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BackgroundTranscription factors (TFs) are proteins that can bind to DNA sequences and regulate gene expression. Many TFs are master regulators in cells that contribute to tissue-specific and cell-type-specific gene expression patterns in eukaryotes. Maize has been a model organism for over one hundred years, but little is known about its tissue-specific gene regulation through TFs. In this study, we used a network approach to elucidate gene regulatory networks (GRNs) in four tissues (leaf, root, SAM and seed) in maize. We utilized GENIE3, a machine-learning algorithm combined with large quantity of RNA-Seq expression data to construct four tissue-specific GRNs. Unlike some other techniques, this approach is not limited by high-quality Position Weighed Matrix (PWM), and can therefore predict GRNs for over 2000 TFs in maize.ResultsAlthough many TFs were expressed across multiple tissues, a multi-tiered analysis predicted tissue-specific regulatory functions for many transcription factors. Some well-studied TFs emerged within the four tissue-specific GRNs, and the GRN predictions matched expectations based upon published results for many of these examples. Our GRNs were also validated by ChIP-Seq datasets (KN1, FEA4 and O2). Key TFs were identified for each tissue and matched expectations for key regulators in each tissue, including GO enrichment and identity with known regulatory factors for that tissue. We also found functional modules in each network by clustering analysis with the MCL algorithm.ConclusionsBy combining publicly available genome-wide expression data and network analysis, we can uncover GRNs at tissue-level resolution in maize. Since ChIP-Seq and PWMs are still limited in several model organisms, our study provides a uniform platform that can be adapted to any species with genome-wide expression data to construct GRNs. We also present a publicly available database, maize tissue-specific GRN (mGRN, https://www.bio.fsu.edu/mcginnislab/mgrn/), for easy querying. All source code and data are available at Github (https://github.com/timedreamer/maize_tissue-specific_GRN).Electronic supplementary materialThe online version of this article (10.1186/s12870-018-1329-y) contains supplementary material, which is available to authorized users.

Many studies have suggested a link between the spatial organization of genomes and fundamental biological processes such as genome reprogramming, gene expression, and differentiation. Multicolor fluorescence in situ hybridization on three-dimensionally preserved nuclei (3D-FISH), in combination with confocal microscopy, has become an effective technique for analyzing 3D genome structure and spatial patterns of defined nucleus targets including entire chromosome territories and single gene loci. This technique usually requires the simultaneous visualization of numerous targets labeled with different colored fluorochromes. Thus, the number of channels and lasers must be sufficient for the commonly used labeling scheme of 3D-FISH, "one probe-one target". However, these channels and lasers are usually restricted by a given microscope system. This paper presents a method for simultaneously delineating multiple targets in 3D-FISH using limited channels, lasers, and fluorochromes. In contrast to other labeling schemes, this method is convenient and simple for multicolor 3D-FISH studies, which may result in widespread adoption of the technique. Lastly, as an application of the method, the nucleus locations of chromosome territory 18/21 and centromere 18/21/13 in normal human lymphocytes were analyzed, which might present evidence of a radial higher order chromatin arrangement.

Primitive proteins are proposed to have utilized organic cofactors more frequently than transition metals in redox reactions. Thus, an experimental validation on whether a protein constituted solely by early amino acids and an organic cofactor can perform electron transfer activity is an urgent challenge. In this paper, by substituting “late amino acids (C, F, M, T, W, and Y)” with “early amino acids (A, L, and V)” in a flavodoxin, we constructed a flavodoxin mutant and evaluated its characteristic properties. The major results showed that: (1) The flavodoxin mutant has structural characteristics similar to wild-type protein; (2) Although the semiquinone and hydroquinone flavodoxin mutants possess lower stability than the corresponding form of wild-type flavodoxin, the redox potential of double electron reduction Em,7 (fld) reached −360 mV, indicating that the flavodoxin mutant constituted solely by early amino acids can exert effective electron transfer activity.