Molecular techniques have been developed for prenatal diagnosis of the most common chromosome disorders (trisomies 21, 13, 18 and sex chromosome aneuploidies) where results are available within a day or two. This involves fluorescence in situ hybridization (FISH) and microscopy analysis of fetal cells or quantitative fluorescence polymerase chain reaction (QF-PCR) on fetal DNA. Guidance is provided on the technological pitfalls in setting up and running these methods. Both methods are reliable, and the risk for misdiagnosis is low, although slightly higher for FISH. FISH is also more labour intensive than QF-PCR, the latter lending itself more easily to automation. These tests have been used as a preamble to full chromosome analysis by microscopy. However, there is a trend to apply the tests as 'stand-alone' tests for women who are at relatively low risk of having a baby with a chromosome disorder, in particular that associated with advanced age or results of maternal serum screening programmes. These women comprise the majority of those currently offered prenatal diagnosis with respect to fetal chromosome disorders and if introduced on a larger scale, the use of FISH and QF-PCR would lead to substantial economical savings. The implication, on the other hand, is that around one in 500 to one in 1000 cases with a mentally and/or physically disabling chromosome disorder would remain undiagnosed.

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Preimplantation genetic diagnosis (PGD) for monogenic disorders currently involves polymerase chain reaction (PCR)-based methods, which must be robust, sensitive and highly accurate, precluding misdiagnosis. Twelve adverse misdiagnoses reported to the ESHRE PGD-Consortium are likely an underestimate. This retrospective study, involving six PGD centres, assessed the validity of PCR-based PGD through reanalysis of untransferred embryos from monogenic-PGD cycles. Data were collected on the genotype concordance at PGD and follow-up from 940 untransferred embryos, including details on the parameters of PGD cycles: category of monogenic disease, embryo morphology, embryo biopsy and genotype assay strategy. To determine the validity of PCR-based PGD, the sensitivity (Se), specificity (Sp) and diagnostic accuracy were calculated. Stratified analyses were also conducted to assess the influence of the parameters above on the validity of PCR-based PGD. The analysis of overall data showed that 93.7% of embryos had been correctly classified at the time of PGD, with Se of 99.2% and Sp of 80.9%. The stratified analyses found that diagnostic accuracy is statistically significantly higher when PGD is performed on two cells versus one cell (P ¼ 0.001). Se was significantly higher when multiplex protocols versus singleplex protocols were applied (P ¼ 0.005), as well as for PGD applied on cells from good compared with poor morphology embryos (P ¼ 0.032). Morphology, however, did not affect diagnostic accuracy. Multiplex PCR-based methods on one cell, are as robust as those on two cells regarding false negative rate, which is the most important criteria for clinical PGD applications. Overall, this study demonstrates the validity, robustness and high diagnostic value of PCR-based PGD.

Fast and accurate analysis of fluorescence in-situ hybridization (FISH) images for signal counting will depend mainly upon two components: a classifier to discriminate between artifacts and valid signals of several fluorophores (colors), and well discriminating features to represent the signals. Our previous work has focused on the first component. To investigate the second component, we evaluate candidate feature sets by illustrating the probability density functions (pdfs) and scatter plots for the features. The analysis provides first insight into dependencies between features, indicates the relative importance of members of a feature set, and helps in identifying sources of potential classification errors. Class separability yielded by different feature subsets is evaluated using the accuracy of several neural network (NN)-based classification strategies, some of them hierarchical, as well as using a feature selection technique making use of a scatter criterion. The complete analysis recommends several intensity and hue features for representing FISH signals. Represented by these features, around 90% of valid signals and artifacts of two fluorophores are correctly classified using the NN. Although applied to cytogenetics, the paper presents a comprehensive, unifying methodology of qualitative and quantitative evaluation of pattern feature representation essential for accurate image classification. This methodology is applicable to many other real-world pattern recognition problems.Index Terms-Color image segmentation, feature representation, fluorescence in-situ hybridization, image analysis, neural networks, signal classification.

From 2006 to 2011, Roslin Cells Ltd derived 17 human embryonic stem cells (hESC) while developing (RCM1, RC-2 to -8, -10) and implementing (RC-9, -11 to -17) quality assured standards of operation in a facility operating in compliance with European Union (EU) directives and United Kingdom (UK) licensure for procurement, processing and storage of human cells as source material for clinical application, and targeted to comply with an EU Good Manufacturing Practice specification. Here we describe the evolution and specification of the facility, its operation and outputs, complementing hESC resource details communicated in Stem Cell Research Lab Resources.

Rett syndrome is an X-linked dominant neurological disorder, which appears to be the commonest genetic cause of profound combined intellectual and physical disability in Caucasian females. Recently, this syndrome has been associated with mutations of the MECP2 gene, a transcriptional repressor of still unknown target genes. Here we report a detailed mutational analysis of 62 patients from UK and Italian archives, representing the first comparative study among different populations and one of the largest number of cases so far analyzed. We review the literature on MECP2 mutations in Rett syndrome. This analysis has permitted us to produce a map of the recurrent mutations identified in this and previous studies. Bioinformatic analysis of the mutations, taking advantage of structural and evolutionary data, leads us to postulate the existence of a new functional domain in the MeCP2 protein, which is conserved among brain-specific regulatory factors.