Tesi etd-06292026-165253 |
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Tipo di tesi
Tesi di laurea magistrale
URN
etd-06292026-165253
Titolo
A Pan-Genome approach to characterise Genomic and Epigenomic diversity in Teff
Dipartimento
BIOLOGIA
Corso di studi
BIOTECNOLOGIE MOLECOLARI
Relatori
.
relatore Dell'Acqua, Matteo
Parole chiave
- Eragrostis tef
- pan-genome
Data inizio appello
20/07/2026
Consultabilità
Non consultabile
Data di rilascio
20/07/2029
Riassunto (Inglese)
Teff (Eragrostis tef) is a predominantly self-pollinating allotetraploid cereal (2n=4x=40) of major cultural and nutritional importance in the Horn of Africa. Despite decades of breeding efforts, teff yields remain substantially lower than those of other cereals cultivated in the region due to several yield-limiting traits including seed shattering and lodging.
To unlock teff’s full potential, we generated de novo genome assemblies for 23 teff accessions using Oxford Nanopore Technology (ONT). These include 20 traditional landraces, selected to represent a broad cross-section of teff genetic diversity and geographic origin, and three improved varieties, including the widely cultivated Quncho.
We characterised genomic variation across the accessions by identifying structural rearrangements, annotating repeat elements with EDTA, predicting genes using Helixer, and extracting DNA CpG methylation profiles. Based on these datasets, we constructed a presence/absence variant (PAV) gene-based pangenome and a graph-based pangenome.
Together, these resources will enable the dissection of the genetic determinants of key agronomic traits, as demonstrated in this study for seed colour variation.
To unlock teff’s full potential, we generated de novo genome assemblies for 23 teff accessions using Oxford Nanopore Technology (ONT). These include 20 traditional landraces, selected to represent a broad cross-section of teff genetic diversity and geographic origin, and three improved varieties, including the widely cultivated Quncho.
We characterised genomic variation across the accessions by identifying structural rearrangements, annotating repeat elements with EDTA, predicting genes using Helixer, and extracting DNA CpG methylation profiles. Based on these datasets, we constructed a presence/absence variant (PAV) gene-based pangenome and a graph-based pangenome.
Together, these resources will enable the dissection of the genetic determinants of key agronomic traits, as demonstrated in this study for seed colour variation.
Riassunto (Italiano)
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