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Non-conventional peptides (NCPs), which include small open reading frame-encoded peptides, play critical roles in fundamental biological processes. In this study, we developed an integrated peptidogenomic pipeline using high-throughput mass spectra to probe a customized six-frame translation database and applied it to large-scale identification of NCPs in plants.A total of 1993 and 1860 NCPs were unambiguously identified in maize and Arabidopsis , respectively. These NCPs showed distinct characteristics compared with conventional peptides and were derived from introns, 3′ UTRs, 5′ UTRs, junctions, and intergenic regions. Furthermore, our results showed that translation events in unannotated transcripts occur more broadly than previously thought. In addition, we found that dozens of maize NCPs are enriched within regions associated with phenotypic variations and domestication selection, indicating that they potentially are involved in genetic regulation of complex traits and domestication in maize. Taken together, our study developed an integrated peptidogenomic pipeline for large-scale identification of NCPs in plants, which would facilitate global characterization of NCPs from other plants. The identification of large-scale NCPs in both monocot (maize) and dicot (Arabidopsis) plants indicates that a large portion of plant genome can be translated into biologically functional molecules, which has important implications for functional genomic studies. This study developed an integrated peptidogenomic pipeline and applied it for large-scale identification of non-conventional peptides (NCPs) in plants. The identified NCPs, which were derived from introns, 3′ UTRs, 5′ UTRs, junctions, and intergenic regions, showed distinct characteristics compared with the conventional peptides. Association analysis unveiled that dozens of NCPs identified are potentially involved in genetic regulation of complex traits and demostication in maize. [ABSTRACT FROM AUTHOR]

A detailed understanding of genetic architecture of mRNA expression by millions of genetic variants is important for studying quantitative trait variation. In this study, we identified 1.25M SNPs with a minor allele frequency greater than 0.05 by combining reduced genome sequencing (GBS), high-density array technologies (600K), and previous deep RNA-sequencing data from 368 diverse inbred lines of maize. The balanced allelic frequencies and distributions in a relatively large and diverse natural panel helped to identify expression quantitative trait loci (eQTLs) associated with more than 18 000 genes (63.4% of tested genes). We found that distant eQTLs were more frequent (∼75% of all eQTLs) across the whole genome. Thirteen novel associated loci affecting maize kernel oil concentration were identified using the new dataset, among which one intergenic locus affected the kernel oil variation by controlling expression of three other known oil-related genes. Altogether, this study provides resources for expanding our understanding of cellular regulatory mechanisms of transcriptome variation and the landscape of functional variants within the maize genome, thereby enhancing the understanding of quantitative variations. [ABSTRACT FROM AUTHOR]

Genome-wide association study (GWAS) has become a widely accepted strategy for decoding genotype-phenotype associations in many species thanks to advances in next-generation sequencing (NGS) technologies. Maize is an ideal crop for GWAS and significant progress has been made in the last decade. This review summarizes current GWAS efforts in maize functional genomics research and discusses future prospects in the omics era. The general goal of GWAS is to link genotypic variations to corresponding differences in phenotype using the most appropriate statistical model in a given population. The current review also presents perspectives for optimizing GWAS design and analysis. GWAS analysis of data from RNA, protein, and metabolite-based omics studies is discussed, along with new models and new population designs that will identify causes of phenotypic variation that have been hidden to date. The joint and continuous efforts of the whole community will enhance our understanding of maize quantitative traits and boost crop molecular breeding designs. [ABSTRACT FROM AUTHOR]

The temperate-tropical division of early maize germplasms to different agricultural environments was arguably the greatest adaptation process associated with the success and near ubiquitous importance of global maize production. Deciphering this history is challenging, but new insight has been gained from examining 558 529 single nucleotide polymorphisms, expression data of 28 769 genes, and 662 traits collected from 368 diverse temperate and tropical maize inbred lines in this study. This is a new attempt to systematically exploit the mechanisms of the adaptation process in maize. Our results indicate that divergence between tropical and temperate lines apparently occurred 3400–6700 years ago. Seven hundred and one genomic selection signals and transcriptomic variants including 2700 differentially expressed individual genes and 389 rewired co-expression network genes were identified. These candidate signals were found to be functionally related to stress responses, and most were associated with directionally selected traits, which may have been an advantage under widely varying environmental conditions faced by maize as it was migrated away from its domestication center. Our study also clearly indicates that such stress adaptation could involve evolution of protein-coding sequences as well as transcriptome-level regulatory changes. The latter process may be a more flexible and dynamic way for maize to adapt to environmental changes along its short evolutionary history. [ABSTRACT FROM AUTHOR]