For their stability and detectability faecal microRNAs represent promising molecules with potential clinical interest as non-invasive diagnostic and prognostic biomarkers. However, there is no ...evidence on how stool miRNA profiles change according to an individual's age, sex, and body mass index (BMI) or how lifestyle habits influence the expression levels of these molecules. We explored the relationship between the stool miRNA levels and common traits (sex, age, BMI, and menopausal status) or lifestyle habits (physical activity, smoking status, coffee, and alcohol consumption) as derived by a self-reported questionnaire, using small RNA-sequencing data of samples from 335 healthy subjects. We detected 151 differentially expressed miRNAs associated with one variable and 52 associated with at least two. Differences in miR-638 levels were associated with age, sex, BMI, and smoking status. The highest number of differentially expressed miRNAs was associated with BMI (n = 92) and smoking status (n = 84), with several miRNAs shared between them. Functional enrichment analyses revealed the involvement of the miRNA target genes in pathways coherent with the analysed variables. Our findings suggest that miRNA profiles in stool may reflect common traits and lifestyle habits and should be considered in relation to disease and association studies based on faecal miRNA expression.
Molecular techniques can complement conventional spermiogram analyses to provide new information on the fertilizing potential of spermatozoa and to identify early alterations due to environmental ...pollution.
Here, we present a multilevel molecular profiling by small RNA sequencing and sperm nuclear basic protein analysis of male germ cells from 33 healthy young subjects residing in low and high-polluted areas.
Although sperm motility and sperm concentration were comparable between samples from the two sites, those from the high-pollution area had a higher concentration of immature/immune cells, a lower protamine/histone ratio, a reduced ability of sperm nuclear basic proteins to protect DNA from oxidative damage, and an altered copper/zinc ratio in sperm. Sperm levels of 32 microRNAs involved in intraflagellar transport, oxidative stress response, and spermatogenesis were different between the two areas. In parallel, a decrease of Piwi-interacting RNA levels was observed in samples from the high-polluted area.
This comprehensive analysis provides new insights into pollution-driven epigenetic alterations in sperm not detectable by spermiogram.
Tobacco smoking is known to impact circulating levels of major immune cells populations, but its effect on specific immune cell subsets remains poorly understood. Here, using high-resolution data ...from 223 healthy women (25 current and 198 never smokers), we investigated the association between smoking status and 35,651 immune traits capturing immune cell subset frequencies. Our results confirmed that active tobacco smoking is associated with increased frequencies of circulating CD8+ T cells expressing the CD25 activation marker. Moreover, we identified novel associations between smoking status and relative abundances of CD8+ CD25+ memory T cells, CD8+ memory T cells expressing the CCR4 chemokine receptor, and CD4+CD8+ (double-positive) CD25+ T cells. We also observed, in current smokers, a decrease in the relative frequencies of CD4+ T cells expressing the CD38 activation marker and an increase in class-switched memory B cell isotypes IgA, IgG, and IgE. Finally, using data from 135 former female smokers, we showed that the relative frequencies of immune traits associated with active smoking are usually completely restored after smoking cessation, with the exception of subsets of CD8+ and CD8+ memory T cells, which persist partially altered. Our results are consistent with previous findings and provide further evidence on how tobacco smoking shapes leukocyte cell subsets proportion toward chronic inflammation.
Background
The 8q24 locus is enriched in cancer‐associated polymorphisms and, despite containing relatively few protein‐coding genes, it hosts the MYC oncogene and other genetic elements connected to ...tumorigenesis, including microRNAs (miRNAs). Research on miRNAs may provide insights into the transcriptomic regulation of this multiple cancer‐associated region.
Material and methods
We profiled all miRNAs located in the 8q24 region in 120 colorectal cancer (CRC) patients and 80 controls. miRNA profiling was performed on cancer/non‐malignant adjacent mucosa, stool, and plasma extracellular vesicles (EVs), and the results validated with The Cancer Genome Atlas (TCGA) data. To verify if the 8q24‐annotated miRNAs altered in CRC were dysregulated in other cancers and biofluids, we evaluated their levels in bladder cancer (BC) cases from the TCGA dataset and in urine and plasma EVs from a set of BC cases and healthy controls.
Results
Among the detected mature miRNAs in the region, 12 were altered between CRC and adjacent mucosa (adj. p < 0.05). Five and four miRNAs were confirmed as dysregulated in the CRC and BC TCGA dataset, respectively. A co‐expression analysis of tumor/adjacent tissue data from the CRC group revealed a correlation between the dysregulated miRNAs and CRC‐related genes (PVT1 and MYC) annotated in 8q24 region. miR‐30d‐5p and miR‐151a‐3p, altered in CRC tissue, were also dysregulated in stool of CRC patients and urine of BC cases, respectively. Functional enrichment of dysregulated miRNA target genes highlighted terms related to TP53‐mediated cell cycle control.
Conclusions
Altered expression of 8q24‐annotated miRNAs may be relevant for the initiation and/or progression of cancer.
The work provided new insights into the transcriptomic regulation of the 8q24 locus, a region enriched in multiple cancer‐associated polymorphisms. Among the 54 mature miRNAs in the region, 12 were altered in colorectal cancer tissues with 5 miRNAs validated in TCGA dataset. miR‐30d‐5p and miR‐151a‐3p resulted also dysregulated in stool of CRC patients and urine of bladder cancer cases, highlighting the importance of 8q24‐annotated miRNAs for the initiation and/or progression of cancer.
Trichoderma gamsii T6085 is a promising beneficial isolate whose effects consist of growth inhibition of the main agents causing Fusarium head blight, reduction of mycotoxin accumulation, competition ...for wheat debris, and reduction of the disease in both the lab and the field. Here, we present the first genome assembly of a T. gamsii isolate, providing a useful platform for the scientific community.
Trichoderma harzianum T6776 is a promising beneficial isolate whose effects consist of growth promotion, positive response of photosynthetic activity, hormonal signaling, and carbon partitioning in ...tomato, coupled with biocontrol of plant pathogens. Here, we present the first genome assembly of T6776, providing a useful platform for the scientific community.
MethylFASTQ: A Tool Simulating Bisulfite Sequencing Data Piaggeschi, Giulia; Licheri, Nicola; Romano, Greta ...
2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP),
2019-Feb.
Conference Proceeding
Odprti dostop
DNA methylation is a DNA modification playing an important role in several diseases, including cancer. The gold-standard technique for measuring DNA methylation is Bisulfite Sequencing (BS). The ...treatment with bisulfite alters the sequence of DNA making the analysis of BS data computationally difficult. There are many tools for analysing BS data but the choice of which to use is difficult due to the extensive biological and technical variability of the data. Synthetic and real datasets can be exploited to evaluate the tool performance and to obtain an accurate data analysis. Today, Sherman is the only available tool to generate BS synthetic datasets. However, this tool does not report any information about the methylated cytosines. For this purpose, in this paper we present MethyIFASTQ, an easy-to-use bioinformatics tool that generates synthetic bisulfite datasets in FASTQ format. MethylFASTQ works in parallel manner using producer-consumer approach. It returns: i) a complete dataset in FASTQ format simulating the results of a BS experiment ii) a report file storing the information about the methylation level of the dataset (i.e. methylated cytosines). First, we test MethylFASTQ performances with an increasing number of concurrent processes and we report the comparison of MethylFASTQ with respect to Sherman tool. Then, we also describe an application of synthetic datasets generated with our tool and we use them as input for two bisulfite mapping and methylation calling tools. Finally, we propose MethylFASTQ as a tool to generate synthetic bisulfite sequencing data.
Nowadays, next generation sequencing is closer to clinical application in the field of oncology. Indeed, it allows the identification of tumor-specific mutations acquired during cancer development, ...progression and resistance to therapy. In parallel with an evolving sequencing technology, novel computational approaches are needed to cope with the requirement of a rapid processing of sequencing data into a list of clinically-relevant genomic variants. Since sequencing data from both tumors and their matched normal samples are not always available (unmatched data), there is a need of a computational pipeline leading to variants calling in unmatched data. Despite the presence of many accurate and precise variant calling algorithms, an efficient approach is still lacking. Here, we propose a parallel pipeline (ParallNormal) designed to efficiently identify genomic variants from whole- exome sequencing data, in absence of their matched normal. ParallNormal integrates well-known algorithms such as BWA and GATK, a novel tool for duplicate removal (DuplicateRemove), and the FreeBayes variant calling algorithm. A re-engineered implementation of FreeBayes, optimized for execution on modern multi-core architectures is also proposed. ParallNormal was applied on whole-exome sequencing data of pancreatic cancer samples without considering their matched normal. The robustness of ParallNormal was tested using results of the same dataset analyzed using matched normal samples and considering genes involved in pancreatic carcinogenesis. Our pipeline was able to confirm most of the variants identified using matched normal data.
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