Identification of mutations in the ALD-gene of 20 families with adrenoleukodystrophy/adrenomyeloneuropathy

Adrenoleukodystrophy (ALD), an X-linked inherited metabolic disorder, is the most frequent inborn peroxisomal disease. It leads to demyelination in the central and peripheral nervous system. Defective -oxidation of saturated very long chain fatty acids (VLCFAs; C22:0–C26:0) in peroxisomes has been shown to lead to an accumulation of VLCFAs in leukoid areas of the central nervous system, peripheral nerves, adrenal gland, and blood. The ALD gene has been recently identified and encodes a 745-amino-acid protein. We screened patients with adrenoleukodystrophy/adrenomyeloneuropathy (ALD/AMN) from 20 kindreds for mutations in the ALD gene. Eleven missense and two nonsense mutations, five deletions, and one insertion were detected by direct sequencing of eight reverse transcribed fragments of the ALD-gene mRNA. Four mutations could be shown to be de novo. All mutations could be confirmed in carriers by sequencing genomic DNA. No correlation between the type of mutation and the severity of the phenotype could be observed. The mutations were not detected in the ALD gene of 30 healthy persons.     

Pre-Analytical Conditions in Non-Invasive Prenatal Testing of Cell-Free Fetal RHD

Background

Non-invasive prenatal testing of cell-free fetal DNA (cffDNA) in maternal plasma can predict the fetal RhD type in D negative pregnant women. In Denmark, routine antenatal screening for the fetal RhD gene (RHD) directs the administration of antenatal anti-D prophylaxis only to women who carry an RhD positive fetus. Prophylaxis reduces the risk of immunization that may lead to hemolytic disease of the fetus and the newborn. The reliability of predicting the fetal RhD type depends on pre-analytical factors and assay sensitivity. We evaluated the testing setup in the Capital Region of Denmark, based on data from routine antenatal RHD screening.

Methods

Blood samples were drawn at gestational age 25 weeks. DNA extracted from 1 mL of plasma was analyzed for fetal RHD using a duplex method for exon 7/10. We investigated the effect of blood sample transportation time (n = 110) and ambient outdoor temperatures (n = 1539) on the levels of cffDNA and total DNA. We compared two different quantification methods, the delta Ct method and a universal standard curve. PCR pipetting was compared on two systems (n = 104).

Results

The cffDNA level was unaffected by blood sample transportation for up to 9 days and by ambient outdoor temperatures ranging from -10°C to 28°C during transport. The universal standard curve was applicable for cffDNA quantification. Identical levels of cffDNA were observed using the two automated PCR pipetting systems. We detected a mean of 100 fetal DNA copies/mL at a median gestational age of 25 weeks (range 10–39, n = 1317).

Conclusion

The setup for real-time PCR-based, non-invasive prenatal testing of cffDNA in the Capital Region of Denmark is very robust. Our findings regarding the transportation of blood samples demonstrate the high stability of cffDNA. The applicability of a universal standard curve facilitates easy cffDNA quantification.     

Development of joint application strategies for two microbial gene finders

MOTIVATION: As a starting point in annotation of bacterial genomes, gene finding programs are used for the prediction of functional elements in the DNA sequence. Due to the faster pace and increasing number of genome projects currently underway, it is becoming especially important to have performant methods for this task. RESULTS: This study describes the development of joint application strategies that combine the strengths of two microbial gene finders to improve the overall gene finding performance. Critica is very specific in the detection of similarity-supported genes as it uses a comparative sequence analysis-based approach. Glimmer employs a very sophisticated model of genomic sequence properties and is sensitive also in the detection of organism-specific genes. Based on a data set of 113 microbial genome sequences, we optimized a combined application approach using different parameters with relevance to the gene finding problem. This results in a significant improvement in specificity while there is similarity in sensitivity to Glimmer. The improvement is especially pronounced for GC rich genomes. The method is currently being applied for the annotation of several microbial genomes. AVAILABILITY: The methods described have been implemented within the gene prediction component of the GenDB genome annotation system.     

Comparing expression level-dependent features in codon usage with protein abundance: an analysis of 'predictive proteomics'

Synonymous codon usage is a commonly used means for estimating gene expression levels of Escherichia coli genes and has also been used for predicting highly expressed genes for a number of prokaryotic genomes. By comparison of expression level-dependent features in codon usage with protein abundance data from two proteome studies of exponentially growing E. coli and Bacillus subtilis cells, we try to evaluate whether the implicit assumption of this approach can be confirmed with experimental data. Log-odds ratio scores are used to model differences in codon usage between highly expressed genes and genomic average. Using these, the strength and significance of expression level-dependent features in codon usage were determined for the genes of the Escherichia coli, Bacillus subtilis and Haemophilus influenzae genomes. The comparison of codon usage features with protein abundance data confirmed a relationship between these to be present, although exceptions to this, possibly related to functional context, were found. For species with expression level-dependent features in their codon usage, the applied methodology could be used to improve in silico simulations of the outcome of two-dimensional gel electrophoretic experiments.     

PathFinder: reconstruction and dynamic visualization of metabolic pathways

MOTIVATION: Beyond methods for a gene-wise annotation and analysis of sequenced genomes new automated methods for functional analysis on a higher level are needed. The identification of realized metabolic pathways provides valuable information on gene expression and regulation. Detection of incomplete pathways helps to improve a constantly evolving genome annotation or discover alternative biochemical pathways. To utilize automated genome analysis on the level of metabolic pathways new methods for the dynamic representation and visualization of pathways are needed. RESULTS: PathFinder is a tool for the dynamic visualization of metabolic pathways based on annotation data. Pathways are represented as directed acyclic graphs, graph layout algorithms accomplish the dynamic drawing and visualization of the metabolic maps. A more detailed analysis of the input data on the level of biochemical pathways helps to identify genes and detect improper parts of annotations. As an Relational Database Management System (RDBMS) based internet application PathFinder reads a list of EC-numbers or a given annotation in EMBL- or Genbank-format and dynamically generates pathway graphs.     

Whole genome shotgun sequencing guided by bioinformatics pipelines--an optimized approach for an established technique

While the sequencing of bacterial genomes has become a routine procedure at major sequencing centers, there are still a number of genome projects at small- or medium-size facilities. For these facilities a maximum of control over sequencing, assembling and finishing is essential. At the same time, facilities have to be able to co-operate at minimum costs for the overall project. We have established a pipeline for the distributed sequencing of Alcanivorax borkumensis SK2, Azoarcus sp. BH72, Clavibacter michiganensis subsp. michiganensis NCPPB382, Sorangium cellulosum So ce56 and Xanthomonas campestris pv. vesicatoria 85-10. Our pipeline relies on standard tools (e.g. PHRED/PHRAP, CAP3 and Consed/Autofinish) wherever possible, supplementing them with new tools (BioMake and BACCardI) to achieve the aims described above.     

Construction and validation of a Sinorhizobium meliloti whole genome DNA microarray: genome-wide profiling of osmoadaptive gene expression

Based on the complete Sinorhizobium meliloti genome sequence we established DNA microarrays as a comprehensive tool for systematic genome-wide gene expression analysis in S. meliloti 1021. For these PCR fragment-based microarrays, called Sm6kPCR, a collection of probes for the 6207 predicted protein-coding genes consisting of 6046 gene-specific PCR fragments and 161 70 mer oligonucleotides was arrayed in high density on glass slides. To obtain these PCR fragments primer pairs were designed to amplify internal gene-specific DNA fragments of 80-350 bp. Additionally, these primers were characterized by a 5' extension that allowed for reamplification using standard primers after the first amplification employing the specific primers. In order to ascertain the quality of the Sm6kPCR microarrays and to validate gene expression studies in S. meliloti parallel hybridizations based on RNA samples obtained from cells cultured under identical conditions were performed. In addition, gene expression in S. meliloti in response to an osmotic upshift imposed by the addition of 0.38 M NaCl was monitored. 137 genes were identified showing significant changes in gene expression resulting from the osmotic upshift. From these genes 52 were induced and 85 genes were repressed. Among the genes displaying different RNA levels some functional groups could be identified that are particularly remarkable. Repression was observed for 8 genes related to motility and chemotaxis, 7 genes encoding amino acid biosynthesis enzymes and 15 genes involved in iron uptake whereas 14 genes involved in transport of small molecules and 4 genes related to polysaccharide biosynthesis were induced.     

GISMO--gene identification using a support vector machine for ORF classification

We present the novel prokaryotic gene finder GISMO, which combines searches for protein family domains with composition-based classification based on a support vector machine. GISMO is highly accurate; exhibiting high sensitivity and specificity in gene identification. We found that it performs well for complete prokaryotic chromosomes, irrespective of their GC content, and also for plasmids as short as 10 kb, short genes and for genes with atypical sequence composition. Using GISMO, we found several thousand new predictions for the published genomes that are supported by extrinsic evidence, which strongly suggest that these are very likely biologically active genes. The source code for GISMO is freely available under the GPL license.