely to be druggable and thus represent potential therapeutic targets.

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Mispan, Muhamad S., Lihua Zhang, Jiuhuan Feng, and Xing-You Gu. "Quantitative Trait Locus and Haplotype Analyses of Wild and Crop-Mimic Traits in U.S. Weedy Rice." G3: Genes|Genomes|Genetics 3, no. 6 (April 19, 2013): 1049–59. http://dx.doi.org/10.1534/g3.113.006395.

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NEUSCHL, CHRISTINA, GUDRUN A. BROCKMANN, and SARA A. KNOTT. "Multiple-trait QTL mapping for body and organ weights in a cross between NMRI8 and DBA/2 mice." Genetical Research 89, no. 1 (February 2007): 47–59. http://dx.doi.org/10.1017/s001667230700852x.

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Multiple-trait analyses have been shown to improve the detection of quantitative trait loci (QTLs) with multiple effects. Here we applied a multiple-trait approach on obesity- and growth-related traits that were surveyed in 275 F2 mice generated from an intercross between the high body weight selected line NMRI8 and DBA/2 as lean control. The parental lines differed 2·5-fold in body weight at the age of 6 weeks. Within the F2 population, the correlations between body weight and weights of abdominal fat weight, muscle, liver and kidney at the age of 6 weeks were about 0·8. A least squares multiple-trait QTL analysis was performed on these data to understand more precisely the cause of the genetic correlation between body weight, body composition traits and weights of inner organs. Regions on Chr 1, 2, 7 and 14 for body weights at different early ages and regions on Chr 1, 2, 4, 7, 14, 17 and 19 for organ weights at 6 weeks were found to have significant multiple effects at the genome-wide level.

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Monson, Tesla A., Marianne F. Brasil, Michael C. Mahaney, Christopher A. Schmitt, Catherine E. Taylor, and Leslea J. Hlusko. "Keeping 21st Century Paleontology Grounded: Quantitative Genetic Analyses and Ancestral State Reconstruction Re-Emphasize the Essentiality of Fossils." Biology 11, no. 8 (August 13, 2022): 1218. http://dx.doi.org/10.3390/biology11081218.

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Advances in genetics and developmental biology are revealing the relationship between genotype and dental phenotype (G:P), providing new approaches for how paleontologists assess dental variation in the fossil record. Our aim was to understand how the method of trait definition influences the ability to reconstruct phylogenetic relationships and evolutionary history in the Cercopithecidae, the Linnaean Family of monkeys currently living in Africa and Asia. We compared the two-dimensional assessment of molar size (calculated as the mesiodistal length of the crown multiplied by the buccolingual breadth) to a trait that reflects developmental influences on molar development (the inhibitory cascade, IC) and two traits that reflect the genetic architecture of postcanine tooth size variation (defined through quantitative genetic analyses: MMC and PMM). All traits were significantly influenced by the additive effects of genes and had similarly high heritability estimates. The proportion of covariate effects was greater for two-dimensional size compared to the G:P-defined traits. IC and MMC both showed evidence of selection, suggesting that they result from the same genetic architecture. When compared to the fossil record, Ancestral State Reconstruction using extant taxa consistently underestimated MMC and PMM values, highlighting the necessity of fossil data for understanding evolutionary patterns in these traits. Given that G:P-defined dental traits may provide insight to biological mechanisms that reach far beyond the dentition, this new approach to fossil morphology has the potential to open an entirely new window onto extinct paleobiologies. Without the fossil record, we would not be able to grasp the full range of variation in those biological mechanisms that have existed throughout evolution.

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Jordan, Rebecca, Suzanne M. Prober, Ary A. Hoffmann, and Shannon K. Dillon. "Combined Analyses of Phenotype, Genotype and Climate Implicate Local Adaptation as a Driver of Diversity in Eucalyptus microcarpa (Grey Box)." Forests 11, no. 5 (April 28, 2020): 495. http://dx.doi.org/10.3390/f11050495.

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Trees are a keystone species in many ecosystems and a critical component of ecological restoration. Understanding their capacity to respond to climate change is essential for conserving biodiversity and determining appropriate restoration seed sources. Patterns of local adaptation to climate between populations within a species can inform such conservation decisions and are often investigated from either a quantitative trait or molecular genetic basis. Here, we present findings from a combined analysis of phenotype (quantitative genetic analysis), genotype (single nucleotide polymorphism (SNP) trait associations), and climate associations. We draw on the strength of this combined approach to investigate pre-existing climate adaptation and its genetic basis in Eucalyptus microcarpa (Grey box), an important tree for ecological restoration in south-eastern Australia. Phenotypic data from a 26-year-old provenance trial demonstrated significant genetic variation in growth and leaf traits at both the family and provenance levels. Growth traits were only associated with temperature, whilst leaf traits were associated with temperature, precipitation and aridity. Genotyping of 40 putatively adaptive SNPs from previous genome-wide analyses identified 9 SNPs associated with these traits. Drawing on previous SNP–climate association results, several associations were identified between all three comparisons of phenotype, genotype and climate. By combining phenotypic with genomic analyses, these results corroborate genomic findings and enhance understanding of climate adaptation in E. microcarpa. We discuss the implication of these results for conservation management and restoration under climate change.

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Storz, Jay F., Jamie T. Bridgham, Scott A. Kelly, and Theodore Garland. "Genetic approaches in comparative and evolutionary physiology." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 309, no. 3 (August 1, 2015): R197—R214. http://dx.doi.org/10.1152/ajpregu.00100.2015.

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Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology.

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Bocianowski, Jan, Kamila Nowosad, Barbara Wróbel, and Piotr Szulc. "Identification of Associations between SSR Markers and Quantitative Traits of Maize (Zea mays L.)." Agronomy 11, no. 1 (January 19, 2021): 182. http://dx.doi.org/10.3390/agronomy11010182.

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Microsatellite or simple sequence repeat (SSR) markers have wide applicability for genetic analysis in crop plant improvement strategies. Marker-assisted selection is an important tool for plant breeders to increase the efficiency of a breeding process, especially for multigenic traits, highly influenced by the environment. In this paper, the relationships between SSR markers and 26 quantitative traits of hybrid maize varieties (Zea mays L.) were analyzed. Association analyses were performed based on 30 SSR primers in a set of thirteen hybrid maize varieties. A total of 112 SSR markers were detected in these genotypes. The number of alleles per locus ranged from 1 to 17, with the average number of alleles per locus equal to 3.7. The number of molecular markers associated with observed traits ranged from 1 (for the number of kernels in row, ears weight and fresh weight of one plant) to 14 (for damage of maize caused by P. nubilalis) in 2016 as well as from 1 (for soil plant analysis development—SPAD, the number of grains in ear and fresh weight of one plant) to 12 (for carotenoids content) in 2017. The sum of statistically significant associations between SSR markers and at least one trait was equal to one hundred sixty in 2016 as well as one hundred twenty-five in 2017. Marker trait associations (MTAs) were found on the basis of regression analysis. The proportion of the total phenotypic variances of individual traits explained by the marker ranged from 24.4% to 77.7% in the first year of study and from 24.3% to 77.9% in 2017. Twenty-two SSR markers performed a significant effect on at least one tested trait in both years of experiment. The three markers (phi021/4, phi036/3, and phi061/2) can be a good tool in marker-assisted selection because they allow simultaneous selection for multiple traits in both years of study, such as the number of kernels in row and the number of grains in ear (phi021/4), the number of plant after germination, the number of plants before harvest, and the number of ears (phi036/3), as well as moisture of grain and length of ears (phi061/2).

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Sicard, Ophélie, Olivier Loudet, Joost J. B. Keurentjes, Thierry Candresse, Olivier Le Gall, Frédéric Revers, and Véronique Decroocq. "Identification of Quantitative Trait Loci Controlling Symptom Development During Viral Infection in Arabidopsis thaliana." Molecular Plant-Microbe Interactions® 21, no. 2 (February 2008): 198–207. http://dx.doi.org/10.1094/mpmi-21-2-0198.

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In compatible interactions between plants and viruses that result in systemic infection, symptom development is a major phenotypic trait. However, host determinants governing this trait are mostly unknown, and the mechanisms underlying it are still poorly understood. In a previous study on the Arabidopsis thaliana–Plum pox virus (PPV) pathosystem, we showed a large degree of variation in symptom development among susceptible accessions. In particular, Cvi-1 (Cape Verde islands) accumulates viral particules but remains symptomless, Col-0 (Columbia) sometimes shows weak symptoms compared with Ler (Landsberg erecta), which always shows severe symptoms. Genetic analyses of Col × Ler and Cvi × Ler F2 and recombinant inbred line (RIL) populations suggested that symptom development as well as viral accumulation traits are polygenic and quantitative. Three of the symptom quantitative trait loci (QTL) identified could be confirmed in near-isogenic lines, including PSI1 (PPV symptom induction 1), which was identified on the distal part of chromosome 1 in both RIL populations. With respect to viral accumulation, several factors have been detected and, interestingly, in the Col × Ler population, two out of three viral accumulation QTL colocalized with loci controlling symptom development, although correlation analysis showed weak linearity between symptom severity and virus accumulation. In addition, in the Cvi × Ler RIL population, a digenic recessive determinant controlling PPV infection was identified.

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Rönnberg-Wästljung, Ann-Christin, Berit Samils, Vasilios Tsarouhas, and Urban Gullberg. "Resistance toMelampsora larici-epitea leaf rust inSalix: analyses of quantitative trait loci." Journal of Applied Genetics 49, no. 4 (December 2008): 321–31. http://dx.doi.org/10.1007/bf03195630.

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Tsukahara, Keita, Hiroko Sawada, Hideyuki Matsumura, Yoshihisa Kohno, and Masanori Tamaoki. "Quantitative trait locus analyses of ozone-induced grain yield reduction in rice." Environmental and Experimental Botany 88 (April 2013): 100–106. http://dx.doi.org/10.1016/j.envexpbot.2011.12.012.

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Wang, Dong, and Song Xi Chen. "Combining quantitative trait loci analyses and microarray data: An empirical likelihood approach." Computational Statistics & Data Analysis 53, no. 5 (March 2009): 1661–73. http://dx.doi.org/10.1016/j.csda.2008.02.023.

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Wei, Suyun, Guo Yang, Yonghua Yang, and Tongming Yin. "Time-sequential detection of quantitative trait loci and candidate genes underlying the dynamic growth of Salix suchowensis." Tree Physiology 42, no. 4 (November 11, 2021): 877–90. http://dx.doi.org/10.1093/treephys/tpab138.

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Abstract Elucidating the genetic factors underlying long-term biological processes remains challenging since the relevant genes and their effects may vary across different developmental stages. In this study, we carried out a large-scale field trial of the progeny of an F1 full-sib pedigree of Salix suchowensis and measured plant height and ground diameter periodically over a time course of 240 days. With the obtained data, we characterized plant growth rhythms and performed time-sequential analyses of quantitative trait loci underlying the dynamic growth of the plants. The dynamic mapping of quantitative trait loci revealed that stem height and ground diameter were under the control of four quantitative trait loci, and the effects of these quantitative trait loci varied greatly throughout the growth process, in which two quantitative trait loci were found to exert a pleiotropic effect determining the correlation between stem height and ground diameter. The analysis of candidate genes in the target genetic intervals showed that the pleiotropic effect of the two quantitative trait loci arises from the colocalization of genes with independent effects on stem height and ground diameter. Further examination of the expression patterns of the candidate genes indicated that height and circumference growth involve different activities of leaf and cambium tissues. This study provides unprecedented information to help us understand the dynamic growth of plants and presents an applicable strategy for elucidating the genetic mechanism underlying a long-term biological process by using plant growth as an example.

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Azevedo Junior, Jairo, Juliana Petrini, Gerson Barreto Mourão, and José Bento Sterman Ferraz. "Preweaning Calf Survival of a Nellore Beef Cattle Population." Journal of Agricultural Science 9, no. 8 (July 18, 2017): 51. http://dx.doi.org/10.5539/jas.v9n8p51.

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The preweaning calf survival (SW) is one of the main economic bottlenecks of beef cattle rearing systems, however there is still few quantitative studies approaching this issue. Being a binary trait, genetic parameters for SW can be estimated considering continuous or categorical data under frequentist and Bayesian methods providing support for the selection and mating of animals in breeding programs. Therefore, the objectives in this study were to obtain and compare the variance component estimates for preweaning calf survival of calves in single-trait analyses and their correlations with a continuous trait in two-trait analyses. An amount of 25 218 data of the categorical trait of calf survival until weaning (SW) and the continuous trait of weaning weight (WW) were collected between the years of 2000 and 2012 in six herds of Nellore cattle. Methods III of Henderson, Maximum Restricted Likelihood (REML), Bayesian Inference and Generalized Linear Mixed Model (GLMM) were tested. Variance components obtained in one-trait analyses were similar to those obtained in two-trait analyses. Estimates of heritability (h2) obtained with different models for SW ranged from 0.0206 to 0.2644. The comparison between different estimation methods in single or two-trait analysis models allows the conclusion that the most appropriate method for SW analysis was the Bayesian estimation under an animal model and assuming linear distribution for phenotypes of SW trait.

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Sprajcer, Madeline, Sarah M. Jay, Grace E. Vincent, Xuan Zhou, Andrew Vakulin, Leon Lack, and Sally A. Ferguson. "Are Individuals with Low Trait Anxiety Better Suited to On-Call Work?" Clocks & Sleep 2, no. 4 (November 12, 2020): 473–86. http://dx.doi.org/10.3390/clockssleep2040035.

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Research has indicated that individuals with certain traits may be better suited to shiftwork and non-standard working arrangements. However, no research has investigated how individual differences impact on-call outcomes. As such, this study investigated the impact of trait anxiety on sleep and performance outcomes on-call. Seventy male participants (20–35 years) completed an adaptation night, a control night, and two on-call nights in a laboratory. Trait anxiety was determined using the State Trait Anxiety Inventory (STAI) X-2, and participants completed the STAI X-1 prior to bed each night to assess state anxiety. Sleep was measured using polysomnography and quantitative electroencephalographic analysis. Performance was assessed using a 10-min psychomotor vigilance task (PVT) performed each day at 0930, 1200, 1430 and 1700 h. Data pooled from three separate but inter-related studies was used for these analyses. Results indicated that the effects of trait anxiety on state anxiety, sleep and performance outcomes on-call were generally limited. These findings suggest that on-call outcomes are not negatively affected by higher levels of trait anxiety.

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Mérida-García, Rosa, Alison R. Bentley, Sergio Gálvez, Gabriel Dorado, Ignacio Solís, Karim Ammar, and Pilar Hernandez. "Mapping Agronomic and Quality Traits in Elite Durum Wheat Lines under Differing Water Regimes." Agronomy 10, no. 1 (January 19, 2020): 144. http://dx.doi.org/10.3390/agronomy10010144.

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Final grain production and quality in durum wheat are affected by biotic and abiotic stresses. The association mapping (AM) approach is useful for dissecting the genetic control of quantitative traits, with the aim of increasing final wheat production under stress conditions. In this study, we used AM analyses to detect quantitative trait loci (QTL) underlying agronomic and quality traits in a collection of 294 elite durum wheat lines from CIMMYT (International Maize and Wheat Improvement Center), grown under different water regimes over four growing seasons. Thirty-seven significant marker-trait associations (MTAs) were detected for sedimentation volume (SV) and thousand kernel weight (TKW), located on chromosomes 1B and 2A, respectively. The QTL loci found were then confirmed with several AM analyses, which revealed 12 sedimentation index (SDS) MTAs and two additional loci for SV (4A) and yellow rust (1B). A candidate gene analysis of the identified genomic regions detected a cluster of 25 genes encoding blue copper proteins in chromosome 1B, with homoeologs in the two durum wheat subgenomes, and an ubiquinone biosynthesis O-methyltransferase gene. On chromosome 2A, several genes related to photosynthetic processes and metabolic pathways were found in proximity to the markers associated with TKW. These results are of potential use for subsequent application in marker-assisted durum wheat-breeding programs.

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Tozlu, Ilhami, Charles L. Guy, and Gloria A. Moore. "QTL analysis of Na+ and Cl- accumulation related traits in an intergeneric BC1 progeny of Citrus and Poncirus under saline and nonsaline environments." Genome 42, no. 4 (August 1, 1999): 692–705. http://dx.doi.org/10.1139/g99-003.

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The effects of salinization with 40 mM NaCl on Poncirus trifoliata (L.) Raf., Citrus grandis (L.) Osb., their F1, and a BC1 progeny population (C. grandis × (F1)) were investigated by means of Na+ and Cl- analyses and QTL (quantitative trait loci) mapping. A total of 38 traits related to different tissue or whole-plant Na+ and (or) Cl- accumulation was analyzed in salinized and nonsalinized BC1 progeny clones. The comparison of the three parental types with the BC1 progeny under control and saline conditions showed that the BC1 progeny plants segregated transgressively for many traits. First mapping analyses resulted in a total of 73 potential quantitative trait loci (PQTL) with LOD scores [Formula: see text]3.0 located on a previously generated linkage map. Fifty-three percent of the mapped PQTLs were for traits associated with salinity. The small progeny population size used made further analyses of these PQTLs necessary. By considering LOD scores, map locations, and correlation analyses of the traits, it was possible to identify 17 regions of the citrus genome of interest: 8 of them may contain genuine QTLs of large effect and 9 regions are worthy of further study. Correlation analyses and locations of PQTLs indicated that many traits were controlled by fewer genes than the actual number of QTLs mapped for them. For example, 21 PQTLs mapped for Na+ accumulation and Cl-/Na+ ratios were located in a cluster at the beginning of one linkage group (LG), while 10 PQTLs mapped for Cl- accumulation and Cl-/Na+ ratios were located in a cluster at the beginning of another LG. This is the first step in identifying QTLs that have a major impact on salt tolerance and (or) mineral accumulation in citrus.Key words: Citrus grandis, Poncirus trifoliata, salinity stress, QTL mapping, transgressive segregation, mineral analysis, sodium, chloride, salt tolerance, citrus genetics.

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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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Chen, N., Q. Zhang, J. Zhi, H. Guo, H. Gao, F. Li, J. Huang, C. Lei, H. Chen, and Y. Ma. "Chinese yellow cattle PPARA gene: Analyses of expression, polymorphism and trait association." Czech Journal of Animal Science 63, No. 12 (December 4, 2018): 473–82. http://dx.doi.org/10.17221/99/2017-cjas.

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Peroxisome proliferator-activated receptor alpha (PPARA) is a member of the nuclear receptor superfamily that regulates key proteins involved in fatty acid oxidation and extracellular lipid metabolism. Given the importance of PPARA in modulating energy metabolism, PPARA may be a suitable candidate gene for assessing economic traits in cattle. In the present study, the genetic diversity of the PPARA gene in Chinese cattle breeds and its effects on growth traits in the Nanyang and Jiaxian breeds were investigated. First, the transcript profiles for PPARA were determined in eight adult cattle tissue types. Next, polymorphisms were identified in the coding and predicted promoter regions of the bovine PPARA gene in 424 animals. Finally, an association study was carried out to evaluate the relationship between PPARA and the development of cattle. Based on quantitative real-time polymerase chain reaction, PPARA was mainly expressed in the kidney and liver. Nine single nucleotide polymorphisms (SNPs) were identified in Chinese domestic cattle, including one novel SNP. Haplotype frequencies and linkage disequilibrium were also investigated. Four SNPs (g.17148558A>T, g.117195348A>G, g.117228160T>C, and g.117233248A>G) showed significant associations with growth traits in NY and JX cattle, including body weight, average daily gain, and hipbone width. These results confirmed the importance of PPARA as a candidate gene for marker-assisted selection for growth traits in cattle.

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Journal articles on the topic 'Quantitative trait analyses'

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