DNA methylation patterns explain missing heritability in maize

Abstract As our population grows and our climate changes, the ability to breed crops that are resilient yet productive enough to feed the world has become vitally important. Over the past few decades, improving accuracy of prediction models from genotype to phenotype has enabled faster development of crops at lower cost. Long-read sequencing technologies have already proven to be of great value to these models by enabling the construction of pangenomes, which significantly improve prediction accuracy compared to single reference genomes. However, there is still significant ‘missing heritability’ for complex traits that confounds our ability to effectively predict which lineages to bring forward during breeding pipelines. Here, using nanopore long-read sequencing and Dorado 5mC methylation calling, we characterize the entire methylome of 202 lines of Zea mays at single cytosine resolution, even in repetitive genomic regions, to power epigenome-wide association studies (epiGWAS) for 27 traits. We identified significant epigenetic loci that were able to improve the proportion of explainable phenotypic variation by over 20%. Many of these epi-loci were not captured by genetic variants, confirming that the epigenome contains novel information that breeders can leverage to accelerate crop development. These results demonstrate that patterns of DNA methylation captured by nanopore sequencing technology affect plant phenotype and explain much of the missing heritability in crop traits. Biography Jack Colicchio received his PhD at the University of Kansas, looking at the transcriptional and epigenetic responses of monkeyflowers to wounding. He then spent a few years at the University of California, Berkeley, looking at how epigenetic inheritance might impact the capacity of natural populations to persist in the face of climate change. For the past three years he has been working as a Data Scientist at Sound Agriculture, where he has been leveraging Oxford Nanopore sequencing data to develop systems to study epigenetics in plant crop systems.