Maria Carlota Vaz Patto Lab

	At the PlantX Lab we unveil the genetic and genomic basis of plant Complex traits, such as nutritional or organoleptic quality or biotic/abiotic stress resistance, using different statistical genetic and genomic approaches.
	Maria Carlota Vaz Patto PhD 2001, Wagenigen University, The Netherlands Phone (+351) 214469631 | Extension 1631 cpatto@itqb.unl.pt

Research Interests

The Genetics and Genomics of Plant Complex Traits (PlantX) Laboratory develops research on molecular quantitative genetics applied to plant breeding. We want to identify genes controlling complex interesting traits, such as end-user quality (nutritional/health beneficial, organoleptic, processing), resistance to biotic (fungal diseases) and abiotic (drought) stresses on cereals and legumes (maize, common bean and grass pea) of national interest. This will allow us to develop control models, scientific methods and molecular tools to assist quality and resistance precision breeding programs.

We make use of different statistical genomics approaches, such as Linkage analysis, Genome-Wide Association and Genetical-Genomics, based on extensive DNA marker fingerprinting, transcriptional profiling and quantitative traits phenotyping.
Overall we are interested in exploiting the potential of national underused plant germplasm as source of interesting breeding traits and contribute indirectly to enhance its cultivation, increasing national food security and sustainability of agricultural systems.

Group Members

• Carmen Santos, Post-Doc
• ​Susana Leitão, Post-Doc
• Davide Martins, Post-Doc
• Estefanía Uberegui, Post-Doc
• Mara Alves, Invited Researcher
• Hélia Sales, PhD Student
• Letice Gonçalves, PhD Student
• Matilde Sanches, PhD Student
• Rita Maravilha Marques, PhD Student
• Francisco Mendes, PhD Student

Selected Publications

1. Gonçalves L, Rubiales D, Bronze MR, Vaz Patto MC (2022) Climate change, challenges and opportunities for grass pea production. Agronomy 12:6 DOI: 10.3390/agronomy12061324.

2. Santos C, Martins, DC, González-Bernal MJ, Rubiales D, Vaz Patto MC (2022) Integrating phenotypic and gene expression linkage mapping to dissect rust resistance in chickling pea. Frontiers in Plant Science 13:837613. DOI: 10.3389/fpls.2022.837613.

3. Sales H, Figueiredo F, Vaz Patto MC, Nunes J (2022) Assessing the environmental sustainability of Portuguese olive growing practices from a life cycle assessment perspective. Journal of Cleaner Production 2022:131692. DOI: 10.1016/j.jclepro.2022.131692.

4. Mendes F, Leitão S, Correia V, Mecha E, Rubiales D, Bronze, MR, VazPatto MC (2022) Portuguese common bean natural variation helps to clarify the genetic architecture of the legume’s nutritional composition and protein quality. Plants 11(1):26. DOI: 10.3390/plants11010026.

5. Mecha E, Erny GL, Guerreiro ACL, Feliciano RP, Barbosa I, Bento da Silva A, Leitão ST, Veloso MM, Rubiales D, Rodriguez-Mateos A, Figueira ME, Vaz Patto MC, Bronze MR (2022) Metabolomics profile responses to changing environments in a Portuguese common bean (Phaseolus vulgaris L.) germplasm collection. Food Chemistry 370:131003. DOI:10.1016/j.foodchem.2021.131003.

Laboratory's Website

For further information visit the laboratory's website

Genética e Genómica das Características Complexas de Plantas (PT)

No grupo de Genética e Genómica das Características Complexas de Plantas (PlantX) desenvolvemos investigação na àrea da genética quantitativa molecular aplicada ao melhoramento de plantas. O nosso principal interesse é a identificação dos genes que controlam características complexas relevantes como a qualidade para o consumidor (nutricional, organolética, de processamento) e a resistência a estresses bióticos (doenças causadas por fungos) e abióticos (tolerância à seca) em cereais e leguminosas de interesse nacional (milho, feijão e chícharo). Com base nesta informação, desenvolvemos modelos de controlo, métodos científicos e ferramentas moleculares para apoiar programas de melhoramento de plantas de precisão.

Utilizamos diferentes abordagens de genómica estatística como ligamento genético, Genome-Wide Association e Genetical-Genomics, baseados numa extensiva genotipagem por marcadores moleculares, análise de perfis transcriptómicos e fenotipagem de características quantitativas.

No cômputo geral, estamos interessados em explorar o potencial do germoplasma nacional como fonte de características interessantes para o melhoramento de plantas e contribuir indiretamente para aumentar o seu cultivo, a segurança alimentar e a sustentabilidade dos sistemas agrícolas nacionais.

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