Literature DB >> 15614728

Integrating genomics into Eucalyptus breeding.

Dario Grattapaglia1.   

Abstract

The advent of high throughput genomic technologies has opened new perspectives in the speed, scale and detail with which one can investigate genes, genomes and complex traits in Eucalyptus species. A genomic approach to a more detailed understanding of important metabolic and physiological processes, which affect tree growth and stress resistance, and the identification of genes and their allelic variants, which determine the major chemical and physical features of wood properties, should eventually lead to new opportunities for directed genetic modifications of far-reaching economic impact in forest industry. It should be kept in mind, however, that basic breeding strategies, coupled with sophisticated quantitative methods, breeder's experience and breeder's intuition, will continue to generate significant genetic gains and have a clear measurable impact on production forestry. Even with a much more global view of genetic processes, genomics will only succeed in contributing to the development of improved industrial forests if it is strongly interconnected with intensive fieldwork and creative breeding. Integrated genomic projects involving multi-species expressed sequence tag sequencing and quantitative trait locus detection, single nucleotide polymorphism discovery for association mapping, and the development of a gene-rich physical map for the Eucalyptus genome will quickly move toward linking phenotypes to genes that control the wood formation processes that define industrial-level traits. Exploiting the full power of the superior natural phenotypic variation in wood properties found in Eucalyptus genetic resources will undoubtedly be a key factor to reach this goal.

Entities:  

Mesh:

Year:  2004        PMID: 15614728

Source DB:  PubMed          Journal:  Genet Mol Res        ISSN: 1676-5680


  6 in total

1.  A high-density transcript linkage map with 1,845 expressed genes positioned by microarray-based Single Feature Polymorphisms (SFP) in Eucalyptus.

Authors:  Leandro G Neves; Eva Mc Mamani; Acelino C Alfenas; Matias Kirst; Dario Grattapaglia
Journal:  BMC Genomics       Date:  2011-04-14       Impact factor: 3.969

2.  EUCANEXT: an integrated database for the exploration of genomic and transcriptomic data from Eucalyptus species.

Authors:  Leandro Costa Nascimento; Marcela Mendes Salazar; Jorge Lepikson-Neto; Eduardo Leal Oliveira Camargo; Lucas Salera Parreiras; Gonçalo Amarante Guimarães Pereira; Marcelo Falsarella Carazzolle
Journal:  Database (Oxford)       Date:  2017-01-01       Impact factor: 3.451

3.  Genomic characterization of DArT markers based on high-density linkage analysis and physical mapping to the Eucalyptus genome.

Authors:  César D Petroli; Carolina P Sansaloni; Jason Carling; Dorothy A Steane; René E Vaillancourt; Alexander A Myburg; Orzenil Bonfim da Silva; Georgios Joannis Pappas; Andrzej Kilian; Dario Grattapaglia
Journal:  PLoS One       Date:  2012-09-11       Impact factor: 3.240

4.  Xylem transcription profiles indicate potential metabolic responses for economically relevant characteristics of Eucalyptus species.

Authors:  Marcela Mendes Salazar; Leandro Costa Nascimento; Eduardo Leal Oliveira Camargo; Danieli Cristina Gonçalves; Jorge Lepikson Neto; Wesley Leoricy Marques; Paulo José Pereira Lima Teixeira; Piotr Mieczkowski; Jorge Maurício Costa Mondego; Marcelo Falsarella Carazzolle; Ana Carolina Deckmann; Gonçalo Amarante Guimarães Pereira
Journal:  BMC Genomics       Date:  2013-03-22       Impact factor: 3.969

Review 5.  Microsatellite resources of Eucalyptus: current status and future perspectives.

Authors:  Murugan Sumathi; Ramasamy Yasodha
Journal:  Bot Stud       Date:  2014-10-25       Impact factor: 2.787

6.  QTLs and eQTLs mapping related to citrandarins' resistance to citrus gummosis disease.

Authors:  Rômulo P M Lima; Maiara Curtolo; Marcus V Merfa; Mariângela Cristofani-Yaly; Marcos A Machado
Journal:  BMC Genomics       Date:  2018-07-03       Impact factor: 3.969

  6 in total

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