Muscle Microdialysis to Investigate Inflammatory Biomarkers in Facioscapulohumeral Muscular Dystrophy

Recent progresses in the understanding of facioscapulohumeral muscular dystrophy (FSHD) genetics opened the way to the development of targeted therapies. However, knowledge about pathophysiology of muscle damage is still limited and there is increasing need to identify biomarkers of disease activity in the perspective of clinical trial readiness.We analyzed inflammatory mediators in the interstitial fluid of muscles with different MRI signal in FSHD patients, comparing muscles displaying early lesions on short-tau inversion recovery (STIR) sequences with normal ones. Patients with one T1-weighted normal and STIR hyperintense (STIR+) and contralateral T1-weighted and STIR normal (STIR-) lower limb muscle were asked to enter the study. Twelve consecutive patients, five controls, and one non-penetrant gene carrier underwent prolonged muscle microdialysis with high cut-off membranes. Microdialysates were analyzed using xMAP technology with a wide panel for cytokines, chemokines, and growth factors. A small number of inflammatory mediators were dysregulated in STIR+ versus STIR- and control muscles: CXCL13, upregulated in STIR+ muscles compared with controls (p < 0.01); CXCL5, downregulated in STIR+ compared with STIR- muscles (p < 0.05); and G-CSF, downregulated in STIR+ muscles compared with controls (p < 0.05). CXCL13 was also upregulated in the STIR+ muscles compared with the contralateral STIR- muscles of the same patient (p < 0.01).These results support the evidence of a selective inflammatory process taking place in STIR+ FSHD muscles. The application of microdialysis could provide insights on novel mechanisms involved in muscle damage in FSHD and in other myopathies. Further studies are needed to validate these investigated molecules as tissue and circulating biomarkers.     

SNP genotyping in melons: genetic variation, population structure, and linkage disequilibrium

Novel sequencing technologies were recently used to generate sequences from multiple melon (Cucumis melo L.) genotypes, enabling the in silico identification of large single nucleotide polymorphism (SNP) collections. In order to optimize the use of these markers, SNP validation and large-scale genotyping are necessary. In this paper, we present the first validated design for a genotyping array with 768 SNPs that are evenly distributed throughout the melon genome. This customized Illumina GoldenGate assay was used to genotype a collection of 74 accessions, representing most of the botanical groups of the species. Of the assayed loci, 91 % were successfully genotyped. The array provided a large number of polymorphic SNPs within and across accessions. This set of SNPs detected high levels of variation in accessions from this crop’s center of origin as well as from several other areas of melon diversification. Allele distribution throughout the genome revealed regions that distinguished between the two main groups of cultivated accessions (inodorus and cantalupensis). Population structure analysis showed a subdivision into five subpopulations, reflecting the history of the crop. A considerably low level of LD was detected, which decayed rapidly within a few kilobases. Our results show that the GoldenGate assay can be used successfully for high-throughput SNP genotyping in melon. Since many of the genotyped accessions are currently being used as the parents of breeding populations in various programs, this set of mapped markers could be used for future mapping and breeding efforts.     

Bleomycin Induces Molecular Changes Directly Relevant to Idiopathic Pulmonary Fibrosis: A Model for “Active” Disease

The preclinical model of bleomycin-induced lung fibrosis, used to investigate mechanisms related to idiopathic pulmonary fibrosis (IPF), has incorrectly predicted efficacy for several candidate compounds suggesting that it may be of limited value. As an attempt to improve the predictive nature of this model, integrative bioinformatic approaches were used to compare molecular alterations in the lungs of bleomycin-treated mice and patients with IPF. Using gene set enrichment analysis we show for the first time that genes differentially expressed during the fibrotic phase of the single challenge bleomycin model were significantly enriched in the expression profiles of IPF patients. The genes that contributed most to the enrichment were largely involved in mitosis, growth factor, and matrix signaling. Interestingly, these same mitotic processes were increased in the expression profiles of fibroblasts isolated from rapidly progressing, but not slowly progressing, IPF patients relative to control subjects. The data also indicated that TGFβ was not the sole mediator responsible for the changes observed in this model since the ALK-5 inhibitor SB525334 effectively attenuated some but not all of the fibrosis associated with this model. Although some would suggest that repetitive bleomycin injuries may more effectively model IPF-like changes, our data do not support this conclusion. Together, these data highlight that a single bleomycin instillation effectively replicates several of the specific pathogenic molecular changes associated with IPF, and may be best used as a model for patients with active disease.     

Morphological variation in tomato: a comprehensive study of quantitative trait loci controlling fruit shape and development

Variation in fruit morphology is a prevalent characteristic among cultivated tomato. The genetic and developmental mechanisms underlying similarities and differences in shape between the fruit of two elongated tomato varieties were investigated. Fruit from two F2 populations constructed from either Solanum lycopersicum cv. Howard German or cv. Banana Legs crossed with S. pimpinellifolium accession LA1589, and one BC1 population constructed with S. lycopersicum Howard German as the recurrent parent, were analysed for shape by using a new software program Tomato Analyzer. Quantitative trait loci (QTLs) controlling 15 individual shape attributes were mapped by both single and multitrait composite interval mapping in each population. In addition, principal components analysis and canonical discriminant analysis were conducted on these shape attributes to determine the greatest sources of variation among and between the populations. Individual principal components and canonical variates were subjected to QTL analysis to map regions of the genome influencing fruit shape in the cultivars. Common and unique regions, as well as previously known and novel QTLs, underlying fruit morphology in tomato were identified. Four major loci were found to control multiple fruit shape traits, principal components, and canonical variates in the populations. In addition, QTLs associated with the principal components better revealed regions of the genome that varied among populations than did the QTL associated with canonical variates. The QTL identified can be compared across additional populations of tomato and other fruit-bearing crop species.     

Functional normalization of 450k methylation array data improves replication in large cancer studies

We propose an extension to quantile normalization that removes unwanted technical variation using control probes. We adapt our algorithm, functional normalization, to the Illumina 450k methylation array and address the open problem of normalizing methylation data with global epigenetic changes, such as human cancers. Using data sets from The Cancer Genome Atlas and a large case–control study, we show that our algorithm outperforms all existing normalization methods with respect to replication of results between experiments, and yields robust results even in the presence of batch effects. Functional normalization can be applied to any microarray platform, provided suitable control probes are available.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0503-2) contains supplementary material, which is available to authorized users.     

Invariant Natural Killer T (iNKT) Cells in HAART-Treated,HIV-Positive Patients with Bone and Cardiovascular Impairment

Background

Invariant Natural Killer T (iNKT) cells represent a determinant in the course of infections and diseases, however, their role in the pathogenesis of non-infectious co-morbidities in HIV-positive patients is unknown.

Methods

Flow cytometry was used to investigate iNKT cell frequency, phenotype and function in HIV-infected patients on HAART with bone and/or cardiovascular disorders and in HIV-positive controls free from co-morbidities.

Results

iNKT cells from subjects with bone and cardiovascular impairment expressed high levels of CD161 and predominantly secreted TNF. iNKT cells from individuals with bone disease alone did not show any distinctive phenotypical or functional characteristics. The functional capacity of iNKT cells in patients with cardiovascular disorder was impaired with no cytokine release upon stimulation.

Conclusion

iNKT cells may have a role in non-infectious co-morbidities in treated HIV disease, possibly through the exacerbation of inflammation. Further studies are needed to investigate iNKT cells in the pathogenesis of non-communicable disorders in HIV infection.     

How old is this mutation? - a study of three Ashkenazi Jewish founder mutations

Background

Several founder mutations leading to increased risk of cancer among Ashkenazi Jewish individuals have been identified, and some estimates of the age of the mutations have been published. A variety of different methods have been used previously to estimate the age of the mutations. Here three datasets containing genotype information near known founder mutations are reanalyzed in order to compare three approaches for estimating the age of a mutation. The methods are: (a) the single marker method used by Risch et al., (1995); (b) the intra-allelic coalescent model known as DMLE, and (c) the Goldgar method proposed in Neuhausen et al. (1996), and modified slightly by our group. The three mutations analyzed were MSH2*1906 G->C, APC*I1307K, and BRCA2*6174delT.

Results

All methods depend on accurate estimates of inter-marker recombination rates. The modified Goldgar method allows for marker mutation as well as recombination, but requires prior estimates of the possible haplotypes carrying the mutation for each individual. It does not incorporate population growth rates. The DMLE method simultaneously estimates the haplotypes with the mutation age, and builds in the population growth rate. The single marker estimates, however, are more sensitive to the recombination rates and are unstable. Mutation age estimates based on DMLE are 16.8 generations for MSH2 (95% credible interval (13, 23)), 106 generations for I1037K (86-129), and 90 generations for 6174delT (71-114).

Conclusions

For recent founder mutations where marker mutations are unlikely to have occurred, both DMLE and the Goldgar method can give good results. Caution is necessary for older mutations, especially if the effective population size may have remained small for a long period of time.