Patterns of positive selection in six Mammalian genomes

Genome-wide scans for positively selected genes (PSGs) in mammals have provided insight into the dynamics of genome evolution, the genetic basis of differences between species, and the functions of individual genes. However, previous scans have been limited in power and accuracy owing to small numbers of available genomes. Here we present the most comprehensive examination of mammalian PSGs to date, using the six high-coverage genome assemblies now available for eutherian mammals. The increased phylogenetic depth of this dataset results in substantially improved statistical power, and permits several new lineage- and clade-specific tests to be applied. Of approximately 16,500 human genes with high-confidence orthologs in at least two other species, 400 genes showed significant evidence of positive selection (FDR<0.05), according to a standard likelihood ratio test. An additional 144 genes showed evidence of positive selection on particular lineages or clades. As in previous studies, the identified PSGs were enriched for roles in defense/immunity, chemosensory perception, and reproduction, but enrichments were also evident for more specific functions, such as complement-mediated immunity and taste perception. Several pathways were strongly enriched for PSGs, suggesting possible co-evolution of interacting genes. A novel Bayesian analysis of the possible "selection histories" of each gene indicated that most PSGs have switched multiple times between positive selection and nonselection, suggesting that positive selection is often episodic. A detailed analysis of Affymetrix exon array data indicated that PSGs are expressed at significantly lower levels, and in a more tissue-specific manner, than non-PSGs. Genes that are specifically expressed in the spleen, testes, liver, and breast are significantly enriched for PSGs, but no evidence was found for an enrichment for PSGs among brain-specific genes. This study provides additional evidence for widespread positive selection in mammalian evolution and new genome-wide insights into the functional implications of positive selection.     

Individual mRNA expression profiles reveal the effects of specific microRNAs

Background  

MicroRNAs (miRNAs) are oligoribonucleotides with an important role in regulation of gene expression at the level of translation. Despite imperfect target complementarity, they can also significantly reduce mRNA levels. The validity of miRNA target gene predictions is difficult to assess at the protein level. We sought, therefore, to determine whether a general lowering of predicted target gene mRNA expression by endogenous miRNAs was detectable within microarray gene expression profiles.     

Demographically-Based Evaluation of Genomic Regions under Selection in Domestic Dogs

Controlling for background demographic effects is important for accurately identifying loci that have recently undergone positive selection. To date, the effects of demography have not yet been explicitly considered when identifying loci under selection during dog domestication. To investigate positive selection on the dog lineage early in the domestication, we examined patterns of polymorphism in six canid genomes that were previously used to infer a demographic model of dog domestication. Using an inferred demographic model, we computed false discovery rates (FDR) and identified 349 outlier regions consistent with positive selection at a low FDR. The signals in the top 100 regions were frequently centered on candidate genes related to brain function and behavior, including LHFPL3, CADM2, GRIK3, SH3GL2, MBP, PDE7B, NTAN1, and GLRA1. These regions contained significant enrichments in behavioral ontology categories. The 3^rd top hit, CCRN4L, plays a major role in lipid metabolism, that is supported by additional metabolism related candidates revealed in our scan, including SCP2D1 and PDXC1. Comparing our method to an empirical outlier approach that does not directly account for demography, we found only modest overlaps between the two methods, with 60% of empirical outliers having no overlap with our demography-based outlier detection approach. Demography-aware approaches have lower-rates of false discovery. Our top candidates for selection, in addition to expanding the set of neurobehavioral candidate genes, include genes related to lipid metabolism, suggesting a dietary target of selection that was important during the period when proto-dogs hunted and fed alongside hunter-gatherers.     

The effect of estrogen on muscle damage biomarkers following prolonged aerobic exercise in eumenorrheic women

This study assessed the influence of estrogen (E₂) on muscle damage biomarkers [skeletal muscle - creatine kinase (CK); cardiac muscle - CK-MB] responses to prolonged aerobic exercise. Eumenorrheic women (n=10) who were physically active completed two 60-minute treadmill running sessions at ∼60-65% maximal intensity during low E₂ (midfollicular menstrual phase) and high E₂ (midluteal menstrual phase) hormonal conditions. Blood samples were collected prior to exercise (following supine rest), immediately post-, 30 min post-, and 24 hours post-exercise to determine changes in muscle biomarkers. Resting blood samples confirmed appropriate E₂ hormonal levels Total CK concentrations increased following exercise and at 24 hours post-exercise were higher in the midfollicular low E₂ phase (p<0.001). However, CK-MB concentrations were unaffected by E₂ level or exercise (p=0.442) resulting in the ratio of CK-MB to total CK being consistently low in subject responses (i.e., indicative of skeletal muscle damage). Elevated E₂ levels reduce the CK responses of skeletal muscle, but had no effect on CK-MB responses following prolonged aerobic exercise. These findings support earlier work showing elevated E₂ is protective of skeletal muscle from exercise-induced damage associated with prolonged aerobic exercise.     

In silico single strand melting curve: a new approach to identify nucleic acid polymorphisms in Totiviridae

Background

The PCR technique and its variations have been increasingly used in the clinical laboratory and recent advances in this field generated new higher resolution techniques based on nucleic acid denaturation dynamics. The principle of these new molecular tools is based on the comparison of melting profiles, after denaturation of a DNA double strand. Until now, the secondary structure of single-stranded nucleic acids has not been exploited to develop identification systems based on PCR. To test the potential of single-strand RNA denaturation as a new alternative to detect specific nucleic acid variations, sequences from viruses of the Totiviridae family were compared using a new in silico melting curve approach. This family comprises double-stranded RNA virus, with a genome constituted by two ORFs, ORF1 and ORF2, which encodes the capsid/RNA binding proteins and an RNA-dependent RNA polymerase (RdRp), respectively.

Results

A phylogenetic tree based on RdRp amino acid sequences was constructed, and eight monophyletic groups were defined. Alignments of RdRp RNA sequences from each group were screened to identify RNA regions with conserved secondary structure. One region in the second half of ORF2 was identified and individually modeled using the RNAfold tool. Afterwards, each DNA or RNA sequence was denatured in silico using the softwares MELTSIM and RNAheat that generate melting curves considering the denaturation of a double stranded DNA and single stranded RNA, respectively. The same groups identified in the RdRp phylogenetic tree were retrieved by a clustering analysis of the melting curves data obtained from RNAheat. Moreover, the same approach was used to successfully discriminate different variants of Trichomonas vaginalis virus, which was not possible by the visual comparison of the double stranded melting curves generated by MELTSIM.

Conclusion

In silico analysis indicate that ssRNA melting curves are more informative than dsDNA melting curves. Furthermore, conserved RNA structures may be determined from analysis of individuals that are phylogenetically related, and these regions may be used to support the reconstitution of their phylogenetic groups. These findings are a robust basis for the development of in vitro systems to ssRNA melting curves detection.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-243) contains supplementary material, which is available to authorized users.     

Are biologics more effective than classical disease-modifying antirheumatic drugs?

Major achievements have been reached in the treatment of rheumatoid arthritis during past decades due to the recognition of methotrexate as an anchor drug for treatment of rheumatoid arthritis, due to the notion of a treatment window of opportunity in patients with recent-onset rheumatoid arthritis necessitating early aggressive therapy, due to the development of biologics and due to remission as a treatment target. Most biologics have a much faster onset of action than synthetic disease-modifying anti-rheumatic drugs, but presently there is no convincing evidence that biologic drugs have a superior clinical efficacy in comparison with the synthetic drugs. Biologics are, however, accompanied by less radiological deterioration.     

CD14 C-159T and early infection with Pseudomonas aeruginosa in children with cystic fibrosis

Early acquisition of Pseudomonas aeruginosa is associated with a poorer prognosis in patients with cystic fibrosis. We investigated whether polymorphisms in CD14, the lipopolysaccharide receptor, increase the risk of early infection. Forty-five children with cystic fibrosis were investigated with annual bronchoalveolar lavage (BAL) and plasma sCD14 levels. Plasma sCD14 levels were significantly lower in children from whom P.aeruginosa was subsequently isolated (492.75 μg/ml vs. 1339.43 μg/ml, p = 0.018). Those with the CD14 -159CC genotype had a significantly increased risk of early infection with P.aeruginosa suggesting that CD14 C-159T plays a role in determining the risk of early infection with P.aeruginosa.     

Myocardial dysfunction in rheumatoid arthritis: epidemiology and pathogenesis

Data from population- and clinic-based epidemiologic studies of rheumatoid arthritis patients suggest that individuals with rheumatoid arthritis are at risk for developing clinically evident congestive heart failure. Many established risk factors for congestive heart failure are over-represented in rheumatoid arthritis and likely account for some of the increased risk observed. In particular, data from animal models of cytokine-induced congestive heart failure have implicated the same inflammatory cytokines produced in abundance by rheumatoid synovium as the driving force behind maladaptive processes in the myocardium leading to congestive heart failure. At present, however, the direct effects of inflammatory cytokines (and rheumatoid arthritis therapies) on the myocardia of rheumatoid arthritis patients are incompletely understood.