Genomic prediction provides an efficient alternative to conventional phenotypic selection for
developing improved cultivars with desirable characteristics. New and improved methods to …

Background Transcription bridges genetic information and phenotypes. Here, we evaluated
how changes in transcriptional regulation enable maize (Zea mays), a crop originally …

Key message The calibration data for genomic prediction should represent the full genetic
spectrum of a breeding program. Data heterogeneity is minimized by connecting data …

Maize (Zea mays L.) provides food security, income, and livelihoods to millions of
smallholders in the developing world. However, maize yields in the tropical rainfed …

Background Artificial selection results in phenotypic evolution. Maize (Zea mays L. ssp.
mays) was domesticated from its wild progenitor teosinte (Zea mays subspecies …

Abstract The Germplasm Enhancement of Maize (GEM) project was initiated in 1993 as a
cooperative effort of public‐and private‐sector maize (Zea mays L.) breeders to enhance the …

The usefulness of genomic prediction (GP) for many animal and plant breeding programs
has been highlighted for many studies in the last 20 years. In maize breeding programs …

Genomic selection (GS) increases genetic gain by reducing the length of the selection cycle,
as has been exemplified in maize using rapid cycling recombination of biparental …

Variation in maize for response to photoperiod is related to geographical adaptation in the
species. Maize possesses homologs of many genes identified as regulators of flowering …

Artificial selection has produced varieties of domesticated maize that thrive in temperate
climates around the world. However, the direct progenitor of maize, teosinte, is indigenous …