DTA

Corso Ordinario Secondo Livello

IOHANNES, SESSEN DANIEL

etd-02142021-184032

A k-mers based approach to detect genetic variants underlying panicle architecture in Ethiopian teff

Cl. Sc. Sperimentali - Agraria

SCIENZE AGRARIE E BIOTECNOLOGIE - SCIENZE AGRARIE E BIOTECNOLOGIE

relatore Prof. PE', MARIO ENRICO
Membro Dott. ROSSETTO, RUDY
Membro Prof.ssa MENSUALI, ANNA
Membro Prof.ssa PUCCIARIELLO, CHIARA
Membro Prof. TONUTTI, PIETRO

• alignment-free methods
• domestication
• genetic variation
• panicle architecture
• teff

09/03/2021;

completa

Alignment-free methods are garnering increasing interest for the genomic characterization of species whose genome assemblies are poor, non-existent or non-representative of intraspecific genetic variation. Moreover, they have been recently brought into focus as powerful tools for the identification of structural variation underlying important traits, which is often overlooked in conventional genome-wide association studies (GWAS). Although several alignment-free approaches have been developed and implemented mainly in bacterial species, plants, and in particular non-model crop species that would greatly benefit from this technology, have been scarcely featured. In this study, I used a k-mers based approach to infer population structure and identify genetic variants underlying panicle architecture in 203 Ethiopian teff accessions. First, I implemented a bioinformatics workflow to build a k-mers presence/absence table from previously sequenced double-digest restriction site-associated DNA sequencing (ddRAD-Seq) teff reads. I then computed a kinship matrix and inferred population structure from k-mers presence/absence patterns across teff accessions. Lastly, I performed an association study to identify k-mers underlying panicle architecture, a key domestication trait in teff, and I compared results with associations obtained using the conventional single nucleotide polymorphisms (SNPs)-based approach. The study suggested a subdivision of the teff population into four main subpopulations and showed higher degrees of relatedness between teff wild relatives and landraces than previously computed SNP-based phylogeny. This result provides interesting insights into the potential of k-mers to capture genetic variation that cannot be identified using SNPs due to reference-genome bias. Moreover, the association study revealed that k-mers based associations had greater statistical support than those identified with SNPs. These associations marked several genetic variants underlying panicle architecture, which have the potential to become targets for de novo domestication of this promising orphan crop.

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