Despite the availability of batch effect correcting algorithms (BECA), no comprehensive tool that combines batch correction and evaluation of the results exists for microbiome datasets. This work outlines the Microbiome Batch Effects Correction Suite development that integrates several BECAs and evaluation metrics into a software package for the statistical computation framework R.

Background/Objectives: The prevalence of food allergy (FA) in children is increasing. Dysbiosis of the microbiome has been linked to FA but needs to be better understood. We aimed to characterize the gut and skin microbiome of young food-allergic children over time and within different types of immunoglobulin E (IgE)-mediated FA. Methods: We studied 23 patients, as a pilot study of an ongoing prospective multicenter cohort study including children < 2y with newly diagnosed IgE-mediated FA. Samples (feces/skin swabs) were collected at enrollment and at 1-year follow-up and sequenced for the bacterial 16S rRNA gene (hypervariable v1–v2 region). Results: Gut and skin bacterial diversity was significantly higher in patients compared with controls and increased over time (beta test, Shannon diversity, p < 0.01). Within different types of IgE-mediated FA, bacterial diversity was similar. Community composition differed significantly over time and within IgE-mediated FA types (PERMANOVA: p < 0.01). Several significantly different genus abundances were revealed. We observed a positive correlation between high total IgE and a high abundance of the genus Collinsella in patients with a higher number of allergies/sensitizations (≥3), and patients with tree nut and/or peanut allergy. Conclusions: This study revealed an increased bacterial diversity in children with FA compared with non-atopic children. Importantly, the gut and skin microbiome differed in their composition over time and within different types of IgE-mediated FA. These findings contribute to the understanding of microbiome changes in children with FA and indicate the potential of the genus Collinsella as a biomarker for tree nut and/or peanut allergy and possibly for allergy persistence.

Reference data on genomic variation forms the basis of genetics research. Limitations in identifying genetic variation from single reference sequences have recently been addressed through improvements in sequencing technologies, allowing the generation of pangenomic references from multiple accurate chromosome-level de novo assemblies. Nevertheless, global pangenomes to date have yet to include genomes from the populations of the Middle Eastern Region. To address this shortcoming, this study provides an Emirati genome reference. Its core is a diploid assembly with a Quality Value (QV) of 60 that includes ten telomere-to-telomere chromosomes. This assembly is incorporated into a pangenome graph constructed of 52 additional high-quality assemblies, half of which are trio-based. This Emirati pangenome reveals a similar level of genomic variation as the one compiled by the Human Pangenome Reference Consortium, underscoring its utility for the identification of both global and population-centered genomic variation, even in genome regions that have been traditionally challenging to assemble but are covered by the Emirati telomere-to-telomere assembly. As such, the Emirati genome reference significantly contributes to genomic research globally and is an essential resource for genomics-based personalized medicine in the United Arab Emirates and other parts of the Middle East.

Reference data on genomic variation form the basis of genetic research. Limitations in identifying genetic variation from single reference sequences have been recently overcome, as improvements in sequencing technologies have allowed the generation of pangenomic references from multiple accurate, chromosome-level de novo assemblies. Here, we present a comprehensive Emirati telomere-to-telomere (T2T) pangenome generated from 58 individuals, comprising 28 trio-based and 30 single-sample assemblies. The resulting 116 haplotype-resolved assemblies demonstrate high contiguity, with a median continuity of 150 Mb and a median quality value (QV) of 59, achieving T2T-level scaffold status for 71.9% of chromosomes. These assemblies form the foundation of the Emirati T2T pangenome graph. The graph reveals levels of genomic diversity comparable to those reported by the Human Pangenome Reference Consortium, while also capturing regionally enriched and difficult-to-assemble variation, uniquely accessible through the Emirati T2T assemblies. This reference makes a valuable global contribution to human pangenomics and serves as a critical resource for advancing precision medicine in the United Arab Emirates.

Reference genomes are essential for identifying and representing human genomic variation, yet single-genome sequences fail to capture population-specific diversity. We present the Emirati pangenome comprising a trio-based, diploid chromosome-level assembly from deep, multi-platform sequencing data and 57 additional high-quality HiFi sequencing-based chromosome-scale assemblies, 27 of which are trio-based. Haplotypes demonstrate high contiguity (median N50 of 151.9 Mb) and good base accuracy (median QV score of 59.31). Of all assembled chromosomes, 31.8% are telomere-to-telomere (T2T) scaffolds (chromosome-spanning sequences flanked by telomeric repeats at both ends), and 64.3% achieved chromosome-level continuity (single scaffolds spanning an entire chromosome but retaining one or more sequence gaps or lacking a telomeric signature at one or both ends). These assemblies form the foundation of the population-specific pangenome graph of the Emirati Reference Genome Project (ERGP), which captures genomic variation comparable to the globally diverse HPRC reference graph, while covering regionally enriched variation. Applying the ERGP pangenome to short‑read genotyping of an independent Emirati cohort revealed structural variant sites in linkage disequilibrium with phenotype‑associated GWAS variants, demonstrating the value of population-graph-based variant inference. The ERGP reference complements human pangenomes and provides a critical foundation for population-specific genomics and precision medicine in the United Arab Emirates.