ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-09242010-092426


Tipo di tesi
Tesi di laurea specialistica
Autore
MILNER, SARA GIULIA
URN
etd-09242010-092426
Titolo
Association mapping in a diverse barley (Hordeum vulgare L.) germplasm collection
Dipartimento
SCIENZE MATEMATICHE, FISICHE E NATURALI
Corso di studi
SCIENZE E TECNOLOGIE BIOMOLECOLARI
Relatori
relatore Dott.ssa Grando, Stefania
relatore Dott. Andreucci, Andrea
correlatore Prof. Cavallini, Andrea
correlatore Dott.ssa Spanò, Carmelina
Parole chiave
  • core collection
  • QTL
  • association mapping
  • barley
  • drought tolerance
Data inizio appello
25/10/2010
Consultabilità
Completa
Riassunto
The systematic evaluation of molecular diversity encompassed in plant genetic resources, is a prerequisite for its efficient exploitation in breeding as well as for optimal conservation of germplasm variability. Genomics and molecular biology are arising as fundamental tools in harnessing the richness harbored in world-wide crop biodiversity, from which sustainable utilization food security and food sovereignty can largely benefit.

The present research is making use of the Genomic based approach of Association mapping to work on resolution of drought-tolerance QTLs in a Core collection of barley (Hordeum vulgare L.). Although drought is one of the major abiotic stresses constraining global crop production, breeding for drought tolerance is still a difficult task, because of its complex multifactorial genetic background.

In recent years, association mapping has been applied as a powerful gene tagging tool, which provide us to access agronomically desirable alleles present at quantitative trait loci (QTLs) detecting via Linkage Disequilibrium significant association between markers and phenotypes related to the abiotic stress under examination.
The diverse collection has therefore been genotyped through fluorescent SSR markers and capillary electrophoresis genetic analyzer, while several drought-correlated morpho-physiological and agronomic important traits were evaluated in Icarda experimental fields.

The genotyping data have been consecutively analyzed for diversity index, clustering and population substructure evaluation (Power Marker, Structure, GeneAlex), to minimize association statistic bias. Significant marker-trait associations, has been finally detected through Tassel software, and putative QTLs discovered are now ready to be further investigated trough functional and comparative genomics, in a multidisciplinary approach towards genomics-assisted breeding.
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