SeedMatchR: identify off-target effects mediated by siRNA seed regions in RNA-seq experiments.

MOTIVATION: On-target gene knockdown, using siRNA, ideally results from binding fully complementary regions in mRNA transcripts to induce direct cleavage. Off-target siRNA gene knockdown can occur through several modes, one being a seed-mediated mechanism mimicking miRNA gene regulation. Seed-mediated off-target effects occur when the ∼8 nucleotides at the 5' end of the guide strand, called a seed region, bind the 3' untranslated regions of mRNA, causing reduced translation. Experiments using siRNA knockdown paired with RNA-seq can be used to detect siRNA sequences with off-target effects driven by the seed region. However, there are limited computational tools designed specifically for detecting siRNA off-target effects mediated by the seed region in differential gene expression experiments. RESULTS: SeedMatchR is an R package developed to provide users a single, unified resource for detecting and visualizing seed-mediated off-target effects of siRNA using RNA-seq experiments. SeedMatchR is designed to extend current differential expression analysis tools, such as DESeq2, by annotating results with predicted seed matches. Using publicly available data, we demonstrate the ability of SeedMatchR to detect cumulative changes in differential gene expression attributed to siRNA seed region activity. AVAILABILITY: SeedMatchR is available on CRAN. Documentation and example workflows are available through the SeedMatchR GitHub page at https://github.com/tacazares/SeedMatchR.

An atlas of gene regulatory networks for memory CD4 + T cells in youth and old age.

Aging profoundly affects immune-system function, promoting susceptibility to pathogens, cancers and chronic inflammation. We previously identified a population of IL-10-producing, T follicular helper-like cells (" Tfh10 "), linked to suppressed vaccine responses in aged mice. Here, we integrate single-cell ( sc )RNA-seq, scATAC-seq and genome-scale modeling to characterize Tfh10 - and the full CD4 + memory T cell ( CD4 + TM ) compartment - in young and old mice. We identified 13 CD4 + TM populations, which we validated through cross-comparison to prior scRNA-seq studies. We built gene regulatory networks ( GRNs ) that predict transcription-factor control of gene expression in each T-cell population and how these circuits change with age. Through integration with pan-cell aging atlases, we identified intercellular-signaling networks driving age-dependent changes in CD4 + TM. Our atlas of finely resolved CD4 + TM subsets, GRNs and cell-cell communication networks is a comprehensive resource of predicted regulatory mechanisms operative in memory T cells, presenting new opportunities to improve immune responses in the elderly.

maxATAC: Genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks.

Transcription factors read the genome, fundamentally connecting DNA sequence to gene expression across diverse cell types. Determining how, where, and when TFs bind chromatin will advance our understanding of gene regulatory networks and cellular behavior. The 2017 ENCODE-DREAM in vivo Transcription-Factor Binding Site (TFBS) Prediction Challenge highlighted the value of chromatin accessibility data to TFBS prediction, establishing state-of-the-art methods for TFBS prediction from DNase-seq. However, the more recent Assay-for-Transposase-Accessible-Chromatin (ATAC)-seq has surpassed DNase-seq as the most widely-used chromatin accessibility profiling method. Furthermore, ATAC-seq is the only such technique available at single-cell resolution from standard commercial platforms. While ATAC-seq datasets grow exponentially, suboptimal motif scanning is unfortunately the most common method for TFBS prediction from ATAC-seq. To enable community access to state-of-the-art TFBS prediction from ATAC-seq, we (1) curated an extensive benchmark dataset (127 TFs) for ATAC-seq model training and (2) built "maxATAC", a suite of user-friendly, deep neural network models for genome-wide TFBS prediction from ATAC-seq in any cell type. With models available for 127 human TFs, maxATAC is the largest collection of high-performance TFBS prediction models for ATAC-seq. maxATAC performance extends to primary cells and single-cell ATAC-seq, enabling improved TFBS prediction in vivo. We demonstrate maxATAC's capabilities by identifying TFBS associated with allele-dependent chromatin accessibility at atopic dermatitis genetic risk loci.

Global discovery of lupus genetic risk variant allelic enhancer activity.

Genome-wide association studies of Systemic Lupus Erythematosus (SLE) nominate 3073 genetic variants at 91 risk loci. To systematically screen these variants for allelic transcriptional enhancer activity, we construct a massively parallel reporter assay (MPRA) library comprising 12,396 DNA oligonucleotides containing the genomic context around every allele of each SLE variant. Transfection into the Epstein-Barr virus-transformed B cell line GM12878 reveals 482 variants with enhancer activity, with 51 variants showing genotype-dependent (allelic) enhancer activity at 27 risk loci. Comparison of MPRA results in GM12878 and Jurkat T cell lines highlights shared and unique allelic transcriptional regulatory mechanisms at SLE risk loci. In-depth analysis of allelic transcription factor (TF) binding at and around allelic variants identifies one class of TFs whose DNA-binding motif tends to be directly altered by the risk variant and a second class of TFs that bind allelically without direct alteration of their motif by the variant. Collectively, our approach provides a blueprint for the discovery of allelic gene regulation at risk loci for any disease and offers insight into the transcriptional regulatory mechanisms underlying SLE.

Abnormal Peyer patch development and B-cell gut homing drive IgA deficiency in Kabuki syndrome.

BACKGROUND: Kabuki syndrome (KS) is commonly caused by mutations in the histone-modifying enzyme lysine methyltransferase 2D (KMT2D). Immune dysfunction is frequently observed in individuals with KS, but the role of KMT2D in immune system function has not been identified. OBJECTIVE: We sought to understand the mechanisms driving KS-associated immune deficiency (hypogammaglobulinemia [low IgA], splenomegaly, and diminished immunization responses). METHODS: We performed a comprehensive evaluation of humoral immunity and secondary lymphoid tissues in an established KS (Kmt2d+/ßGeo) mouse model and validated select findings in a patient with KS. RESULTS: Compared with wild-type littermates, Kmt2d+/ßGeo mice demonstrated deficiencies in multiple B-cell lineages and reduced serum IgA and elevated IgM levels across multiple ages. The bone marrow, spleen, and intestine of Kmt2d+/ßGeo mice contained diminished numbers of IgA-secreting cells, while elevated germinal center B cells were found in the mesenteric lymph node and Peyer patches. Kmt2d+/ßGeo mice have decreased size and numbers of Peyer patches, a finding confirmed in human samples. We identified deficiency of Itgb7 RNA and protein expression, a gene encoding an adhesion protein that mediates intestinal homing, and we demonstrated KMT2D-dependent control of ITGB7 expression in a human cell line. CONCLUSIONS: Kmt2d haploinsufficiency has broad deleterious effects on B-cell differentiation, specifically hampering gut lymphocyte homing and IgA+ plasma cell differentiation. Intestinal lymphoid defects caused by ITGB7 deficiency have not previously been recognized in KS, and these results provide new mechanistic insights into the pathogenesis of KS-associated immune deficiency.

Lipid Mediators of Allergic Disease: Pathways, Treatments, and Emerging Therapeutic Targets.

Bioactive lipids are critical regulators of inflammation. Over the last 75 years, these diverse compounds have emerged as clinically-relevant mediators of allergic disease pathophysiology. Animal and human studies have demonstrated the importance of lipid mediators in the development of asthma, allergic rhinitis, urticaria, anaphylaxis, atopic dermatitis, and food allergy. Lipids are critical participants in cell signaling events which influence key physiologic (bronchoconstriction) and immune phenomena (degranulation, chemotaxis, sensitization). Lipid-mediated cellular mechanisms including: (1) formation of structural support platforms (lipid rafts) for receptor signaling complexes, (2) activation of a diverse family of G-protein coupled receptors, and (3) mediating intracellular signaling cascades by acting as second messengers. Here, we review four classes of bioactive lipids (platelet activating factor, the leukotrienes, the prostanoids, and the sphingolipids) with special emphasis on lipid synthesis pathways and signaling, atopic disease pathology, and the ongoing development of atopy treatments targeting lipid mediator pathways.