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Science Papers Present More Than Two Dozen Maize Genomes, Approach for Studying RNA Modifications

The de novo genome assemblies, transcriptomes, annotations, and methylomes for 26 diverse maize lines are published in Science this week. Despite maize being the most widely planted crop in the world, most current genomic resources for the plant are referenced to a single inbred — called B73 — that contains only 63 percent to 74 percent of the genes and/or low-copy sequences in the full maize pan-genome. To address this, a multi-institute team led by scientists from the University of Georgia selected 25 founder inbred lines that represent the breadth of maize diversity for sequencing, while also improving the reference assembly for B73. An analysis of the genomes uncovered variation in both the genic and repetitive fractions of the pan-genome. Tropical, temperate, and flint-derived popcorn and sweet corn germplasm, meantime, were found to be differentiated in distinctive ways including their pan-gene complement, homolog retention after polyploidy, and abundance of transposable elements. The findings "will have broad utility for genetic and genomic studies and facilitate rapid associations to phenotyping information," the study's authors write. "More generally, these resources should motivate a shift away from the single-reference mindset to a multireference view."

A statistical framework for studying RNA modifications in large clinical cohorts using standard RNA sequencing datasets generated in such studies is described in Science Advances this week. Association studies in large clinical cohorts are highly effective in identifying possible relationships between human diseases and variations on the genetic, epigenetic, transcriptomic, and proteomic layers. Because RNA modifications are important regulators of molecular processes and appear to be involved in human disease, studying the epitranscriptome in large clinical cohorts could also likely reveal unexpected relationships between different types of RNA modifications and a multitude of human diseases. To that end, a National University of Singapore team developed a computational method, called ModTect, that relies on two principles for RNA modification detection: the presence of a multinucleotide mismatch signal and the presence of a deletion signal. Applying ModTect to 11,371 patient samples and 934 cell lines across 33 cancer types, the researchers show that the epitranscriptome was dysregulated in patients across multiple cancer types and was associated with cancer progression and survival outcomes. They also find that some types of RNA modifications were also more disrupted than others in patients with cancer and that RNA modifications contribute to multiple types of RNA-DNA sequence differences that escape detection with Sanger sequencing.