Damiano Puglisi
Ciclo: XXXIII
Data inizio: 31/10/2017
Curriculum: Agroalimentari
Borsa: MIUR PON R&I
Titolo tesi: Development and validation of barley genetic improvement methodologies based on genomic prediction to underpin varietal innovation and the agriculture of the future
Abstract: The genetic improvement of crops, started circa 10.000 years ago, is based on a complex process of selection of genetic variation to create varieties that are 1) resistant to diseases, 2) capable of adapting to unfavorable climatic conditions, 3) high-yielding and 4) fit for purpose for the needs of human society. Varietal innovation is pivotal to underpin the agriculture of the future and cope with climate change and the exponential growth of the world population. Among the tools in the breeders’s toolbox, genomic selection or genomic prediction is gaining momentum and is becoming popular for genetic improvement of crops. This methodology aims to regress genome-wide single nucleotide polymorphisms or other types of DNA markers on phenotypes of individuals to simultaneously predict their effects. The population of individuals having both phenotypic and genotypic information is named training population and is used for constructing predictive models, which allow to compute “Genomic Estimated Breeding Values” in individuals for which only genotyping information is available (breeding population). Typically, the predictive models used in GP require to regress a large number of predictors (DNA markers) that greatly exceeds the number of observations or phenotypes and several parametric and non-parametric models have been proposed to deal with overfitting and the ‘large p, small n’ problem as in these conditions the estimation of marker effects using ordinary least squares method is not practicable (Chapter 1). In the present work, genomic prediction has been implemented and investigated on a panel of Multi Parent Advanced Generation Inter-crosses population of barley. This population was created crossing eight winter genotypes following “half-diallel” crosses. The resulting panel of Multi Parent Advanced Generation Inter-crosses lines was genotyped using the barley 50K SNP chip and was phenotyped in different site-by-season and site-by-season-by-management combinations to examine grain yield and heading date. Using phenotypic and genotypic information, models for grain yield predictions have been fitted and cross-validated using single-environment- and multi-environment-genomic prediction models (Chapter 2). Subsequently, the same panel of barley Multi Parent Advanced Generation Inter-crosses was phenotyped for belowground and physiological traits related to drought tolerance and grain yield. Particularly, these lines were phenotyped for seminal root number, seminal root angle and transpiration rate response to increasing evaporative demand. Standard and threshold models were subsequently fitted and cross-validated to predict these traits, which might support ideotype breeding for dry environments (Chapter 3). The aims of this project are: 1) Testing and assessing the performance of genomic prediction on Multi Parent Advanced Generation Inter-crosses to select high-yielding barley lines. 2) Examining the variability of Multi Parent Advanced Generation Inter-crosses lines for seminal root number, seminal root angle and transpiration rate to increasing evaporative demand. 3) Developing, fitting and cross-validating genomic prediction models for seminal root number, seminal root angle and transpiration rate to increasing evaporative demand to underpin ideotype breeding for crop improvement.
Tutor: Cattivelli
Data Conseguimento Titolo: 08/11/2021
Linkedin: Indicate il link
Email: damiano_puglisi@yahoo.it
Periodi all'estero- Sede e data: ICARDA, Rabat (Marocco)
Esperienze post-Dottorato ed attuale occupazione: Vincitore di un assegno di ricerca presso CREA - Centro di ricerca Olivicoltura, Frutticoltura e Agrumicoltura (Acireale) Attualmente Borsista presso CREA Centro di Ricerca Genomica e Bioinformatica (Fiorenzuola d’Arda)