Relevant bibliographies by topics / QTL

Academic literature on the topic 'QTL'

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Published: 4 June 2021
Last updated: 31 August 2024

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Journal articles on the topic "QTL"

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Takahashi, Hidekazu. "QTL analysis using the Windows QTL Cartographer." Breeding Research 10, no. 1 (2008): 11–14. http://dx.doi.org/10.1270/jsbbr.10.11.

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Broman, K. W., H. Wu, S. Sen, and G. A. Churchill. "R/qtl: QTL mapping in experimental crosses." Bioinformatics 19, no. 7 (May 1, 2003): 889–90. http://dx.doi.org/10.1093/bioinformatics/btg112.

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Kang, Yiwei, Miao Zhang, Yue Zhang, Weixun Wu, Pao Xue, Xiaodeng Zhan, Liyong Cao, Shihua Cheng, and Yingxin Zhang. "Genetic Mapping of Grain Shape Associated QTL Utilizing Recombinant Inbred Sister Lines in High Yielding Rice (Oryza sativa L.)." Agronomy 11, no. 4 (April 7, 2021): 705. http://dx.doi.org/10.3390/agronomy11040705.

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Grain shape is a key factor for yield and quality in rice. To investigate the genetic basis of grain shape in the high-yielding hybrid rice variety Nei2You No.6, a set of recombinant inbred sister lines (RISLs) were used to map quantitative trait loci (QTLs) determining grain length (GL), grain width (GW), and length-width ratio (LWR) in four environments. A total of 91 medium/minor-effect QTL were detected using a high-density genetic map consisting of 3203 Bin markers composed of single nucleotide polymorphisms, among which 64 QTL formed 15 clusters. Twelve of 15 clusters co-localized with QTL previously reported for grain shape/weight. Three new QTL were detected: qGL-7a, qGL-8, and qGL-11a. A QTL cluster, qLWR-12c/qGW-12, was detected across all four environments with phenotypic variation explained (PVE) ranging from 3.67% to 11.93%, which was subsequently validated in paired lines of F17 progeny and tightly linked marker assay in F10 generation. Subsequently, 17 candidate genes for qLWR-12c/qGW-12 were detected in the 431 Kb interval utilizing bulk segregant analysis (BSA). Among these, OsR498G1222170400, OsR498G1222171900, OsR498G1222185100, OsR498G1222173400, and OsR498G1222170500 were the best candidates, which lays the foundation for further cloning and will facilitate high-yield breeding in rice.
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Zhang, Hongwei, Xi Wang, Qingchun Pan, Pei Li, Yunjun Liu, Xiaoduo Lu, Wanshun Zhong, et al. "QTG-Seq Accelerates QTL Fine Mapping through QTL Partitioning and Whole-Genome Sequencing of Bulked Segregant Samples." Molecular Plant 12, no. 3 (March 2019): 426–37. http://dx.doi.org/10.1016/j.molp.2018.12.018.

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Georges, Michel. "QTL Mapping to QTL Cloning: Mice to the Rescue." Genome Research 7, no. 7 (July 1, 1997): 663–65. http://dx.doi.org/10.1101/gr.7.7.663.

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Arends, Danny, Pjotr Prins, Ritsert C. Jansen, and Karl W. Broman. "R/qtl: high-throughput multiple QTL mapping: Fig. 1." Bioinformatics 26, no. 23 (October 21, 2010): 2990–92. http://dx.doi.org/10.1093/bioinformatics/btq565.

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Liu, Jingxian, Danfeng Wang, Mingyu Liu, Meijin Jin, Xuecheng Sun, Yunlong Pang, Qiang Yan, Cunzhen Liu, and Shubing Liu. "QTL Mapping for Agronomic Important Traits in Well-Adapted Wheat Cultivars." Agronomy 14, no. 5 (April 30, 2024): 940. http://dx.doi.org/10.3390/agronomy14050940.

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Wheat (Triticum aestivum L.) is one of the most important food crops worldwide and provides the staple food for 40% of the world’s population. Increasing wheat production has become an important goal to ensure global food security. The grain yield of wheat is a complex trait that is usually influenced by multiple agronomically important traits. Thus, the genetic dissection and discovery of quantitative trait loci (QTL) of wheat-yield-related traits are very important to develop high-yield cultivars to improve wheat production. To analyze the genetic basis and discover genes controlling important agronomic traits in wheat, a recombinant inbred lines (RILs) population consisting of 180 RILs derived from a cross between Xinong822 (XN822) and Yannong999 (YN999), two well-adapted cultivars, was used to map QTL for plant height (PH), spike number per spike (SNS), spike length (SL), grain number per spike (GNS), spike number per plant (SN), 1000- grain weight (TGW), grain length (GL), grain width (GW), length/width of grain (GL/GW), perimeter of grain (Peri), and surface area of grains (Sur) in three environments. A total of 64 QTL were detected and distributed on all wheat chromosomes except 3A and 5A. The identified QTL individually explained 2.24–38.24% of the phenotypic variation, with LOD scores ranging from 2.5 to 29. Nine of these QTL were detected in multiple environments, and seven QTL were associated with more than one trait. Additionally, Kompetitive Allele Specific PCR (KASP) assays for five major QTL QSns-1A.2 (PVE = 6.82), QPh-2D.1 (PVE = 37.81), QSl-2D (PVE = 38.24), QTgw-4B (PVE = 8.78), and QGns-4D (PVE = 13.54) were developed and validated in the population. The identified QTL and linked markers are highly valuable in improving wheat yield through marker-assisted breeding, and the large-effect QTL can be fine-mapped for further QTL cloning of yield-related traits in wheat.
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Mangin, B., P. Thoquet, and N. Grimsley. "Pleiotropic QTL Analysis." Biometrics 54, no. 1 (March 1998): 88. http://dx.doi.org/10.2307/2533998.

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Anderson, Jill T., and Thomas Mitchell-Olds. "Beyond QTL Cloning." PLoS Genetics 6, no. 11 (November 11, 2010): e1001197. http://dx.doi.org/10.1371/journal.pgen.1001197.

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Niemitz, Emily. "RNA decay QTL." Nature Genetics 44, no. 12 (November 28, 2012): 1293. http://dx.doi.org/10.1038/ng.2488.

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Dissertations / Theses on the topic "QTL"

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Xing, Liqun. "Marker density, marker distribution and QTL-by-environment interaction in QTL mapping." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0034/NQ64696.pdf.

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Xing, Liqun 1962. "Marker density, marker distribution and QTL-by-environment interaction in QTL mapping." Thesis, McGill University, 1999. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=36734.

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Two studies were conducted on gene mapping analysis. For the first study, genetic simulation experiments were conducted to address the effects of marker density, method of mapping analysis, and gaps in a marker map on the efficiency of QTL detection and the accuracy of QTL parameter estimation. The simulated genome consisted of seven chromosomes with seven or eight segregating QTL affecting the simulated quantitative trait. A set of six randomly segregating QTL outside the test region was consistently used to represent 40% of phenotypic variation. An individual QTL or a linkage block of two QTL on a target chromosome contributed 10% of phenotypic variation. The marker map was either dense (with markers every 4 cM) or sparse (with markers every 20 cM). The gap in the marker map was either 32 cM or 56 cM. Interval mapping and composite interval mapping were used to map QTL on the target chromosome. A dense map provided more power of QTL detection, better accuracy of QTL parameter estimation, and higher false-positive error rates for the target chromosome than a sparse map. Composite interval mapping provided more power of QTL detection, better accuracy of QTL parameter estimation, and lower false-positive error rates than interval mapping. Presence of a large gap in a marker map affected QTL detection and QTL parameter estimation for a QTL inside or near the gap. The use of a dense map with composite interval mapping was the most efficient combination tested in this study. For the second study, a mixed factorial regression model for interval mapping was developed for conducting QTL-by-environment interaction analysis and for providing inferences about QTL that are applicable beyond the environments used in the experiments. Genetic simulation was used to test the model for the power of detecting QTL-by-environment interaction and identifying the types of such interaction as crossover or non-crossover, and for the accuracy of estimating QTL parameters. The model prov
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Bauman, Lara Elizabeth. "QTL variance component models." Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1464110531&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Yalçin, Biannaz. "QTL mapping in animal models." Thesis, University of Oxford, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.410716.

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Wahlberg, Per. "Chicken Genomics - Linkage and QTL mapping." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Universitetsbiblioteket [distributör], 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9502.

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Ljungberg, Kajsa. "Numerical methods for mapping of multiple QTL." Licentiate thesis, Uppsala universitet, Avdelningen för teknisk databehandling, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-86133.

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This thesis concerns numerical methods for mapping of multiple quantitative trait loci, QTL. Interactions between multiple genetic loci influencing important traits, such as growth rate in farm animals and predisposition to cancer in humans, make it necessary to search for several QTL simultaneously. Simultaneous search for n QTL involves solving an n-dimensional global optimization problem, where each evaluation of the objective function consists of solving a generalized least squares problem. In Paper A we present efficient algorithms, mainly based on updated QR factorizations, for evaluating the objective functions of different parametric QTL mapping methods. One of these algorithms reduces the computational work required for an important function class by one order of magnitude compared with the best of the methods used by other authors. In Paper B previously utilized techniques for finding the global optimum of the objective function are compared with a new approach based on the DIRECT algorithm of Jones et al. The new method gives accurate results in one order of magnitude less time than the best of the formerly employed algorithms. Using the algorithms presented in Papers A and B, simultaneous search for at least three QTL, including computation of the relevant empirical significance thresholds, can be performed routinely.
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Wang, Austin T. "Allele-Specic QTL fine-mapping with PLASMA." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129928.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020
Cataloged from student-submitted PDF of thesis.
Includes bibliographical references (pages 35-37).
We introduce PLASMA (PopuLation Allele-Specic MApping), a statistical ne- mapping method that leverages allele-specic (AS) genomic data to improve detection of quantitative trait loci (QTLs) with causal effects on molecular traits. In simulations, PLASMA accurately prioritizes causal QTL variants over a wide range of genetic architectures. Applied to RNA-Seq data from 524 kidney tumor samples, PLASMA achieves a greater power at 50 samples than conventional QTL-based ne-mapping at 500 samples: with over 17% of loci ne-mapped to within 5 causal variants compared to 2% by QTL-based ne-mapping, and a 6.9-fold overall reduction in median credible set size. PLASMA offers high accuracy even at small sample sizes, yielding a 1.3-fold reduction in median credible set size compared to QTL-based ne-mapping when applied to H3K27AC ChIP-Seq from just 28 prostate tumor/normal samples. Our results demonstrate how integrating AS activity can substantially improve the detection of causal variants from existing molecular data.
by Austin T. Wang.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Hu, Wei-Hua. "The use of QTL in Hebrew aphorism." Theological Research Exchange Network (TREN), 2001. http://www.tren.com.

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QUADROS, I. P. S. "MAPEAMENTO E DETECÇÃO DE QTL EM MANDIOCA." Universidade Federal do Espírito Santo, 2016. http://repositorio.ufes.br/handle/10/7844.

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Made available in DSpace on 2018-08-01T22:57:28Z (GMT). No. of bitstreams: 1 tese_10266_Dissertação Final Iana Pedro da Silva Quadros.pdf: 2554686 bytes, checksum: 3716e4642d5c167349ceddb1c5ee793f (MD5) Previous issue date: 2016-08-31
A mandioca é típica dos trópicos e fonte de segurança alimentar para mais de 600 milhões de pessoas, utilizada na alimentação humana e animal e na indústria, pela extração de amido e produção de biocombustível. O Brasil é o segundo país em produção, entretanto o incremento em produção é baixo para atender o crescente mercado. A compreenção da arquitetura genética de caracteres agronomicamente importantes é útil para delinear cruzamentos e possibilita a identificação de loci controladores de características quantitativas (QTL), no intuito de seleção assistida e clonagem de genes candidatos. Neste trabalho objetivou-se identificar, mapear e caracterizar QTL para as características de altura das plantas (AP), produtividade de parte aérea (PPA), produtividade total de raízes fresca (PTR), teor de matéria seca da raiz (MS) e produtividade de amido (PROD-AMD) de mandioca. Para isto foi utilizada uma população F1 de 141 indivíduos, oriunda do cruzamento entre as cultivares Fécula Branca e BRS Formosa, mantida em delineamento em blocos, com duas repetições e 16 plantas por parcela para as análises fenotípicas. A genotipagem dos indivíduos foi realizada usando SNPs, microssatélites e minissatélites. O mapa foi construído com abordagem multiponto e a detecção dos QTL realizada por análise de contraste entre médias e intervalo, considerando os diferentes tipos de segregação do QTL. Variabilidade foi observada para todas as características e altas correlações fenotípicas, exceto para MS, com destaque para PTR e PROD-AMD (0,98), bem como alta herdabilidade para AP (74,29%). Também, segregação transgressiva foi detectada para todas as características, indicando complementariedade de alelos dos pais na progênie segregante. O mapa genético representou regiões dos 18 cromossomos da mandioca e foi composto por 283 marcadores em 32 grupos de ligação. Uma região do cromossomo 10 apresentou evidência de pleitropia. Para AP, PPA e PROD-AMD um QTL comum foi identificado, bem como para PTR e PROD-AMD, três QTL comuns foram verificados. O MS apresentou QTL exclusivos. Estes resultados indicam o controle quantitativo das características estudadas, com QTL de grande e pequeno efeito detectados. Estes são úteis no melhoramento da cultura visando maior produtividade.
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Pinto, Luis Fernando Batista. "Ocorrência de interações QTL x Sexo, de epistasias e de QTLs pleiotrópicos em aves (Gallus gallus)." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/11/11139/tde-15062007-093204/.

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Este estudo teve por objetivo mapear QTLs para características de desempenho e de carcaça em Gallus gallus . Foram estudadas 350 aves F2 oriundas de um cruzamento, na primeira geração, de machos de corte da linhagem TT com fêmeas de postura da linhagem CC. O peso vivo com 1, 35 e 42 dias de idade; o ganho de peso, o consumo de ração e a conversão alimentar de 35 a 41 dias de idade; os pesos dos pulmões, fígado, coração, moela, peito, coxas (peso de coxas e sobre-coxas), carcaça (sem vísceras, pés e cabeça), carcaça residual (peso da carcaça sem peito, asas e coxas), asas, cabeça, pés e gordura abdominal; o comprimento do intestino e o percentual de hematócrito, foram os fenótipos analisados. Foram utilizados 79 marcadores microssatélites, os quais cobriram 1510,7 cM dos cromossomos 1, 2, 3, 4, 5, 8, 11 e 13. Primeiramente, foram realizadas análises isoladas de cada fenótipo original e de variáveis canônicas obtidas por análise de componentes principais dos fenótipos. O teste razão de verossimilhanças (LRT) entre um modelo incompleto (apenas com efeitos fixos de sexo, incubação e o efeito aleatório de valor genético infinitesimal) e um completo (todos os efeitos anteriores mais os efeitos de QTL) foi o procedimento utilizado nas análises, exceto para testar modelos com interações epistáticas, onde a metodologia de quadrados mínimos foi utilizada. Modelos com interação QTL x sexo também foram testados. Posteriormente, foram feitas análises de múltiplos fenótipos simultaneamente, onde foi possível testar a hipótese de QTL pleiotrópico x QTLs ligados, além dos testes descritos acima, com exceção de efeitos epistáticos. As análises descritivas e de componentes principais foram obtidas no SAS, enquanto o mapeamento de QTL foi realizado no programa QxPak, exceto para análise de efeitos epistáticos, em que um código em Fortran 90 foi empregado. O modelo univariado, sem interações, permitiu mapear oito QTLs altamente significativos (cinco no GGA1 para PV35, PV42, gordura abdominal, comprimento do intestino e peso da cabeça; dois QTLs no GGA2 para PV35 e PV42; e um QTL no GGA3 para gordura abdominal) seis significativos (dois no GGA1 para conversão alimentar e ganho de peso; dois no GGA3 para peso das asas e das coxas; um no GGA4 para peso da cabeça; e um no GGA8 para peso da moela), além de 13 ligações sugestivas para diversas características. Dez QTLs apresentaram interação com sexo, sendo cinco específicos para machos. O modelo com busca simultânea de dois QTLs mapeou seis QTLs anteriormente perdidos (cinco para PV35 e PV42; e um para peso da cabeça). Interações epistáticas foram observadas para PV35 e PV42 entre um QTL em 69 cM do GGA1 com QTLs em 333 cM do GGA1, 272 cM do GGA3 e 77 cM do GGA5. Dois QTLs e seis ligações sugestivas foram mapeados na análise de variáveis canônicas, os quais não haviam sido mapeados com as variáveis originais. Com o procedimento de múltiplas características foi possível mapear nove QTLs pleiotrópicos e o aumento de poder do teste foi evidenciado, principalmente, no GGA2.
This study aim to map QTL for performance and carcass traits in (Gallus gallus) . There were used 350 F2 chickens developed by crossing a broiler male line (TT) with a layer line (CC). The body weight with 1, 35 and 42 days of age, weight gain, feed intake and feed conversion from 35 to 41 days, weights of lung, liver, heart, gizzard, breast, drums and thighs, carcass (without giblets, feet and head), residual carcass (weight of carcass without breast, drums, thighs, and wings), wings, head, feet, and abdominal fat, intestine length and hematócrito value were the phenotypes analyzed. Seventy nine microssatellite markers were used, which covered 1510.7 cM of chromosomes 1, 2, 3, 4, 5, 8, 11, and 13. Firstly, QTL analysis was carried out for each original trait and for canonical variables, obtained from principal components analysis of the phenotypes. The likelihood ratio test (LRT) between a reduced model (only fixed effects of sex, hatch and random effect of infinitesimal genetic value) and a full model (all anterior effects and QTL effects) was applied to map QTL, but mean square approach was used for mapping QTL with epistatic effect. Besides, models with QTL by sex interaction were also tested. Finally, multi-trait analysis was used to test the hypothesis of pleiotropic x linkage QTLs, besides of the tests previously described, except models with epistatic effects. For descriptive and principal components analysis the SAS software was used. QTL mapping was carried out with QxPak software and a fortran 90 source code to test models with epistatic effect. The univariate model, without interactions, allowed to map eight highly significant QTLs (five in the GGA1, for PV35, PV42, abdominal fat, intestine length, and head weight; two QTLs in the GGA2, for PV35 and PV42; and one QTL in the GGA3 for abdominal fat), six significant QTLs (two in the GGA1 for feed conversion and weight gain; two in the GGA3 for wings and drums and thighs weights; one in the GGA4 for head weight; and one in the GGA8 for gizzard weight), besides 13 suggestive linkages for several traits. Ten QTLs interacted with sex, being five of them male specific QTLs. The model with simultaneous search for two QTLs was important to map six QTLs previously lost (five for body weight at 35 and 42 days; and one for head weight). Epistatic Interactions were observed for body weight among a QTL in 69 cM of GGA1 with QTLs in 333 cM of GGA1, 272 cM of GGA3 and 77 cM of GGA5. Two QTLs and six suggestive linkages were mapped with the analysis on canonical variables, which have not been mapped with the original variables. With the multi-trait approach nine pleiotropic QTLs were mapped and an increase in the test power was observed mainly in the GGA2 chromosome.
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Books on the topic "QTL"

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Broman, Karl W., and Saunak Sen. A Guide to QTL Mapping with R/qtl. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-92125-9.

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Saunak, Sen, and SpringerLink (Online service), eds. A Guide to QTL Mapping with R/qtl. New York, NY: Springer-Verlag New York, 2009.

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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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Hyne, Virginia. QTL analysis in segregating populations. Birmingham: University of Birmingham, 1995.

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Tamil Nadu Agricultural University. Centre for Plant Breeding and Genetics., ed. QTL mapping for crop improvement, March 5-16, 2001. Coimbatore: Centre of Advanced Studies in Genetics and Plant Breeding, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, 2001.

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Ngwako, Samodimo. QTL mapping and marker-assisted selection in Brassica and Arabidopsis. Birmingham: University of Birmingham, 2003.

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Lebreton, Claude Maurice. A methodological study of comparative QTL mapping applied to common wheat (Triticum aestivum L.). Birmingham: University of Birmingham, 1999.

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Nōrin Suisan Gijutsu Kaigi. Jimukyoku., ed. Genomu ikushu ni yoru kōritsuteki hinshu ikusei gijutsu no kaihatsu, QTL idenshi kaiseki no suishin =: Genetic and molecular dissection of quantitative traits in rice. Tōkyō: Nōrin Suisan Gijutsu Kaigi Jimukyoku, 2009.

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Nōrin Suisan Gijutsu Kaigi. Jimukyoku., ed. Genomu ikushu ni yoru kōritsuteki hinshu ikusei gijutsu no kaihatsu, QTL idenshi kaiseki no suishin =: Genetic and molecular dissection of quantitative traits in rice. Tōkyō: Nōrin Suisan Gijutsu Kaigi Jimukyoku, 2009.

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Rāsī, Salām. al- Qīl: Wa-al-qāl wa-al-nazar fī ʻuqūl al-rijāl. Bayrūt: Nawfal, 1994.

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Book chapters on the topic "QTL"

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Turner, J. Rick, Maartje Wit, Tibor Hajos, Maartje Wit, M. Bryant Howren, Salvatore Insana, and Matthew A. Simonson. "QTL." In Encyclopedia of Behavioral Medicine, 1601. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_101419.

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Lee, Hyun Sook, Sun-Goo Hwang, Cheol Seong Jang, and Sang Nag Ahn. "QTL Identification." In Current Technologies in Plant Molecular Breeding, 51–94. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9996-6_3.

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Boopathi, N. Manikanda. "QTL Analysis." In Genetic Mapping and Marker Assisted Selection, 253–326. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2949-8_7.

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Boopathi, N. Manikanda. "QTL Identification." In Genetic Mapping and Marker Assisted Selection, 117–63. India: Springer India, 2012. http://dx.doi.org/10.1007/978-81-322-0958-4_6.

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Broman, Karl W., and Śaunak Sen. "Single-QTL analysis." In Statistics for Biology and Health, 75–133. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-92125-9_4.

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Giri, Prerna, Manohar Lal Yadav, and Bhagyalaxmi Mohapatra. "QTL Linkage Analysis." In Encyclopedia of Animal Cognition and Behavior, 5821–26. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-55065-7_161.

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Giri, Prerna, Manohar Lal Yadav, and Bhagyalaxmi Mohapatra. "QTL Linkage Analysis." In Encyclopedia of Animal Cognition and Behavior, 1–6. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-47829-6_161-1.

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Subramaniam, Meena, Noah Zaitlen, and Jimmie Ye. "PhAT-QTL: A Phase-Aware Test for QTL Detection." In Bioinformatics Research and Applications, 150–61. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59575-7_14.

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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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Xu, Shizhong. "Bayesian Multiple QTL Mapping." In Principles of Statistical Genomics, 223–56. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-0-387-70807-2_15.

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Conference papers on the topic "QTL"

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Кудинова, А. К., Н. Г. Варламова, Я. Э. Азаров, and Е. Р. Бойко. "Динамика QT интервала ЭКГ элитных лыжников-гонщиков в тесте с максимальной физической нагрузкой." In IX Vserossijskaja konferencija s mezhdunarodnym uchastiem «Mediko-fiziologicheskie problemy jekologii cheloveka». Publishing center of Ulyanovsk State University, 2023. http://dx.doi.org/10.34014/mpphe.2023-211-214.

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Изучена динамика длительности интервала QT и его корригированных форм (Bazett - QTc, Fridericia - QTf, Sagie/Framingham - QTs) у элитных лыжников-гонщиков во время прохождения максимального нагрузочного теста. Измерение ЭКГ и потребления кислорода проводили на системе Oxycon Pro, начиная с 120 Вт до отказа от нагрузки (шаг 40 Вт). Динамика QT представлена относительно потребления кислорода в процентах от максимального потребления кислорода (МПК). Длительности QTf и QTs обладали сходной динамикой, снижались при 60-100 % от МПК, однако значение QTс увеличилось при 40-50 % от МПК, далее не отличалось от исходного. Отмечено, что применение формулы Bazett для коррекции приводит к увеличению QTс, превышающему критические нормы. Ключевые слова: электрокардиограмма, реполяризация, спортсмены, максимальная физическая нагрузка.
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Villanueva, Gloria, Elena Rosa-Martínez, Santiago Vilanova, Pietro Gramazio, Jaime Prohens, and Mariola Plazas. "QTL MAPPING MADE EASY: A PRACTICAL TUTORIAL USING R/QTL." In 15th International Conference on Education and New Learning Technologies. IATED, 2023. http://dx.doi.org/10.21125/edulearn.2023.2186.

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Prowse-Wilkins, C. P., T. J. Lopdell, R. Xiang, C. J. Vander Jagt, M. D. Littlejohn, A. J. Chamberlain, and M. E. Goddard. "552. Regulatory QTL and exon expression QTL in the mammary gland of dairy cows." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_552.

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Chesnokov, Yuriy. "Value of QTL analysis in precision agriculture system." In VIIth International Scientific Conference “Genetics, Physiology and Plant Breeding”. Institute of Genetics, Physiology and Plant Protection, Republic of Moldova, 2021. http://dx.doi.org/10.53040/gppb7.2021.32.

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A possible relationship between the approaches of adaptive crop production and precision agriculture to produce environmentally friendly lines and varieties with high adaptive potential and productivity is shown. In recent decades, more and more attention has been paid to technogenic and biological systems of farming, based on the ecologization and biologization of the intensification processes of adaptive crop produc-tion. Such approaches are precision agriculture (PA) system and QTL analysis. The use of these approaches allows not only to ensure a sustainable increase in productivity through the combined use of the advantages of precision agriculture and molecular genetic assessment, including the creation of new forms and varieties re-sponsive to agricultural practices of PA, but also to neutralize the negative impact of abiotic and biotic envi-ronmental factors limiting the size and quality of the crop as well as plant productivity.
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Lu, Hong, Huaijin Guan, Hui Chen, and Lu Lu. "Expression QTL and genetic regulatory network analysis of Col11a1." In 2012 5th International Conference on Biomedical Engineering and Informatics (BMEI). IEEE, 2012. http://dx.doi.org/10.1109/bmei.2012.6512879.

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Ashikari, M., S. Lin, T. Yamamoto, T. Takashi, A. Nishimura, E. R. Angeles, Q. Qian, H. Kitano, and M. Matsuoka. "Isolation of a QTL gene controlling grain number and QTL pyramiding to combine loci for grain number and plant height in rice." In Proceedings of the Fifth International Rice Genetics Symposium. World Scientific Publishing Company, 2007. http://dx.doi.org/10.1142/9789812708816_0012.

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Bo Song, Weibing Yang, Mingyu Chen, Xiaofang Zhao, and Jianping Fan. "QTL: An efficient scheduling policy for 10Gbps network intrusion detection system." In 2010 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2010. http://dx.doi.org/10.1109/iscc.2010.5546727.

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"QTL mapping of oil-related traits in sunflower from VNIIMK collection." In Systems Biology and Bioinformatics (SBB-2021) : The 13th International Young Scientists School;. ICG SB RAS, 2021. http://dx.doi.org/10.18699/sbb-plantgen-2021-02.

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"The grapevine QTLome is ripe: QTL survey, databasing, and first applications." In Open-GPB. International Viticulture and Enology Society, 2024. http://dx.doi.org/10.58233/tw6ij14f.

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Mollah, Md Nurul Haque, and Shinto Eguchi. "Robust Composite Interval Mapping for QTL Analysis by Minimum beta-Divergence Method." In 2008 IEEE International Conference on Bioinformatics and Biomedicine. IEEE, 2008. http://dx.doi.org/10.1109/bibm.2008.43.

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Reports on the topic "QTL"

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Sun, Xiaochen, David Habier, Rohan L. Fernando, Dorian J. Garrick, and Jack C. M. Dekkers. Genomic Prediction and QTL Mapping Using Bayesian Methods. Ames (Iowa): Iowa State University, January 2011. http://dx.doi.org/10.31274/ans_air-180814-959.

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Park, Carissa A., Zhiliang Hu, and James M. Reecy. Ontology Development and its Utility in QTL Data Annotation. Ames (Iowa): Iowa State University, January 2014. http://dx.doi.org/10.31274/ans_air-180814-1151.

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Santa S, Juan David, Jhon Alexander Berdugo C., Teresa Mosquera V., Nubia Liliana Cely, Mauricio Soto S., and Carlos H. Galeano M. QTL analysis for late blight resistance in an Andean Tetraploid potato population. Corporación Colombiana de Investigación Agropecuaria - AGROSAVIA, 2016. http://dx.doi.org/10.21930/agrosavia.poster.2016.49.

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Un problema fitosanitario importante en la producción de papa en Colombia es el tizón tardío, causado por el oomiceto Phythopthora infestans (Mont) de Bary. Este problema fitosanitario puede alcanzar hasta el 100% de las pérdidas en el campo. En este momento, la producción de papa en Colombia cuenta con poca resistencia cultivares y dependientes del manejo de enfermedades principalmente en el uso de fungicidas, por lo tanto el control químico representa un impacto negativo en el medio ambiente y el consumidor. Por lo general, múltiples genes o QTL controlan la resistencia cuantitativa a las enfermedades. Para resistencia hasta el tizón tardío, un mapa de consenso reportó 24 meta QTL agrupando 144 QTLs reportados previamente. Los avances en las plataformas de genotipado, como el Innium Potato Array, han hecho posible mapeo genético de alta densidad en genotipos tetraploides de diversos caracteres con interés agronómico. A pesar de estos avances, la investigación sobre la genética de la papa tetraploide y específicamente sobre la resistencia a enfermedades es limitada. Por lo tanto, los objetivos del presente estudio fueron: construir un mapa de ligamiento y para mapear QTL de resistencia a P. infestans usando la cruz F1 RN × 2384.
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Medrano, Juan, Adam Friedmann, Moshe (Morris) Soller, Ehud Lipkin, and Abraham Korol. High resolution linkage disequilibrium mapping of QTL affecting milk production traits in Israel Holstein dairy cattle. United States Department of Agriculture, March 2008. http://dx.doi.org/10.32747/2008.7696509.bard.

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Original objectives: To create BAC contigs covering two QTL containing chromosomal regions (QTLR) and obtain BAC end sequence information as a platform for SNP identification. Use the SNPs to search for marker-QTL linkage disequilibrium (LD) in the test populations (US and Israel Holstein cattle). Identify candidate genes, test for association with dairy cattle production and functional traits, and confirm any associations in a secondary test population. Revisions in the course of the project: The selective recombinant genotyping (SRG) methodology which we implemented to provide moderate resolution QTL mapping turned out to be less effective than expected, due to problems introduced by incomplete marker informativity. This required a no-cost one-year extension of the project. Aside from this, the project was implemented essentially as envisaged, but only with respect to a single QTLR and single population association-test. Background to the topic. Dairy cattle breeders are looking to marker-assisted selection (MAS) as a means of identifying genetically superior sires and dams. MAS based on population-wide LD can be many times more effective than MAS based on within-family linkage mapping. In this proposal we developed a protocol leading from family based QTL mapping to population-wide LD between markers and the QTL Major conclusions, solutions, achievements. The critical importance of marker informativity for application of the SRG design in outcrossing random mating populations was identified, and an alternative Fractioned Pool Design (FPD) based on selective DNA pooling was developed. We demonstrated the feasibility of constructing a BAC contig across a targeted chromosomal region flanking the marker RM188 on bovine chromosome BTA4, which was shown in previous work to contain a QTL affecting milk production traits. BAC end sequences were obtained and successfully screened for SNPs. LD studies of these SNPs in the Israel population, and of an independent set of SNPs taken across the entire proximal region of BTA4 in the USA population, showed a much lower degree of LD than previously reported in the literature. Only at distances in the sub-cM level did an appreciable fraction of SNP marker-pairs show levels of LD useful for MAS. In contrast, studies in the Israel population using microsatellite markers, presented an equivalent degree of LD at a 1-5 separation distance. SNP LD appeared to reflect historical population size of Bostaurus (Ne=5000- 10,000), while microsatellite LD appeared to be in proportion to more recent effective population size of the Holstein breed (Ne=50-100). An appreciable fraction of the observed LD was due to Family admixture structure of the Holstein population. The SNPs MEOX2/IF2G (found within the gene SETMAR at 23,000 bp from RM188) and SNP23 were significantly associated with PTA protein, Cheese dollars and Net Merit Protein in the Davis bull resource population, and were also associated with protein and casein percentages in the Davis cow resource population. Implications. These studies document a major difference in degree of LD presented by SNPs as compared to microsatellites, and raise questions as to the source of this difference and its implications for QTL mapping and MAS. The study lends significant support to the targeted approach to fine map a previously identified QTL. Using high density genotyping with SNP discovered in flanking genes to the QTL, we have identified important markers associated with milk protein percentage that can be tested in markers assisted selection programs.
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Claire G. Williams. QTL and Candidate Genes for Growth Traits in Pinus Taeda L. Office of Scientific and Technical Information (OSTI), October 2002. http://dx.doi.org/10.2172/804720.

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Sun, Xiaochen, Rohan L. Fernando, Dorian J. Garrick, and Jack C. M. Dekkers. Improved Accuracy of Genomic Prediction for Traits with Rare QTL by Fitting Haplotypes. Ames (Iowa): Iowa State University, January 2015. http://dx.doi.org/10.31274/ans_air-180814-1339.

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Tanksley, Steven D., and Dani Zamir. Development and Testing of a Method for the Systematic Discovery and Utilization of Novel QTLs in the Production of Improved Crop Varieties: Tomato as a Model System. United States Department of Agriculture, June 1995. http://dx.doi.org/10.32747/1995.7570570.bard.

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Modern cultivated varieties carry only a small fraction of the variation present in the gene pool. The narrow genetic basis of modern crop plants is a result of genetic bottlenecks imposed during early domestication and modern plant breeding. The wild ancestors of most crop plants can still be found in their natural habitats and Germplasm Centers have been established to collect and maintain this material. These wild and unadapted resources can potentially fuel crop plant improvement efforts for many years into the future (Tanksley and McCouch 1997). Unfortunately, scientists have been unable to exploit the majority of the genetic potential warehoused in germplasm repositories. This is especially true as regards to the improvement of quantitative traits like yield and quality. One of the major problems is that much of the wild germplasm is inferior to modern cultivars for many of the quantitative traits that breeders would like to improve. Our research, focusing on the tomato as a model system, has shown that despite their inferior phenotypes, wild species are likely to contain QTLs that can substantially increase the yield and quality of elite cultivars (de Vicente and Tanksley 1992, Eshed and Zamir 1994, Eshed et al. 1996). Using novel population structures of introgression lines (ILs; Eshed and Zamir 1995) and advanced backcross lines (AB; Tanksley et al. 1996) we identified and introduced valuable QTLs from unadapted germplasm into elite processing tomato varieties. Populations involving crosses with five Lycopersicon species (L. pennellii (Eshed and Zamir 1994; Eshed et al. 1996; Eshed and Zamir 1996), L. hirsutum (Bernacchi et al. 1998), L. pimpinellifolium (Tanksley et al. 1996), L. parviflorum (unpub.), L. peruvianum (Fulton et al. 1997) have been field and laboratory tested in a number of locations around the world. QTLs from the wild parent were identified that improve one or more of the key quantitative traits for processing tomatoes (yield, brix, sugar and acid composition and earliness) by as much as 10-30%. Nearly isogenic lines (QTL-NILs) have been generated for a subset of these QTLs. Each QTL-NIL contains the entire genome of the elite cultivated parent except for a segment (5-40 cM) of the wild species genome corresponding to a specific QTL. The genetic material and information that was developed in this program is presently used by American and Israeli seed companies for the breeding of superior varieties. We expect that in the next few years these varieties will make a difference in the marketplace.
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Wisniewski, Michael E., Samir Droby, John L. Norelli, Noa Sela, and Elena Levin. Genetic and transcriptomic analysis of postharvest decay resistance in Malus sieversii and the characterization of pathogenicity effectors in Penicillium expansum. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7600013.bard.

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Blue mold of apple caused by Penicilliumexpansumis a major postharvest disease. Selection for postharvest disease resistance in breeding programs has been ignored in favor of fruit quality traits such as size, color, taste, etc. The identification of postharvest disease resistance as a heritable trait would represent a significant accomplishment and has not been attempted in apple. Furthermore, insight into the biology of the pathogenicity of P. expansumin apple could provide new approaches to postharvest decay management. Hypothesis: Postharvest resistance of apple to P. expansumcan be mapped to specific genetic loci and significant quantitative-trait-loci (QTLs) can be identified that account for a major portion of the population variance. Susceptibility of apple fruit to P. expansumis dependent on the ability of the pathogen to produce LysM effectors that actively suppress primary and/or secondary resistance mechanisms in the fruit. Objectives: 1) Identify QTL(s) and molecular markers for blue mold resistance in GMAL4593 mapping population (‘Royal Gala’ X MalussieversiiPI613981), 2) Characterize the transcriptome of the host and pathogen (P. expansum) during the infection process 3) Determine the function of LysM genes in pathogenicity of P. expansum. Methods: A phenotypic evaluation of blue mold resistance in the GMAL4593 mapping population, conducted in several different years, will be used for QTL analysis (using MapQTL 6.0) to identify loci associated with blue mold resistance. Molecular markers will be developed for the resistance loci. Transcriptomic analysis by RNA-seq will be used to conduct a time course study of gene expression in resistant and susceptible apple GMAL4593 genotypes in response to P. expansum, as well as fungal responses to both genotypes. Candidate resistance genes identified in the transcriptomic study and or bioinformatic analysis will be positioned in the ‘Golden Delicious’ genome to identify markers that co-locate with the identified QTL(s). A functional analysis of LysM genes on pathogenicity will be conducted by eliminating or reducing the expression of individual effectors by heterologous recombination and silencing technologies. LysMeffector genes will also be expressed in a yeast expression system to study protein function. Expected Results: Identification of postharvest disease resistance QTLs and tightly-linked genetic markers. Increased knowledge of the role of effectors in blue mold pathogenic
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Santa Sepúlveda, Juan David, Jhon Berdugo Cely, Mauricio Soto Suárez, Teresa Mosquera, and Carlos Galeano. A genetic linkage map of tetraploid potato (Solanum tuberosum L.) for Phytophthora infestans and Tecia solanivora quantitative resistance. Corporación Colombiana de Investigación Agropecuaria - AGROSAVIA, 2016. http://dx.doi.org/10.21930/agrosavia.poster.2016.28.

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Los avances en la selección asistida de selección molecular y marcadores han sido limitados debido a a los problemas de alta heterocigosis y ploidía en el grupo de papa Andigenum (adg). Recientemente, Se han desarrollado mapas basados ??en SNP de alta densidad para papa diploide y tetraploide. Además, los modelos estadísticos que incluyen la dosificación alélica, están mejorando la vinculación mapeo y análisis de QTL en papa autotetraploide (Hackett et al., 2014). Estos enfoques han facilitado el análisis de QTL de rasgos agronómicos como resistencia a P. infestans (Massa et al., 2015). La producción de papa en Colombia está afectada por el tizón tardío (P. infestans) y guatemalteco la polilla del tubérculo de la papa (T. solanivora) provoca pérdidas de hasta el 100% en el campo y el almacenamiento. Por lo tanto, en para comprender los factores genéticos que subyacen a la resistencia a P. infestans y T. solanivora, el objetivo principal de esta investigación es construir un mapa genético de alta saturación de SNP población tetraploide que se utilizará para mapear la resistencia QTL.
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Simon, James, and Yigal Cohen. Basil gene pool enrichment for Downy Mildew resistance and QTL development using genotyping by sequencing. United States Department of Agriculture, January 2016. http://dx.doi.org/10.32747/2016.7604273.bard.

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