Importance of hereditary factors in the etiology of Idiopathic Scoliosis is widely accepted. In clinical practice some of the IS patients present with positive familial history of the deformity and some do not. Traditionally about 90% of patients have been considered as sporadic cases without familial recurrence. However the exact proportion of Familial and Sporadic Idiopathic Scoliosis is still unknown. Housekeeping genes encode proteins that are usually essential for the maintenance of basic cellular functions. ACTB and GAPDH are two housekeeping genes encoding respectively a cytoskeletal protein β-actin, and glyceraldehyde-3-phosphate dehydrogenase, an enzyme of glycolysis. Although their expression levels can fluctuate between different tissues and persons, human housekeeping genes seem to exhibit a preserved tissue-wide expression ranking order. It was hypothesized that expression ranking order of two representative housekeeping genes ACTB and GAPDH might be disturbed in the tissues of patients with Familial Idiopathic Scoliosis (with positive family history of idiopathic scoliosis) opposed to the patients with no family members affected (Sporadic Idiopathic Scoliosis). An artificial neural network (ANN) was developed that could serve to differentiate between familial and sporadic cases of idiopathic scoliosis based on the expression levels of ACTB and GAPDH in different tissues of scoliotic patients. The aim of the study was to investigate whether the expression levels of ACTB and GAPDH in different tissues of idiopathic scoliosis patients could be used as a source of data for specially developed artificial neural network in order to predict the positive family history of index patient. The comparison of developed models showed, that the most satisfactory classification accuracy was achieved for ANN model with 18 nodes in the first hidden layer and 16 nodes in the second hidden layer. The classification accuracy for positive Idiopathic Scoliosis anamnesis only with the expression measurements of ACTB and GAPDH with the use of ANN based on 6-18-16-1 architecture was 8 of 9 (88%). Only in one case the prediction was ambiguous. Specially designed artificial neural network model proved possible association between expression level of ACTB, GAPDH and positive familial history of Idiopathic Scoliosis.

When we were asked for help with high-level microarray data analysis (on Affymetrix HGU-133A microarray), we faced the problem of selecting an appropriate method. We wanted to select a method that would yield "the best result" (detected as many "really" differentially expressed genes (DEGs) as possible, without false positives and false negatives). However, life scientists could not help us – they use their "favorite" method without special argumentation. We also did not find any norm or recommendation. Therefore, we decided to examine it for our own purpose. We considered whether the results obtained using different methods of high-level microarray data analyses – Significant Analysis of Microarrays, Rank Products, Bland-Altman, Mann-Whitney test, T test and the Linear Models for Microarray Data – would be in agreement. Initially, we conducted a comparative analysis of the results on eight real data sets from microarray experiments (from the Array Express database). The results were surprising. On the same array set, the set of DEGs by different methods were significantly different. We also applied the methods to artificial data sets and determined some measures that allow the preparation of the overall scoring of tested methods for future recommendation. We found a very low level concordance of results from tested methods on real array sets. The number of common DEGs (detected by all six methods on fixed array sets, checked on eight array sets) ranged from 6 to 433 (22,283 total array readings). Results on artificial data sets were better than those on the real data. However, they were not fully satisfying. We scored tested methods on accuracy, recall, precision, f-measure and Matthews correlation coefficient. Based on the overall scoring, the best methods were SAM and LIMMA. We also found TT to be acceptable. The worst scoring was MW. Based on our study, we recommend: 1. Carefully taking into account the need for study when choosing a method, 2. Making high-level analysis with more than one method and then only taking the genes that are common to all methods (which seems to be reasonable) and 3. Being very careful (while summarizing facts) about sets of differentially expressed genes: different methods discover different sets of DEGs.

Most researchers agree that idiopathic scoliosis (IS) is a multifactorial disease influenced by complex genetic and environmental factors. The onset of the spinal deformity that determines the natural course of the disease, usually occurs in the juvenile or adolescent period. Transforming growth factorsβ(TGF-βs) and their receptors, TGFBRs, may be considered as candidate genes related to IS susceptibility and natural history. This study explores the transcriptional profile of TGF-βs, TGFBRs, and TGF-βresponsive genes in the paravertebral muscles of patients with juvenile and adolescent idiopathic scoliosis (JIS and AIS, resp.). Muscle specimens were harvested intraoperatively and grouped according to the side of the curve and the age of scoliosis onset. The results of microarray and qRT-PCR analysis confirmed significantly higher transcript abundances of TGF-β2, TGF-β3, and TGFBR2 in samples from the curve concavity of AIS patients, suggesting a difference in TGF-βsignaling in the pathogenesis of juvenile and adolescent curves. Analysis of TGF-βresponsive genes in the transcriptomes of patients with AIS suggested overrepresentation of the genes localized in the extracellular region of curve concavity: LTBP3, LTBP4, ITGB4, and ITGB5. This finding suggests the extracellular region of paravertebral muscles as an interesting target for future molecular research into AIS pathogenesis.

The spatial organization of chromatin within the interphase nucleus and the interactions between chromosome territories (CTs) are essential for various biological processes, such as DNA replication, transcription, and repair. However, detailed data about the CT arrangement in monocotyledonous plants are scarce. In this study, chromosome painting was used to analyse the distribution and associations of individual chromosomes in the 3-D preserved nuclei of Brachypodium distachyon root cells in order to determine the factors that may have an impact on the homologous CT arrangement. It was shown that the frequency of CT association is linked to the steric constraints imposed by the limited space within the nucleus and may depend on chromosome size and morphology as well as on the nuclear shape. Furthermore, in order to assess whether the distribution of interphase chromosomes is random or is subject to certain patterns, a comparison between the experimental data and the results of a computer simulation (ChroTeMo), which was based on a fully probabilistic distribution of the CTs, was performed. This comparison revealed that homologous chromosome arm CTs associate more often than if they were randomly arranged inside the interphase nucleus.

This paper presents ChroTeMo, a tool for chromosome territory modelling, accompanied by ChroTeVi–a chromosome territory visualisation software that uses the data obtained by ChroTeMo. These tools have been developed in order to complement the molecular cytogenetic research of interphase nucleus structure in a model grass Brachypodium distachyon. Although the modelling tool has been initially created for one particular species, it has universal application. The proposed version of ChroTeMo allows for generating a model of chromosome territory distribution in any given plant or animal species after setting the initial, species-specific parameters. ChroTeMo has been developed as a fully probabilistic modeller. Due to this feature, the comparison between the experimental data on the structure of a nucleus and the results obtained from ChroTeMo can indicate whether the distribution of chromosomes inside a nucleus is also fully probabilistic or is subjected to certain non-random patterns. The presented tools have been written in Python, so they are multiplatform, portable and easy to read. Moreover, if necessary they can be further developed by users writing their portions of code. The source code, documentation, and wiki, as well as the issue tracker and the list of related articles that use ChroTeMo and ChroTeVi, are accessible in a public repository at Github under GPL 3.0 license.