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The ITS2 Database
(2012)
The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation.
The ITS2 Database presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank accurately reannotated. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold.
The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE and ProfDistS for multiple sequence-structure alignment calculation and Neighbor Joining tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure.
In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.
Obsessive compulsive disorder (OCD) and attention deficit hyperactivity disorder (ADHD) are two of the most common neuropsychiatric diseases in paediatric populations. The high comorbidity of ADHD and OCD with each other, especially of ADHD in paediatric OCD, is well described. OCD and ADHD often follow a chronic course with persistent rates of at least 40–50 %. Family studies showed high heritability in ADHD and OCD, and some genetic findings showed similar variants for both disorders of the same pathogenetic mechanisms, whereas other genetic findings may differentiate between ADHD and OCD. Neuropsychological and neuroimaging studies suggest that partly similar executive functions are affected in both disorders. The deficits in the corresponding brain networks may be responsible for the perseverative, compulsive symptoms in OCD but also for the disinhibited and impulsive symptoms characterizing ADHD. This article reviews the current literature of neuroimaging, neurochemical circuitry, neuropsychological and genetic findings considering similarities as well as differences between OCD and ADHD.
The risk of Parkinson's disease increases with age. However, the etiology of the illness remains obscure. It appears highly likely that the neurodegenerative processes involve an array of elements that influence each other. In addition, genetic, endogenous, or exogenous toxins need to be considered as viable partners to the cellular degeneration. There is compelling evidence that indicate the key involvement of modified α-synuclein (Lewy bodies) at the very core of the pathogenesis of the disease. The accumulation of misfolded α-synuclein may be a consequence of some genetic defect or/and a failure of the protein clearance system. Importantly, α-synuclein pathology appears to be a common denominator for many cellular deleterious events such as oxidative stress, mitochondrial dysfunction, dopamine synaptic dysregulation, iron dyshomeostasis, and neuroinflammation. These factors probably employ a common apoptotic/or autophagic route in the final stages to execute cell death. The misfolded α-synuclein inclusions skillfully trigger or navigate these processes and thus amplify the dopamine neuron fatalities. Although the process of neuroinflammation may represent a secondary event, nevertheless, it executes a fundamental role in neurodegeneration. Some viral infections produce parkinsonism and exhibit similar characteristic neuropathological changes such as a modest brain dopamine deficit and α-synuclein pathology. Thus, viral infections may heighten the risk of developing PD. Alternatively, α-synuclein pathology may induce a dysfunctional immune system. Thus, sporadic Parkinson's disease is caused by multifactorial trigger factors and metabolic disturbances, which need to be considered for the development of potential drugs in the disorder.
Questions: What are the relative contributions of kin selection and individual selection to the evolution of dispersal rates in fragmented landscapes? How do environmental parameters influence the relative contributions of both evolutionary forces? Features of the model: Individual-based simulation model of a metapopulation. Logistic local growth dynamics and density-dependent dispersal. An optional shuffling algorithm allows the continuous destruction of any genetic structure in the metapopulation. Ranges of key variables: Depending on dispersal mortality (0.05-0.4) and the strength of environmental fluctuations, mean dispersal probability varied between 0.05 and 0.5. Conclusions: For local population sizes of 100 individuals, kin selection alone could account for dispersal probabilities of up to 0.1. It may result in a ten-fold increase of optimal dispersal rates compared with those predicted on the basis of individual selection alone. Such a substantial contribution of kin selection to dispersal is restricted to cases where the overall dispersal probabilities are small (textless 0.1). In the latter case, as much as 30% of the total fitness of dispersing individuals could arise from the increased reproduction of kin left in the natal patch.