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G3 (Bethesda) ; 8(6): 1897-1908, 2018 05 31.
Article in English | MEDLINE | ID: mdl-29626084

ABSTRACT

Immature pollen can be induced to switch developmental pathways from gametogenesis to embryogenesis and subsequently regenerate into homozygous, diploid plants. Such androgenic production of doubled haploids is particularly useful for species where inbreeding is hampered by effective self-incompatibility systems. Therefore, increasing the generally low androgenic capacity of perennial ryegrass (Lolium perenne L.) germplasm would enable the efficient production of homozygous plant material, so that a more effective exploitation of heterosis through hybrid breeding schemes can be realized. Here, we present the results of a genome-wide association study in a heterozygous, multiparental population of perennial ryegrass (n = 391) segregating for androgenic capacity. Genotyping-by-sequencing was used to interrogate gene- dense genomic regions and revealed over 1,100 polymorphic sites. Between one and 10 quantitative trait loci (QTL) were identified for anther response, embryo and total plant production, green and albino plant production and regeneration. Most traits were under polygenic control, although a major QTL on linkage group 5 was associated with green plant regeneration. Distinct genetic factors seem to affect green and albino plant recovery. Two intriguing candidate genes, encoding chromatin binding domains of the developmental phase transition regulator, Polycomb Repressive Complex 2, were identified. Our results shed the first light on the molecular mechanisms behind perennial ryegrass microspore embryogenesis and enable marker-assisted introgression of androgenic capacity into recalcitrant germplasm of this forage crop of global significance.


Subject(s)
Genetic Loci , Lolium/genetics , Pollen/genetics , Genome, Plant , Genome-Wide Association Study , Genotyping Techniques , Molecular Sequence Annotation , Phenotype , Quantitative Trait Loci/genetics , Quantitative Trait, Heritable , Sequence Analysis, DNA , Software
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