Готові списки джерел за темами / Quantitative trait locis

Добірка наукової літератури з теми "Quantitative trait locis"

Автор: Grafiati
Опубліковано: 23 вересня 2022
Оновлено: 28 січня 2023

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Статті в журналах з теми "Quantitative trait locis"

1

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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2

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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3

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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4

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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5

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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7

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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9

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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Дисертації з теми "Quantitative trait locis"

1

Polineni, Pavana. "Developing a web accessible integrated database and visualization tool for bovine quantitative trait loci." Thesis, Texas A&M University, 2003. http://hdl.handle.net/1969.1/2449.

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A quantitative trait locus (QTL) is the location of a gene that affects a trait that is measured on a quantitative (linear) scale. Many important agricultural traits such as weight gain, milk fat content and intramuscular fat in cattle are quantitative traits. There is a need to integrate genomic sequence data with QTL data and to develop an analytical tool to visualize the data. Without integration, application of this data to agricultural enterprise productivity will be slow and inefficient. My thesis presents a web-accessible tool called the Bovine QTL Viewer developed to solve this problem. It consists of an integrated database of bovine QTL and the QTL viewer to view the QTL and their relative chromosomal position. This tool generates dynamic and interactive images and supports research in the field of genomics. For this tool, the data is modeled and the QTL viewer is developed based on the requirements and feedback of experts in the field of bovine genomics.
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2

Podisi, Baitsi Kingsley. "Quantitative trait loci mapping of sexual maturity traits applied to chicken breeding." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5561.

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Many phenotypes are controlled by factors which include the genes, the environment, interactions between genes and interaction between the genotypes and the environment. Great strides have been made to understand how these various factors affect traits of agricultural, medical and environmental importance. The chicken is regarded as a model organism whose study would not only assist efforts towards increased agricultural productivity but also provide insight into the genetic determination of traits with potential application in understanding human health and disease. Detection of genomic regions or loci responsible for controlling quantitative traits (QTL) in poultry has focussed mainly on growth and production traits with limited information on reproductive traits. Most of the reported results have used additive-dominance models which are easy to implement because they ignore epistatic gene action despite indications that it may be important for traits with low heritability and high heterosis. The thesis presents results on the detection of loci and genetic mechanisms involved in sexual maturity traits through modelling both additive-dominance gene actions and epistasis. The study was conducted on an F2 broiler x White Leghorn layer cross for QTL detection for age, weight, abdominal fat, ovary weight, oviduct weight, comb weight, number of ovarian yellow follicles, a score for the persistence of the right oviduct and bone density. In addition, body weight QTL at 3, 6, 12, 24, 48 and 72 weeks of age, QTL for growth rate between the successive ages and QTL for the parameters of the growth curve were also detected. Most of the QTL for traits at sexual maturity acted additively. A few of the QTL explained a modest proportion of the phenotypic variation with most of the QTL explaining a small component of the cumulative proportion of the variation explained by the QTL. Body weight QTL were critical in determining the attainment of puberty. The broiler allele had positive effects on weight at first egg and negative effects on age at first egg. Most QTL affecting weight at first egg overlapped with QTL for age at first egg and for early growth rate (6-9 weeks) suggesting that growth rate QTL are intimately related to the onset of puberty. Specific QTL for early and adult growth were detected but most QTL had varying influence on growth throughout life. Chromosome 4 harboured most of QTL for the assessed traits which explained the highest proportion of the phenotypic variation in the traits confirming its critical role in influencing traits of economic importance. There was no evidence for epistasis for almost all the studied traits. Evidence for role of epistasis was significant for ovary weight and suggestive for both growth rate and abdominal fat.
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3

Lu, Yue. "Genetic mapping of quantitative trait loci for slow-rusting traits in wheat." Diss., Kansas State University, 2016. http://hdl.handle.net/2097/32179.

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Doctor of Philosophy
Department of Agronomy
Guihua Bai
Allan K. Fritz
Wheat leaf rust, caused by Puccinia triticina, is an important fungal disease worldwide. Growing resistant cultivars is an effective practice to reduce the losses caused by the disease, and using slow-rusting resistance genes can improve the durability of rust resistance in the cultivars. CI13227 is a winter wheat line that shows a high level of slow-rusting resistance to leaf rust and has been studied extensively. In this research, two recombinant inbreed line (RIL) populations derived from CI13227 x Suwon (104 RILs) and CI13227 x Everest (184 RILs) and one doubled haploid (DH) population derived from CI13227 x Lakin with 181 lines were used to identify quantitative trait loci (QTLs) for slow leaf rusting resistance. Each population and its parents were evaluated for slow-rusting traits in two greenhouse experiments. A selected set of 384 simple sequence repeat markers (SSRs), single nucleotide polymorphism markers (SNPs) derived from genotyping-by-sequencing (GBS-SNPs) or 90K-SNP chip (90K-SNPs) were analyzed in the three populations. Six QTLs for slow-rusting resistance, QLr.hwwgru-2DS, QLr.hwwgru-7BL, QLr.hwwgru-7AL, QLr.hwwgru-3B_1, QLr.hwwgru-3B_2, and QLr.hwwgru-1D were detected in the three populations with three stable QTLs, QLr.hwwgru-2DS, QLr.hwwgru-7BL and QLr.hwwgru-7AL. These were detected and validated by Kompetitive Allele-Specific PCR (KASP) markers converted from GBS-SNPs and 90K-SNPs in at least two populations. Another three QTLs were detected only in a single population, and either showed a minor effect or came from the susceptible parents. The KASP markers tightly linked to QLr.hwwgru-2DS (IWB34642, IWB8545 and GBS_snpj2228), QLr.hwwgru-7BL (GBS_snp1637 and IWB24039) and QLr.hwwgru-7AL (IWB73053 and IWB42182) are ready to be used in marker-assisted selection (MAS) to transfer these QTLs into wheat varieties to improve slow-rusting resistance in wheat.
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4

Clevinger, Elizabeth. "Mapping Quantitative Trait Loci for Soybean Quality Traits from Two Different Sources." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/33468.

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Soybeans are economically and agriculturally the most important legume in the world, providing protein and oil to the food and animal feed industries and base ingredients for hundreds of chemical products. Their value could be enhanced, however, if the oil and protein content remained high and the oligosaccharide and phytate contents were lowered to make soybeans more acceptable for human and animal consumption. A soybean population of 55 families segregating for genes controlling quality traits was chosen for this study. Both parental lines have high sucrose and low stachyose. The former contains a high level of phytate while the latter is low phytate. The objective of this experiment was to determine whether or not both parents had the same gene(s) for low stachyose. An additional objective was to determine quantitative trait loci (QTL) controlling quality traits: sucrose, stachyose and phytate. An acetonitrile precipitation method and a modified colorimetric method were used to determine amounts of sugars and phytate, respectively. The phenotypic data for stachyose was analyzed and it was determined that two recessive genes control low stachyose content in this population. A map was constructed using 141 SSR markers and 15 molecular linkage groups (MLGs) were identified. After analyzing trait and marker data in QTL Cartographer, potential QTL were found on MLGs: B1, C2, D1b, F, M and N. Sucrose and stachyose QTL were identified on B1, C2, M and N. Phytate QTL were observed on B1, D1b, F and N. The markers identified for quality traits in this population may be useful in marker-assisted selection and the germplasm should be useful for the development of a cultivar.
Master of Science
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5

Shimomura, Koichiro. "Quantitative trait locus analysis of agronomic traits in weedy cucumber lines for breeding." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263362.

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6

Nyström, Per-Erik. "Quantitative trait loci in pig production /." Uppsala : Swedish Univ. of Agricultural Sciences (Sveriges lantbruksuniv.), 1999. http://epsilon.slu.se/avh/1999/91-576-5712-2.pdf.

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7

Turri, Maria Grazia. "Mapping of behavioural quantitative trait loci." Thesis, University of Oxford, 2002. http://ora.ox.ac.uk/objects/uuid:89823fa1-c1d3-49e3-acb9-46da18b12245.

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Anxiety is a common disorder which affects about 25% of the population and whose pathophysiology is still poorly understood. Animal models of disease have been widely used to investigate the molecular basis of human disorders, including psychiatric illnesses. This thesis is about the study of the genetic basis of a mouse model of anxiety. I have carried out a QTL mapping study of behavioural measures thought to model anxiety. I report results from 1,636 mice, assessed for a large number of phenotypes in five ethological tests. Mice belonged to two F2 intercrosses originated by four lines generated in a replicate selection experiment. By comparing mapping results between the two crosses, I have demonstrated that selection operated on the same relatively small number of loci in the four selected lines. Analysis of genetic effect of QTL across phenotypes has allowed me to identify loci with specific roles on different dimensions of anxious behaviour, therefore enhancing our understanding of the anxiety phenotype in mice. For some of these QTL I have also accomplished fine mapping experiments: a locus on chromosome 15 is now contained in an interval of only 3 centimorgans. This work is the basis for further molecular dissection of the genetic loci that underlie anxiety and provides a starting point for the discovery of genes involved in a common psychiatric condition.
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8

Joehanes, Roby. "Multiple-trait multiple-interval mapping of quantitative-trait loci." Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1605.

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Somorjai, Ildikó M. L. "Quantitative trait loci for fitness traits in Arctic charr, conservation in rainbow trout and correlations among traits." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ61949.pdf.

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Joehanes, Roby. "Generalized and multiple-trait extensions to Quantitative-Trait Locus mapping." Diss., Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1919.

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Книги з теми "Quantitative trait locis"

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Camp, Nicola J., and Angela Cox. Quantitative Trait Loci. New Jersey: Humana Press, 2002. http://dx.doi.org/10.1385/1592591760.

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Rifkin, Scott A., ed. Quantitative Trait Loci (QTL). Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-785-9.

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Salinas-Garcia, Gilberto Eduardo. Mapping quantitative trait loci controlling agronomic traits in Brassica napus L. Birmingham: University of Birmingham, 1996.

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4

Weller, Joel Ira. Quantitative trait loci analysis in animals. Oxon, UK: CABI Pub., 2001.

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5

J, Camp Nicola, and Cox Angela 1961-, eds. Quantitative trait loci: Methods and protocols. Totowa, N.J: Humana Press, 2002.

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6

Weller, J. I., ed. Quantitative trait loci analysis in animals. Wallingford: CABI, 2009. http://dx.doi.org/10.1079/9781845934675.0000.

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Weller, J. I., ed. Quantitative trait loci analysis in animals. Wallingford: CABI, 2001. http://dx.doi.org/10.1079/9780851994024.0000.

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Weller, Joel Ira. Quantitative trait loci analysis in animals. 2nd ed. Cambridge, MA: CABI North American Office, 2009.

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9

Lantbruksuniversitet, Sveriges, ed. Genome analysis of quantitative trait loci in the pig. Uppsala: Sveriges Lantbruksuniversitet, 1997.

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10

Burns, Malcolm James. Quantitative trait loci mapping in Arabidopsis: Theory and practice. Birmingham: University of Birmingham, 1997.

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Частини книг з теми "Quantitative trait locis"

1

Cardon, Lon R. "Quantitative Trait Loci." In Behavior Genetic Approaches in Behavioral Medicine, 237–50. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4757-9377-2_13.

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2

Xu, Shizhong. "Mapping Quantitative Trait Loci." In Quantitative Genetics, 307–45. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83940-6_18.

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3

Turner, J. Rick, Maartje Wit, Tibor Hajos, Maartje Wit, M. Bryant Howren, Salvatore Insana, and Matthew A. Simonson. "Quantitative Trait Locus (QTL)." In Encyclopedia of Behavioral Medicine, 1609–10. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_716.

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Simonson, Matthew A. "Quantitative Trait Locus (QTL)." In Encyclopedia of Behavioral Medicine, 1830–31. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_716.

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Weller, Joel I. "Mapping Quantitative Trait Loci." In Bovine Genomics, 169–91. Oxford, UK: Wiley-Blackwell, 2012. http://dx.doi.org/10.1002/9781118301739.ch12.

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Knapp, Steven J. "Mapping quantitative trait loci." In Advances in Cellular and Molecular Biology of Plants, 58–96. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1104-1_4.

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Xiong, Dong-Hai, Jian-Feng Liu, Yan-Fang Guo, Yan Guo, Tie-Lin Yang, Hui Jiang, Yuan Chen, Fang Yang, Robert R. Recker, and Hong-Wen Deng. "Quantitative Trait Loci Mapping." In Osteoporosis, 203–35. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-59745-104-8_16.

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Knapp, Steven J. "Mapping quantitative trait loci." In Advances in Cellular and Molecular Biology of Plants, 59–99. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9815-6_5.

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Brandenberger, Luke. "Quantitative Trait Loci (QTL)." In Encyclopedia of Animal Cognition and Behavior, 1–4. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-47829-6_209-1.

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Brandenberger, Luke. "Quantitative Trait Loci (QTL)." In Encyclopedia of Animal Cognition and Behavior, 5839–42. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-55065-7_209.

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Тези доповідей конференцій з теми "Quantitative trait locis"

1

Beyer, Andreas, Silpa Suthram, and Trey Ideker. "Uncovering Regulatory Pathways with Expression Quantitative Trait Loci." In 2007 IEEE International Workshop on Genomic Signal Processing and Statistics. IEEE, 2007. http://dx.doi.org/10.1109/gensips.2007.4365837.

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Boone, Edward L., Karl Ricanek, and Susan J. Simmons. "Quantitative Trait Loci Analysis Using a Bayesian Framework." In 2007 International Joint Conference on Neural Networks. IEEE, 2007. http://dx.doi.org/10.1109/ijcnn.2007.4371053.

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Fu, Chen-Ping, Fernando Pardo-Manuel de Villena, and Leonard McMillan. "Quantitative trait loci mapping with microarray marker intensities." In BCB '14: ACM-BCB '14. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2649387.2649432.

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Lu, Hong, and Lu Lu. "Expression quantitative trait loci and genetic regulatory network analysis of Fbn1." In INTERNATIONAL SYMPOSIUM ON THE FRONTIERS OF BIOTECHNOLOGY AND BIOENGINEERING (FBB 2019). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5110812.

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Saferali, A., W. Kim, J. Yun, Z. Xu, R. Chase, M. H. Cho, P. Castaldi, and C. P. Hersh. "Splice Quantitative Trait Loci (sQTLs) in Whole Blood and Lung Tissue." In American Thoracic Society 2022 International Conference, May 13-18, 2022 - San Francisco, CA. American Thoracic Society, 2022. http://dx.doi.org/10.1164/ajrccm-conference.2022.205.1_meetingabstracts.a4660.

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Purrington, Kristen S., Drakoulis Yannoukakos, Jane Carpenter, Heli Nevanlinna, Angela Cox, Gianluca Severi, Christine Ambrosone, et al. "Abstract 3266: Expression quantitative trait locus analysis of triple negative breast cancer." In Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA. American Association for Cancer Research, 2014. http://dx.doi.org/10.1158/1538-7445.am2014-3266.

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Dowling, Caroline. "Perfect Timing: Quantitative trait locus analysis of flowering time in Cannabis sativa." In ASPB PLANT BIOLOGY 2020. USA: ASPB, 2020. http://dx.doi.org/10.46678/pb.20.1053029.

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8

High, MD, HY Cho, F. Polack, T. Wiltshire, and S. Kleeberger. "Quantitative Trait Loci Associated with Respiratory Syncytial Virus Susceptibility in Inbred Mice." In American Thoracic Society 2009 International Conference, May 15-20, 2009 • San Diego, California. American Thoracic Society, 2009. http://dx.doi.org/10.1164/ajrccm-conference.2009.179.1_meetingabstracts.a5985.

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9

Chua, Z., Y. Y. Sio, and F. T. Chew. "Genome-wide cis-expression-Quantitative Trait Loci (eQTL) in association with asthma." In ERS International Congress 2022 abstracts. European Respiratory Society, 2022. http://dx.doi.org/10.1183/13993003.congress-2022.2593.

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HE, DAN, and LAXMI PARIDA. "MUSE: A MULTI-LOCUS SAMPLING-BASED EPISTASIS ALGORITHM FOR QUANTITATIVE GENETIC TRAIT PREDICTION." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2016. http://dx.doi.org/10.1142/9789813207813_0040.

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Звіти організацій з теми "Quantitative trait locis"

1

Hu, Zhiliang, James M. Reecy, and Max F. Rothschild. A Quantitative Trait Loci Resource and Comparison Tool for Pigs: PigQTLDB. Ames (Iowa): Iowa State University, January 2005. http://dx.doi.org/10.31274/ans_air-180814-1068.

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2

Moore, Gloria A., Gozal Ben-Hayyim, Charles L. Guy, and Doron Holland. Mapping Quantitative Trait Loci in the Woody Perennial Plant Genus Citrus. United States Department of Agriculture, May 1995. http://dx.doi.org/10.32747/1995.7570565.bard.

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Анотація:
As is true for all crops, production of Citrus fruit is limited by traits whose characteristics are the products of many genes (i.e. cold hardiness). In order to modify these traits by marker aided selection or molecular genetic techniques, it is first necessary to map the relevant genes. Mapping of quantitative trait loci (QTLs) in perennial plants has been extremely difficult, requiring large numbers of mature plants. Production of suitable mapping populations has been inhibited by aspects of reproductive biology (e.g. incompatibility, apomixis) and delayed by juvenility. New approaches promise to overcome some of these obstacles. The overall objective of this project was to determine whether QTLs for environmental stress tolerance could be effectively mapped in the perennial crop Citrus, using an extensive linkage map consisting of various types of molecular markers. Specific objectives were to: 1) Produce a highly saturated genetic linkage map of Citrus by continuing to place molecular markers of several types on the map. 2) Exploiting recently developed technology and already characterized parental types, determine whether QTLs governing cold acclimation can be mapped using very young seedling populations. 3) Determine whether the same strategy can be transferred to a different situation by mapping QTLs influencing Na+ and C1- exclusion (likely components of salinity tolerance) in the already characterized cross and in new alternative crosses. 4) Construct a YAC library of the citrus genome for future mapping and cloning.
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3

Weller, Joel I., Harris A. Lewin, and Micha Ron. Determination of Allele Frequencies for Quantitative Trait Loci in Commercial Animal Populations. United States Department of Agriculture, February 2005. http://dx.doi.org/10.32747/2005.7586473.bard.

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Individual loci affecting economic traits in dairy cattle (ETL) have been detected via linkage to genetic markers by application of the granddaughter design in the US population and the daughter design in the Israeli population. From these analyses it is not possible to determine allelic frequencies in the population at large, or whether the same alleles are segregating in different families. We proposed to answer this question by application of the "modified granddaughter design", in which granddaughters with a common maternal grandsire are both genotyped and analyzed for the economic traits. The objectives of the proposal were: 1) to fine map three segregating ETL previously detected by a daughter design analysis of the Israeli dairy cattle population; 2) to determine the effects of ETL alleles in different families relative to the population mean; 3) for each ETL, to determine the number of alleles and allele frequencies. The ETL on Bostaurusautosome (BT A) 6 chiefly affecting protein concentration was localized to a 4 cM chromosomal segment centered on the microsatellite BM143 by the daughter design. The modified granddaughter design was applied to a single family. The frequency of the allele increasing protein percent was estimated at 0.63+0.06. The hypothesis of equal allelic frequencies was rejected at p<0.05. Segregation of this ETL in the Israeli population was confirmed. The genes IBSP, SPP1, and LAP3 located adjacent to BM143 in the whole genome cattle- human comparative map were used as anchors for the human genome sequence and bovine BAC clones. Fifteen genes within 2 cM upstream of BM143 were located in the orthologous syntenic groups on HSA4q22 and HSA4p15. Only a single gene, SLIT2, was located within 2 cM downstream of BM143 in the orthologous HSA4p15 region. The order of these genes, as derived from physical mapping of BAC end sequences, was identical to the order within the orthologous syntenic groups on HSA4: FAM13A1, HERC3. CEB1, FLJ20637, PP2C-like, ABCG2, PKD2. SPP, MEP, IBSP, LAP3, EG1. KIAA1276, HCAPG, MLR1, BM143, and SLIT2. Four hundred and twenty AI bulls with genetic evaluations were genotyped for 12 SNPs identified in 10 of these genes, and for BM143. Seven SNPs displayed highly significant linkage disequilibrium effects on protein percentage (P<0.000l) with the greatest effect for SPP1. None of SNP genotypes for two sires heterozygous for the ETL, and six sires homozygous for the ETL completely corresponded to the causative mutation. The expression of SPP 1 and ABCG2 in the mammary gland corresponded to the lactation curve, as determined by microarray and QPCR assays, but not in the liver. Anti-sense SPP1 transgenic mice displayed abnormal mammary gland differentiation and milk secretion. Thus SPP 1 is a prime candidate gene for this ETL. We confirmed that DGAT1 is the ETL segregating on BTA 14 that chiefly effects fat concentration, and that the polymorphism is due to a missense mutation in an exon. Four hundred Israeli Holstein bulls were genotyped for this polymorphism, and the change in allelic frequency over the last 20 years was monitored.
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4

Hulata, Gideon, and Graham A. E. Gall. Breed Improvement of Tilapia: Selective Breeding for Cold Tolerance and for Growth Rate in Fresh and Saline Water. United States Department of Agriculture, November 2003. http://dx.doi.org/10.32747/2003.7586478.bard.

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The main objective of this project was to initiate a breeding program to produce cold-tolerant and salinity-tolerant synthetic breeds of tilapia, from a base population consisting of a four-species hybrid population created under an earlier BARD project. A secondary objective was to estimate genetic parameters for the traits growth rate under fresh- and salt-water and for cold tolerance. A third objective was to place quantitative trait loci that affect these traits of interest (e.g., growth rate in fresh-water, salt-water and cold tolerance) on the growing linkage map of primarily microsatellite loci. We have encountered fertility problems that were apparently the result of the complex genetic structure of this base population. The failure in producing the first generation of the breeding program has forced us to stop the intended breeding program. Thus, upon approval of BARD office, this objective was dropped and during the last year we have focused on the secondary objective of the original project during the third year of the project, but failed to perform the intended analysis to estimate genetic parameters for the traits of interest. We have succeeded, however, to strengthen the earlier identification of a QTL for cold tolerance by analyzing further segregating families. The results support the existence of a QTL for cold tolerance on linkage group 15, corresponding to UNH linkage group 23. The results also indicate a QTL for the same trait on linkage group 12, corresponding to UNH linkage group 4.
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5

Tuggle, Christopher K., Yuandan Zhang, Max F. Rothschild, Maria Moller, Frida Berg, Leif Andersson, Juliette Riquet, et al. A detailed gene map of pig chromosome 4, where the first quantitative trait locus in livestock was mapped. Ames (Iowa): Iowa State University, January 2004. http://dx.doi.org/10.31274/ans_air-180814-605.

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6

Fridman, Eyal, Jianming Yu, and Rivka Elbaum. Combining diversity within Sorghum bicolor for genomic and fine mapping of intra-allelic interactions underlying heterosis. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7597925.bard.

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Heterosis, the enigmatic phenomenon in which whole genome heterozygous hybrids demonstrate superior fitness compared to their homozygous parents, is the main cornerstone of modern crop plant breeding. One explanation for this non-additive inheritance of hybrids is interaction of alleles within the same locus. This proposal aims at screening, identifying and investigating heterosis trait loci (HTL) for different yield traits by implementing a novel integrated mapping approach in Sorghum bicolor as a model for other crop plants. Originally, the general goal of this research was to perform a genetic dissection of heterosis in a diallel built from a set of Sorghum bicolor inbred lines. This was conducted by implementing a novel computational algorithm which aims at associating between specific heterozygosity found among hybrids with heterotic variation for different agronomic traits. The initial goals of the research are: (i) Perform genotype by sequencing (GBS) of the founder lines (ii) To evaluate the heterotic variation found in the diallel by performing field trails and measurements in the field (iii) To perform QTL analysis for identifying heterotic trait loci (HTL) (iv) to validate candidate HTL by testing the quantitative mode of inheritance in F2 populations, and (v) To identify candidate HTL in NAM founder lines and fine map these loci by test-cross selected RIL derived from these founders. The genetic mapping was initially achieved with app. 100 SSR markers, and later the founder lines were genotyped by sequencing. In addition to the original proposed research we have added two additional populations that were utilized to further develop the HTL mapping approach; (1) A diallel of budding yeast (Saccharomyces cerevisiae) that was tested for heterosis of doubling time, and (2) a recombinant inbred line population of Sorghum bicolor that allowed testing in the field and in more depth the contribution of heterosis to plant height, as well as to achieve novel simulation for predicting dominant and additive effects in tightly linked loci on pseudooverdominance. There are several conclusions relevant to crop plants in general and to sorghum breeding and biology in particular: (i) heterosis for reproductive (1), vegetative (2) and metabolic phenotypes is predominantly achieved via dominance complementation. (ii) most loci that seems to be inherited as overdominant are in fact achieving superior phenotype of the heterozygous due to linkage in repulsion, namely by pseudooverdominant mechanism. Our computer simulations show that such repulsion linkage could influence QTL detection and estimation of effect in segregating populations. (iii) A new height QTL (qHT7.1) was identified near the genomic region harboring the known auxin transporter Dw3 in sorghum, and its genetic dissection in RIL population demonstrated that it affects both the upper and lower parts of the plant, whereas Dw3 affects only the part below the flag leaf. (iv) HTL mapping for grain nitrogen content in sorghum grains has identified several candidate genes that regulate this trait, including several putative nitrate transporters and a transcription factor belonging to the no-apical meristem (NAC)-like large gene family. This activity was combined with another BARD-funded project in which several de-novo mutants in this gene were identified for functional analysis.
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Paran, Ilan, and Molly Jahn. Analysis of Quantitative Traits in Pepper Using Molecular Markers. United States Department of Agriculture, January 2000. http://dx.doi.org/10.32747/2000.7570562.bard.

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Original objectives: The overall goal of the proposal was to determine the genetic and molecular control of pathways leading to the production of secondary metabolites determining major fruit quality traits in pepper. The specific objectives were to: (1) Generate a molecular map of pepper based on simple sequence repeat (SSR) markers. (2) Map QTL for capsaicinoids content (3) Determine possible association between capsaicinoids and carotenoid content and structural genes for capsaicinoid and carotenoid biosynthesis. (4) Map QTL for quantitative traits controlling additional fruit traits. (5) Map fruit-specific ESTs and determine possible association with fruit QTL (6) Map the C locus that determines the presence and absence of capsaicinoids in pepper fruit and identify candidate genes for C. Background: Pungency, color, fruit shape and fruit size are among the most important fruit quality characteristics of pepper. Despite the importance of the pepper crop both in the USA and Israel, the genetic basis of these traits was only little known prior to the studies conducted in the present proposal. In addition, molecular tools for use in pepper improvement were lacking. Major conclusions and achievements: Our studies enabled the development of a saturated genetic map of pepper that includes numerous simple sequence repeat (SSR) markers and the integration of several independent maps into a single resource map that consists of over 2000 markers. Unlike previous maps that consisted mostly of tomato-originated RFLP markers, the SSR-based map consists of largely pepper markers. Therefore, the SSR and integrated maps provide ample of tools for use in marker-assisted selection for diverse targets throughout the Capsicum genome. We determined the genetic and molecular bases of qualitative and quantitative variation of pungency, the most unique characteristics of pepper fruit. We mapped and subsequently cloned the Pun1 gene that serves as a master key for capsaicinoids accumulation and showed that it is an acyltransferase. By sequencing the Pun1 gene in pungent and non-pungent cultivars we identified a deletion that abolishes the expression of the gene in the latter cultivars. We also identified QTLs that control capsaicinoids content and therefore pungency level. These genes will allow pepper breeders to manipulate the level of pungency for specific agricultural and industrial purposes. In addition to pungency we identified genes and QTLs that control other key developmental processes of fruit development such as color, texture and fruit shape. The A gene controlling anthocyanin accumulation in the immature fruit was found as the ortholog of the petunia transcription factor Anthocyanin2. The S gene required for the soft flesh and deciduous fruit nature typical of wild peppers was identified as the ortholog of tomato polygalacturonase. We identified two major QTLs controlling fruit shape, fs3.1 and fs10.1, that differentiate between elongated and blocky and round fruit shapes, respectively. Scientific and agricultural implications: Our studies allowed significant advancement of our understanding at the genetic and molecular levels of important processes of pepper fruit development. Concomitantly to gaining biological knowledge, we were able to develop molecular tools that can be implemented for pepper improvement.
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8

Weller, Joel I., Derek M. Bickhart, Micha Ron, Eyal Seroussi, George Liu, and George R. Wiggans. Determination of actual polymorphisms responsible for economic trait variation in dairy cattle. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600017.bard.

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Анотація:
The project’s general objectives were to determine specific polymorphisms at the DNA level responsible for observed quantitative trait loci (QTLs) and to estimate their effects, frequencies, and selection potential in the Holstein dairy cattle breed. The specific objectives were to (1) localize the causative polymorphisms to small chromosomal segments based on analysis of 52 U.S. Holstein bulls each with at least 100 sons with high-reliability genetic evaluations using the a posteriori granddaughter design; (2) sequence the complete genomes of at least 40 of those bulls to 20 coverage; (3) determine causative polymorphisms based on concordance between the bulls’ genotypes for specific polymorphisms and their status for a QTL; (4) validate putative quantitative trait variants by genotyping a sample of Israeli Holstein cows; and (5) perform gene expression analysis using statistical methodologies, including determination of signatures of selection, based on somatic cells of cows that are homozygous for contrasting quantitative trait variants; and (6) analyze genes with putative quantitative trait variants using data mining techniques. Current methods for genomic evaluation are based on population-wide linkage disequilibrium between markers and actual alleles that affect traits of interest. Those methods have approximately doubled the rate of genetic gain for most traits in the U.S. Holstein population. With determination of causative polymorphisms, increasing the accuracy of genomic evaluations should be possible by including those genotypes as fixed effects in the analysis models. Determination of causative polymorphisms should also yield useful information on gene function and genetic architecture of complex traits. Concordance between QTL genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects that are segregating in the U.S. Holstein population; a probability of <10²⁰ was used to accept the null hypothesis that no segregating gene within the chromosomal segment was affecting the trait. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome. Variant sites were identified from previous studies (such as the 1000 Bull Genomes Project) and from DNA sequencing of bulls unique to this project, which is one of the largest marker variant surveys conducted for the Holstein breed of cattle. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: (1) complete or nearly complete concordance, (2) nominal significance of the polymorphism effect after correction for all other polymorphisms, and (3) marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. The missense polymorphism Phe279Tyr in GHR at 31,909,478 base pairs on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage, 12 additional missensepolymorphisms on chromosome 14 were found that had nearly complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The markers used in routine U.S. genomic evaluations were increased from 60,000 to 80,000 by adding markers for known QTLs and markers detected in BARD and other research projects. Objectives 1 and 2 were completely accomplished, and objective 3 was partially accomplished. Because no new clear-cut causative polymorphisms were discovered, objectives 4 through 6 were not completed.
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9

Seroussi, Eyal, and George Liu. Genome-Wide Association Study of Copy Number Variation and QTL for Economic Traits in Holstein Cattle. United States Department of Agriculture, September 2010. http://dx.doi.org/10.32747/2010.7593397.bard.

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Анотація:
Copy number variation (CNV) has been recently identified in human and other mammalian genomes and increasing awareness that CNV might be a major source for heritable variation in complex traits has emerged. Despite this, little has been published on CNVs in Holsteins. In order to fill this knowledge-gap, we proposed a genome-wide association study between quantitative trait loci (QTL) for economic traits and CNV in the Holstein cattle. The approved feasibility study was aimed at the genome-wide characterization of CNVs in Holstein cattle and at the demonstrating of their possible association with economic traits by performing the activities of preparation of DNA samples, Comparative Genomic Hybridization (CGH), initial association study between CNVs and production traits and characterization of CNVSNP associations. For both countries, 40 genomic DNA samples of bulls representing the extreme sub-populations for economically important traits were CGH analyzed using the same reference genome on a NimbleGen tiling array. We designed this array based on the latest build of the bovine genome (UMD3) with average probe spacing of 1150 bases (total number of probes was 2,166,672). Two CNV gene clusters, PLA2G2D on BTA2 and KIAA1683 on BTA7 revealed significant association with milk percentage and cow fertility, respectively, and were chosen for further characterization and verification in a larger sample using other methodologies including sequencing, tag SNPs and real time PCR (qPCR). Comparison between these four methods indicated that there is under estimation of the number of CNV loci in Holstein cattle and their complexity. The variation in sequence between different copies seemed to affect their functionality and thus the hybridization based methods were less informative than the methods that are based on sequencing. We thus conclude that large scale sequencing effort complemented by array CGH should be considered to better detect and characterize CNVs in order to effectively employ them in marker-assisted selection.
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Feldman, Moshe, Eitan Millet, Calvin O. Qualset, and Patrick E. McGuire. Mapping and Tagging by DNA Markers of Wild Emmer Alleles that Improve Quantitative Traits in Common Wheat. United States Department of Agriculture, February 2001. http://dx.doi.org/10.32747/2001.7573081.bard.

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Анотація:
The general goal was to identify, map, and tag, with DNA markers, segments of chromosomes of a wild species (wild emmer wheat, the progenitor of cultivated wheat) determining the number, chromosomal locations, interactions, and effects of genes that control quantitative traits when transferred to a cultivated plant (bread wheat). Slight modifications were introduced and not all objectives could be completed within the human and financial resources available, as noted with the specific objectives listed below: 1. To identify the genetic contribution of each of the available wild emmer chromosome-arm substitution lines (CASLs) in the bread wheat cultivar Bethlehem for quantitative traits, including grain yield and its components and grain protein concentration and yield, and the effect of major loci affecting the quality of end-use products. [The quality of end-use products was not analyzed.] 2. To determine the extent and nature of genetic interactions (epistatic effects) between and within homoeologous groups 1 and 7 for the chromosome arms carrying "wild" and "cultivated" alleles as expressed in grain and protein yields and other quantitative traits. [Two experiments were successful, grain protein concentration could not be measured; data are partially analyzed.] 3. To derive recombinant substitution lines (RSLs) for the chromosome arms of homoeologous groups 1 and 7 that were found previously to promote grain and protein yields of cultivated wheat. [The selection of groups 1 and 7 tons based on grain yield in pot experiments. After project began, it was decided also to derive RSLs for the available arms of homoeologous group 4 (4AS and 4BL), based on the apparent importance of chromosome group 4, based on early field trials of the CASLs.] 4. To characterize the RSLs for quantitative traits as in objective 1 and map and tag chromosome segments producing significant effects (quantitative trait loci, QTLs by RFLP markers. [Producing a large population of RSLs for each chromosome arm and mapping them proved more difficult than anticipated, low numbers of RSLs were obtained for two of the chromosome arms.] 5. To construct recombination genetic maps of chromosomes of homoeologous groups 1 and 7 and to compare them to existing maps of wheat and other cereals [Genetic maps are not complete for homoeologous groups 4 and 7.] The rationale for this project is that wild species have characteristics that would be valuable if transferred to a crop plant. We demonstrated the sequence of chromosome manipulations and genetic tests needed to confirm this potential value and enhance transfer. This research has shown that a wild tetraploid species harbors genetic variability for quantitative traits that is interactive and not simply additive when introduced into a common genetic background. Chromosomal segments from several chromosome arms improve yield and protein in wheat but their effect is presumably enhanced when combination of genes from several segments are integrated into a single genotype in order to achieve the benefits of genes from the wild species. The interaction between these genes and those in the recipient species must be accounted for. The results of this study provide a scientific basis for some of the disappointing results that have historically obtained when using wild species as donors for crop improvement and provide a strategy for further successes.
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