Identification of embryonic pancreatic genes using Xenopus DNA microarrays

Expression Data Analysis for the Identification of Potential Biomarker of Pregnancy Associated Breast Cancer

Breast cancer affects every 1 of 3000 pregnant women or in the first post-partum year is referred as Pregnancy Associated Breast Cancer (PABC) in mid 30s. Even-though rare disease, classified under hormone receptor negative status which metastasis quickly to other parts by extra cellular matrix degradation. Hence it is important to find an optimal treatment option for a PABC patient. Also additional care should be taken to choose the drug; in order to avoid fetal malformation and post-partum stage side-effects. The adaptation of target based therapy in the clinical practice may help to substitute the mastectomy treatment. Recent studies suggested that certain altered Post Translational Modifications (PTMs) may be an indicative of breast cancer progression; an attempt is made to consider the over represented PTM as a parameter for gene selection. The public dataset of PABC from GEO were examined to select Differentially Expressed Genes (DEG). The corresponding PTMs for DEG were collected and association between them was found using data mining technique. Usually clustering algorithm has been applied for the study of gene expression with drawback of clustering of gene products based on specified features. But association rule mining method overcome this shortcoming and determines the useful and in depth relationships. From the association, genes were selected to study the interactions and pathways. These studies emphasis that the genes KLF12, FEN1 MUC1 and SP110, can be chosen as target, which control cancer development, without any harm to pregnancy as well as fetal developmental process.

Xenopus as a model system for studying pancreatic development and diabetes

Diabetes is a chronic disease caused by the loss or dysfunction of the insulin-producing β-cells in the pancreas. To date, much of our knowledge about β-cells in humans comes from studying rare monogenic forms of diabetes. Importantly, the majority of mutations so far associated to monogenic diabetes are in genes that exert a regulatory role in pancreatic development and/or β-cell function. Thus, the identification and study of novel mutations open an unprecedented window into human pancreatic development. In this review, we summarize major advances in the genetic dissection of different types of monogenic diabetes and the insights gained from a developmental perspective. We highlight future challenges to bridge the gap between the fast accumulation of genetic data through next-generation sequencing and the need of functional insights into disease mechanisms. Lastly, we discuss the relevance and advantages of studying candidate gene variants in vivo using the Xenopus as model system.

UNCLES: method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background

Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets.

Results

Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn.

Conclusions

The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0614-0) contains supplementary material, which is available to authorized users.

Chronic sublethal exposure to silver nanoparticles disrupts thyroid hormone signaling during Xenopus laevis metamorphosis

Nanoparticles (NPs) are engineered in the nanoscale (<100 nm) to have unique physico-chemical properties from their bulk counterparts. Nanosilver particles (AgNPs) are the most prevalent NPs in consumer products due to their strong antimicrobial action. While AgNP toxicity at high concentrations has been thoroughly investigated, the sublethal effects at or below regulatory guidelines are relatively unknown. Amphibian metamorphosis is mediated by thyroid hormone (TH), and initial studies with bullfrogs (Rana catesbeiana) indicate that low concentrations of AgNPs disrupt TH-dependent responses in premetamorphic tadpole tailfin tissue. The present study examined the effects of low, non-lethal, environmentally-relevant AgNP concentrations (0.018, 0.18 or 1.8 μg/L Ag; ∼10 nm particle size) on naturally metamorphosing Xenopus laevis tadpoles in two-28 day chronic exposures beginning with either pre- or prometamorphic developmental stages. Asymmetric flow field flow fractionation with online inductively coupled plasma mass spectrometry and nanoparticle tracking analysis indicated a mixture of single AgNPs with homo-agglomerates in the exposure water with a significant portion (∼30-40%) found as dissolved Ag. Tadpoles bioaccumulated AgNPs and displayed transient alterations in snout/vent and hindlimb length with AgNP exposure. Using MAGEX microarray and quantitative real time polymerase chain reaction transcript analyses, AgNP-induced disruption of five TH-responsive targets was observed. The increased mRNA abundance of two peroxidase genes by AgNP exposure suggests the presence of reactive oxygen species even at low, environmentally-relevant concentrations. Furthermore, differential responsiveness to AgNPs was observed at each developmental stage. Therefore, low concentrations of AgNPs had developmental stage-specific endocrine disrupting effects during TH-dependent metamorphosis.

Islet organogenesis, angiogenesis and innervation

The pancreas is characterized by a major component, an exocrine and ductal system involved in digestion, and a minor component, the endocrine islets represented by islet micro-organs that tightly regulate glucose homoeostasis. Pancreatic organogenesis is strictly co-ordinated by transcription factors that are expressed sequentially to yield functional islets capable of maintaining glucose homoeostasis. Angiogenesis and innervation complete islet development, equipping islets to respond to metabolic demands. Proper regulation of this triad of processes during development is critical for establishing functional islets.