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Pleiotropy-when a single gene controls two or more seemingly unrelated traits-has been shown to impact genes with effects on flowering time, leaf architecture, and inflorescence morphology in maize. However, the genome-wide impact of biological pleiotropy across all maize phenotypes is largely unknown. Here, we investigate the extent to which biological pleiotropy impacts phenotypes within maize using GWAS summary statistics reanalyzed from previously published metabolite, field, and expression phenotypes across the Nested Association Mapping population and Goodman Association Panel. Through phenotypic saturation of 120,597 traits, we obtain over 480 million significant quantitative trait nucleotides. We estimate that only 1.56-32.3% of intervals show some degree of pleiotropy. We then assess the relationship between pleiotropy and various biological features such as gene expression, chromatin accessibility, sequence conservation, and enrichment for gene ontology terms. We find very little relationship between pleiotropy and these variables when compared to permuted pleiotropy. We hypothesize that biological pleiotropy of common alleles is not widespread in maize and is highly impacted by nuisance terms such as population structure and linkage disequilibrium. Natural selection on large standing natural variation in maize populations may target wide and large effect variants, leaving the prevalence of detectable pleiotropy relatively low., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Traditional phenotyping methods, coupled with genetic mapping in segregating populations, have identified loci governing complex traits in many crops. Unoccupied aerial systems (UAS)-based phenotyping has helped to reveal a more novel and dynamic relationship between time-specific associated loci with complex traits previously unable to be evaluated. Over 1,500 maize (Zea mays L.) hybrid row plots containing 280 different replicated maize hybrids from the Genomes to Fields (G2F) project were evaluated agronomically and using UAS in 2017. Weekly UAS flights captured variation in plant heights during the growing season under three different management conditions each year: optimal planting with irrigation (G2FI), optimal dryland planting without irrigation (G2FD), and a stressed late planting (G2LA). Plant height of different flights were ranked based on importance for yield using a random forest (RF) algorithm. Plant heights captured by early flights in G2FI trials had higher importance (based on Gini scores) for predicting maize grain yield (GY) but also higher accuracies in genomic predictions which fluctuated for G2FD (-0.06∼0.73), G2FI (0.33∼0.76), and G2LA (0.26∼0.78) trials. A genome-wide association analysis discovered 52 significant single nucleotide polymorphisms (SNPs), seven were found consistently in more than one flights or trial; 45 were flight or trial specific. Total cumulative marker effects for each chromosome's contributions to plant height also changed depending on flight. Using UAS phenotyping, this study showed that many candidate genes putatively play a role in the regulation of plant architecture even in relatively early stages of maize growth and development., (© 2021 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.)

Background: Chronic stress-induced cardiac pathology exhibits both a wide range in severity and a high degree of heterogeneity in clinical manifestation in human patients. This variability is contributed to by complex genetic and environmental etiologies within the human population. Genetic approaches to elucidate the genetics underlying the acquired forms of cardiomyopathies, including genome-wide association studies, have been largely unsuccessful, resulting in limited knowledge as to the contribution of genetic variations for this important disease., Methods and Results: Using the β-adrenergic agonist isoproterenol as a specific pathological stressor to circumvent the problem of etiologic heterogeneity, we performed a genome-wide association study for genes influencing cardiac hypertrophy and fibrosis in a large panel of inbred mice. Our analyses revealed 7 significant loci and 17 suggestive loci, containing an average of 14 genes, affecting cardiac hypertrophy, fibrosis, and surrogate traits relevant to heart failure. Several loci contained candidate genes which are known to contribute to Mendelian cardiomyopathies in humans or have established roles in cardiac pathology based on molecular or genetic studies in mouse models. In particular, we identify Abcc6 as a novel gene underlying a fibrosis locus by validating that an allele with a splice mutation of Abcc6 dramatically and rapidly promotes isoproterenol-induced cardiac fibrosis., Conclusions: Genetic variants significantly contribute to the phenotypic heterogeneity of stress-induced cardiomyopathy. Systems genetics is an effective approach to identify genes and pathways underlying the specific pathological features of cardiomyopathies. Abcc6 is a previously unrecognized player in the development of stress-induced cardiac fibrosis., (© 2014 American Heart Association, Inc.)