Vast amount of data can readily be analysed by using Qlucore Omics Explorer software to help unravel the mystery of the human eye. According to Dr Kulkarni, gene analysis generates enormous amount of data and previous studies before using Omics Explorer, definitely felt more complicated to understand.

The vast amount of data that is produced by gene expression studies poses a serious challenge for scientists studying human biology, said Carl-Johan Ivarsson from Qlucore. However, new software in this area is now helping researchers to perform sophisticated data analysis on proteomic, genomic and microarray data, without the need for specialist biostatisticians

Although gene expression studies are proving invaluable to the study of human biology, the amount of data that is produced by these experiments is enormous. As a result, it is impossible to derive any real biological meaning from these findings unless sophisticated data algorithms are used to help interpret the data effectively.

For this reason, most of the software that has been designed for use in this area has mainly focused on the ability to handle increasingly vast amounts of data, which means that the role of the scientist/researcher has been largely set aside. As a result, a lot of data analysis has been passed on to bioinformaticians and biostatisticians. However, in most cases, this model has several drawbacks, since it is typically the scientists themselves who know the most about biology.

Fortunately, the latest technological advances in this area are making it much easier for the scientists themselves to compare the vast quantity of genomic data generated, to test different hypotheses, and to explore alternative scenarios within seconds. Not only that, but the latest generation of data analysis software is also helping the scientists (biologist, MD, and so on) to regain control of the analysis and to realise the true potential of gene expression profiling.

Using gene expression analysis to study the human eye

Scientists who are currently studying the human eye at the Division of Ophthalmology and Visual Sciences at Queen’s Medical Centre (QMC), part of the University of Nottingham, are already benefiting from this paradigm shift.

"Compared to what is possible with modern data analysis software, our analysis of microarray data from previous studies definitely felt more complicated and difficult to understand," according to Dr Kulkarni, one of the researchers working at QMC. "Before, our analysis had to be performed on software for spot analysis and generation of raw data set files (which were then filtered and normalised), so that a range of filters and Interarray normalisation could be performed on the data set prior to the application of statistical analysis."

"However, by analysing the data with the latest software in this area, we were able to eliminate the problem of the missing data in the data sets. At the same time, instant graphical visualisation of the statistical tests in the form of heat maps, as well as variable and sample PCA plots, helped us to understand the analysis and the changes in gene expression patterns across different samples," Dr Kulkani added. "Not only was the software highly interactive, but it could also be easily understood by biologists, even if they had little or no previous knowledge of bioinformatics."

According to Dr Kulkarni, there is a large body of clinical and scientific evidence to suggest that corneal epithelial stem cells are located at the limbus, the name given to the visible borderline between the clear window (cornea) and the white globe (sclera) of the eye. However, despite multiple studies in this area, definitive identification of limbal stem cells has remained elusive.

In a recent breakthrough, however, Dr Kulkarni and her team have discovered a unique anatomical structure at the limbus; termed the Limbal Epithelial Crypt (LEC)1. The LEC is a solid cord of epithelial cells (between 50-100 microns long) that extends from the base of palisade of Vogt into the subepithelial tissue of the limbus, either peripherally or circumferentially.

Preliminary studies on the microanatomy and immunohistochemistry of the LEC strongly suggest that it has the potential to serve as the limbal stem cell niche 2, 3. As such, the aim of the QMC study is to generate a gene expression profile of LEC in comparison with rest of the ocular surface epithelia with Human Gene ST 1.0 Array in order to find the putative stem cell marker.

This exciting project involves seven scientists in total, including two supervisors as well as researchers from the division of Ophthalmology and Department of Pathology at QMC, and from the Genomics Centre at Kings College London.

Stem cell research: How can technology help?

The latest breakthrough in bioinformatics software enables scientists to analyse very large data sets by a combination of statistical methods and visualisation techniques such as Heatmaps and Principal Component Analysis (PCA). With the benefit of instant user feedback on all actions, as well as an intuitive user interface that can present all data in 3D, scientists studying the structure of the human eye and other organs can now easily analyse all of this important information in real-time, directly on their computer screen.

For all of these reasons, the latest software in this area is increasingly playing a key role in unveiling important new discoveries, as it allows the actual researchers involved – the people with the most biological insight – to study the data and to look for patterns and structures, without having to be a statistics or computer expert.

Coping with vast amount of data

Modern data analysis software now enables researchers to analyse and explore extremely large data sets – even those with more than 100 million data samples – on a regular PC. This kind of specialist software can even take advantage of annotations and other links that are connected with the data being studied, as well as a number statistical functions such as false discovery rates (FDR) and p-values.

According to Dr Kulkarni, this approach opens up many new possibilities, as previous research on the LEC and limbal stem cells were based on morphological and histological studies in which antibodies of known stem cell markers (identified from other studies) were used to identify limbal stem cells. However, with this method, even if an antibody was expressed in this stem cell population, it was not possible to quantify it, nor to perform quantitative protein analysis due to small sample size of the tissue obtained.

As a result, a specific limbal stem cell marker has not yet been identified for isolation of these cells. Recent advances in research techniques such as laser microdissection, microarrays from amplified RNA samples, however, have now enabled Dr Kulkarni to generate gene expression profiles from a very small amount of tissues like those found in the LEC.

Recent improvements in technology

The research being conducted at QMC represents a significant breakthrough in how modern data analysis is being performed. Less than ten years ago, researchers were only able to work with analysis methods that provided information about single genes. The number of information points per subject has grown to hundreds of thousands in recent years, however, thanks to important technological advances in this area.

Most recently, perhaps within the past two years, the overall performance of data analysis software has been optimised significantly. In fact, with key actions and plots now displayed within a fraction of a second, researchers can increasingly perform the research they want and find the results they need instantly – without the wait.

For example, the software being used for the QMC study allows the researchers there to visualise data using dynamic PCA, an innovative way of combining traditional PCA analysis with immediate user interaction. The program, called Qlucore Omics Explorer, is also unique in that it is able to manipulate the different PCA-plots – interactively and in real time – directly on the computer screen, and to work with all annotations and other links in a fully integrated way, all at the same time.

This approach has helped to open up new ways of working with the analysis and, as a consequence, has helped to bring the biologists back into the analysis phase.

Making sense of important data

According to Dr Kulkarni, the Qlucore software works by transforming high dimensional data down to lower dimensions, which can then be plotted in 3-dimensions on a computer screen and then rotated manually or automatically and examined by the naked eye. The instant visualization techniques are combined with powerful statistical methods and filters. All filters and activities are handled with only one mouse-click. Different colours can make this analysis even easier, as each sub-group can be labelled with its own unique colour. As such, the view of the data can be changed in an instant, so that researchers are only looking at the specific sub-group that interests them at any given moment.

Although Dr Kulkarni is using the software to study gene expression microarray data, other researchers have used it to study protein array data, miRNA data, and RT-PCR data as part of their research studies. The software has also been used to analyse protein data from 2-D gels, image analysis data, and in fact with any data set of multivariate data of sizes up to 1000 samples and 100,000 variables, or 1,000 variables and 100,000 samples.

The future

The research project being conducted at QMC started with the discovery of the LEC – followed by its anatomical and immunohistochemical characterisation – but that was just the beginning. Dr Kulkarni and her team then performed gene expression profiling of the LEC in comparison with surrounding ocular surface epithelia, such as the cornea and the limbus. This project is expected to continue for another two to three years, so that various methods for isolation and growing the limbal stem cells on suitable substrate for transplantation can be validated.

This project will also serve to complement the existing morphological studies of the LEC, and also to highlight geographical differences in gene expression of the LEC with the epithelium and the rest of the ocular surface epithelium regions. As such, these microarray studies on the LEC will help to identify putative stem cell markers.

Based on these important gene expression studies, the antibody markers for stem cells having the highest efficiency to sort out side population cells from the limbus and the LEC can then be designed. These cells could then be grown on suitable substrate for corneal transplantation in patients with limbal stem cell failure, a condition which occurs due to various causes such as alkaline burns and autoimmune disorders like Steven Johnson syndrome.

"Although current treatment modalities for limbal stem cell failure have proven benefits for a limited time period, patients often need to be kept on immunosuppressive drugs afterwards, and the failure rates in long-term periods are still quite high," says Dr Kulkarni. "Our research project at Queen’s Medical Centre therefore has important therapeutic ramifications, and the real potential to progress from bench to bedside. As such, we hope that the successful outcome of our data analysis will pave the way for further research, which would contribute to enhancing the efficiency and the survival of the corneal grafts in limbal stem cell failure patients."

References:
1. Dua, H. S., V. A. Shanmuganathan, et al. (2005). Br J Ophthalmol 89(5): 529-32.
2. Shanmughanathan VA, Foster T, B Kulkarni, et al. (2007). Br J Ophthalmol 91(4): 514-9
3. Yeung AM, Schlötzer-Schrehardt U, Kulkarni B, Tint NL, Hopkinson A, Dua HS. Arch Ophthalmol.
2008 May; 126(5):665-9.