Small RNA-based prediction of hybrid performance in maize

Felix Seifert,Stefan Scholten,Alexander Thiemann,Dominika Rybka,Albrecht E Melchinger,Tobias A Schrag,Matthias Frisch

doi:10.1186/s12864-018-4708-8

Felix Seifert, Stefan Scholten + Show 5 more

Open Access

https://doi.org/10.1186/s12864-018-4708-8

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Abstract

BackgroundSmall RNA (sRNA) sequences are known to have a broad impact on gene regulation by various mechanisms. Their performance for the prediction of hybrid traits has not yet been analyzed. Our objective was to analyze the relation of parental sRNA expression with the performance of their hybrids, to develop a sRNA-based prediction approach, and to compare it to more common SNP and mRNA transcript based predictions using a factorial mating scheme of a maize hybrid breeding program.ResultsCorrelation of genomic differences and messenger RNA (mRNA) or sRNA expression differences between parental lines with hybrid performance of their hybrids revealed that sRNAs showed an inverse relationship in contrast to the other two data types. We associated differences for SNPs, mRNA and sRNA expression between parental inbred lines with the performance of their hybrid combinations and developed two prediction approaches using distance measures based on associated markers. Cross-validations revealed parental differences in sRNA expression to be strong predictors for hybrid performance for grain yield in maize, comparable to genomic and mRNA data. The integration of both positively and negatively associated markers in the prediction approaches enhanced the prediction accurary. The associated sRNAs belong predominantly to the canonical size classes of 22- and 24-nt that show specific genomic mapping characteristics.ConclusionExpression profiles of sRNA are a promising alternative to SNPs or mRNA expression profiles for hybrid prediction, especially for plant species without reference genome or transcriptome information. The characteristics of the sRNAs we identified suggest that association studies based on breeding populations facilitate the identification of sRNAs involved in hybrid performance.

Highlights

Small RNA sequences are known to have a broad impact on gene regulation by various mechanisms
Correlation of genomic, messenger RNA (mRNA) and Small RNA (sRNA) expression differences with hybrid performance For all three data types (SNP, mRNA, sRNA) we correlated the sum of differences between inbred line combinations with HP for grain yield (GY) to test for relations of parental differences and HP for GY
The correlation of Single Nucleotide polymorphism (SNP) differences and mRNA differences between inbred line combinations with HP for GY in their hybrids resulted in moderate (r = 0.474, p = 8. 110 × 10− 7, Fig. 1a) and weak (r = 0.343, p = 5.5 × 10− 4, Fig. 1b) positive correlations, respectively

Summary

Introduction

Small RNA (sRNA) sequences are known to have a broad impact on gene regulation by various mechanisms Their performance for the prediction of hybrid traits has not yet been analyzed. Artificial selection from an isogenic plant population over multiple generations resulted in plants with superior phenotypic performance, which could be stably inherited over generations [18] These results suggest that epigenetics has the potential to enhance future plant breeding as well as to provide useful markers [18, 19]. The mechanisms of trans-chromosomal methylation and demethylation have been associated with small RNA expression level differences between parental inbred lines [23] These relations suggest that parental sRNAs play a major role in setting genome-wide changes in the epigenetic landscape through hybridization. Parental sRNAs are likely to reflect these changes to a certain extend and we assume that they might be promising markers for the prediction of hybrid traits

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