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Haplotype Associated RNA Expression (HARE) Improves Prediction of Complex Traits in Maize

View ORCID ProfileAnju Giri, View ORCID ProfileMerritt Khaipho-Burch, View ORCID ProfileEdward S. Buckler, View ORCID ProfileGuillaume P. Ramstein
doi: https://doi.org/10.1101/2021.04.30.442099
Anju Giri
1Institute of Genomic Diversity, Cornell University, Ithaca, NY, 14853
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  • For correspondence: ag2484@cornell.edu ramstein@qgg.au.dk
Merritt Khaipho-Burch
2Plant Breeding and Genetics Section, Cornell University, Ithaca, NY, 14853
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Edward S. Buckler
1Institute of Genomic Diversity, Cornell University, Ithaca, NY, 14853
2Plant Breeding and Genetics Section, Cornell University, Ithaca, NY, 14853
3U.S. Department of Agriculture-Agricultural Research Service, Ithaca, NY, 14853
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Guillaume P. Ramstein
1Institute of Genomic Diversity, Cornell University, Ithaca, NY, 14853
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  • For correspondence: ag2484@cornell.edu ramstein@qgg.au.dk
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Abstract

Genomic prediction typically relies on associations between single-site polymorphisms and traits of interest. This representation of genomic variability has been successful for prediction within populations. However, it usually cannot capture the complex effects due to combination of alleles in haplotypes. Therefore, accuracy across populations has usually been low. Here we present a novel and cost-effective method for imputing cis haplotype associated RNA expression (HARE, RNA expression of genes by haplotype), studied their transferability across tissues, and evaluated genomic prediction models within and across populations. HARE focuses on tightly linked cis acting causal variants in the immediate vicinity of the gene, while excluding trans effects from diffusion and metabolism, so it would be more transferrable across different tissues and populations. We showed that HARE estimates captured one-third of the variation in gene expression and were more transferable across diverse tissues than the measured transcript expression. HARE estimates were used in genomic prediction models evaluated within and across two diverse maize panels – a diverse association panel (Goodman Association panel) and a large half-sib panel (Nested Association Mapping panel) – for predicting 26 complex traits. HARE resulted in up to 15% higher prediction accuracy than control approaches that preserved haplotype structure, suggesting that HARE carried functional information in addition to information about haplotype structure. The largest increase was observed when the model was trained in the Nested Association Mapping panel and tested in the Goodman Association panel. Additionally, HARE yielded higher within-population prediction accuracy as compared to measured expression values. The accuracy achieved by measured expression was variable across tissues whereas accuracy using HARE was more stable across tissues. Therefore, imputing RNA expression of genes by haplotype is stable, cost-effective, and transferable across populations.

Author summary The increasing availability of genomic data has been widely used in the prediction of many traits. However, genome wide prediction has been mostly carried out within populations and without explicit modeling of RNA or protein expression. In this study, we explored the prediction of field traits within and across populations using estimated RNA expression attributable to only the DNA sequence around a gene. We showed that the estimated RNA expression was more transferable than overall measured RNA expression. We improved prediction of field traits up to 15% using estimated gene expression as compared to observed expression or gene sequence alone. Overall, these findings indicate that structural and functional information in the gene sequence are highly transferable.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.
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Posted May 04, 2021.
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Haplotype Associated RNA Expression (HARE) Improves Prediction of Complex Traits in Maize
Anju Giri, Merritt Khaipho-Burch, Edward S. Buckler, Guillaume P. Ramstein
bioRxiv 2021.04.30.442099; doi: https://doi.org/10.1101/2021.04.30.442099
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Haplotype Associated RNA Expression (HARE) Improves Prediction of Complex Traits in Maize
Anju Giri, Merritt Khaipho-Burch, Edward S. Buckler, Guillaume P. Ramstein
bioRxiv 2021.04.30.442099; doi: https://doi.org/10.1101/2021.04.30.442099

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