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. 2021 Jul 23;22:213. doi: 10.1186/s13059-021-02416-w

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 5 — Benefit of MegaLMM and geographic distributions of among-trial genetic correlations vary among traits. Traits analyzed included: days to silking (DTS), anthesis-silking interval (ASI), grain yield, and plant height. A Trial locations for each trait are shown. Points were jittered west-to-east to prevent overlap of repeated trials across years. Size and color of each point correspond to the increase in prediction accuracy for MegaLMM versus a univariate LMM. B Smoothed estimates (computed using geom_smooth with a bandwidth of 1.0) of the relationship between geographic distance and genetic correlation for each trial. Line colors correspond to the benefit of MegaLMM in each focal trial. C Genetic correlations between the trial with the greatest benefit of MegaLMM for each trait and each other trial