Association analysis (GWAS) of pea (Pisum sativum L.) and identification of SNP markers for genomic selection of economically important traits

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F26784246%3A_____%2F23%3AN0000020" target="_blank" >RIV/26784246:_____/23:N0000020 - isvavai.cz</a>

Výsledek na webu

<a href="https://ilsgranada2023.com/?seccion=scientificArea&subSeccion=abstractsPDF" target="_blank" >https://ilsgranada2023.com/?seccion=scientificArea&subSeccion=abstractsPDF</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Association analysis (GWAS) of pea (Pisum sativum L.) and identification of SNP markers for genomic selection of economically important traits

Popis výsledku v původním jazyce

The aim of the work was to use new breeding techniques and accelerate the development of new varieties of pea. Genome-Wide-Association Study (GWAS) was performed to identify DNA markers associated with agronomic (plant height, number of branches, leaf type, seed shape and colour, seed yield and seed weight, TSW, resistance to powdery mildew and PEMV) and seed quality (protein and starch content) traits in pea (Pisum sativum L.). Pea enation mosaic virus (PEMV) causes an important disease of peas, resulting in significant yield loss worldwide. A set of 564 accessions of field and garden pea was evaluated in 2019-2022 on three locations (Šumperk, Olomouc, Smržice). DArTseq sequencing of DNA libraries with reduced complexity was used for identification of SNP variants. 376 SNP markers were obtained, whose position on individual chromosomes (Fig. 1) was determined based on pea reference sequence. For SNP detection, a 69 bp sequence attached to associated SNPs was provided, which can be used for any available approaches of SNP markers detection (hybridization, enzymatic, sequenation and physical SNP detection methods). The identified SNP loci will be used to design PCR markers for marker-assisted selection to streamline and accelerate the breeding process and to generate qualitatively new, competitive field and garden pea varieties. In: Fourth International Legume Society Conference: Book of abstracts. Granada, 2023.

Název v anglickém jazyce

Association analysis (GWAS) of pea (Pisum sativum L.) and identification of SNP markers for genomic selection of economically important traits

Popis výsledku anglicky

The aim of the work was to use new breeding techniques and accelerate the development of new varieties of pea. Genome-Wide-Association Study (GWAS) was performed to identify DNA markers associated with agronomic (plant height, number of branches, leaf type, seed shape and colour, seed yield and seed weight, TSW, resistance to powdery mildew and PEMV) and seed quality (protein and starch content) traits in pea (Pisum sativum L.). Pea enation mosaic virus (PEMV) causes an important disease of peas, resulting in significant yield loss worldwide. A set of 564 accessions of field and garden pea was evaluated in 2019-2022 on three locations (Šumperk, Olomouc, Smržice). DArTseq sequencing of DNA libraries with reduced complexity was used for identification of SNP variants. 376 SNP markers were obtained, whose position on individual chromosomes (Fig. 1) was determined based on pea reference sequence. For SNP detection, a 69 bp sequence attached to associated SNPs was provided, which can be used for any available approaches of SNP markers detection (hybridization, enzymatic, sequenation and physical SNP detection methods). The identified SNP loci will be used to design PCR markers for marker-assisted selection to streamline and accelerate the breeding process and to generate qualitatively new, competitive field and garden pea varieties. In: Fourth International Legume Society Conference: Book of abstracts. Granada, 2023.

Druh

O - Ostatní výsledky

CEP obor

—

OECD FORD obor

40401 - Agricultural biotechnology and food biotechnology

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů