Implementing a collaborative pre-breeding multi-parental population efficiently identifies promising donor x elite pairs to enrich the flint maize elite germplasm. Genetic diversity is crucial for maintaining genetic gains and ensuring breeding programs' long-term success. In a closed breeding program, selection inevitably leads to a loss of genetic diversity. While managing diversity can delay this loss, introducing external sources of diversity is necessary to bring back favorable genetic variation. Genetic resources exhibit greater diversity than elite materials, but their lower performance levels hinder their use. This is the case for European flint maize, for which elite germplasm has incorporated only a limited portion of the diversity available in landraces. To enrich the diversity of this elite genetic pool, we established an original cooperative maize bridging population that involves crosses between private elite materials and diversity donors to create improved genotypes that will facilitate the incorporation of original favorable variations. Twenty donor × elite BC1S2 families were created and phenotyped for hybrid value for yield related traits. Crosses showed contrasted means and variances and therefore contrasted potential in terms of selection as measured by their usefulness criterion (UC). Average expected mean performance gain over the initial elite material was 5%. The most promising donor for each elite line was identified. Results also suggest that one more generation, i.e., 3 in total, of crossing to the elite is required to fully exploit the potential of a donor. Altogether, our results support the usefulness of incorporating genetic resources into elite flint maize. They call for further effort to create fixed diversity donors and identify those most suitable for each elite program.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10786986PMC
http://dx.doi.org/10.1007/s00122-023-04509-5DOI Listing

Publication Analysis

Top Keywords

flint maize
16
elite
13
elite germplasm
12
donor elite
12
diversity
9
genetic
8
promising donor
8
maize elite
8
genetic diversity
8
genetic resources
8

Similar Publications

Article Synopsis
  • Indigenous maize varieties from eastern North America have significantly influenced breeding programs, but their origins remain unclear.
  • Paleogenomic studies trace maize's journey to this region, indicating multiple migrations from Mexico, especially towards the northern U.S., including a notable path from the Southwest.
  • Analysis shows that ancient Ozark maize specimens exhibit a unique wx1 gene linked to starch metabolism, demonstrating how selective pressures shaped maize domestication and connecting these varieties to the Northern Flints, vital for today's commercial maize.
View Article and Find Full Text PDF

Expanding the BonnMu sequence-indexed repository of transposon induced maize (Zea mays L.) mutations in dent and flint germplasm.

Plant J

December 2024

INRES, Institute of Crop Science and Resource Conservation, Crop Functional Genomics, University of Bonn, Bonn, 53113, Germany.

The BonnMu resource is a transposon tagged mutant collection designed for functional genomics studies in maize. To expand this resource, we crossed an active Mutator (Mu) stock with dent (B73, Co125) and flint (DK105, EP1, and F7) germplasm, resulting in the generation of 8064 mutagenized BonnMu F-families. Sequencing of these Mu-tagged families revealed 425 924 presumptive heritable Mu insertions affecting 36 612 (83%) of the 44 303 high-confidence gene models of maize (B73v5).

View Article and Find Full Text PDF

Microencapsulation of highly concentrated polyphenolic compounds from purple corn pericarp by spray-drying with various biomacromolecules.

Int J Biol Macromol

June 2024

Department of Chemical and Biomedical Engineering, University of Missouri, Columbia, MO 65211, United States of America; Food Science Program, Division of Food, Nutrition and Exercise Sciences, University of Missouri, Columbia, MO 65211, United States of America. Electronic address:

Colored corn pericarp contains unusually high amounts of industrially valuable phytochemicals, such as anthocyanins, flavanols, flavonoids, and phenolic acids. Polyphenols were extracted in an aqueous solution and spray-dried to produce microencapsulates using four carrier materials, namely, maltodextrin (MD), gum arabic (GA), methylcellulose (MC), and skim milk powder (SMP) at three concentrations (1, 2, and 3 %, respectively). The encapsulates were evaluated for their polyphenolic contents using spectrophotometric techniques and HPLC analyses, and their antioxidant properties were evaluated using four different assays.

View Article and Find Full Text PDF

An ARF gene mutation creates flint kernel architecture in dent maize.

Nat Commun

March 2024

National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology & Ecology, Chinese Academy of Sciences, Shanghai, 200032, China.

Dent and flint kernel architectures are important characteristics that affect the physical properties of maize kernels and their grain end uses. The genes controlling these traits are unknown, so it is difficult to combine the advantageous kernel traits of both. We found mutation of ARFTF17 in a dent genetic background reduces IAA content in the seed pericarp, creating a flint-like kernel phenotype.

View Article and Find Full Text PDF

Portability of genomic predictions trained on sparse factorial designs across two maize silage breeding cycles.

Theor Appl Genet

March 2024

Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution (GQE) - Le Moulon, 91190, Gif-Sur-Yvette, France.

We validated the efficiency of genomic predictions calibrated on sparse factorial training sets to predict the next generation of hybrids and tested different strategies for updating predictions along generations. Genomic selection offers new prospects for revisiting hybrid breeding schemes by replacing extensive phenotyping of individuals with genomic predictions. Finding the ideal design for training genomic prediction models is still an open question.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!