Biology subjects

Ghanbari, M.

Publications and source records attributed to Ghanbari, M..

9 recordsLinked to original sources

bioRxiv2026

Bundling Alleles Within Haplotype Blocks Improves QTL Detection Under Allelic Heterogeneity

Allelic heterogeneity is a term from genetics which means that alleles that differ in primary sequence can have a similar phenotypic outcome. In other words, they are functional equivalents, and they naturally appear through convergent evolution under selection. Current GWAS has trouble detecting these instances, as allelic heterogeneity leads to signal dilution in these analyses, often leading to a LOD score that stays below detection thresholds. In this paper, we show a method that can overcome this problem by bundling haplotypes into Artificial Combined Markers. The created marker matrix can then easily be used in existing GWAS software.

genetics↗

bioRxiv2026

Development of a microRNA clock for gestational age in the general population

IntroductionDNA methylation (DNAm) has shown promise as a biological marker of gestational age (GA). Here, we aimed to characterize how plasma circulating miRNAs - another epigenetic mechanism regulating gene expression - associate with GA at birth, and to construct a miRNA-based GA clock (miRClock-GA). MethodsWe leveraged 2083 umbilical cord plasma-derived circulating miRNAs from Generation R (N=1695). First, we performed linear regressions to identify miRNome-wide significant miRNAs associated with GA. Second, we applied elastic net regression to construct miRClock-GA. These steps were validated in Gen3G (N=213). Finally, we computed age acceleration (miRClock-AA) and evaluated association of miRClock-GA and miRClock-AA with child developmental outcomes up to 17 years of age, including comparisons with DNAmClocks. FindingsWe identified 123 miRNAs associated with GA, with miR-150-5p showing the strongest positive association ( B=0.244, SE=0.036, P=2.3e-11) and miR-373-3p the strongest negative association ( B=-0.255, SE=0.065, P=8.6e-5). MiRClock-GA correlated consistently with GA in Generation R train (rrange=0.62-0.72) and test sets (rrange=0.45-0.52) and in the independent validation cohort (rGen3G =0.33). Correlations between miRClock-GA and DNAmClocks were weak to moderate (rrange=0.28-0.42). MiRClock-AA explained significant variance in birthweight and childhood BMI beyond clinical GA. ConclusionsThis study reveals widespread associations between circulating miRNAs and GA, supports miRClock-GA as a consistent, well-performing biological marker of GA, with miRClock-AA predicting birthweight and childhood BMI beyond GA itself. Our findings provide a broader perspective on the potential utility of miRNAs as early markers of development. FundingE.U. Horizon Europe Research and Innovation Programme (FAMILY,No.101057529); European Research Council (TEMPO,No.101039672). Full funding in Acknowledgements. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSEpigenetic clocks have emerged as powerful tools for assessing individual differences in biological ageing. Existing epigenetic clocks are typically constructed using DNA methylation (DNAm) data and are developed to estimate whether an individuals epigenetic age deviates relative to their chronological age. In adults, higher predicted biological epigenetic age than chronological age (accelerated epigenetic ageing) is an established indicator of mortality risk and other age-related morbidities. MicroRNAs are another epigenetic mechanism associated with chronological age and age-related phenotypes across species such as C. elegans, mice, primates and humans. Recently, a plasma-derived, cell-free circulating miRNA clock was developed in a sample of older European adults, with accelerated miRNA age predicting biological age-related conditions such as frailty and multi-system blood biomarkers. However, miRNA-based estimations of biological gestational age at birth have not been previously done and their relationship to child health outcomes are unknown. Added value of this studyTo gain a broader perspective on the role of epigenetic markers in biological gestational age at birth and the potential utility of miRNAs as early markers of (altered) development, we leveraged cord blood plasma circulating miRNA data collected at birth in a large population-based cohort. First, we identified 123 miRNAs associated with gestational age. Second, we used this information to construct a miRNA-based epigenetic clock for gestational age (miRClock-GA) and validated this clock in an independent cohort. MiRClock-GA showed moderate correlations with both gestational age and existing DNAm-based gestational clocks. Third, we found that miRClock-GA correlated cross-sectionally with birthweight, as well as prospectively with several adaptive, behavioural, cognitive, and growth outcomes measured up to age 17y, after taking into account maternal influences such as maternal education level, smoking, pre-pregnancy BMI, and age. Accelerated ageing of miRClock-GA (miRClock-AA) explained variance in birthweight and childhood BMI beyond clinical GA, after accounting for maternal influences. Implications of all available evidenceOur study provides the first large-scale evidence that circulating miRNAs in cord blood plasma show widespread associations with gestational age at birth and can be used to derive a robust biological marker of GA (MiRClock-GA), which explains a substantial proportion of the variation in clinical GA. MiRClock-AA provides information beyond GA in some child outcomes, such as BMI. These findings extend adult research, supporting the potential of miRNAs as promising markers for early risk assessment and health monitoring in a developmental context.

genomics↗

bioRxiv2021

Computational Mapping of the Human-SARS-CoV-2 Protein-RNA Interactome

Strong evidence suggests that human human RNA-binding proteins (RBPs) are critical factors for viral infection, yet there is no feasible experimental approach to map exact binding sites of RBPs across the SARS-CoV-2 genome systematically at a large scale. We investigated the role of RBPs in the context of SARS-CoV-2 by constructing the first in silico map of human RBP / viral RNA interactions at nucleotide-resolution using two deep learning methods (pysster and DeepRiPe) trained on data from CLIP-seq experiments. We evaluated conservation of RBP binding between 6 other human pathogenic coronaviruses and identified sites of conserved and differential binding in the UTRs of SARS-CoV-1, SARS-CoV-2 and MERS. We scored the impact of variants from 11 viral strains on protein-RNA interaction, identifying a set of gain-and loss of binding events. Lastly, we linked RBPs to functional data and OMICs from other studies, and identified MBNL1, FTO and FXR2 as potential clinical biomarkers. Our results contribute towards a deeper understanding of how viruses hijack host cellular pathways and are available through a comprehensive online resource (https://sc2rbpmap.helmholtz-muenchen.de).

bioinformatics↗

bioRxiv2019

Characterization of the gut microbiota in the Anjak (Schizocypris altidorsalis), a native fish species of Iran

The antiquity, diversity and dietary variations among fish species present an exceptional opportunity for understanding the variety and nature of symbioses in vertebrate gut microbial communities. In this study for the first time the composition of the gut bacterial communities in the anjak was surveyed by 16S rRNA gene 454-pyrosequencing. Anjak (Schizocypris altidorsalis), is a native benthopelagic and commercially important fish species in Hamun Lake and Hirmand River system in Sistan basin, Iran. Thirteen 16S rRNA PCR libraries were generated, representing 13 samples of Anjak gut microbiota. After quality filtering, a total of 137 978 read pairs remained from the V3-V6 16S rRNA gene regions, each measuring 680 bp, and were assigned to bacterial OTUs at a minimum sequence homology of 97%, resulted in total 608 OTUs. The results provided evidence of the presence of a very diverse microbial community present in this fish. The majority of sequences belonged to members of the Firmicutes; however, members of the Proteobacteria, Tenericutes, Bacteroidetes and Cyanobacteria were also well represented in the anjak gut microbiota. The most abundant classes recorded in the samples were uncultured CK-1C4-19 class of Tenericutes, Flavobacteriia, -Proteobacteria, Erysipelotrichi, Synechococcophycideae, {gamma}-Proteobacteria, and Clostridia. The presence of many different types of bacteria in the anjak is not unexpected since it has been shown that eukaryotes with a detritivorous and planktivorous diet have a higher microbial diversity compared to omnivorous and herbivorous fish species. Many of these microbes might be of high physiological relevance for snow trout and may play key roles in the functioning of a healthy gut in this fish.

microbiology↗

bioRxiv2019

Exploring the microbial diversity in oil-contaminated mangrove sediments using 16S rRNA metagenomics

With an area of 390 hectares, the mangrove forests of Nayband Bay are the widest mangrove communities above 27 degrees latitude in the Persian Gulf. They are the last dense, extensive structures of these ecosystems found in the north-west Indian Ocean. Growing industrial activities near the Nayband Bay and the consequent marine pollution has resulted in damage and threatened different marine habitats in recent years. To date, a comprehensive description of the microbial life in the mangrove ecosystem that has been exposed to oil contamination is lacking. This information could significantly contribute to a better overview of the function and resilience of the ecosystem. This work represents a first effort to better understand the Nayband Bay mangrove microbiology by applying 16S rRNA metagenomics. A total of 65,408 readings from the V3-V4 16S rRNA gene regions were obtained from 24 sediment samples, each measuring 440 bp. Most sequences belonged to members of the Proteobacteria phylum (mainly {gamma}-Proteobacteria); however, members of the Bacteroidetes phylum (mainly Flavobacteriia) were also well represented in the samples. We discovered that the community of this ecosystem strongly exhibit typical structures of oil-contaminated marine environments. This is likely due to the growing industrial activity in the area and its consequent marine polluting effects. The use of practicable and applicable bioremediation protocols for habitat restoration in this valuable area is needed.

microbiology↗

bioRxiv2019

A prospective role for the rumen in generating antibiotic resistance

Antibiotics were a revolutionary discovery of the 20th century, but the ability of bacteria to spread the genetic determinants of resistance via horizontal gene transfer (HGT) has quickly endangered their use1. Indeed, there is a global network of microbial gene exchange, the analysis of which has revealed particularly frequent transfer of resistance determinants between farm animals and human-associated bacteria2. Here, we leverage the recent release of a rumen microbial genome reference set and show that the wide-spread resistance gene cluster aadE-sat4-aphA-3 is harboured in ruminal Bacteroidetes. While this cluster appears to have been recently transferred between commensal bacteria in the rumen and many diverse animal and human pathogens, comparative analysis suggests that the cluster stabilized in the pathogens. Then, focusing on streptomycin resistance, it was found that homologues from the rumen span much of the known diversity of aminoglycoside O-nucleotidyltransferases (AadEs) and that distinct variants of the enzyme are present in a single rumen bacterial genome. Notably, a second variant of AadE has also been recently transferred, albeit more often as a single gene, throughout a different set of animal and human associated bacteria. By examining the synteny of AadE orthologues in various bacterial genomes and analyzing corresponding gene trees in an environmental context, we speculate that the ruminant associated microbiome has a salient role in the emergence of specific resistance variants and clusters. In light of the recent literature on the evolutionary origin of antibiotic resistance, we further suggest that the rumen provides a possible route of dissemination of resistance genes from soil resistomes, throughout the farm, and to human pathogens3.

microbiology↗

bioRxiv2019

Deep neural networks for interpreting RNA binding protein target preferences

Deep learning has become a powerful paradigm to analyze the binding sites of regulatory factors including RNA-binding proteins (RBPs), owing to its strength to learn complex features from possibly multiple sources of raw data. However, the interpretability of these models, which is crucial to improve our understanding of RBP binding preferences and functions, has not yet been investigated in significant detail. We have designed a multitask and multimodal deep neural network for characterizing in vivo RBP binding preferences. The model incorporates not only the sequence but also the region type of the binding sites as input, which helps the model to boost the prediction performance. To interpret the model, we quantified the contribution of the input features to the predictive score of each RBP. Learning across multiple RBPs at once, we are able to avoid experimental biases and to identify the RNA sequence motifs and transcript context patterns that are the most important for the predictions of each individual RBP. Our findings are consistent with known motifs and binding behaviors of RBPs and can provide new insights about the regulatory functions of RBPs.

bioinformatics↗

bioRxiv2018

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

We conducted genome-wide association study (GWAS) meta-analyses of relative caloric intake from fat, protein, carbohydrates and sugar in over 235,000 individuals. We identified 21 approximately independent lead SNPs. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg {approx} 0.15 - 0.5). Relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood poverty (|rg| {approx} 0.1 - 0.3). Overall, our results show that the relative intake of each macronutrient has a distinct genetic architecture and pattern of genetic correlations suggestive of health implications beyond caloric content.

genetics↗

bioRxiv2018

Deciphering human ribonucleoprotein regulatory networks

RNA-binding proteins (RBPs) control and coordinate each stage in the life cycle of RNAs. Although in vivo binding sites of RBPs can now be determined genome-wide, most studies typically focused on individual RBPs. Here, we examined a large compendium of 114 high-quality transcriptome-wide in vivo RBP-RNA cross-linking interaction datasets generated by the same protocol in the same cell line and representing 64 distinct RBPs. Comparative analysis of categories of target RNA binding preference, sequence preference, and transcript region specificity was performed, and identified potential posttranscriptional regulatory modules, i.e. specific combinations of RBPs that bind to specific sets of RNAs and targeted regions. These regulatory modules encoded functionally related proteins and exhibited distinct differences in RNA metabolism, expression variance, as well as subcellular localization. This integrative investigation of experimental RBP-RNA interaction evidence and RBP regulatory function in a human cell line will be a valuable resource for understanding the complexity of post-transcriptional regulation.

genomics↗