Methylation profiles at birth linked to early childhood obesity.

Childhood obesity represents a significant global health concern and identifying its risk factors is crucial for developing intervention programs. Many "omics" factors associated with the risk of developing obesity have been identified, including genomic, microbiomic, and epigenomic factors. Here, using a sample of 48 infants, we investigated how the methylation profiles in cord blood and placenta at birth were associated with weight outcomes (specifically, conditional weight gain, body mass index, and weight-for-length ratio) at age six months. We characterized genome-wide DNA methylation profiles using the Illumina Infinium MethylationEpic chip, and incorporated information on child and maternal health, and various environmental factors into the analysis. We used regression analysis to identify genes with methylation profiles most predictive of infant weight outcomes, finding a total of 23 relevant genes in cord blood and 10 in placenta. Notably, in cord blood, the methylation profiles of three genes (PLIN4, UBE2F, and PPP1R16B) were associated with all three weight outcomes, which are also associated with weight outcomes in an independent cohort suggesting a strong relationship with weight trajectories in the first six months after birth. Additionally, we developed a Methylation Risk Score (MRS) that could be used to identify children most at risk for developing childhood obesity. While many of the genes identified by our analysis have been associated with weight-related traits (e.g., glucose metabolism, BMI, or hip-to-waist ratio) in previous genome-wide association and variant studies, our analysis implicated several others, whose involvement in the obesity phenotype should be evaluated in future functional investigations.

Methylation profiles at birth linked to early childhood obesity.

Childhood obesity represents a significant global health concern and identifying risk factors is crucial for developing intervention programs. Many 'omics' factors associated with the risk of developing obesity have been identified, including genomic, microbiomic, and epigenomic factors. Here, using a sample of 48 infants, we investigated how the methylation profiles in cord blood and placenta at birth were associated with weight outcomes (specifically, conditional weight gain, body mass index, and weight-for-length ratio) at age six months. We characterized genome-wide DNA methylation profiles using the Illumina Infinium MethylationEpic chip, and incorporated information on child and maternal health, and various environmental factors into the analysis. We used regression analysis to identify genes with methylation profiles most predictive of infant weight outcomes, finding a total of 23 relevant genes in cord blood and 10 in placenta. Notably, in cord blood, the methylation profiles of three genes (PLIN4, UBE2F, and PPP1R16B) were associated with all three weight outcomes, which are also associated with weight outcomes in an independent cohort suggesting a strong relationship with weight trajectories in the first six months after birth. Additionally, we developed a Methylation Risk Score (MRS) that could be used to identify children most at risk for developing childhood obesity. While many of the genes identified by our analysis have been associated with weight-related traits (e.g., glucose metabolism, BMI, or hip-to-waist ratio) in previous genome-wide association and variant studies, our analysis implicated several others, whose involvement in the obesity phenotype should be evaluated in future functional investigations.

Potential implications of shortened rotation length for forest birds, bryophytes, lichens and vascular plants: An example from southern Swedish production forests.

The rotation lengths of intensively managed production forests may be altered to achieve a variety of goals, with correspondingly implications for biodiversity. Here we consider the potential implications of shortened rotation times for biodiversity in planted monocultures of the two most common production tree species in Sweden, Scots pine (Pinus sylvestris) and Norway spruce (Picea abies). To do so we surveyed bird, bryophyte, epiphytic lichen and vascular plant diversity in 80 and 55-year-old stands; stand ages which approximate present-day and potential future rotation lengths in this region respectively. We found clear differences in the species communities of the 55 compared to the 80-year-old stands for both understory species and epiphytes, but not for birds. Nevertheless, bird species richness was still highest in the 80-year-old Norway spruce dominated stands. Dead wood amount was also highest the 80-year-old Norway spruce stands. Highest species richness of epiphytic lichens was found in 80-year-old Scots pine stands. However, 55-year-old Scots pine stands had a higher understory species richness and diversity than the older Scots pine stands, including a larger number of open land species. The 80-year-old forest stands examined may be considered old with respect to production forest rotation lengths in Sweden but are relatively young when comparing stand ages of unmanaged natural forest stands. Nevertheless, our results indicate that shortening the rotation time of Scots pine and Norway spruce, in this part of Sweden from 80 to 55 years, could have important consequences for forest biodiversity. These consequences are primarily inferred from the likely implications from shortened rotations for lichens community composition and diversity in both Norway spruce and Scots pine stands, as well as impacts on understory plant species in Norway spruce stands.

Scalable, accessible, and reproducible reference genome assembly and evaluation in Galaxy.

Improvements in genome sequencing and assembly are enabling high-quality reference genomes for all species. However, the assembly process is still laborious, computationally and technically demanding, lacks standards for reproducibility, and is not readily scalable. Here we present the latest Vertebrate Genomes Project assembly pipeline and demonstrate that it delivers high-quality reference genomes at scale across a set of vertebrate species arising over the last ~500 million years. The pipeline is versatile and combines PacBio HiFi long-reads and Hi-C-based haplotype phasing in a new graph-based paradigm. Standardized quality control is performed automatically to troubleshoot assembly issues and assess biological complexities. We make the pipeline freely accessible through Galaxy, accommodating researchers even without local computational resources and enhanced reproducibility by democratizing the training and assembly process. We demonstrate the flexibility and reliability of the pipeline by assembling reference genomes for 51 vertebrate species from major taxonomic groups (fish, amphibians, reptiles, birds, and mammals).

Galaxy Training: A powerful framework for teaching!

There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis, and stewardship are still rarely taught in life science educational programs, resulting in a skills gap in many of the researchers tasked with analysing these big datasets. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN) has previously developed the Galaxy Training Platform (https://training.galaxyproject.org), an open access, community-driven framework for the collection of FAIR (Findable, Accessible, Interoperable, Reusable) training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform. Since its inception, this training platform has thrived, with the number of tutorials and contributors growing rapidly, and the range of topics extending beyond life sciences to include topics such as climatology, cheminformatics, and machine learning. While initially aimed at supporting researchers directly, the GTN framework has proven to be an invaluable resource for educators as well. We have focused our efforts in recent years on adding increased support for this growing community of instructors. New features have been added to facilitate the use of the materials in a classroom setting, simplifying the contribution flow for new materials, and have added a set of train-the-trainer lessons. Here, we present the latest developments in the GTN project, aimed at facilitating the use of the Galaxy Training materials by educators, and its usage in different learning environments.

RapGreen, an interactive software and web package to explore and analyze phylogenetic trees.

RapGreen is a modular software package targeted at scientists handling large datasets for phylogenetic analysis. Its primary function is the graphical visualization and exploration of large trees. In addition, RapGreen offers a tree pattern search function to seek evolutionary scenarios among large collections of phylogenetic trees. Other functionalities include tree reconciliation with a given species tree: the detection of duplication or loss events during evolution and tree rooting. Last but not least, RapGreen features the ability to integrate heterogeneous data while visualizing and otherwise analyzing phylogenetic trees.

Reproducible and accessible analysis of transposon insertion sequencing in Galaxy for qualitative essentiality analyses.

BACKGROUND: Significant progress has been made in advancing and standardizing tools for human genomic and biomedical research. Yet, the field of next-generation sequencing (NGS) analysis for microorganisms (including multiple pathogens) remains fragmented, lacks accessible and reusable tools, is hindered by local computational resource limitations, and does not offer widely accepted standards. One such "problem areas" is the analysis of Transposon Insertion Sequencing (TIS) data. TIS allows probing of almost the entire genome of a microorganism by introducing random insertions of transposon-derived constructs. The impact of the insertions on the survival and growth under specific conditions provides precise information about genes affecting specific phenotypic characteristics. A wide array of tools has been developed to analyze TIS data. Among the variety of options available, it is often difficult to identify which one can provide a reliable and reproducible analysis. RESULTS: Here we sought to understand the challenges and propose reliable practices for the analysis of TIS experiments. Using data from two recent TIS studies, we have developed a series of workflows that include multiple tools for data de-multiplexing, promoter sequence identification, transposon flank alignment, and read count repartition across the genome. Particular attention was paid to quality control procedures, such as determining the optimal tool parameters for the analysis and removal of contamination. CONCLUSIONS: Our work provides an assessment of the currently available tools for TIS data analysis. It offers ready to use workflows that can be invoked by anyone in the world using our public Galaxy platform ( https://usegalaxy.org ). To lower the entry barriers, we have also developed interactive tutorials explaining details of TIS data analysis procedures at https://bit.ly/gxy-tis .

Using Galaxy to Perform Large-Scale Interactive Data Analyses-An Update.

Modern biology continues to become increasingly computational. Datasets are becoming progressively larger, more complex, and more abundant. The computational savviness necessary to analyze these data creates an ongoing obstacle for experimental biologists. Galaxy (galaxyproject.org) provides access to computational biology tools in a web-based interface. It also provides access to major public biological data repositories, allowing private data to be combined with public datasets. Galaxy is hosted on high-capacity servers worldwide and is accessible for free, with an option to be installed locally. This article demonstrates how to employ Galaxy to perform biologically relevant analyses on publicly available datasets. These protocols use both standard and custom tools, serving as a tutorial and jumping-off point for more intensive and/or more specific analyses using Galaxy. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Finding human coding exons with highest SNP density Basic Protocol 2: Calling peaks for ChIP-seq data Basic Protocol 3: Compare datasets using genomic coordinates Basic Protocol 4: Working with multiple alignments Basic Protocol 5: Single cell RNA-seq.

No more business as usual: Agile and effective responses to emerging pathogen threats require open data and open analytics.

The current state of much of the Wuhan pneumonia virus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) research shows a regrettable lack of data sharing and considerable analytical obfuscation. This impedes global research cooperation, which is essential for tackling public health emergencies and requires unimpeded access to data, analysis tools, and computational infrastructure. Here, we show that community efforts in developing open analytical software tools over the past 10 years, combined with national investments into scientific computational infrastructure, can overcome these deficiencies and provide an accessible platform for tackling global health emergencies in an open and transparent manner. Specifically, we use all SARS-CoV-2 genomic data available in the public domain so far to (1) underscore the importance of access to raw data and (2) demonstrate that existing community efforts in curation and deployment of biomedical software can reliably support rapid, reproducible research during global health crises. All our analyses are fully documented at https://github.com/galaxyproject/SARS-CoV-2.

Community-Driven Data Analysis Training for Biology.

The primary problem with the explosion of biomedical datasets is not the data, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences. This project is accessible at https://training.galaxyproject.org.

Comparison between visual and numerical metrics for the evaluation of patients with Takayasu arteritis with 18F-FDG-PET.

INTRODUCTION: The choice of metrics for defining active Takayasu arteritis (TAK) using fluorine-18-fluorodeoxyglucose (F-FDG)-PET remains controversial. OBJECTIVE: The aim of this study was to compare in the same patients the diagnostic performance for the detection of active TAK of different metrics applied for the quantification of vascular F-FDG uptake with PET. PATIENTS AND METHODS: Overall, 62 PET acquisitions were performed 90 min after F-FDG injection in 15 patients with TAK and analyzed retrospectively. The intensity of vascular F-FDG uptake was graded visually in comparison with the liver signal and with the numerical metrics, including maximum standard uptake value (SUV), maximum target to background ratio (TBR, ratio of SUVmax in the vessel wall and SUVmean of blood), most-diseased segment (MDS)-TBR (average of TBR from all active lesions), and global TBR (average TBR along the aorta and carotid arteries). The gold standard was disease activity identified using the National Institute of Health score for TAK. RESULTS: Using visual analysis, the definition of F-FDG-PET as positive in presence of at least one vascular lesion with a signal more than liver provided the best diagnostic performance for detecting active TAK with a specificity of 98%, a sensitivity of 62% and an accuracy of 89%. Using numerical metrics, SUVmax [SUVmax >3.3; area under the curve (AUC)=0.84] and TBRmax (TBRmax >2.3; AUC=0.84) offered the best diagnostic performance for the detection of active TAK in comparison with MDS-TBR (MDS-TBR>1.7; AUC=0.70) and global TBR (global TBR >1.4; AUC=0.51). CONCLUSION: In this study, we found that the analysis of the vascular region with the highest F-FDG uptake using either visual or numerical metrics provided the best diagnostic performance for the detection of active TAK with PET.

Giant Cell Arteritis-related Stroke: A Retrospective Multicenter Case-control Study.

OBJECTIVE: Our aim was to describe patients with giant cell arteritis (GCA)-related stroke and to compare them with a control group of GCA patients without stroke. METHODS: We created a retrospective multicenter cohort of patients with (1) GCA diagnosed according to the American College of Rheumatology criteria between 1995 and 2015, and (2) stroke occurring at the time of GCA diagnosis or occurring within 4 weeks of starting GCA therapy. The control group consisted of GCA patients without stroke. RESULTS: Forty patients [21 women (53%), median age 78 (60-91) yrs] with GCA-related stroke were included and were compared with 200 control patients. Stroke occurred at GCA diagnosis in 29 patients (73%), whereas it occurred after diagnosis in 11 patients. Vertebrobasilar territory was involved in 29 patients (73%). Seven patients died within a few hours or days following stroke. Compared with the control group, stroke patients had more ophthalmic ischemic symptoms [25 (63%) vs 50 (25%), p < 0.001]. Conversely, they demonstrated lower biological inflammatory variables [C-reactive protein: 61 (28-185) mg/l vs 99 (6-400) mg/l, p = 0.04] and less anemia [22/37 (59%) vs 137/167 (79%), p = 0.03] than patients without stroke. Multivariate logistic regression revealed that the best predictors for the occurrence of stroke were the presence of ophthalmic ischemic symptoms at diagnosis (OR 5, 95% CI 2.14-12.33, p = 0.0002) and the absence of anemia (OR 0.39, 95% CI 0.16-0.99, p = 0.04). CONCLUSION: Stroke, especially in the vertebrobasilar territory, is more likely to occur in patients with GCA who experience recent ophthalmic ischemic symptoms and who exhibit low inflammatory variables.

Positron emission tomography and computed tomography angiography for the diagnosis of giant cell arteritis: A real-life prospective study.

The use of 18F-fluoro-deoxyglucose positron emission tomography scan (FDG-PET) and computed tomography angiography (CTA) to improve accuracy of diagnosis of giant cell arteritis (GCA) is a very important clinical need. We aimed to compare the diagnostic performance of FDG-PET and CTA in patients with GCA.FDG-PET and CTA were acquired in all consecutive patients suspected for GCA. Results of FDG-PET and CTA were compared with the final diagnosis based on clinical judgment, temporal artery biopsy (TAB) findings, and ACR criteria. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for each method.Twenty-four patients suspected for GCA were included. Fifteen (62.5%) were ultimately diagnosed as having GCA. Among them, all fulfilled ACR criteria and 6 had biopsy-proven GCA. Strong FDG uptake in large vessels was found in 10 patients who all had GCA. Mean maximal standard uptake values (SUVmax) per patient measured at all the arterial territories were of 3.7 (range: 2.8-4.7). FDG uptake was negative in 14 patients including 9 and 5 patients without and with GCA, respectively. Mural thickening suggestive of aortitis or branch vessel arteritis was observed on CTA in 11 patients with and 2 patients without GCA. No mural thickening was observed in 11 patients including 7 patients without and 4 patients with GCA. Overall, sensitivity was 66.7% and 73.3%, specificity was 100% and 84.6%, NPV was 64.3% and 64.6%, and PPV was 100% and 84.6% of FDG-PET and CTA, respectively.Both FDG-PET and CTA have a strong diagnostic yield for the diagnosis of GCA. FDG-PET appeared to have a higher PPV as compared to CTA and may be the preferred noninvasive technique to explore patients with suspected GCA.

Extra- and intracranial cerebral vasculitis in giant cell arteritis: an observational study.

Recognizing giant cell arteritis (GCA) in patients with stroke may be challenging. We aimed to highlight the clinical spectrum and long-term follow-up of GCA-specific cerebrovascular accidents. Medical charts of all patients followed in a French Department of Internal Medicine for GCA between January 2008 and January 2014 were retrospectively reviewed. Patients with cerebrovascular accidents at GCA diagnosis were included. Diagnosis of GCA was based on American College of Rheumatology criteria. Transient ischemic attacks and stroke resulting from an atherosclerotic or cardioembolic mechanism were excluded. Clinical features, GCA-diagnosis workup, brain imaging, cerebrospinal fluid (CSF) study, treatment, and follow-up data were analyzed. From January 2008 to January 2014, 97 patients have been followed for GCA. Among them, 8 biopsy-proven GCA patients (mean age 70±7.8 years, M/F sex ratio 3/1) had stroke at GCA diagnosis. Six patients reported headache and visual impairment. Brain MR angiography showed involvement of vertebral and/or basilar arteries in all cases with multiple or unique ischemic lesions in the infratentorial region of the brain in all but one case. Intracranial cerebral arteries involvement was observed in 4 cases including 2 cases with cerebral angiitis. Long lasting lesions on diffusion-weight brain MRI sequences were observed in 1 case. All patients received steroids for a mean of 28.1±12.8 months. Side effects associated with long-term steroid therapy occurred in 6 patients. Relapses occurred in 4 patients and required immunosuppressive drugs in 3 cases. After a mean follow-up duration of 36.4±16.4 months, all but 1 patient achieved complete remission without major sequelae. The conjunction of headache with vertebral and basilar arteries involvement in elderly is highly suggestive of stroke associated with GCA. Intracranial cerebral arteries involvement with cerebral angiitis associated with long lasting brain lesions on diffusion-weight brain MRI sequences may occur in GCA. Both frequent relapses and steroid-induced side effects argue for the use of immunosuppressive agents combined with steroids as first-line therapy.

The banana genome hub.

Banana is one of the world's favorite fruits and one of the most important crops for developing countries. The banana reference genome sequence (Musa acuminata) was recently released. Given the taxonomic position of Musa, the completed genomic sequence has particular comparative value to provide fresh insights about the evolution of the monocotyledons. The study of the banana genome has been enhanced by a number of tools and resources that allows harnessing its sequence. First, we set up essential tools such as a Community Annotation System, phylogenomics resources and metabolic pathways. Then, to support post-genomic efforts, we improved banana existing systems (e.g. web front end, query builder), we integrated available Musa data into generic systems (e.g. markers and genetic maps, synteny blocks), we have made interoperable with the banana hub, other existing systems containing Musa data (e.g. transcriptomics, rice reference genome, workflow manager) and finally, we generated new results from sequence analyses (e.g. SNP and polymorphism analysis). Several uses cases illustrate how the Banana Genome Hub can be used to study gene families. Overall, with this collaborative effort, we discuss the importance of the interoperability toward data integration between existing information systems. Database URL: http://banana-genome.cirad.fr/