Literature DB >> 15319261

MCQTL: multi-allelic QTL mapping in multi-cross design.

Marie-Françoise Jourjon1, Sylvain Jasson, Jacques Marcel, Baba Ngom, Brigitte Mangin.   

Abstract

UNLABELLED: The aim of the MCQTL software package is to perform QTL mapping in multi-cross designs. It allows the analysis of the usual populations derived from inbred lines and can link the families by assuming that the QTL locations are the same in all of them. Moreover, a diallel modelling of the QTL genotypic effects is allowed in multiple related families. The implemented model is a linear regression model. A composite interval mapping and an iterative QTL mapping are implemented to deal with multiple QTL models. Marker cofactor selections by forward or backward stepwise methods are implemented as well as computation of threshold test value by permutation. AVAILABILITY: The program is available on request after signing a licence agreement; free of charge for academic and non-profit organizations at http://www.genoplante.org (Bioinformatics products).

Mesh:

Year:  2004        PMID: 15319261     DOI: 10.1093/bioinformatics/bth481

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  50 in total

1.  Multi-population QTL detection for aerial morphogenetic traits in the model legume Medicago truncatula.

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Journal:  Theor Appl Genet       Date:  2011-11-11       Impact factor: 5.699

2.  A Random-Model Approach to QTL Mapping in Multiparent Advanced Generation Intercross (MAGIC) Populations.

Authors:  Julong Wei; Shizhong Xu
Journal:  Genetics       Date:  2015-12-29       Impact factor: 4.562

3.  Choice of models for QTL mapping with multiple families and design of the training set for prediction of Fusarium resistance traits in maize.

Authors:  Sen Han; H Friedrich Utz; Wenxin Liu; Tobias A Schrag; Michael Stange; Tobias Würschum; Thomas Miedaner; Eva Bauer; Chris-Carolin Schön; Albrecht E Melchinger
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4.  Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize.

Authors:  G Blanc; A Charcosset; B Mangin; A Gallais; L Moreau
Journal:  Theor Appl Genet       Date:  2006-05-20       Impact factor: 5.699

5.  Consensus mapping of major resistance genes and independent QTL for quantitative resistance to sunflower downy mildew.

Authors:  Patrick Vincourt; Falah As-Sadi; Amandine Bordat; Nicolas B Langlade; Jerome Gouzy; Nicolas Pouilly; Yannick Lippi; Frédéric Serre; Laurence Godiard; Denis Tourvieille de Labrouhe; Felicity Vear
Journal:  Theor Appl Genet       Date:  2012-05-11       Impact factor: 5.699

6.  Genetic dissection of nitrogen nutrition in pea through a QTL approach of root, nodule, and shoot variability.

Authors:  Virginie Bourion; Syed Masood Hasan Rizvi; Sarah Fournier; Henri de Larambergue; Fabien Galmiche; Pascal Marget; Gérard Duc; Judith Burstin
Journal:  Theor Appl Genet       Date:  2010-02-24       Impact factor: 5.699

7.  Use of Mutant-Assisted Gene Identification and Characterization (MAGIC) to identify novel genetic loci that modify the maize hypersensitive response.

Authors:  Vijay Chaikam; Adisu Negeri; Rahul Dhawan; Bala Puchaka; Jiabing Ji; Satya Chintamanani; Emma W Gachomo; Allen Zillmer; Timothy Doran; Cliff Weil; Peter Balint-Kurti; Guri Johal
Journal:  Theor Appl Genet       Date:  2011-07-27       Impact factor: 5.699

8.  QTL detection for forage quality and stem histology in four connected mapping populations of the model legume Medicago truncatula.

Authors:  Luz Del Carmen Lagunes Espinoza; Bernadette Julier
Journal:  Theor Appl Genet       Date:  2012-10-26       Impact factor: 5.699

9.  Genetic control of photoperiod sensitivity in maize revealed by joint multiple population analysis.

Authors:  Nathan D Coles; Michael D McMullen; Peter J Balint-Kurti; Richard C Pratt; James B Holland
Journal:  Genetics       Date:  2009-12-14       Impact factor: 4.562

10.  QTL mapping of carrot resistance to leaf blight with connected populations: stability across years and consequences for breeding.

Authors:  V Le Clerc; S Marques; A Suel; S Huet; L Hamama; L Voisine; E Auperpin; M Jourdan; L Barrot; R Prieur; M Briard
Journal:  Theor Appl Genet       Date:  2015-07-08       Impact factor: 5.699

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