Genetic mapping and prediction of flowering time and plant height in a maize Stiff Stalk MAGIC population

Michel, Kathryn J.; Lima, Dayane C.; Hundley, Hope; Singan, Vasanth; Yoshinaga, Yuko; Daum, Chris; Barry, Kerrie; Broman, Karl W.; Robin Buell, C.; de Leon, Natalia; Kaeppler, Shawn M.; Daetwyler, H.

doi:10.1093/genetics/iyac063

Genetic mapping and prediction of flowering time and plant height in a maize Stiff Stalk MAGIC population

Journal Article · Wed Apr 20 00:00:00 EDT 2022 · Genetics (Online)

DOI:https://doi.org/10.1093/genetics/iyac063· OSTI ID:1979486

^[1]; ; ; ; ; ; ; ; ; ; ; Daetwyler, H.

OSTI

Abstract

The Stiff Stalk heterotic pool is a foundation of US maize seed parent germplasm and has been heavily utilized by both public and private maize breeders since its inception in the 1930s. Flowering time and plant height are critical characteristics for both inbred parents and their test crossed hybrid progeny. To study these traits, a 6-parent multiparent advanced generation intercross population was developed including maize inbred lines B73, B84, PHB47 (B37 type), LH145 (B14 type), PHJ40 (novel early Stiff Stalk), and NKH8431 (B73/B14 type). A set of 779 doubled haploid lines were evaluated for flowering time and plant height in 2 field replicates in 2016 and 2017, and a subset of 689 and 561 doubled haploid lines were crossed to 2 testers, respectively, and evaluated as hybrids in 2 locations in 2018 and 2019 using an incomplete block design. Markers were derived from a practical haplotype graph built from the founder whole genome assemblies and genotype-by-sequencing and exome capture-based sequencing of the population. Genetic mapping utilizing an update to R/qtl2 revealed differing profiles of significant loci for both traits between 635 of the DH lines and 2 sets of 570 and 471 derived hybrids. Genomic prediction was used to test the feasibility of predicting hybrid phenotypes based on the per se data. Predictive abilities were highest on direct models trained using the data they would predict (0.55–0.63), and indirect models trained using per se data to predict hybrid traits had slightly lower predictive abilities (0.49–0.55). Overall, this finding is consistent with the overlapping and nonoverlapping significant quantitative trait loci found within the per se and hybrid populations and suggests that selections for phenology traits can be made effectively on doubled haploid lines before hybrid data is available.

Research Organization:: Pennsylvania State Univ., University Park, PA (United States); Univ. of Wisconsin, Madison, WI (United States); Univ. of California, Oakland, CA (United States)

Sponsoring Organization:: USDOE Advanced Research Projects Agency - Energy (ARPA-E)

DOE Contract Number:: AR0000821; FC02-07ER64494; AC02-05CH11231

OSTI ID:: 1979486

Journal Information:: Genetics (Online), Journal Name: Genetics (Online) Journal Issue: 2 Vol. 221; ISSN 1943-2631

Publisher:: Oxford University Press; Genetics Society of America

Country of Publication:: United States

Language:: English

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