Next-generation sequencing of common osteogenesis imperfecta-related genes in clinical practice

Next generation sequencing (NGS) is a rapidly developing area in genetics. Utilizing this technology in the management of disorders with complex genetic background and not recurrent mutation hot spots can be extremely useful. In this study, we applied NGS, namely semiconductor sequencing to determine the most significant osteogenesis imperfecta-related genetic variants in the clinical practice. We selected genes coding collagen type I alpha-1 and-2 (COL1A1, COL1A2) which are responsible for more than 90% of all cases. CRTAP and LEPRE1/P3H1 genes involved in the background of the recessive forms with relatively high frequency (type VII and VIII) represent less than 10% of the disease. In our six patients (1-41 years), we identified 23 different variants. We found a total of 14 single nucleotide variants (SNV) in COL1A1 and COL1A2, 5 in CRTAP and 4 in LEPRE1. Two novel and two already well-established pathogenic SNVs have been identified. Among the newly recognized mutations, one results in an amino acid change and one of them is a stop codon. We have shown that a new full-scale cost-effective NGS method can be developed and utilized to supplement diagnostic process of osteogenesis imperfecta with molecular genetic data in clinical practice

The Cyprinodon variegatus genome reveals gene expression changes underlying differences in skull morphology among closely related species

Genes in durophage intersection set at 15 dpf. This is a comma separated table of the genes in the 15 dpf durophage intersection set. Given are edgeR results for each pairwise comparison. Columns indicating whether a gene is included in the intersection set at a threshold of 1.5 or 2 fold are provided. (CSV 13 kb

Next generation sequencing has lower sequence coverage and poorer SNP-detection capability in the regulatory regions

The rapid development of next generation sequencing (NGS) technology provides a new chance to extend the scale and resolution of genomic research. How to efficiently map millions of short reads to the reference genome and how to make accurate SNP calls are two major challenges in taking full advantage of NGS. In this article, we reviewed the current software tools for mapping and SNP calling, and evaluated their performance on samples from The Cancer Genome Atlas (TCGA) project. We found that BWA and Bowtie are better than the other alignment tools in comprehensive performance for Illumina platform, while NovoalignCS showed the best overall performance for SOLiD. Furthermore, we showed that next-generation sequencing platform has significantly lower coverage and poorer SNP-calling performance in the CpG islands, promoter and 5′-UTR regions of the genome. NGS experiments targeting for these regions should have higher sequencing depth than the normal genomic region

Evaluation of next-generation sequencing software in mapping and assembly

Next-generation high-throughput DNA sequencing technologies have advanced progressively in sequence-based genomic research and novel biological applications with the promise of sequencing DNA at unprecedented speed. These new non-Sanger-based technologies feature several advantages when compared with traditional sequencing methods in terms of higher sequencing speed, lower per run cost and higher accuracy. However, reads from next-generation sequencing (NGS) platforms, such as 454/Roche, ABI/SOLiD and Illumina/Solexa, are usually short, thereby restricting the applications of NGS platforms in genome assembly and annotation. We presented an overview of the challenges that these novel technologies meet and particularly illustrated various bioinformatics attempts on mapping and assembly for problem solving. We then compared the performance of several programs in these two fields, and further provided advices on selecting suitable tools for specific biological applications.published_or_final_versio

Why Can't Rodents Vomit? A Comparative Behavioral, Anatomical, and Physiological Study

The vomiting (emetic) reflex is documented in numerous mammalian species, including primates and carnivores, yet laboratory rats and mice appear to lack this response. It is unclear whether these rodents do not vomit because of anatomical constraints (e.g., a relatively long abdominal esophagus) or lack of key neural circuits. Moreover, it is unknown whether laboratory rodents are representative of Rodentia with regards to this reflex. Here we conducted behavioral testing of members of all three major groups of Rodentia; mouse-related (rat, mouse, vole, beaver), Ctenohystrica (guinea pig, nutria), and squirrel-related (mountain beaver) species. Prototypical emetic agents, apomorphine (sc), veratrine (sc), and copper sulfate (ig), failed to produce either retching or vomiting in these species (although other behavioral effects, e.g., locomotion, were noted). These rodents also had anatomical constraints, which could limit the efficiency of vomiting should it be attempted, including reduced muscularity of the diaphragm and stomach geometry that is not well structured for moving contents towards the esophagus compared to species that can vomit (cat, ferret, and musk shrew). Lastly, an in situ brainstem preparation was used to make sensitive measures of mouth, esophagus, and shoulder muscular movements, and phrenic nerve activity-key features of emetic episodes. Laboratory mice and rats failed to display any of the common coordinated actions of these indices after typical emetic stimulation (resiniferatoxin and vagal afferent stimulation) compared to musk shrews. Overall the results suggest that the inability to vomit is a general property of Rodentia and that an absent brainstem neurological component is the most likely cause. The implications of these findings for the utility of rodents as models in the area of emesis research are discussed. © 2013 Horn et al

Genome-Scale Reconstruction and Analysis of the Pseudomonas putida KT2440 Metabolic Network Facilitates Applications in Biotechnology

A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA) enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, 13C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype–phenotype relationships and provides a sound framework to explore this versatile bacterium and to capitalize on its vast biotechnological potential