Protein interaction network of Arabidopsis thaliana female gametophyte development identifies novel proteins and relations

Long-Term Calorie Restriction Alters Anxiety-like Behaviour and the Brain and Adrenal Gland Transcriptomes of the Ageing Male Rat

Further examination of the molecular regulators of long-term calorie restriction (CR), reported to have an anxiolytic effect, may highlight novel therapeutic targets for anxiety disorders. Here, adult male Hooded Wistar rats were exposed to a 25% CR whilst anxiety-like behaviour was assessed at 6-, 12-, and 18-months of age via the elevated plus maze, open field, and acoustic startle tests. Next-generation sequencing was then used to measure transcriptome-wide gene expression in the hypothalamus, amygdala, pituitary, and adrenal glands. Results showed an anxiolytic behavioural profile across early, middle, and late adulthood by CR, with the strongest effects noted at 6-months. Transcriptomic analysis by seven attribute weighting algorithms, including Info Gain Ratio, Rule, Chi Squared, Gini Index, Uncertainty, Relief, and Info Gain, led to the development of a signature of long-term CR, independent of region. Complement C1q A chain (C1qa), an extracellular protein, expression was significantly decreased by CR in most regions examined. Furthermore, text mining highlighted the positive involvement of C1qa in anxiety, depression, neurodegeneration, stress, and ageing, collectively identifying a suitable biomarker candidate for CR. Overall, the current study identified anxiety-related phenotypic changes and a novel transcriptome signature of long-term CR, indicating potential therapeutic targets for anxiety, depression, and neurodegeneration.

From gene to biomolecular networks: a review of evidences for understanding complex biological function in plants

Although at the infancy stage, biomolecular network biology is a comprehensive approach to understand complex biological function in plants. Recent advancements in the accumulation of multi-omics data coupled with computational approach have accelerated our current understanding of the complexities of gene function at the system level. Biomolecular networks such as protein-protein interaction, co-expression and gene regulatory networks have extensively been used to decipher the intricacies of transcriptional reprogramming of hundreds of genes and their regulatory interaction in response to various environmental perturbations mainly in the model plant Arabidopsis. This review describes recent applications of network-based approaches to understand the biological functions in plants and focuses on the challenges and opportunities to harness the full potential of the approach.

Transcriptome analysis of a novel maize bsd C4 mutant using RNA-seq

The C4 plants like maize are at an advantage because they exhibit higher carbon conversion efficiency than C3 during photosynthesis. Using the evaluation of photosynthetic phenotypes and subcellular structure, and high-quality transcriptome analysis for four types of leaves from a bundle sheath defective maize mutant (bsd) and 501 wild line, the key target genes, important transcription factors, and specific pathways were obtained, which may regulate the C-concentrating mechanisms and antioxidant protection of the photosynthetic system, gibberellin signaling, ribosome editing, glycolysis, and chlorophyll biosynthesis. Based on these target genes, a novel network with photosynthetic transformation efficiency with oxidative decarboxylation and ribosome regulation was filtered innovatively by Cytoscape, which adds to our understanding for high-efficiency C-fixation and its genetic improvement in C3 and C4 plants.

Chemodiversity of the Glucosinolate-Myrosinase System at the Single Cell Type Resolution

Glucosinolates (GLSs) are a well-defined group of specialized metabolites, and like any other plant specialized metabolites, their presence does not directly affect the plant survival in terms of growth and development. However, specialized metabolites are essential to combat environmental stresses, such as pathogens and herbivores. GLSs naturally occur in many pungent plants in the order of Brassicales. To date, more than 200 different GLS structures have been characterized and their distribution differs from species to species. GLSs co-exist with classical and atypical myrosinases, which can hydrolyze GLS into an unstable aglycone thiohydroximate-O-sulfonate, which rearranges to produce different degradation products. GLSs, myrosinases, myrosinase interacting proteins, and GLS degradation products constitute the GLS-myrosinase (GM) system ("mustard oil bomb"). This review discusses the cellular and subcellular organization of the GM system, its chemodiversity, and functions in different cell types. Although there are many studies on the functions of GLSs and/or myrosinases at the tissue and whole plant levels, very few studies have focused on different single cell types. Single cell type studies will help to reveal specific functions that are missed at the tissue and organismal level. This review aims to highlight (1) recent progress in cellular and subcellular compartmentation of GLSs, myrosinases, and myrosinase interacting proteins; (2) molecular and biochemical diversity of GLSs and myrosinases; and (3) myrosinase interaction with its interacting proteins, and how it regulates the degradation of GLSs and thus the biological functions (e.g., plant defense against pathogens). Future prospects may include targeted approaches for engineering/breeding of plants and crops in the cell type-specific manner toward enhanced plant defense and nutrition.

Cross-Species Meta-Analysis of Transcriptomic Data in Combination With Supervised Machine Learning Models Identifies the Common Gene Signature of Lactation Process

Lactation, a physiologically complex process, takes place in mammary gland after parturition. The expression profile of the effective genes in lactation has not comprehensively been elucidated. Herein, meta-analysis, using publicly available microarray data, was conducted identify the differentially expressed genes (DEGs) between pre- and post-peak milk production. Three microarray datasets of Rat, Bos Taurus, and Tammar wallaby were used. Samples related to pre-peak (n = 85) and post-peak (n = 24) milk production were selected. Meta-analysis revealed 31 DEGs across the studied species. Interestingly, 10 genes, including MRPS18B, SF1, UQCRC1, NUCB1, RNF126, ADSL, TNNC1, FIS1, HES5 and THTPA, were not detected in original studies that highlights meta-analysis power in biosignature discovery. Common target and regulator analysis highlighted the high connectivity of CTNNB1, CDD4 and LPL as gene network hubs. As data originally came from three different species, to check the effects of heterogeneous data sources on DEGs, 10 attribute weighting (machine learning) algorithms were applied. Attribute weighting results showed that the type of organism had no or little effect on the selected gene list. Systems biology analysis suggested that these DEGs affect the milk production by improving the immune system performance and mammary cell growth. This is the first study employing both meta-analysis and machine learning approaches for comparative analysis of gene expression pattern of mammary glands in two important time points of lactation process. The finding may pave the way to use of publically available to elucidate the underlying molecular mechanisms of physiologically complex traits such as lactation in mammals.

The Zebrafish Equivalent of Alzheimer's Disease-Associated PRESENILIN Isoform PS2V Regulates Inflammatory and Other Responses to Hypoxic Stress

Dominant mutations in the PRESENILIN genes PSEN1 and PSEN2 cause familial Alzheimer's disease (fAD) that usually shows onset before 65 years of age. In contrast, genetic variation at the PSEN1 and PSEN2 loci does not appear to contribute to risk for the sporadic, late onset form of the disease (sAD), leading to doubts that these genes play a role in the majority of AD cases. However, a truncated isoform of PSEN2, PS2V, is upregulated in sAD brains and is induced by hypoxia and high cholesterol intake. PS2V can increase γ-secretase activity and suppress the unfolded protein response (UPR), but detailed analysis of its function has been hindered by lack of a suitable, genetically manipulable animal model since mice and rats lack this PRESENILIN isoform. We recently showed that zebrafish possess an isoform, PS1IV, that is cognate to human PS2V. Using an antisense morpholino oligonucleotide, we can block specifically the induction of PS1IV that normally occurs under hypoxia. Here, we exploit this ability to identify gene regulatory networks that are modulated by PS1IV. When PS1IV is absent under hypoxia-like conditions, we observe changes in expression of genes controlling inflammation (particularly sAD-associated IL1B and CCR5), vascular development, the UPR, protein synthesis, calcium homeostasis, catecholamine biosynthesis, TOR signaling, and cell proliferation. Our results imply an important role for PS2V in sAD as a component of a pathological mechanism that includes hypoxia/oxidative stress and support investigation of the role of PS2V in other diseases, including schizophrenia, when these are implicated in the pathology.

Isolation, Characterization, Cryopreservation of Human Amniotic Stem Cells and Differentiation to Osteogenic and Adipogenic Cells

Human stem cells and progenitor cells can be used to treat cancer and replace dysfunctional cells within a tissue or organ. The objective of this study was to identify the appropriate cells type in regenerative medicine and targeted therapy. As an alternative to embryonic and bone marrow stem cells, we examined human amniotic fluid stem cells (hAFSCs), one of the potential source of multipotent stem cells isolated from both cell pellet (using single-stage method), and supernatant of human amniotic fluid. Source of isolation and unique property of the cells emphasize that these cells are one of the promising new tools in therapeutic field. Double sources for isolation and availability of the left over samples in diagnostic laboratory at the same time have less legal and ethical concerns compared with embryonic stem cell studies. Cells were isolated, cultured for 18^th passage for 6 months and characterized using qPCR and flow cytometry. Cells showed good proliferative ability in culture condition. The cells successfully differentiated into the adipogenic and osteogenic lineages. Based on these findings, amniotic fluid can be considered as an appropriate and convenient source of human amniotic fluid stem cells. These cells provide potential tools for therapeutic applications in the field of regenerative medicine. To get a better understanding of crosstalk between Oct4/NANOG with osteogenesis and adipogenesis, we used network analysis based on Common Targets algorithm and Common Regulators algorithm as well as subnetwork discovery based on gene set enrichment. Network analysis highlighted the possible role of MIR 302A and MIR let-7g. We demonstrated the high expression of MIR 302A and low expression of MIR let7g in hAFSCs by qPCR.

Patterning of the angiosperm female gametophyte through the prism of theoretical paradigms

The FG (female gametophyte) of flowering plants (angiosperms) is a simple highly polar structure composed of only a few cell types. The FG develops from a single cell through mitotic divisions to generate, depending on the species, four to 16 nuclei in a syncytium. These nuclei are then partitioned into three or four distinct cell types. The mechanisms underlying the specification of the nuclei in the FG has been a focus of research over the last decade. Nevertheless, we are far from understanding the patterning mechanisms that govern cell specification. Although some results were previously interpreted in terms of static positional information, several lines of evidence now show that local interactions are important. In the present article, we revisit the available data on developmental mutants and cell fate markers in the light of theoretical frameworks for biological patterning. We argue that a further dissection of the mechanisms may be impeded by the combinatorial and dynamical nature of developmental cues. However, accounting for these properties of developing systems is necessary to disentangle the diversity of the phenotypic manifestations of the underlying molecular interactions.

A novel pairwise comparison method for in silico discovery of statistically significant cis-regulatory elements in eukaryotic promoter regions: application to Arabidopsis

Cis regulatory elements (CREs), located within promoter regions, play a significant role in the blueprint for transcriptional regulation of genes. There is a growing interest to study the combinatorial nature of CREs including presence or absence of CREs, the number of occurrences of each CRE, as well as of their order and location relative to their target genes. Comparative promoter analysis has been shown to be a reliable strategy to test the significance of each component of promoter architecture. However, it remains unclear what level of difference in the number of occurrences of each CRE is of statistical significance in order to explain different expression patterns of two genes. In this study, we present a novel statistical approach for pairwise comparison of promoters of Arabidopsis genes in the context of number of occurrences of each CRE within the promoters. First, using the sample of 1000 Arabidopsis promoters, the results of the goodness of fit test and non-parametric analysis revealed that the number of occurrences of CREs in a promoter sequence is Poisson distributed. As a promoter sequence contained functional and non-functional CREs, we addressed the issue of the statistical distribution of functional CREs by analyzing the ChIP-seq datasets. The results showed that the number of occurrences of functional CREs over the genomic regions was determined as being Poisson distributed. In accordance with the obtained distribution of CREs occurrences, we suggested the Audic and Claverie (AC) test to compare two promoters based on the number of occurrences for the CREs. Superiority of the AC test over Chi-square (2×2) and Fisher's exact tests was also shown, as the AC test was able to detect a higher number of significant CREs. The two case studies on the Arabidopsis genes were performed in order to biologically verify the pairwise test for promoter comparison. Consequently, a number of CREs with significantly different occurrences was identified between the promoters. The results of the pairwise comparative analysis together with the expression data for the studied genes revealed the biological significance of the identified CREs.

Prediction of potential cancer-risk regions based on transcriptome data: towards a comprehensive view

A novel integrative pipeline is presented for discovery of potential cancer-susceptibility regions (PCSRs) by calculating the number of altered genes at each chromosomal region, using expression microarray datasets of different human cancers (HCs). Our novel approach comprises primarily predicting PCSRs followed by identification of key genes in these regions to obtain potential regions harboring new cancer-associated variants. In addition to finding new cancer causal variants, another advantage in prediction of such risk regions is simultaneous study of different types of genomic variants in line with focusing on specific chromosomal regions. Using this pipeline we extracted numbers of regions with highly altered expression levels in cancer condition. Regulatory networks were also constructed for different types of cancers following the identification of altered mRNA and microRNAs. Interestingly, results showed that GAPDH, LIFR, ZEB2, mir-21, mir-30a, mir-141 and mir-200c, all located at PCSRs, are common altered factors in constructed networks. We found a number of clusters of altered mRNAs and miRNAs on predicted PCSRs (e.g.12p13.31) and their common regulators including KLF4 and SOX10. Large scale prediction of risk regions based on transcriptome data can open a window in comprehensive study of cancer risk factors and the other human diseases.