PiNGO: a Cytoscape plugin to find candidate genes in biological networks

Integrating Genome-Wide Association Study, Transcriptome and Metabolome Reveal Novel QTL and Candidate Genes That Control Protein Content in Soybean

Protein content (PC) is crucial to the nutritional quality of soybean [Glycine max (L.) Merrill]. In this study, a total of 266 accessions were used to perform a genome-wide association study (GWAS) in three tested environments. A total of 23,131 high-quality SNP markers (MAF ≥ 0.02, missing data ≤ 10%) were identified. A total of 40 association signals were significantly associated with PC. Among them, five novel quantitative trait nucleotides (QTNs) were discovered, and another 32 QTNs were found to be overlapping with the genomic regions of known quantitative trait loci (QTL) related to soybean PC. Combined with GWAS, metabolome and transcriptome sequencing, 59 differentially expressed genes (DEGs) that might control the change in protein content were identified. Meantime, four commonly upregulated differentially abundant metabolites (DAMs) and 29 commonly downregulated DAMs were found. Remarkably, the soybean gene Glyma.08G136900, which is homologous with Arabidopsis hydroxyproline-rich glycoproteins (HRGPs), may play an important role in improving the PC. Additionally, Glyma.08G136900 was divided into two main haplotype in the tested accessions. The PC of haplotype 1 was significantly lower than that of haplotype 2. The results of this study provided insights into the genetic mechanisms regulating protein content in soybean.

Combined analysis of the metabolome and transcriptome provides insight into seed oil accumulation in soybean

BACKGROUND

Soybean (Glycine max (L.) Merr) is an important source of human food, animal feed, and bio-energy. Although the genetic network of lipid metabolism is clear in Arabidopsis, the understanding of lipid metabolism in soybean is limited.

RESULTS

In this study, 30 soybean varieties were subjected to transcriptome and metabolome analysis. In total, 98 lipid-related metabolites were identified, including glycerophospholipid, alpha-linolenic acid, linoleic acid, glycolysis, pyruvate, and the sphingolipid pathway. Of these, glycerophospholipid pathway metabolites accounted for the majority of total lipids. Combining the transcriptomic and metabolomic analyses, we found that 33 lipid-related metabolites and 83 lipid-related genes, 14 lipid-related metabolites and 17 lipid-related genes, and 12 lipid-related metabolites and 25 lipid-related genes were significantly correlated in FHO (five high-oil varieties) vs. FLO (five low-oil varieties), THO (10 high-oil varieties) vs. TLO (10 low-oil varieties), and HO (15 high-oil varieties) vs. LO (15 low-oil varieties), respectively.

CONCLUSIONS

The GmGAPDH and GmGPAT genes were significantly correlated with lipid metabolism genes, and the result revealed the regulatory relationship between glycolysis and oil synthesis. These results improve our understanding of the regulatory mechanism of soybean seed oil improvement.

Tanshinone I: Pharmacological activities, molecular mechanisms against diseases and future perspectives

BACKGROUND

Tanshinone I (Tan I) is known as one of the important active components in Salvia miltiorrhiza. In recent years, Tan I has received a substantial amount of attention from the research community for various studies being updated and has been shown to possess favorable activities including anti-oxidative stress, regulation of cell autophagy or apoptosis, inhibition of inflammation, etc. PURPOSE: To summarize the investigation progress on the anti-disease efficacy and effect mechanism of Tan I in recent years, and provide perspectives for future study on the active ingredient.

METHOD

Web of Science and PubMed databases were used to search for articles related to "Tanshinone I" published from 2010 to 2022. Proteins or genes and signaling pathways referring to Tan I against diseases were summarized and classified along with its different therapeutic actions. Protein-protein interaction (PPI) analysis was then performed, followed by molecular docking between proteins with high node degree and Tan I, as well as bioinformactic analysis including GO, KEGG and DO enrichment analysis with the collected proteins or genes.

RESULTS

Tan I shows multiple therapeutic effects, including protection of the cardiovascular system, anti-cancer, anti-inflammatory, anti-neurodegenerative diseases, etc. The targets (proteins or genes) affected by Tan I against diseases involve Bcl-2, Bid, ITGA2, PPAT, AURKA, VEGF, PI3K, AKT, PRK, JNK, MMP9, ABCG2, CASP3, Cleaved-caspase-3, AMPKα, PARP, etc., and the regulatory pathways refer to Akt/Nrf2, SAPK/JNK, PI3K/Akt/mTOR, JAK/STAT3, ATF-2/ERK, etc. What's more, AKT1, CASP3, and STAT3 were predicted as the key action targets for Tan I by PPI analysis combined with molecular docking, and the potential therapeutic effects mechanisms against diseases were also further predicted by bioinformatics analyses based on the reported targets, providing new insights into the future investigation and helping to facilitate the drug development of Tan I.

Integrated transcriptome and proteome analysis of developing embryo reveals the mechanisms underlying the high levels of oil accumulation in Carya cathayensis Sarg

Hickory (Carya cathayensis Sarg.) is an extraordinary nut-bearing deciduous arbor with high content of oil in its embryo. However, the molecular mechanism underlying high oil accumulation is mostly unknown. Here, we reported that the lipid droplets and oil accumulation gradually increased with the embryo development and the oil content was up to ~76% at maturity. Furthermore, transcriptome and proteome analysis of developing hickory embryo identified 32,907 genes and 9857 proteins. Time-series analysis of gene expressions showed that these genes were divided into 12 clusters and lipid metabolism-related genes were enriched in Cluster 3, with the highest expression levels at 95 days after pollination (S2). Differentially expressed genes and proteins indicated high correlation, and both were enriched in the lipid metabolism. Notably, the genes involved in biosynthesis, transport of fatty acid/lipid and lipid droplets formation had high expression levels at S2, while the expression levels of other genes required for suberin/wax/cutin biosynthesis and lipid degradation were very low at all the sampling time points, ultimately promoting the accumulation of oil. Quantitative reverse-transcription PCR analysis also verified the results of RNA-seq. The co-regulatory networks of lipid metabolism were further constructed and WRINKLED1 (WRI1) was a core transcriptional factor located in the nucleus. Of note, CcWRI1A/B could directly activate the expression of some genes (CcBCCP2A, CcBCCP2B, CcFATA and CcFAD3) required for fatty acid synthesis. These results provided in-depth evidence for revealing the molecular mechanism of high oil accumulation in hickory embryo.

Global Transcriptome Analysis Revealed the Molecular Regulation Mechanism of Pigment and Reactive Oxygen Species Metabolism During the Stigma Development of Carya cathayensis

Hickory (Carya cathayensis Sarg.) is a monoecious plant of the genus Carya of the Juglandaceae family. Its nuts contain a number of nutritional compounds and are deeply loved by consumers. Interestingly, it was observed that the color of hickory stigma changed obviously from blooming to mature. However, the molecular mechanism underlying color formation during stigma development and the biological significance of this phenomenon was mostly unknown. In this work, pigment content, reactive oxygen species (ROS) removal capacity, and transcriptome analysis of developing stigma of hickory at 4 differential sampling time points (S1, S2, S3, and S4) were performed to reveal the dynamic changes of related pigment, antioxidant capacity, and its internal molecular regulatory mechanism. It was found that total chlorophyll content was decreased slightly from S1 to S4, while total carotenoids content was increased from S1 to S3 but decreased gradually from S3 to S4. Total anthocyanin content continued to increase during the four periods of stigma development, reaching the highest level at the S4. Similarly, the antioxidant capacity of stigma was also gradually improved from S1 to S4. Furthermore, transcriptome analysis of developing hickory stigma identified 31,027 genes. Time-series analysis of gene expressions showed that these genes were divided into 12 clusters. Cluster 5 was enriched with some genes responsible for porphyrin and chlorophyll metabolism, carotenoid metabolism, and photosynthesis. Meanwhile, cluster 10 was enriched with genes related to flavonoid metabolism, including anthocyanin involved in ROS scavenging, and its related genes were mainly distributed in cluster 12. Based on the selected threshold values, a total of 10432 differentially expressed genes were screened out and enriched in the chlorophyll, carotenoid, anthocyanin, and ROS metabolism. The expression trends of these genes provided plausible explanations for the dynamic change of color and ROS level of hickory stigma with development. qRT-PCR analyses were basically consistent with the results of RNA-seq. The gene co-regulatory networks of pigment and ROS metabolism were further constructed and MYB113 (CCA0887S0030) and WRKY75 (CCA0573S0068) were predicted to be two core transcriptional regulators. These results provided in-depth evidence for revealing the molecular mechanism of color formation in hickory stigma and its biological significance.

Transcriptome Analysis of Walnut (Juglans regia L.) Embryos Reveals Key Developmental Stages and Genes Involved in Lipid Biosynthesis and Polyunsaturated Fatty Acid Metabolism

Walnut (Juglans regia L.) is a widely cultivated woody oilseed tree species, and its embryo is rich in polyunsaturated fatty acids. Thus far, the pathways and essential genes involved in oil biosynthesis in developing walnut embryos remain largely unclear. Our analyses revealed that a mature walnut embryo accumulated 69% oil, in which 71% were polyunsaturated fatty acids with 64% linoleic acid and 7% linolenic acid. RNA sequencing generated 39 384 unigenes in 24 cDNA libraries prepared from walnut embryos collected at 49, 63, 77, 91, 105, 119, 133, and 147 days after pollination (DAP). The principal components analysis (PCA) of samples and cluster analysis of differentially expressed genes (DEGs) showed that the total samples were divided into three main groups: 49 DAP, 63-119 DAP, and 133-147 DAP. We identified 108 unigenes associated with lipid biosynthesis, including 60 unigenes for fatty acid biosynthesis, 33 for triacylglycerol biosynthesis, 7 for oil bodies, and 8 for transcription factors. The expression levels of the genes encoding WRI1, ACCase, ACP, KASII, SAD, FAD2, FAD3, and PDAT were upregulated at 63-119 DAP relative to the levels at 49 DAP. Additionally, the lipid biosynthesis in walnut embryos began to increase while oil contents increased from 15 to 69%. We identified eight SAD, three FAD2, one FAD3, one FAD5, one FAD6, and three FAD7/8 genes. In addition, SAD, FAD2, and FAD3 were highly abundantly expressed in the walnut embryo, and their FPKM values achieved were 834, 2205, and 9038, respectively. High expression levels of FAD2 and FAD3 may be the reason why walnuts are rich in polyunsaturated fatty acids. Subcellular localization confirmed that the JrFAD3 protein played a role in the endoplasmic reticulum rather than the plastid, suggesting that linolenic acid was mainly synthesized in the endoplasmic reticulum. Weighted gene coexpression network analysis (WGCNA) showed that ACP, ENO, VAMP727, and IDD14 were coexpressed with WRI1. Our study provides large-scale and comprehensive transcriptome data of walnut embryo development. These data lay the foundation for the metabolic engineering of walnuts to increase oil contents and modify fatty acid compositions.

Using single-plant-omics in the field to link maize genes to functions and phenotypes

Most of our current knowledge on plant molecular biology is based on experiments in controlled laboratory environments. However, translating this knowledge from the laboratory to the field is often not straightforward, in part because field growth conditions are very different from laboratory conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional laboratory-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

Tracing the footsteps of autophagy in computational biology

Autophagy plays a crucial role in maintaining cellular homeostasis through the degradation of unwanted materials like damaged mitochondria and misfolded proteins. However, the contribution of autophagy toward a healthy cell environment is not only limited to the cleaning process. It also assists in protein synthesis when the system lacks the amino acids’ inflow from the extracellular environment due to diet consumptions. Reduction in the autophagy process is associated with diseases like cancer, diabetes, non-alcoholic steatohepatitis, etc., while uncontrolled autophagy may facilitate cell death. We need a better understanding of the autophagy processes and their regulatory mechanisms at various levels (molecules, cells, tissues). This demands a thorough understanding of the system with the help of mathematical and computational tools. The present review illuminates how systems biology approaches are being used for the study of the autophagy process. A comprehensive insight is provided on the application of computational methods involving mathematical modeling and network analysis in the autophagy process. Various mathematical models based on the system of differential equations for studying autophagy are covered here. We have also highlighted the significance of network analysis and machine learning in capturing the core regulatory machinery governing the autophagy process. We explored the available autophagic databases and related resources along with their attributes that are useful in investigating autophagy through computational methods. We conclude the article addressing the potential future perspective in this area, which might provide a more in-depth insight into the dynamics of autophagy.

Comparative transcriptome and co-expression analysis reveal key genes involved in leaf margin serration in Perilla frutescens

Objective

In this study, we aimed to identify the genes involved in leaf margin serration in Perilla frutescens. P. frutescens (Family: Lamiaceae) is widely grown in Asian countries. Perilla leaf is the medicinal part stipulated in the Chinese Pharmacopoeia. There are mainly two types of perilla leaves: one with serrated leaf margin which is the phenotype described in the pharmacopoeia and the other with smooth leaf margin.

Methods

Transcriptome sequencing, co-expression analysis, and qRT-PCR analysis of six perilla tissues sampled from two different phenotypes (serrated and smooth leaves) were performed.

Results

Forty-three differentially expressed genes (DEGs), which may potentially regulate leaf shape, were identified through de novo transcriptome sequencing between the two groups. Genes involved in leaf shape regulation were identified. Simultaneously, we validated five DEGs by qRT-PCR, and the results were consistent with the transcriptome data. In addition, 1186 transcription factors (TFs) belonging to 45 TF families were identified. Moreover, the co-expression network of DEGs was constructed.

Conclusion

The study identified the key genes that control leaf shape by comparing the transcriptomes. Our findings also provide basic data for further exploring P. frutescens, which can help study the mechanism of leaf shape development and molecular breeding.

Awakening ancient polar Actinobacteria: diversity, evolution and specialized metabolite potential

Polar and subpolar ecosystems are highly vulnerable to global climate change with consequences for biodiversity and community composition. Bacteria are directly impacted by future environmental change and it is therefore essential to have a better understanding of microbial communities in fluctuating ecosystems. Exploration of Polar environments, specifically sediments, represents an exciting opportunity to uncover bacterial and chemical diversity and link this to ecosystem and evolutionary parameters. In terms of specialized metabolite production, the bacterial order Actinomycetales, within the phylum Actinobacteria are unsurpassed, producing 10 000 specialized metabolites accounting for over 45 % of all bioactive microbial metabolites. A selective isolation approach focused on spore-forming Actinobacteria of 12 sediment cores from the Antarctic and sub-Arctic generated a culture collection of 50 strains. This consisted of 39 strains belonging to rare A ctinomycetales genera including Microbacterium, Rhodococcus and Pseudonocardia. This study used a combination of nanopore sequencing and molecular networking to explore the community composition, culturable bacterial diversity, evolutionary relatedness and specialized metabolite potential of these strains. Metagenomic analyses using MinION sequencing was able to detect the phylum Actinobacteria across polar sediment cores at an average of 13 % of the total bacterial reads. The resulting molecular network consisted of 1652 parent ions and the lack of known metabolite identification supports the argument that Polar bacteria are likely to produce previously unreported chemistry.

WGCNA Analysis of Salt-Responsive Core Transcriptome Identifies Novel Hub Genes in Rice

Rice, being a major staple food crop and sensitive to salinity conditions, bears heavy yield losses due to saline soil. Although some salt responsive genes have been identified in rice, their applications in developing salt tolerant cultivars have resulted in limited achievements. Herein, we used bioinformatic approaches to perform a meta-analysis of three transcriptome datasets from salinity and control conditions in order to reveal novel genes and the molecular pathways underlying rice response to salt. From a total of 28,432 expressed genes, we identify 457 core differentially expressed genes (DEGs) constitutively responding to salt, regardless of the stress duration, genotype, or the tissue. Gene co-expression analysis divided the core DEGs into three different modules, each of them contributing to salt response in a unique metabolic pathway. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses highlighted key biological processes and metabolic pathways involved in the salt response. We identified important novel hub genes encoding proteins of different families including CAM, DUF630/632, DUF581, CHL27, PP2-13, LEA4-5, and transcription factors, which could be functionally characterized using reverse genetic experiments. This novel repertoire of candidate genes related to salt response in rice will be useful for engineering salt tolerant varieties.

Identification of Fatty Acid Desaturases in Maize and Their Differential Responses to Low and High Temperature

Plant fatty acid desaturases (FADs) catalyze the desaturation of fatty acids in various forms and play important roles in regulating fatty acid composition and maintaining membrane fluidity under temperature stress. A total of 30 FADs were identified from a maize genome, including 13 soluble and 17 membrane-bound FADs, which were further classified into two and five sub-groups, respectively, via phylogenetic analysis. Although there is no evolutionary relationship between the soluble and the membrane-bound FADs, they all harbor a highly conserved FA_desaturase domain, and the types and the distributions of conserved motifs are similar within each sub-group. The transcriptome analysis revealed that genes encoding FADs exhibited different expression profiles under cold and heat stresses. The expression of ZmFAD2.1&2.2, ZmFAD7, and ZmSLD1&3 were significantly up-regulated under cold stress; moreover, the expression of ZmFAD2.1&2.3 and ZmSLD1&3 were obviously down-regulated under heat stress. The co-expression analysis demonstrated close correlation among the transcription factors and the significant responsive FAD genes under cold or heat stress. This study helps to understand the roles of plant FADs in temperature stress responses.

Red and Blue Light Promote the Accumulation of Artemisinin in Artemisia Annua L

Artemisinin, which has been isolated from Artemisia annua L., is the most effective antimalarial drug and has saved millions of lives. In addition, artemisinin and its derivatives have anti-tumor, anti-parasitic, anti-fibrosis, and anti-arrhythmic properties, which enhances the demand for these compounds. Improving the content of artemisinin in A. annua is therefore becoming an increasing research interest, as the chemical synthesis of this metabolite is not viable. Ultraviolet B and C irradiation have been reported to improve the artemisinin content in A. annua, but they are harmful to plant growth and development. Therefore, we screened other light sources to examine if they could promote artemisinin content without affecting plant growth and development. We found that red and blue light could enhance artemisinin accumulation by promoting the expression of the genes that were involved in artemisinin biosynthesis, such as amorpha-4,11-diene synthase (ADS) and cytochrome P450 monooxygenase (CYP71AV1) genes. Thus, in addition to being the main light sources for photosynthesis, red and blue light play a key role in plant secondary metabolism, and optimizing the combination of these light might allow for the productionof artemisinin-rich A. annua.

RNA Sequencing and Coexpression Analysis Reveal Key Genes Involved in α-Linolenic Acid Biosynthesis in Perilla frutescens Seed

Perilla frutescen is used as traditional food and medicine in East Asia. Its seeds contain high levels of α-linolenic acid (ALA), which is important for health, but is scarce in our daily meals. Previous reports on RNA-seq of perilla seed had identified fatty acid (FA) and triacylglycerol (TAG) synthesis genes, but the underlying mechanism of ALA biosynthesis and its regulation still need to be further explored. So we conducted Illumina RNA-sequencing in seven temporal developmental stages of perilla seeds. Sequencing generated a total of 127 million clean reads, containing 15.88 Gb of valid data. The de novo assembly of sequence reads yielded 64,156 unigenes with an average length of 777 bp. A total of 39,760 unigenes were annotated and 11,693 unigenes were found to be differentially expressed in all samples. According to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, 486 unigenes were annotated in the “lipid metabolism” pathway. Of these, 150 unigenes were found to be involved in fatty acid (FA) biosynthesis and triacylglycerol (TAG) assembly in perilla seeds. A coexpression analysis showed that a total of 104 genes were highly coexpressed (r > 0.95). The coexpression network could be divided into two main subnetworks showing over expression in the medium or earlier and late phases, respectively. In order to identify the putative regulatory genes, a transcription factor (TF) analysis was performed. This led to the identification of 45 gene families, mainly including the AP2-EREBP, bHLH, MYB, and NAC families, etc. After coexpression analysis of TFs with highly expression of FAD2 and FAD3 genes, 162 TFs were found to be significantly associated with two FAD genes (r > 0.95). Those TFs were predicted to be the key regulatory factors in ALA biosynthesis in perilla seed. The qRT-PCR analysis also verified the relevance of expression pattern between two FAD genes and partial candidate TFs. Although it has been reported that some TFs are involved in seed development, more direct evidence is still needed to verify their function. However, these findings can provide clues to reveal the possible molecular mechanisms of ALA biosynthesis and its regulation in perilla seed.

Annexin A2 links poor myofiber repair with inflammation and adipogenic replacement of the injured muscle

Repair of skeletal muscle after sarcolemmal damage involves dysferlin and dysferlin-interacting proteins such as annexins. Mice and patient lacking dysferlin exhibit chronic muscle inflammation and adipogenic replacement of the myofibers. Here, we show that similar to dysferlin, lack of annexin A2 (AnxA2) also results in poor myofiber repair and progressive muscle weakening with age. By longitudinal analysis of AnxA2-deficient muscle we find that poor myofiber repair due to the lack of AnxA2 does not result in chronic inflammation or adipogenic replacement of the myofibers. Further, deletion of AnxA2 in dysferlin deficient mice reduced muscle inflammation, adipogenic replacement of myofibers, and improved muscle function. These results identify multiple roles of AnxA2 in muscle repair, which includes facilitating myofiber repair, chronic muscle inflammation and adipogenic replacement of dysferlinopathic muscle. It also identifies inhibition of AnxA2-mediated inflammation as a novel therapeutic avenue for treating muscle loss in dysferlinopathy.

Sex chromosomes drive gene expression and regulatory dimorphisms in mouse embryonic stem cells

BACKGROUND

Pre-implantation embryos exhibit sexual dimorphisms in both primates and rodents. To determine whether these differences reflected sex-biased expression patterns, we generated transcriptome profiles for six 40,XX, six 40,XY, and two 39,X mouse embryonic stem (ES) cells by RNA sequencing.

RESULTS

We found hundreds of coding and non-coding RNAs that were differentially expressed between male and female cells. Surprisingly, the majority of these were autosomal and included RNA encoding transcription and epigenetic and chromatin remodeling factors. We showed differential Prdm14-responsive enhancer activity in male and female cells, correlating with the sex-specific levels of Prdm14 expression. This is the first time sex-specific enhancer activity in ES cells has been reported. Evaluation of X-linked gene expression patterns between our XX and XY lines revealed four distinct categories: (1) genes showing 2-fold greater expression in the female cells; (2) a set of genes with expression levels well above 2-fold in female cells; (3) genes with equivalent RNA levels in male and female cells; and strikingly, (4) a small number of genes with higher expression in the XY lines. Further evaluation of autosomal gene expression revealed differential expression of imprinted loci, despite appropriate parent-of-origin patterns. The 39,X lines aligned closely with the XY cells and provided insights into potential regulation of genes associated with Turner syndrome in humans. Moreover, inclusion of the 39,X lines permitted three-way comparisons, delineating X and Y chromosome-dependent patterns.

CONCLUSIONS

Overall, our results support the role of the sex chromosomes in establishing sex-specific networks early in embryonic development and provide insights into effects of sex chromosome aneuploidies originating at those stages.

Identifying Gene Interaction Networks

In this chapter, we introduce interaction networks by describing how they are generated, where they are stored, and how they are shared. We focus on publicly available interaction networks and describe a simple way of utilizing these resources. This chapter features two case studies, both of which utilize Cytoscape, an open source and user-friendly network visualization and analysis tool. In the first example, we demonstrate the basic functionalities of Cytoscape by building an interaction network from a publicly available database, analyzing its topological features, and performing gene ontology enrichment. For the second section, we constructed a network from scratch starting with an experimental gene expression dataset. From there, we implement more advanced visual annotations of the network and perform subnetwork enrichment. The methods described are applicable to larger networks that can be collected from various resources.

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the unique characteristic to color regulatory relations between genes and reveal their phenotype inclination. This unique characteristic makes MinePath a valuable tool for in silico molecular biology experimentation as it serves the biomedical researchers' exploratory needs to reveal and interpret the regulatory mechanisms that underlie and putatively govern the expression of target phenotypes.

MYC functions are specific in biological subtypes of breast cancer and confers resistance to endocrine therapy in luminal tumours

BACKGROUND

MYC is amplified in approximately 15% of breast cancers (BCs) and is associated with poor outcome. c-MYC protein is multi-faceted and participates in many aspects of cellular function and is linked with therapeutic response in BCs. We hypothesised that the functional role of c-MYC differs between molecular subtypes of BCs.

METHODS

We therefore investigated the correlation between c-MYC protein expression and other proteins involved in different cellular functions together with clinicopathological parameters, patients' outcome and treatments in a large early-stage molecularly characterised series of primary invasive BCs (n=1106) using immunohistochemistry. The METABRIC BC cohort (n=1980) was evaluated for MYC mRNA expression and a systems biology approach utilised to identify genes associated with MYC in the different BC molecular subtypes.

RESULTS

High MYC and c-MYC expression was significantly associated with poor prognostic factors, including grade and basal-like BCs. In luminal A tumours, c-MYC was associated with ATM (P=0.005), Cyclin B1 (P=0.002), PIK3CA (P=0.009) and Ki67 (P<0.001). In contrast, in basal-like tumours, c-MYC showed positive association with Cyclin E (P=0.003) and p16 (P=0.042) expression only. c-MYC was an independent predictor of a shorter distant metastases-free survival in luminal A LN+ tumours treated with endocrine therapy (ET; P=0.013). In luminal tumours treated with ET, MYC mRNA expression was associated with BC-specific survival (P=0.001). In ER-positive tumours, MYC was associated with expression of translational genes while in ER-negative tumours it was associated with upregulation of glucose metabolism genes.

CONCLUSIONS

c-MYC function is associated with specific molecular subtypes of BCs and its overexpression confers resistance to ET. The diverse mechanisms of c-MYC function in the different molecular classes of BCs warrants further investigation particularly as potential therapeutic targets.

Investigating the underlying mechanisms of temperature-related skin diseases in Atlantic salmon, Salmo salar L., as measured by quantitative histology, skin transcriptomics and composition

Skin integrity is recognized as of vital consideration for both animal welfare and final product quality of farmed fish. This study examines the effects of three different rearing temperatures (4, 10 and 16 °C) on the skin of healthy Atlantic salmon post-smolts. Changes in skin condition were assessed by the means of skin composition analyses, quantitative histology assessments and transcriptome analysis. Level of protein, vitamin C and vitamin E was significantly higher at 16 °C compared with 4 °C. Quantitative histology measurements showed that the epidermal thickness decreased from low to high temperature, whereas the epidermal area comprising mucous cells increased. The difference was only significant between 4 and 16 °C. Both high and low temperature exhibited significant changes in the skin transcriptome. A number of immune-related transcripts responded at both temperatures. Contrary to well-described immunosuppressive effects of low water temperature on systemic immunity, a subtle increase in skin-mediated immunity was observed, suggesting a pre-activation of the mucosal system at 4 °C. Upregulation of a number of heat-shock proteins correlating with a decrease in epidermal thickness suggested a stress response in the skin at high temperature. The results demonstrate distinctive temperature-related effects on the skin of Atlantic salmon.

Advances in Human Biology: Combining Genetics and Molecular Biophysics to Pave the Way for Personalized Diagnostics and Medicine

Advances in several biology-oriented initiatives such as genome sequencing and structural genomics, along with the progress made through traditional biological and biochemical research, have opened up a unique opportunity to better understand the molecular effects of human diseases. Human DNA can vary significantly from person to person and determines an individual’s physical characteristics and their susceptibility to diseases. Armed with an individual’s DNA sequence, researchers and physicians can check for defects known to be associated with certain diseases by utilizing various databases. However, for unclassified DNA mutations or in order to reveal molecular mechanism behind the effects, the mutations have to be mapped onto the corresponding networks and macromolecular structures and then analyzed to reveal their effect on the wild type properties of biological processes involved. Predicting the effect of DNA mutations on individual’s health is typically referred to as personalized or companion diagnostics. Furthermore, once the molecular mechanism of the mutations is revealed, the patient should be given drugs which are the most appropriate for the individual genome, referred to as pharmacogenomics. Altogether, the shift in focus in medicine towards more genomic-oriented practices is the foundation of personalized medicine. The progress made in these rapidly developing fields is outlined.

Systemic inflammatory response to smoking in chronic obstructive pulmonary disease: evidence of a gender effect

BACKGROUND

Tobacco smoking is the main risk factor of chronic obstructive pulmonary disease (COPD) but not all smokers develop the disease. An abnormal pulmonary and systemic inflammatory response to smoking is thought to play a major pathogenic role in COPD, but this has never been tested directly.

METHODS

We studied the systemic biomarker and leukocyte transcriptomic response (Affymetrix microarrays) to smoking exposure in 10 smokers with COPD and 10 smokers with normal spirometry. We also studied 10 healthy never smokers (not exposed to smoking) as controls. Because some aspects of COPD may differ in males and females, and the inflammatory response to other stressors (infection) might be different in man and women, we stratified participant recruitment by sex. Differentially expressed genes were validated by q-PCR. Ontology enrichment was evaluated and interaction networks inferred.

RESULTS

Principal component analysis identified sex differences in the leukocyte transcriptomic response to acute smoking. In both genders, we identified genes that were differentially expressed in response to smoking exclusively in COPD patients (COPD related signature) or smokers with normal spirometry (Smoking related signature), their ontologies and interaction networks.

CONCLUSIONS

The use of an experimental intervention (smoking exposure) to investigate the transcriptomic response of peripheral leukocytes in COPD is a step beyond the standard case-control transcriptomic profiling carried out so far, and has facilitated the identification of novel COPD and Smoking expression related signatures which differ in males and females.

Module-based functional pathway enrichment analysis of a protein-protein interaction network to study the effects of intestinal microbiota depletion in mice

Complex communities of microorganisms play important roles in human health, and alterations in the intestinal microbiota may induce intestinal inflammation and numerous diseases. The purpose of this study was to identify the key genes and processes affected by depletion of the intestinal microbiota in a murine model. The Affymetrix microarray dataset GSE22648 was downloaded from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) were identified using the limma package in R. A protein-protein interaction (PPI) network was constructed for the DEGs using the Cytoscape software, and the network was divided into several modules using the MCODE plugin. Furthermore, the modules were functionally annotated using the PiNGO plugin, and DEG-related pathways were retrieved and analyzed using the GenMAPP software. A total of 53 DEGs were identified, of which 26 were upregulated and 27 were downregulated. The PPI network of these DEGs comprised 3 modules. The most significant module-related DEGs were the cytochrome P450 (CYP) 4B1 isozyme gene (CYP4B1) in module 1, CYP4F14 in module 2 and the tachykinin precursor 1 gene (TAC1) in module 3. The majority of enriched pathways of module 1 and 2 were oxidation reduction pathways (metabolism of xenobiotics by CYPs) and lipid metabolism-related pathways, including linoleic acid and arachidonic acid metabolism. The neuropeptide signaling pathway was the most significantly enriched functional pathway of module 3. In conclusion, our findings strongly suggest that intestinal microbiota depletion affects cellular metabolism and oxidation reduction pathways. In addition, this is the first time, to the best of our knowledge, that the neuropeptide signaling pathway is reported to be affected by intestinal microbiota depletion in mice. The present study provides a list of candidate genes and processes related to the interaction of microbiota with the intestinal tract.

Mitochondria in ageing: there is metabolism beyond the ROS

Mitochondria are responsible for a series of metabolic functions. Superoxide leakage from the respiratory chain and the resulting cascade of reactive oxygen species-induced damage, as well as mitochondrial metabolism in programmed cell death, have been intensively studied during ageing in single-cellular and higher organisms. Changes in mitochondrial physiology and metabolism resulting in ROS are thus considered to be hallmarks of ageing. In this review, we address 'other' metabolic activities of mitochondria, carbon metabolism (the TCA cycle and related underground metabolism), the synthesis of Fe/S clusters and the metabolic consequences of mitophagy. These important mitochondrial activities are hitherto less well-studied in the context of cellular and organismic ageing. In budding yeast, they strongly influence replicative, chronological and hibernating lifespan, connecting the diverse ageing phenotypes studied in this single-cellular model organism. Moreover, there is evidence that similar processes equally contribute to ageing of higher organisms as well. In this scenario, increasing loss of metabolic integrity would be one driving force that contributes to the ageing process. Understanding mitochondrial metabolism may thus be required for achieving a unifying theory of eukaryotic ageing.

Predicting gene function from uncontrolled expression variation among individual wild-type Arabidopsis plants

Gene expression profiling studies are usually performed on pooled samples grown under tightly controlled experimental conditions to suppress variability among individuals and increase experimental reproducibility. In addition, to mask unwanted residual effects, the samples are often subjected to relatively harsh treatments that are unrealistic in a natural context. Here, we show that expression variations among individual wild-type Arabidopsis thaliana plants grown under the same macroscopic growth conditions contain as much information on the underlying gene network structure as expression profiles of pooled plant samples under controlled experimental perturbations. We advocate the use of subtle uncontrolled variations in gene expression between individuals to uncover functional links between genes and unravel regulatory influences. As a case study, we use this approach to identify ILL6 as a new regulatory component of the jasmonate response pathway.

Facilitating the use of large-scale biological data and tools in the era of translational bioinformatics

As both the amount of generated biological data and the processing compute power increase, computational experimentation is no longer the exclusivity of bioinformaticians, but it is moving across all biomedical domains. For bioinformatics to realize its translational potential, domain experts need access to user-friendly solutions to navigate, integrate and extract information out of biological databases, as well as to combine tools and data resources in bioinformatics workflows. In this review, we present services that assist biomedical scientists in incorporating bioinformatics tools into their research. We review recent applications of Cytoscape, BioGPS and DAVID for data visualization, integration and functional enrichment. Moreover, we illustrate the use of Taverna, Kepler, GenePattern, and Galaxy as open-access workbenches for bioinformatics workflows. Finally, we mention services that facilitate the integration of biomedical ontologies and bioinformatics tools in computational workflows.

Pivotal role of the muscle-contraction pathway in cryptorchidism and evidence for genomic connections with cardiomyopathy pathways in RASopathies

BACKGROUND

Cryptorchidism is the most frequent congenital disorder in male children; however the genetic causes of cryptorchidism remain poorly investigated. Comparative integratomics combined with systems biology approach was employed to elucidate genetic factors and molecular pathways underlying testis descent.

METHODS

Literature mining was performed to collect genomic loci associated with cryptorchidism in seven mammalian species. Information regarding the collected candidate genes was stored in MySQL relational database. Genomic view of the loci was presented using Flash GViewer web tool (http://gmod.org/wiki/Flashgviewer/). DAVID Bioinformatics Resources 6.7 was used for pathway enrichment analysis. Cytoscape plug-in PiNGO 1.11 was employed for protein-network-based prediction of novel candidate genes. Relevant protein-protein interactions were confirmed and visualized using the STRING database (version 9.0).

RESULTS

The developed cryptorchidism gene atlas includes 217 candidate loci (genes, regions involved in chromosomal mutations, and copy number variations) identified at the genomic, transcriptomic, and proteomic level. Human orthologs of the collected candidate loci were presented using a genomic map viewer. The cryptorchidism gene atlas is freely available online: http://www.integratomics-time.com/cryptorchidism/. Pathway analysis suggested the presence of twelve enriched pathways associated with the list of 179 literature-derived candidate genes. Additionally, a list of 43 network-predicted novel candidate genes was significantly associated with four enriched pathways. Joint pathway analysis of the collected and predicted candidate genes revealed the pivotal importance of the muscle-contraction pathway in cryptorchidism and evidence for genomic associations with cardiomyopathy pathways in RASopathies.

CONCLUSIONS

The developed gene atlas represents an important resource for the scientific community researching genetics of cryptorchidism. The collected data will further facilitate development of novel genetic markers and could be of interest for functional studies in animals and human. The proposed network-based systems biology approach elucidates molecular mechanisms underlying co-presence of cryptorchidism and cardiomyopathy in RASopathies. Such approach could also aid in molecular explanation of co-presence of diverse and apparently unrelated clinical manifestations in other syndromes.

Visualization and analysis of biological networks

The study of the interactome-the totality of the protein-protein interactions taking place in a cell-has experienced an enormous growth in the last few years. Biological networks representation and analysis has become an everyday tool for many biologists and bioinformatics, as these interaction graphs allow us to map and characterize signaling pathways and predict the function of unknown proteins. However, given the size and complexity of interactome datasets, extracting meaningful information from interaction networks can be a daunting task. Many different tools and approaches can be used to build, represent, and analyze biological networks. In this chapter, we will use a practical example to guide novice users through this process. We will be making use of the popular open source tool Cytoscape and of other resources such as : the PSICQUIC client to access several protein interaction repositories and the BiNGO plugin to perform GO enrichment analysis of the resulting network.

Early mechanisms of pathobiology are revealed by transcriptional temporal dynamics in hippocampal CA1 neurons of prion infected mice

Prion diseases typically have long pre-clinical incubation periods during which time the infectious prion particle and infectivity steadily propagate in the brain. Abnormal neuritic sprouting and synaptic deficits are apparent during pre-clinical disease, however, gross neuronal loss is not detected until the onset of the clinical phase. The molecular events that accompany early neuronal damage and ultimately conclude with neuronal death remain obscure. In this study, we used laser capture microdissection to isolate hippocampal CA1 neurons and determined their pre-clinical transcriptional response during infection. We found that gene expression within these neurons is dynamic and characterized by distinct phases of activity. We found that a major cluster of genes is altered during pre-clinical disease after which expression either returns to basal levels, or alternatively undergoes a direct reversal during clinical disease. Strikingly, we show that this cluster contains a signature highly reminiscent of synaptic N-methyl-D-aspartic acid (NMDA) receptor signaling and the activation of neuroprotective pathways. Additionally, genes involved in neuronal projection and dendrite development were also altered throughout the disease, culminating in a general decline of gene expression for synaptic proteins. Similarly, deregulated miRNAs such as miR-132-3p, miR-124a-3p, miR-16-5p, miR-26a-5p, miR-29a-3p and miR-140-5p follow concomitant patterns of expression. This is the first in depth genomic study describing the pre-clinical response of hippocampal neurons to early prion replication. Our findings suggest that prion replication results in the persistent stimulation of a programmed response that is mediated, at least in part, by synaptic NMDA receptor activity that initially promotes cell survival and neurite remodelling. However, this response is terminated prior to the onset of clinical symptoms in the infected hippocampus, seemingly pointing to a critical juncture in the disease. Manipulation of these early neuroprotective pathways may redress the balance between degeneration and survival, providing a potential inroad for treatment.

Neurodegenerative diseases affect an ever-increasing proportion of the population; therefore, there is an urgent need to develop treatments. Prion disorders belong to this group of diseases and although rare and uniquely transmissible, share many features on a sub-cellular level. Central to disease is progressive synaptic impairment that invariably leads to the irreversible loss of neurons. Understanding this process is undoubtedly essential for rational drug discovery. In this study we looked at neurons very early in disease, when prions are barely detectable and there are no clinical symptoms observed. Specifically, we performed a comprehensive analysis of transcriptional changes within a particularly dense area of neurons, the CA1 hippocampus region, from prion-infected and control mice. In this way we were able to enrich our data for molecular changes unique to neurons and minimize those changes characteristic of support cells such as astrocytes and microglia. We detected the activation of a transcriptional program indicative of a protective mechanism within these neurons early in disease. This mechanism diminished as disease progressed and was lost altogether, concurrently with the onset of clinical symptoms. These findings demonstrate the ability of neurons to mount an initial neuroprotective response to prions that could be exploited for therapy development.

A travel guide to Cytoscape plugins

Cytoscape is open-source software for integration, visualization and analysis of biological networks. It can be extended through Cytoscape plugins, enabling a broad community of scientists to contribute useful features. This growth has occurred organically through the independent efforts of diverse authors, yielding a powerful but heterogeneous set of tools. We present a travel guide to the world of plugins, covering the 152 publicly available plugins for Cytoscape 2.5-2.8. We also describe ongoing efforts to distribute, organize and maintain the quality of the collection.

Predicting disease-related subnetworks for type 1 diabetes using a new network activity score

In this study we investigated the advantage of including network information in prioritizing disease genes of type 1 diabetes (T1D). First, a naïve Bayesian network (NBN) model was developed to integrate information from multiple data sources and to define a T1D-involvement probability score (PS) for each individual gene. The algorithm was validated using known functional candidate genes as a benchmark. Genes with higher PS were found to be more likely to appear in T1D-related publications. Next a new network activity metric was proposed to evaluate the T1D relevance of protein-protein interaction (PPI) subnetworks. The metric considered the contribution both from individual genes and from network topological characteristics. The predictions were confirmed by several independent datasets, including a genome wide association study (GWAS), and two large-scale human gene expression studies. We found that novel candidate genes in the T1D subnetworks showed more significant associations with T1D than genes predicted using PS alone. Interestingly, most novel candidates were not encoded within the human leukocyte antigen (HLA) region, and their expression levels showed correlation with disease only in cohorts with low-risk HLA genotypes. The results suggested the importance of mapping disease gene networks in dissecting the genetics of complex diseases, and offered a general approach to network-based disease gene prioritization from multiple data sources.

Uncovering Arabidopsis membrane protein interactome enriched in transporters using mating-based split ubiquitin assays and classification models

High-throughput data are a double-edged sword; for the benefit of large amount of data, there is an associated cost of noise. To increase reliability and scalability of high-throughput protein interaction data generation, we tested the efficacy of classification to enrich potential protein-protein interactions. We applied this method to identify interactions among Arabidopsis membrane proteins enriched in transporters. We validated our method with multiple retests. Classification improved the quality of the ensuing interaction network and was effective in reducing the search space and increasing true positive rate. The final network of 541 interactions among 239 proteins (of which 179 are transporters) is the first protein interaction network enriched in membrane transporters reported for any organism. This network has similar topological attributes to other published protein interaction networks. It also extends and fills gaps in currently available biological networks in plants and allows building a number of hypotheses about processes and mechanisms involving signal-transduction and transport systems.

CytoITMprobe: a network information flow plugin for Cytoscape

Background

Cytoscape is a well-developed flexible platform for visualization, integration and analysis of network data. Apart from the sophisticated graph layout and visualization routines, it hosts numerous user-developed plugins that significantly extend its core functionality. Earlier, we developed a network information flow framework and implemented it as a web application, called ITM Probe. Given a context consisting of one or more user-selected nodes, ITM Probe retrieves other network nodes most related to that context. It requires neither user restriction to subnetwork of interest nor additional and possibly noisy information. However, plugins for Cytoscape with these features do not yet exist. To provide the Cytoscape users the possibility of integrating ITM Probe into their workflows, we developed CytoITMprobe, a new Cytoscape plugin.

Findings

CytoITMprobe maintains all the desirable features of ITM Probe and adds additional flexibility not achievable through its web service version. It provides access to ITM Probe either through a web server or locally. The input, consisting of a Cytoscape network, together with the desired origins and/or destinations of information and a dissipation coefficient, is specified through a query form. The results are shown as a subnetwork of significant nodes and several summary tables. Users can control the composition and appearance of the subnetwork and interchange their ITM Probe results with other software tools through tab-delimited files.

Conclusions

The main strength of CytoITMprobe is its flexibility. It allows the user to specify as input any Cytoscape network, rather than being restricted to the pre-compiled protein-protein interaction networks available through the ITM Probe web service. Users may supply their own edge weights and directionalities. Consequently, as opposed to ITM Probe web service, CytoITMprobe can be applied to many other domains of network-based research beyond protein-networks. It also enables seamless integration of ITM Probe results with other Cytoscape plugins having complementary functionality for data analysis.

Identifying gene interaction networks

In this chapter, we introduce interaction networks by describing how they are generated, where they are stored, and how they are shared. We focus on publicly available interaction networks and describe a simple way of utilizing these resources. As a case study, we used Cytoscape, an open source and easy-to-use network visualization and analysis tool to first gather and visualize a small network. We have analyzed this network's topological features and have looked at functional enrichment of the network nodes by integrating the gene ontology database. The methods described are applicable to larger networks that can be collected from various resources.

Reliability-oriented bioinformatic networks visualization

SUMMARY

We present our protein-protein interaction (PPI) network visualization system RobinViz (reliability-oriented bioinformatic networks visualization). Clustering the PPI network based on gene ontology (GO) annotations or biclustered gene expression data, providing a clustered visualization model based on a central/peripheral duality, computing layouts with algorithms specialized for interaction reliabilities represented as weights, completely automated data acquisition, processing are notable features of the system.

AVAILABILITY

RobinViz is a free, open-source software protected under GPL. It is written in C++ and Python, and consists of almost 30 000 lines of code, excluding the employed libraries. Source code, user manual and other Supplementary Material are available for download at http://code.google.com/p/robinviz/.