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. 2017 Dec;10(1):22.
doi: 10.1186/s12284-017-0163-4. Epub 2017 May 19.

Genome-Based Identification of Heterotic Patterns in Rice

Ulrike Beukert  1 , Zuo Li  1 , Guozheng Liu  1 , Yusheng Zhao  1 , Nadhigade Ramachandra  2 , Vilson Mirdita  3 , Fabiano Pita  4 , Klaus Pillen  5 , Jochen Christoph Reif  6
Affiliations

Genome-Based Identification of Heterotic Patterns in Rice

Ulrike Beukert et al. Rice (N Y). 2017 Dec.

Abstract

Background: Hybrid rice breeding facilitates to increase grain yield and yield stability. Long-term success of hybrid breeding depends on the recognition of high-yielding complementary heterotic patterns, which is lacking in crops like rice.

Result: The main goal of this study was to evaluate the potential and limits to use genomics for establishing heterotic patterns in rice. For this purpose, data of a commercial hybrid rice breeding program targeted to India was analyzed, including 1,960 phenotyped hybrids from three market segments and 262 genotyped parental lines. Our cross-validation study revealed that grain yield of all potential single-crosses can be accurately predicted. Based on the full matrix of hybrid performances, high-yielding heterotic patterns were identified. These heterotic patterns increased grain yield up to 9% compared to the currently employed groups. Heterotic groups of around 14 individuals reflect a good compromise between long-term and short-term selection response.

Conclusions: Our findings clearly underlined the benefits of a genome-based establishment of heterotic patterns in rice as a requirement for a sustainable long-term success of hybrid rice breeding.

Keywords: Genome-Wide Predictions; Heterotic Groups; Heterotic Pattern; Hybrid Rice.

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Figures

Fig. 1
Fig. 1
Best linear unbiased estimations for grain yield performance of hybrids and checks of the market segments LS, MM, and SS
Fig. 2
Fig. 2
Principal coordinate analyses of parental lines (a) for market segments LS, (c) MM, and (e) SS with relating distribution of Rogers’ distances within and between parental pools (b) for market segments LS, (d) MM, and (f) SS
Fig. 3
Fig. 3
Prediction ability of grain yield performance for different subgroups of market segments LS, MM, and SS
Fig. 4
Fig. 4
Short- (Hybrid performance) and long-term success (Representativeness, Theoretical selection limit) in dependence of heterotic group size for market segments (a) LS, (b) MM, and (c) SS
Fig. 5
Fig. 5
Distribution of predicted hybrid performances for 256 best performing female x male crosses in comparison to heterotic groups of size 16
See this image and copyright information in PMC

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