Tissue-specific patterns of allelically-skewed DNA methylation

While DNA methylation is usually thought to be symmetrical across both alleles, there are some notable exceptions. Genomic imprinting and X chromosome inactivation are two well-studied sources of allele-specific methylation (ASM), but recent research has indicated a more complex pattern in which genotypic variation can be associated with allelically-skewed DNA methylation in cis. Given the known heterogeneity of DNA methylation across tissues and cell types we explored inter- and intra-individual variation in ASM across several regions of the human brain and whole blood from multiple individuals. Consistent with previous studies, we find widespread ASM with > 4% of the ～220,000 loci interrogated showing evidence of allelically-skewed DNA methylation. We identify ASM flanking known imprinted regions, and show that ASM sites are enriched in DNase I hypersensitivity sites and often located in an extended genomic context of intermediate DNA methylation. We also detect examples of genotype-driven ASM, some of which are tissue-specific. These findings contribute to our understanding of the nature of differential DNA methylation across tissues and have important implications for genetic studies of complex disease. As a resource to the community, ASM patterns across each of the tissues studied are available in a searchable online database: http://epigenetics.essex.ac.uk/ASMBrainBlood.     

BiC2PAM: constraint-guided biclustering for biological data analysis with domain knowledge

Background

Biclustering has been largely used in biological data analysis, enabling the discovery of putative functional modules from omic and network data. Despite the recognized importance of incorporating domain knowledge to guide biclustering and guarantee a focus on relevant and non-trivial biclusters, this possibility has not yet been comprehensively addressed. This results from the fact that the majority of existing algorithms are only able to deliver sub-optimal solutions with restrictive assumptions on the structure, coherency and quality of biclustering solutions, thus preventing the up-front satisfaction of knowledge-driven constraints. Interestingly, in recent years, a clearer understanding of the synergies between pattern mining and biclustering gave rise to a new class of algorithms, termed as pattern-based biclustering algorithms. These algorithms, able to efficiently discover flexible biclustering solutions with optimality guarantees, are thus positioned as good candidates for knowledge incorporation. In this context, this work aims to bridge the current lack of solid views on the use of background knowledge to guide (pattern-based) biclustering tasks.

Methods

This work extends (pattern-based) biclustering algorithms to guarantee the satisfiability of constraints derived from background knowledge and to effectively explore efficiency gains from their incorporation. In this context, we first show the relevance of constraints with succinct, (anti-)monotone and convertible properties for the analysis of expression data and biological networks. We further show how pattern-based biclustering algorithms can be adapted to effectively prune of the search space in the presence of such constraints, as well as be guided in the presence of biological annotations. Relying on these contributions, we propose BiClustering with Constraints using PAttern Mining (BiC2PAM), an extension of BicPAM and BicNET biclustering algorithms.

Results

Experimental results on biological data demonstrate the importance of incorporating knowledge within biclustering to foster efficiency and enable the discovery of non-trivial biclusters with heightened biological relevance.

Conclusions

This work provides the first comprehensive view and sound algorithm for biclustering biological data with constraints derived from user expectations, knowledge repositories and/or literature.

     

Identifying SNP markers tightly associated with six major genes in peach [<Emphasis Type="Italic">Prunus persica</Emphasis> (L.) Batsch] using a high-density SNP array with an objective of marker-assisted selection (MAS)

One of the applications of genomics is to identify genetic markers linked to loci responsible for variation in phenotypic traits, which could be used in breeding programs to select individuals with favorable alleles, particularly at the seedling stage. With this aim, in the framework of the European project FruitBreedomics, we selected five main peach fruit characters and a resistance trait, controlled by major genes with Mendelian inheritance: fruit flesh color Y, fruit skin pubescence G, fruit shape S, sub-acid fruit D, stone adhesion-flesh texture F-M, and resistance to green peach aphid Rm2. They were all previously mapped in Prunus. We then selected three F₁ and three F₂ progenies segregating for these characters and developed genetic maps of the linkage groups including the major genes, using the single nucleotide polymorphism (SNP) genome-wide scans obtained with the International Peach SNP Consortium (IPSC) 9K SNP array v1. We identified SNPs co-segregating with the characters in all cases. Their positions were in agreement with the known positions of the major genes. The number of SNPs linked to each of these, as well as the size of the physical regions encompassing them, varied depending on the maps. As a result, the number of useful SNPs for marker-assisted selection varied accordingly. As a whole, this study establishes a sound basis for further development of MAS on these characters. Additionally, we also discussed some limitations that were observed regarding the SNP array efficiency.     

Low diversity and abundance of root endophytes prevail throughout the life cycle of an annual halophyte

Plants growing in highly saline soils harbor unique communities of fungal root endophytes. We aimed to gain insight into how these communities are established in natural plant populations. We used cultivation-based and molecular approaches to examine root-endophytic colonization in the annual halophyte Salicornia patula at three time points over a 5-month period, from establishment to flowering. At the last sampling, the endophytic community of S. patula was compared to that in the related but perennial halophyte Arthrocnemum macrostachyum. The presence of root endophytes in S. patula was negligible at the first two sampling times, and remained low at the last sampling compared to A. macrostachyum. The latter species showed a well-established endophytic community in its roots that differed from that in S. patula, which was dominated by members of Pleosporales. Although such differences could be partially due to the host lifestyle, the possibility of a strong effect of the substratum could not be excluded. Altogether, our data indicate that the fungal endophytic colonization of roots is a slow process under salt stress. Therefore, we suggest that, in contrast to what is proposed for other systems, endophyte symbioses are unlikely to impact the development of the short-life-cycled S. patula living in these environments.     

Tracking Resilience to Infections by Mapping Disease Space

Infected hosts differ in their responses to pathogens; some hosts are resilient and recover their original health, whereas others follow a divergent path and die. To quantitate these differences, we propose mapping the routes infected individuals take through “disease space.” We find that when plotting physiological parameters against each other, many pairs have hysteretic relationships that identify the current location of the host and predict the future route of the infection. These maps can readily be constructed from experimental longitudinal data, and we provide two methods to generate the maps from the cross-sectional data that is commonly gathered in field trials. We hypothesize that resilient hosts tend to take small loops through disease space, whereas nonresilient individuals take large loops. We support this hypothesis with experimental data in mice infected with Plasmodium chabaudi, finding that dying mice trace a large arc in red blood cells (RBCs) by reticulocyte space as compared to surviving mice. We find that human malaria patients who are heterozygous for sickle cell hemoglobin occupy a small area of RBCs by reticulocyte space, suggesting this approach can be used to distinguish resilience in human populations. This technique should be broadly useful in describing the in-host dynamics of infections in both model hosts and patients at both population and individual levels.     

Spatiotemporal Clustering of Mycobacterium tuberculosis Complex Genotypes in Florida: Genetic Diversity Segregated by Country of Birth

BackgroundTuberculosis (TB) is caused by members of the Mycobacterium tuberculosis complex (MTBC). Although the MTBC is highly clonal, between-strain genetic diversity has been observed. In low TB incidence settings, immigration may facilitate the importation of MTBC strains with a potential to complicate TB control efforts.MethodsWe investigated the genetic diversity and spatiotemporal clustering of 2,510 MTBC strains isolated in Florida, United States, between 2009 and 2013 and genotyped using spoligotyping and 24-locus MIRU-VNTR. We mapped the genetic diversity to the centroid of patient residential zip codes using a geographic information system (GIS). We assessed transmission dynamics and the influence of immigration on genotype clustering using space-time permutation models adjusted for foreign-born population density and county-level HIV risk and multinomial models stratified by country of birth and timing of immigration in SaTScan.Conclusions/SignificanceAlmost five percent of TB cases reported in Florida during 2009–2013 were potentially due to recent transmission. Improvements to TB screening practices among the prison population and recent immigrants are likely to impact TB control. Due to the monomorphic nature of available markers, whole genome sequencing is needed to conclusively delineate recent transmission events between U.S. and foreign-born persons.     

Biochemical Screening of Five Protein Kinases from Plasmodium falciparum against 14,000 Cell-Active Compounds

In 2010 the identities of thousands of anti-Plasmodium compounds were released publicly to facilitate malaria drug development. Understanding these compounds’ mechanisms of action—i.e., the specific molecular targets by which they kill the parasite—would further facilitate the drug development process. Given that kinases are promising anti-malaria targets, we screened ~14,000 cell-active compounds for activity against five different protein kinases. Collections of cell-active compounds from GlaxoSmithKline (the ~13,000-compound Tres Cantos Antimalarial Set, or TCAMS), St. Jude Children’s Research Hospital (260 compounds), and the Medicines for Malaria Venture (the 400-compound Malaria Box) were screened in biochemical assays of Plasmodium falciparum calcium-dependent protein kinases 1 and 4 (CDPK1 and CDPK4), mitogen-associated protein kinase 2 (MAPK2/MAP2), protein kinase 6 (PK6), and protein kinase 7 (PK7). Novel potent inhibitors (IC₅₀ < 1 μM) were discovered for three of the kinases: CDPK1, CDPK4, and PK6. The PK6 inhibitors are the most potent yet discovered for this enzyme and deserve further scrutiny. Additionally, kinome-wide competition assays revealed a compound that inhibits CDPK4 with few effects on ~150 human kinases, and several related compounds that inhibit CDPK1 and CDPK4 yet have limited cytotoxicity to human (HepG2) cells. Our data suggest that inhibiting multiple Plasmodium kinase targets without harming human cells is challenging but feasible.     

Impact of Obstructive Sleep Apnea on the Levels of Placental Growth Factor (PlGF) and Their Value for Predicting Short-Term Adverse Outcomes in Patients with Acute Coronary Syndrome

Background

Placental growth factor (PlGF) induces angiogenesis and promotes tissue repair, and plasma PlGF levels change markedly during acute myocardial infarction (AMI). Currently, the impact of obstructive sleep apnea (OSA) in patients with AMI is a subject of debate. Our objective was to evaluate the relationships between PlGF levels and both the severity of acute coronary syndrome (ACS) and short-term outcomes after ACS in patients with and without OSA.

Methods

A total of 538 consecutive patients (312 OSA patients and 226 controls) admitted for ACS were included in this study. All patients underwent polygraphy in the first 72 hours after hospital admission. The severity of disease and short-term prognoses were evaluated during the hospitalization period. Plasma PlGF levels were measured using an electrochemiluminescence immunoassay.

Results

Patients with OSA were significantly older and more frequently hypertensive and had higher BMIs than those without OSA. After adjusting for age, smoking status, BMI and hypertension, PlGF levels were significantly elevated in patients with OSA compared with patients without OSA (19.9 pg/mL, interquartile range: 16.6–24.5 pg/mL; 18.5 pg/mL, interquartile range: 14.7–22.7 pg/mL; p<0.001), and a higher apnea-hypopnea index (AHI) was associated with higher PlGF concentrations (p<0.003). Patients with higher levels of PlGF had also an increased odds ratio for the presence of 3 or more diseased vessels and for a Killip score>1, even after adjustment.

Conclusions

The results of this study show that in patients with ACS, elevated plasma levels of PlGF are associated with the presence of OSA and with adverse outcomes during short-term follow-up.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01335087","term_id":"NCT01335087"}}NCT01335087