TY - JOUR
T1 - Genomic prediction within and among doubled-haploid libraries from maize landraces
AU - Brauner, Pedro C.
AU - Müller, Dominik
AU - Schopp, Pascal
AU - Böhm, Juliane
AU - Bauer, Eva
AU - Schön, Chris Carolin
AU - Melchinger, Albrecht E.
N1 - Publisher Copyright:
© 2018 by the Genetics Society of America.
PY - 2018/12
Y1 - 2018/12
N2 - Thousands of maize landraces are stored in seed banks worldwide. Doubled-haploid libraries (DHL) produced from landraces harness their rich genetic diversity for future breeding. We investigated the prospects of genomic prediction (GP) for line per se performance in DHL from six European landraces and 53 elite flint (EF) lines by comparing four scenarios: GP within a single library (sL); GP between pairs of libraries (LwL); and GP among combined libraries, either including (cLi) or excluding (cLe) lines from the training set (TS) that belong to the same DHL as the prediction set. For scenario sL, with N = 50 lines in the TS, the prediction accuracy (ρ) among seven agronomic traits varied from ‒0.53 to 0.57 for the DHL and reached up to 0.74 for the EF lines. For LwL, ρ was close to zero for all DHL and traits. Whereas scenario cLi showed improved ρ values compared to sL, ρ for cLe remained at the low level observed for LwL. Forecasting ρ with deterministic equations yielded inflated values compared to empirical estimates of ρ for the DHL, but conserved the ranking. In conclusion, GP is promising within DHL, but large TS sizes (N > 100) are needed to achieve decent prediction accuracy because LD between QTL and markers is the primary source of information that can be exploited by GP. Since production of DHL from landraces is expensive, we recommend GP only for very large DHL produced from a few highly preselected landraces.
AB - Thousands of maize landraces are stored in seed banks worldwide. Doubled-haploid libraries (DHL) produced from landraces harness their rich genetic diversity for future breeding. We investigated the prospects of genomic prediction (GP) for line per se performance in DHL from six European landraces and 53 elite flint (EF) lines by comparing four scenarios: GP within a single library (sL); GP between pairs of libraries (LwL); and GP among combined libraries, either including (cLi) or excluding (cLe) lines from the training set (TS) that belong to the same DHL as the prediction set. For scenario sL, with N = 50 lines in the TS, the prediction accuracy (ρ) among seven agronomic traits varied from ‒0.53 to 0.57 for the DHL and reached up to 0.74 for the EF lines. For LwL, ρ was close to zero for all DHL and traits. Whereas scenario cLi showed improved ρ values compared to sL, ρ for cLe remained at the low level observed for LwL. Forecasting ρ with deterministic equations yielded inflated values compared to empirical estimates of ρ for the DHL, but conserved the ranking. In conclusion, GP is promising within DHL, but large TS sizes (N > 100) are needed to achieve decent prediction accuracy because LD between QTL and markers is the primary source of information that can be exploited by GP. Since production of DHL from landraces is expensive, we recommend GP only for very large DHL produced from a few highly preselected landraces.
KW - Doubled-haploid
KW - Genomic prediction
KW - Genpred
KW - Maize landraces
KW - Shared data resources
UR - http://www.scopus.com/inward/record.url?scp=85058365184&partnerID=8YFLogxK
U2 - 10.1534/genetics.118.301286
DO - 10.1534/genetics.118.301286
M3 - Article
C2 - 30257934
AN - SCOPUS:85058365184
SN - 0016-6731
VL - 210
SP - 1185
EP - 1196
JO - Genetics
JF - Genetics
IS - 4
ER -