Unknown

Dataset Information

0

Exploring the gene pool of Brassica napus by genomics-based approaches.


ABSTRACT: De novo allopolyploidization in Brassica provides a very successful model for reconstructing polyploid genomes using progenitor species and relatives to broaden crop gene pools and understand genome evolution after polyploidy, interspecific hybridization and exotic introgression. B. napus (AACC), the major cultivated rapeseed species and the third largest oilseed crop in the world, is a young Brassica species with a limited genetic base resulting from its short history of domestication, cultivation, and intensive selection during breeding for target economic traits. However, the gene pool of B. napus has been significantly enriched in recent decades that has been benefit from worldwide effects by the successful introduction of abundant subgenomic variation and novel genomic variation via intraspecific, interspecific and intergeneric crosses. An important question in this respect is how to utilize such variation to breed crops adapted to the changing global climate. Here, we review the genetic diversity, genome structure, and population-level differentiation of the B. napus gene pool in relation to known exotic introgressions from various species of the Brassicaceae, especially those elucidated by recent genome-sequencing projects. We also summarize progress in gene cloning, trait-marker associations, gene editing, molecular marker-assisted selection and genome-wide prediction, and describe the challenges and opportunities of these techniques as molecular platforms to exploit novel genomic variation and their value in the rapeseed gene pool. Future progress will accelerate the creation and manipulation of genetic diversity with genomic-based improvement, as well as provide novel insights into the neo-domestication of polyploid crops with novel genetic diversity from reconstructed genomes.

SUBMITTER: Hu D 

PROVIDER: S-EPMC8428838 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC3304059 | biostudies-literature
2024-09-25 | GSE276833 | GEO
| S-EPMC10811367 | biostudies-literature
| S-EPMC1804201 | biostudies-literature
| S-EPMC8854361 | biostudies-literature
| S-EPMC2702316 | biostudies-literature
| S-EPMC8912142 | biostudies-literature
| S-EPMC7041300 | biostudies-literature
| S-EPMC3382996 | biostudies-literature
| S-EPMC6453480 | biostudies-literature