Agnes Baross

Oligonucleotide Microarray Analysis of Genomic Imbalance in Children with Mental Retardation

The cause of mental retardation in one-third to one-half of all affected individuals is unknown. Microscopically detectable chromosomal abnormalities are the most frequently recognized cause, but gain or loss of chromosomal segments that are too small to be seen by conventional cytogenetic analysis has been found to be another important cause. Array-based methods offer a practical means of performing a high-resolution survey of the entire genome for submicroscopic copy-number variants. We studied 100 children with idiopathic mental retardation and normal results of standard chromosomal analysis, by use of whole-genome sampling analysis with Affymetrix GeneChip Human Mapping 100K arrays. We found de novo deletions as small as 178 kb in eight cases, de novo duplications as small as 1.1 Mb in two cases, and unsuspected mosaic trisomy 9 in another case. This technology can detect at least twice as many potentially pathogenic de novo copy-number variants as conventional cytogenetic analysis can in people with mental retardation.

A patient with vertebral, cognitive and behavioural abnormalities and a de novo deletion of NRXN1α

The authors report a patient with mild mental retardation, autistic features, multiple vertebral malformations, and an unusual facial appearance who carries a de novo submicroscopic deletion of chromosome 2p16.3. The patient’s deletion is ∼320 kb in size and includes only the part of the NRXN1 gene that codes for the neurexin1α promoter and initial coding exons. The more downstream neurexin1β promoter and the region surrounding it are intact. Neurexin1β has been associated with autism in several recent studies, but this is the first reported patient with loss of only neurexin1α and not of neurexin1β. These findings suggest that neurexin1α function in correct dosage is necessary for normal neurological development.

Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data

BackgroundGenomic deletions and duplications are important in the pathogenesis of diseases, such as cancer and mental retardation, and have recently been shown to occur frequently in unaffected individuals as polymorphisms. Affymetrix GeneChip whole genome sampling analysis (WGSA) combined with 100 K single nucleotide polymorphism (SNP) genotyping arrays is one of several microarray-based approaches that are now being used to detect such structural genomic changes. The popularity of this technology and its associated open source data format have resulted in the development of an increasing number of software packages for the analysis of copy number changes using these SNP arrays.ResultsWe evaluated four publicly available software packages for high throughput copy number analysis using synthetic and empirical 100 K SNP array data sets, the latter obtained from 107 mental retardation (MR) patients and their unaffected parents and siblings. We evaluated the software with regards to overall suitability for high-throughput 100 K SNP array data analysis, as well as effectiveness of normalization, scaling with various reference sets and feature extraction, as well as true and false positive rates of genomic copy number variant (CNV) detection.ConclusionWe observed considerable variation among the numbers and types of candidate CNVs detected by different analysis approaches, and found that multiple programs were needed to find all real aberrations in our test set. The frequency of false positive deletions was substantial, but could be greatly reduced by using the SNP genotype information to confirm loss of heterozygosity.

LongSAGE profiling of nine human embryonic stem cell lines

To facilitate discovery of novel human embryonic stem cell (ESC) transcripts, we generated 2.5 million LongSAGE tags from 9 human ESC lines. Analysis of this data revealed that ESCs express proportionately more RNA binding proteins compared with terminally differentiated cells, and identified novel ESC transcripts, at least one of which may represent a marker of the pluripotent state.

Detection of pathogenic copy number variants in children with idiopathic intellectual disability using 500 K SNP array genomic hybridization

BackgroundArray genomic hybridization is being used clinically to detect pathogenic copy number variants in children with intellectual disability and other birth defects. However, there is no agreement regarding the kind of array, the distribution of probes across the genome, or the resolution that is most appropriate for clinical use.ResultsWe performed 500 K Affymetrix GeneChip® array genomic hybridization in 100 idiopathic intellectual disability trios, each comprised of a child with intellectual disability of unknown cause and both unaffected parents. We found pathogenic genomic imbalance in 16 of these 100 individuals with idiopathic intellectual disability. In comparison, we had found pathogenic genomic imbalance in 11 of 100 children with idiopathic intellectual disability in a previous cohort who had been studied by 100 K GeneChip® array genomic hybridization. Among 54 intellectual disability trios selected from the previous cohort who were re-tested with 500 K GeneChip® array genomic hybridization, we identified all 10 previously-detected pathogenic genomic alterations and at least one additional pathogenic copy number variant that had not been detected with 100 K GeneChip® array genomic hybridization. Many benign copy number variants, including one that was de novo, were also detected with 500 K array genomic hybridization, but it was possible to distinguish the benign and pathogenic copy number variants with confidence in all but 3 (1.9%) of the 154 intellectual disability trios studied.ConclusionAffymetrix GeneChip® 500 K array genomic hybridization detected pathogenic genomic imbalance in 10 of 10 patients with idiopathic developmental disability in whom 100 K GeneChip® array genomic hybridization had found genomic imbalance, 1 of 44 patients in whom 100 K GeneChip® array genomic hybridization had found no abnormality, and 16 of 100 patients who had not previously been tested. Effective clinical interpretation of these studies requires considerable skill and experience.

ALEXA: a microarray design platform for alternative expression analysis

To the editor: Eukaryotic genomes are predicted to contain about 7,000–29,000 genes1. Each of these genes may be alternatively processed to produce multiple distinct mRNAs by alternative transcript initiation, splicing and polyadenylation (collectively referred to as alternative expression). Although analysis of available transcript resources indicates that up to ~75% of genes are alternatively processed, most microarray expression platforms cannot detect alternative transcripts2. Proof-of-principle experiments have described the use of oligonucleotide microarrays to profile transcript isoforms generated by alternative expression, but resources to create such arrays are lacking3,4. To address this limitation we created a microarray design platform for alternative expression analysis (ALEXA), which is capable of designing arrays that can detect all of the major categories of alternative expression. The ALEXA platform facilitates selection and annotation of oligonucleotide probes representing alternative expression events for any species in the EnsEMBL database1. For each target gene, probes are selected within every exon, intron, exon junction and exon boundary. This approach allows for the detection of constitutive and alternative exons, canonical exon junctions, junctions of known or new exon-skipping events, alternative exon boundaries and retained introns (Supplementary Fig. 1 online). We designed the platform to be flexible to the user’s experimental interests and preferred array manufacturer. The user may limit probe selection to known alternative expression events or include all possible exon junctions and boundaries to drive the discovery of transcripts. Probes may be designed for an arbitrary subset of genes or for all genes. Most technical parameters of the design can be modified by the user, including: the amount and types of control probes; the use of varying or fixed probe length; and the thresholds for filtering of probe sequences. The probe design process begins with retrieval of genomic sequences from EnsEMBL, removal of pseudogenes, masking of repeat elements and extraction of probe sequences. Random probe sequences are generated to uniformly represent the melting temperature and length of all experimental probes. Extracted and randomly generated probes are scored according to their melting temperature, folding potential, complexity and specificity (Supplementary Methods online). Although several publications have described using microarrays to study alternative expression in model organisms and specific tissues2, to our knowledge ours is the first report of a resource that makes alternative expression microarray designs readily available. Using the ALEXA approach, we precomputed microarray designs representing ~100 million probe sequences for ten EnsEMBL genomes (Supplementary Table 1 online). We assessed the ALEXA approach by using a prototype human array to profile the expression of alternative mRNA isoforms in 5-fluorouracil (5-FU)sensitive and resistant colorectal cancer cell lines5 and compared the results to those from the Affymetrix ‘GeneChip Human Exon 1.0 ST’ array (see Supplementary Results, Supplementary Fig. 2 and Supplementary Table 2 online). Genes and exons differentially expressed between 5-FU–sensitive and resistant cells were identified by both platforms (with significant overlap), but ALEXA arrays provided additional information on the connectivity and boundaries of exons (Table 1). Furthermore, alternative expression events identified by ALEXA were significantly enriched for known alternative expression events represented in publicly available mRNA and expressed sequence tag (EST) databases (Supplementary Results and Supplementary Data 1 online). Finally, we demonstrated the advantage of the ALEXA approach by identifying several differentially expressed known and predicted isoforms with potential relevance to 5-FU resistance (Supplementary Fig. 3 and Supplementary Tables 3 and 4 online). The approach and resources described in this work have considerable potential to advance studies of gene regulation, transcript processing, human disease and evolutionary biology (Supplementary Discussion online). The source code, precomputed array designs and related materials to assist in the creation of custom alternative expression microarrays are available on the ALEXA website (http://www.alexaplatform.org).

Effect of TERT and ATM on gene expression profiles in human fibroblasts

Telomeres protect chromosomes from degradation, end‐to‐end fusion, and illegitimate recombination. Loss of telomeres may lead to cell death or senescence or may cause genomic instability, leading to tumor formation. Expression of human telomerase reverse transcriptase (TERT) in human fibroblast cells elongates their telomeres and extends their lifespan. Ataxia telangiectasia mutated (ATM) deficiency in A‐T human fibroblasts results in accelerated telomere shortening, abnormal cell‐cycle response to DNA damage, and early senescence. Gene expression profiling was performed by serial analysis of gene expression (SAGE) on BJ normal human skin fibroblasts, A‐T cells, and BJ and A‐T cells transduced with TERT cDNA and expressing telomerase activity. In the four SAGE libraries, 36,921 unique SAGE tags were detected. Pairwise comparisons between the libraries showed differential expression levels of 1%–8% of the tags. Transcripts affected by both TERT and ATM were identified according to expression patterns, making them good candidates for further studies of pathways affected by both TERT and ATM. These include MT2A, P4HB, LGALS1, CFL1, LDHA, S100A10, EIF3S8, RANBP9, and SEC63. These genes are involved in apoptosis or processes related to cell growth, and most have been found to be deregulated in cancer. Our results have provided further insight into the roles of TERT and ATM by identifying genes likely to be involved in their function. Supplementary material for this article can be found on the Genes, Chromosomes and Cancer website at http://www.interscience.wiley.com/jpages/1045‐2257/suppmat/index.html.