A simple, one-tube assay for the simultaneous detection and diagnosis of ten Australian poultry Eimeria

Coccidiosis is a costly worldwide enteric disease of chickens caused by parasites of the genus Eimeria. At present, there are seven described species that occur globally and a further three undescribed, operational taxonomic units (OTUs X, Y, and Z) that are known to infect chickens from Australia. Species of Eimeria have both overlapping morphology and pathology and frequently occur as mixed-species infections. This makes definitive diagnosis with currently available tests difficult and, to date, there is no test for the detection of the three OTUs. This paper describes the development of a PCR-based assay that is capable of detecting all ten species of Eimeria, including OTUs X, Y, and Z in field samples. The assay is based on a single set of generic primers that amplifies a single diagnostic fragment from the mitochondrial genome of each species. This one-tube assay is simple, low-cost, and has the capacity to be high throughput. It will therefore be of great benefit to the poultry industry for Eimeria detection and control, and the confirmation of identity and purity of vaccine strains.

Polymerization of Ethene and Branched α-olefins with Group IV Metal Complexes Bearing Nitrogen- and Oxygen-Based Ligands

The commodity plastics that are used in our everyday lives are based on polyolefin resins and they find wide variety of applications in several areas. Most of the production is carried out in catalyzed low pressure processes. As a consequence polymerization of ethene and α-olefins has been one of the focus areas for catalyst research both in industry and academia. Enormous amount of effort have been dedicated to fine tune the processes and to obtain better control of the polymerization and to produce tailored polymer structures The literature review of the thesis concentrates on the use of Group IV metal complexes as catalysts for polymerization of ethene and branched α-olefins. More precisely the review is focused on the use of complexes bearing [O,O] and [O,N] type ligands which have gained considerable interest. Effects of the ligand framework as well as mechanical and fluxional behaviour of the complexes are discussed. The experimental part consists mainly of development of new Group IV metal complexes bearing [O,O] and [O,N] ligands and their use as catalysts precursors in ethene polymerization. Part of the experimental work deals with usage of high-throughput techniques in tailoring properties of new polymer materials which are synthesized using Group IV complexes as catalysts. It is known that the by changing the steric and electronic properties of the ligand framework it is possible to fine tune the catalyst and to gain control over the polymerization reaction. This is why in this thesis the complex structures were designed so that the ligand frameworks could be fairly easily modified. All together 14 complexes were synthesised and used as catalysts in ethene polymerizations. It was found that the ligand framework did have an impact within the studied catalyst families. The activities of the catalysts were affected by the changes in complex structure and also effects on the produced polymers were observed: molecular weights and molecular weight distributions were depended on the used catalyst structure. Some catalysts also produced bi- or multi-modal polymers. During last decade high-throughput techniques developed in pharmaceutical industries have been adopted into polyolefin research in order to speed-up and optimize the catalyst candidates. These methods can now be regarded as established method suitable for both academia and industry alike. These high-throughput techniques were used in tailoring poly(4-methyl-1-pentene) polymers which were synthesized using Group IV metal complexes as catalysts. This work done in this thesis represents the first successful example where the high-throughput synthesis techniques are combined with high-throughput mechanical testing techniques to speed-up the discovery process for new polymer materials.

Deriving structural information from non-coding ribonucleic acids by mass spectrometry

The purpose of this study is to describe the development of application of mass spectrometry for the structural analyses of non-coding ribonucleic acids during past decade. Mass spectrometric methods are compared of traditional gel electrophoretic methods, the characteristics of performance of mass spectrometric, analyses are studied and the future trends of mass spectrometry of ribonucleic acids are discussed. Non-coding ribonucleic acids are short polymeric biomolecules which are not translated to proteins, but which may affect the gene expression in all organisms. Regulatory ribonucleic acids act through transient interactions with key molecules in signal transduction pathways. Interactions are mediated through specific secondary and tertiary structures. Posttranscriptional modifications in the structures of molecules may introduce new properties to the organism, such as adaptation to environmental changes or development of resistance to antibiotics. In the scope of this study, the structural studies include i) determination of the sequence of nucleobases in the polymer chain, ii) characterisation and localisation of posttranscriptional modifications in nucleobases and in the backbone structure, iii) identification of ribonucleic acid-binding molecules and iv) probing of higher order structures in the ribonucleic acid molecule. Bacteria, archaea, viruses and HeLa cancer cells have been used as target organisms. Synthesised ribonucleic acids consisting of structural regions of interest have been frequently used. Electrospray ionisation (ESI) and matrix-assisted laser desorption ionisation (MALDI) have been used for ionisation of ribonucleic analytes. Ammonium acetate and 2-propanol are common solvents for ESI. Trihydroxyacetophenone is the optimal MALDI matrix for ionisation of ribonucleic acids and peptides. Ammonium salts are used in ESI buffers and MALDI matrices as additives to remove cation adducts. Reverse phase high performance liquid chromatography has been used for desalting and fractionation of analytes either off-line of on-line, coupled with ESI source. Triethylamine and triethylammonium bicarbonate are used as ion pair reagents almost exclusively. Fourier transform ion cyclotron resonance analyser using ESI coupled with liquid chromatography is the platform of choice for all forms of structural analyses. Time-of-flight (TOF) analyser using MALDI may offer sensitive, easy-to-use and economical solution for simple sequencing of longer oligonucleotides and analyses of analyte mixtures without prior fractionation. Special analysis software is used for computer-aided interpretation of mass spectra. With mass spectrometry, sequences of 20-30 nucleotides of length may be determined unambiguously. Sequencing may be applied to quality control of short synthetic oligomers for analytical purposes. Sequencing in conjunction with other structural studies enables accurate localisation and characterisation of posttranscriptional modifications and identification of nucleobases and amino acids at the sites of interaction. High throughput screening methods for RNA-binding ligands have been developed. Probing of the higher order structures has provided supportive data for computer-generated three dimensional models of viral pseudoknots. In conclusion. mass spectrometric methods are well suited for structural analyses of small species of ribonucleic acids, such as short non-coding ribonucleic acids in the molecular size region of 20-30 nucleotides. Structural information not attainable with other methods of analyses, such as nuclear magnetic resonance and X-ray crystallography, may be obtained with the use of mass spectrometry. Sequencing may be applied to quality control of short synthetic oligomers for analytical purposes. Ligand screening may be used in the search of possible new therapeutic agents. Demanding assay design and challenging interpretation of data requires multidisclipinary knowledge. The implement of mass spectrometry to structural studies of ribonucleic acids is probably most efficiently conducted in specialist groups consisting of researchers from various fields of science.

Methods to improve gene signal: Application to cDNA microarrays

Microarrays are high throughput biological assays that allow the screening of thousands of genes for their expression. The main idea behind microarrays is to compute for each gene a unique signal that is directly proportional to the quantity of mRNA that was hybridized on the chip. A large number of steps and errors associated with each step make the generated expression signal noisy. As a result, microarray data need to be carefully pre-processed before their analysis can be assumed to lead to reliable and biologically relevant conclusions. This thesis focuses on developing methods for improving gene signal and further utilizing this improved signal for higher level analysis. To achieve this, first, approaches for designing microarray experiments using various optimality criteria, considering both biological and technical replicates, are described. A carefully designed experiment leads to signal with low noise, as the effect of unwanted variations is minimized and the precision of the estimates of the parameters of interest are maximized. Second, a system for improving the gene signal by using three scans at varying scanner sensitivities is developed. A novel Bayesian latent intensity model is then applied on these three sets of expression values, corresponding to the three scans, to estimate the suitably calibrated true signal of genes. Third, a novel image segmentation approach that segregates the fluorescent signal from the undesired noise is developed using an additional dye, SYBR green RNA II. This technique helped in identifying signal only with respect to the hybridized DNA, and signal corresponding to dust, scratch, spilling of dye, and other noises, are avoided. Fourth, an integrated statistical model is developed, where signal correction, systematic array effects, dye effects, and differential expression, are modelled jointly as opposed to a sequential application of several methods of analysis. The methods described in here have been tested only for cDNA microarrays, but can also, with some modifications, be applied to other high-throughput technologies. Keywords: High-throughput technology, microarray, cDNA, multiple scans, Bayesian hierarchical models, image analysis, experimental design, MCMC, WinBUGS.

Drug discovery approaches utilizing three-dimensional cell culture

Historically, two-dimensional (2D) cell culture has been the preferred method of producing disease models in vitro. Recently, there has been a move away from 2D culture in favor of generating three-dimensional (3D) multicellular structures, which are thought to be more representative of the in vivo environment. This transition has brought with it an influx of technologies capable of producing these structures in various ways. However, it is becoming evident that many of these technologies do not perform well in automated in vitro drug discovery units. We believe that this is a result of their incompatibility with high-throughput screening (HTS). In this study, we review a number of technologies, which are currently available for producing in vitro 3D disease models. We assess their amenability with high-content screening and HTS and highlight our own work in attempting to address many of the practical problems that are hampering the successful deployment of 3D cell systems in mainstream research.

Computational Techniques for Haplotype Inference and for Local Alignment Significance

This thesis which consists of an introduction and four peer-reviewed original publications studies the problems of haplotype inference (haplotyping) and local alignment significance. The problems studied here belong to the broad area of bioinformatics and computational biology. The presented solutions are computationally fast and accurate, which makes them practical in high-throughput sequence data analysis. Haplotype inference is a computational problem where the goal is to estimate haplotypes from a sample of genotypes as accurately as possible. This problem is important as the direct measurement of haplotypes is difficult, whereas the genotypes are easier to quantify. Haplotypes are the key-players when studying for example the genetic causes of diseases. In this thesis, three methods are presented for the haplotype inference problem referred to as HaploParser, HIT, and BACH. HaploParser is based on a combinatorial mosaic model and hierarchical parsing that together mimic recombinations and point-mutations in a biologically plausible way. In this mosaic model, the current population is assumed to be evolved from a small founder population. Thus, the haplotypes of the current population are recombinations of the (implicit) founder haplotypes with some point--mutations. HIT (Haplotype Inference Technique) uses a hidden Markov model for haplotypes and efficient algorithms are presented to learn this model from genotype data. The model structure of HIT is analogous to the mosaic model of HaploParser with founder haplotypes. Therefore, it can be seen as a probabilistic model of recombinations and point-mutations. BACH (Bayesian Context-based Haplotyping) utilizes a context tree weighting algorithm to efficiently sum over all variable-length Markov chains to evaluate the posterior probability of a haplotype configuration. Algorithms are presented that find haplotype configurations with high posterior probability. BACH is the most accurate method presented in this thesis and has comparable performance to the best available software for haplotype inference. Local alignment significance is a computational problem where one is interested in whether the local similarities in two sequences are due to the fact that the sequences are related or just by chance. Similarity of sequences is measured by their best local alignment score and from that, a p-value is computed. This p-value is the probability of picking two sequences from the null model that have as good or better best local alignment score. Local alignment significance is used routinely for example in homology searches. In this thesis, a general framework is sketched that allows one to compute a tight upper bound for the p-value of a local pairwise alignment score. Unlike the previous methods, the presented framework is not affeced by so-called edge-effects and can handle gaps (deletions and insertions) without troublesome sampling and curve fitting.

Construction of a global map of human gene expression : the process, tools and analysis

This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level.

Genomic regions influencing seminal root traits in barley

Water availability is a major limiting factor for crop production, making drought adaptation and its many component traits a desirable attribute of plant cultivars. Previous studies in cereal crops indicate that root traits expressed at early plant developmental stages, such as seminal root angle and root number, are associated with water extraction at different depths. Here, we conducted the first study to map seminal root traits in barley (Hordeum vulgare L.). Using a recently developed high-throughput phenotyping method, a panel of 30 barley genotypes and a doubled-haploid (DH) population (ND24260 × 'Flagship') comprising 330 lines genotyped with diversity array technology (DArT) markers were evaluated for seminal root angle (deviation from vertical) and root number under controlled environmental conditions. A high degree of phenotypic variation was observed in the panel of 30 genotypes: 13.5 to 82.2 and 3.6 to 6.9° for root angle and root number, respectively. A similar range was observed in the DH population: 16.4 to 70.5 and 3.6 to 6.5° for root angle and number, respectively. Seven quantitative trait loci (QTL) for seminal root traits (root angle, two QTL; root number, five QTL) were detected in the DH population. A major QTL influencing both root angle and root number (RAQ2/RNQ4) was positioned on chromosome 5HL. Across-species analysis identified 10 common genes underlying root trait QTL in barley, wheat (Triticum aestivum L.), and sorghum [Sorghum bicolor (L.) Moench]. Here, we provide insight into seminal root phenotypes and provide a first look at the genetics controlling these traits in barley.

Genomic approach to organ-specific growth control

Growth is a fundamental aspect of life cycle of all organisms. Body size varies highly in most animal groups, such as mammals. Moreover, growth of a multicellular organism is not uniform enlargement of size, but different body parts and organs grow to their characteristic sizes at different times. Currently very little is known about the molecular mechanisms governing this organ-specific growth. The genome sequencing projects have provided complete genomic DNA sequences of several species over the past decade. The amount of genomic sequence information, including sequence variants within species, is constantly increasing. Based on the universal genetic code, we can make sense of this sequence information as far as it codes proteins. However, less is known about the molecular mechanisms that control expression of genes, and about the variations in gene expression that underlie many pathological states in humans. This is caused in part by lack of information about the second genetic code that consists of the binding specificities of transcription factors and the combinatorial code by which transcription factor binding sites are assembled to form tissue-specific and/or ligand-regulated enhancer elements. This thesis presents a high-throughput assay for identification of transcription factor binding specificities, which were then used to measure the DNA binding profiles of transcription factors involved in growth control. We developed ‘enhancer element locator’, a computational tool, which can be used to predict functional enhancer elements. A genome-wide prediction of human and mouse enhancer elements generated a large database of enhancer elements. This database can be used to identify target genes of signaling pathways, and to predict activated transcription factors based on changes in gene expression. Predictions validated in transgenic mouse embryos revealed the presence of multiple tissue-specific enhancers in mouse c- and N-Myc genes, which has implications to organ specific growth control and tumor type specificity of oncogenes. Furthermore, we were able to locate a variation in a single nucleotide, which carries a susceptibility to colorectal cancer, to an enhancer element and propose a mechanism by which this SNP might be involved in generation of colorectal cancer.

The role of MicroRNAs in stress response in the resurrection plant Tripogon loliiformis

Research in this thesis focussed on the improvement of agricultural crops in increasing water use efficiency that impacts global crop productivity. The study identified key genetic regulatory mechanisms that the resurrection plant Tripogon loliiformis utilises to tolerate desiccation. Due to the conserved nature of the pathways involved, this information can be transferred for the enhancement of drought tolerance and water use efficiency in agricultural crops. Specifically this study used high throughput sequencing, microscopy and plant transformation to further the understanding of post-transcriptional regulatory mechanisms. It was shown that T. loliiformis uses microRNAs to regulate pro-survival autophagy pathways to tolerate desiccation.

Gene Expression : From Microarrays to Functional Genomics

The time of the large sequencing projects has enabled unprecedented possibilities of investigating more complex aspects of living organisms. Among the high-throughput technologies based on the genomic sequences, the DNA microarrays are widely used for many purposes, including the measurement of the relative quantity of the messenger RNAs. However, the reliability of microarrays has been strongly doubted as robust analysis of the complex microarray output data has been developed only after the technology had already been spread in the community. An objective of this study consisted of increasing the performance of microarrays, and was measured by the successful validation of the results by independent techniques. To this end, emphasis has been given to the possibility of selecting candidate genes with remarkable biological significance within specific experimental design. Along with literature evidence, the re-annotation of the probes and model-based normalization algorithms were found to be beneficial when analyzing Affymetrix GeneChip data. Typically, the analysis of microarrays aims at selecting genes whose expression is significantly different in different conditions followed by grouping them in functional categories, enabling a biological interpretation of the results. Another approach investigates the global differences in the expression of functionally related groups of genes. Here, this technique has been effective in discovering patterns related to temporal changes during infection of human cells. Another aspect explored in this thesis is related to the possibility of combining independent gene expression data for creating a catalog of genes that are selectively expressed in healthy human tissues. Not all the genes present in human cells are active; some involved in basic activities (named housekeeping genes) are expressed ubiquitously. Other genes (named tissue-selective genes) provide more specific functions and they are expressed preferably in certain cell types or tissues. Defining the tissue-selective genes is also important as these genes can cause disease with phenotype in the tissues where they are expressed. The hypothesis that gene expression could be used as a measure of the relatedness of the tissues has been also proved. Microarray experiments provide long lists of candidate genes that are often difficult to interpret and prioritize. Extending the power of microarray results is possible by inferring the relationships of genes under certain conditions. Gene transcription is constantly regulated by the coordinated binding of proteins, named transcription factors, to specific portions of the its promoter sequence. In this study, the analysis of promoters from groups of candidate genes has been utilized for predicting gene networks and highlighting modules of transcription factors playing a central role in the regulation of their transcription. Specific modules have been found regulating the expression of genes selectively expressed in the hippocampus, an area of the brain having a central role in the Major Depression Disorder. Similarly, gene networks derived from microarray results have elucidated aspects of the development of the mesencephalon, another region of the brain involved in Parkinson Disease.

Microbial communities in Pb contaminated boreal forest soil

Lead contamination in the environment is of particular concern, as it is a known toxin. Until recently, however, much less attention has been given to the local contamination caused by activities at shooting ranges compared to large-scale industrial contamination. In Finland, more than 500 tons of Pb is produced each year for shotgun ammunition. The contaminant threatens various organisms, ground water and the health of human populations. However, the forest at shooting ranges usually shows no visible sign of stress compared to nearby clean environments. The aboveground biota normally reflects the belowground ecosystem. Thus, the soil microbial communities appear to bear strong resistance to contamination, despite the influence of lead. The studies forming this thesis investigated a shooting range site at Hälvälä in Southern Finland, which is heavily contaminated by lead pellets. Previously it was experimentally shown that the growth of grasses and degradation of litter are retarded. Measurements of acute toxicity of the contaminated soil or soil extracts gave conflicting results, as enchytraeid worms used as toxicity reporters were strongly affected, while reporter bacteria showed no or very minor decreases in viability. Measurements using sensitive inducible luminescent reporter bacteria suggested that the bioavailability of lead in the soil is indeed low, and this notion was supported by the very low water extractability of the lead. Nevertheless, the frequency of lead-resistant cultivable bacteria was elevated based on the isolation of cultivable strains. The bacterial and fungal diversity in heavily lead contaminated shooting sectors were compared with those of pristine sections of the shooting range area. The bacterial 16S rRNA gene and fungal ITS rRNA gene were amplified, cloned and sequenced using total DNA extracted from the soil humus layer as the template. Altogether, 917 sequenced bacterial clones and 649 sequenced fungal clones revealed a high soil microbial diversity. No effect of lead contamination was found on bacterial richness or diversity, while fungal richness and diversity significantly differed between lead contaminated and clean control areas. However, even in the case of fungi, genera that were deemed sensitive were not totally absent from the contaminated area: only their relative frequency was significantly reduced. Some operational taxonomic units (OTUs) assigned to Basidiomycota were clearly affected, and were much rarer in the lead contaminated areas. The studies of this thesis surveyed EcM sporocarps, analyzed morphotyped EcM root tips by direct sequencing, and 454-pyrosequenced fungal communities in in-growth bags. A total of 32 EcM fungi that formed conspicuous sporocarps, 27 EcM fungal OTUs from 294 root tips, and 116 EcM fungal OTUs from a total of 8 194 ITS2 454 sequences were recorded. The ordination analyses by non-parametric multidimensional scaling (NMS) indicated that Pb enrichment induced a shift in the EcM community composition. This was visible as indicative trends in the sporocarp and root tip datasets, but explicitly clear in the communities observed in the in-growth bags. The compositional shift in the EcM community was mainly attributable to an increase in the frequencies of OTUs assigned to the genus Thelephora, and to a decrease in the OTUs assigned to Pseudotomentella, Suillus and Tylospora in Pb-contaminated areas when compared to the control. The enrichment of Thelephora in contaminated areas was also observed when examining the total fungal communities in soil using DNA cloning and sequencing technology. While the compositional shifts are clear, their functional consequences for the dominant trees or soil ecosystem remain undetermined. The results indicate that at the Hälvälä shooting range, lead influences the fungal communities but not the bacterial communities. The forest ecosystem shows apparent functional redundancy, since no significant effects were seen on forest trees. Recently, by means of 454 pyrosequencing , the amount of sequences in a single analysis run can be up to one million. It has been applied in microbial ecology studies to characterize microbial communities. The handling of sequence data with traditional programs is becoming difficult and exceedingly time consuming, and novel tools are needed to handle the vast amounts of data being generated. The field of microbial ecology has recently benefited from the availability of a number of tools for describing and comparing microbial communities using robust statistical methods. However, although these programs provide methods for rapid calculation, it has become necessary to make them more amenable to larger datasets and numbers of samples from pyrosequencing. As part of this thesis, a new program was developed, MuSSA (Multi-Sample Sequence Analyser), to handle sequence data from novel high-throughput sequencing approaches in microbial community analyses. The greatest advantage of the program is that large volumes of sequence data can be manipulated, and general OTU series with a frequency value can be calculated among a large number of samples.

Serum proteomics of glioma: methods and applications

The prognosis of patients with glioblastoma, the most malignant adult glial brain tumor, remains poor in spite of advances in treatment procedures, including surgical resection, irradiation and chemotherapy.Genetic heterogeneity of glioblastoma warrants extensive studies in order to gain a thorough understanding of the biology of this tumor. While there have been several studies of global transcript profiling of glioma with the identification of gene signatures for diagnosis and disease management, translation into clinics is yet to happen. Serum biomarkers have the potential to revolutionize the process of cancer diagnosis, grading, prognostication and treatment response monitoring. Besides having the advantage that serum can be obtained through a less invasive procedure, it contains molecules at an extraordinary dynamic range of ten orders of magnitude in terms of their concentrations. While the conventional methods, such as 2DE, have been in use for many years, the ability to identify the proteins through mass spectrometry techniques such as MALDI-TOF led to an explosion of interest in proteomics. Relatively new high-throughput proteomics methods such as SELDI-TOF and protein microarrays are expected to hasten the process of serum biomarker discovery. This review will highlight the recent advances in the proteomics platform in discovering serum biomarkers and the current status of glioma serum markers. We aim to provide the principles and potential of the latest proteomic approaches and their applications in the biomarker discovery process. Besides providing a comprehensive list of available serum biomarkers of glioma, we will also propose how these markers will revolutionize the clinical management of glioma patients.

Compound heterozygous mutations in RIPPLY2 associated with vertebral segmentation defects

Segmentation defects of the vertebrae (SDV) are caused by aberrant somite formation during embryogenesis and result in irregular formation of the vertebrae and ribs. The Notch signal transduction pathway plays a critical role in somite formation and patterning in model vertebrates. In humans, mutations in several genes involved in the Notch pathway are associated with SDV, with both autosomal recessive (MESP2, DLL3, LFNG, HES7) and autosomal dominant (TBX6) inheritance. However, many individuals with SDV do not carry mutations in these genes. Using whole-exome capture and massive parallel sequencing, we identified compound heterozygous mutations in RIPPLY2 in two brothers with multiple regional SDV, with appropriate familial segregation. One novel mutation (c.A238T:p.Arg80*) introduces a premature stop codon. In transiently transfected C2C12 mouse myoblasts, the RIPPLY2 mutant protein demonstrated impaired transcriptional repression activity compared with wild-type RIPPLY2 despite similar levels of expression. The other mutation (c.240-4T>G), with minor allele frequency <0.002, lies in the highly conserved splice site consensus sequence 5' to the terminal exon. Ripply2 has a well-established role in somitogenesis and vertebral column formation, interacting at both gene and protein levels with SDV-associated Mesp2 and Tbx6. We conclude that compound heterozygous mutations in RIPPLY2 are associated with SDV, a new gene for this condition. © The Author 2014.

Next-generation sequencing: A frameshift in skeletal dysplasia gene discovery

In the last decade, huge breakthroughs in genetics - driven by new technology and different statistical approaches - have resulted in a plethora of new disease genes identified for both common and rare diseases. Massive parallel sequencing, commonly known as next-generation sequencing, is the latest advance in genetics, and has already facilitated the discovery of the molecular cause of many monogenic disorders. This article describes this new technology and reviews how this approach has been used successfully in patients with skeletal dysplasias. Moreover, this article illustrates how the study of rare diseases can inform understanding and therapeutic developments for common diseases such as osteoporosis. © International Osteoporosis Foundation and National Osteoporosis Foundation 2013.