Identification of Novel Regulatory Regions Induced by Intrauterine Growth Restriction in Rat Islets

Intrauterine growth restriction (IUGR) leads to development of type 2 diabetes in adulthood and the permanent alterations in gene expression implicate an epigenetic mechanism. Using a rat model of IUGR, we performed TrueSeq-HELP Tagging to assess the association of DNA methylation changes and gene dysregulation in islets. We identified 511 differentially methylated regions (DMRs) and 4377 significantly altered single CpG sites. Integrating the methylome and our published transcriptome datasets resulted in the identification of pathways critical for islet function. The identified DMRs were enriched with transcription factor binding motifs, such as Elk1, Etv1, Foxa1, Foxa2, Pax7, Stat3, Hnf1, and AR. In silico analysis of 3D chromosomal interactions using human pancreas and islet Hi-C datasets identified interactions between 14 highly conserved DMRs and 35 genes with significant expression changes at an early age, many of which persisted in adult islets. In adult islets, there were far more interactions between DMRs and genes with significant expression changes identified with Hi-C and most of them were critical to islet metabolism and insulin secretion. The methylome was integrated with our published genome-wide histone modification datasets from IUGR islets resulting in further characterization of important regulatory regions of the genome altered by IUGR containing both significant changes in DNA methylation and specific histone marks. In summary we identified novel regulatory regions in islets after exposure to IUGR suggesting that epigenetic changes at key transcription factor binding motifs and other gene regulatory regions may contribute to gene dysregulation and an abnormal islet phenotype in IUGR rats.

Massively multiplex single-molecule oligonucleosome footprinting

Our understanding of the beads-on-a-string arrangement of nucleosomes has been built largely on high-resolution sequence-agnostic imaging methods and sequence-resolved bulk biochemical techniques. To bridge the divide between these approaches, we present the single-molecule adenine methylated oligonucleosome sequencing assay (SAMOSA). SAMOSA is a high-throughput single-molecule sequencing method that combines adenine methyltransferase footprinting and single-molecule real-time DNA sequencing to natively and nondestructively measure nucleosome positions on individual chromatin fibres. SAMOSA data allows unbiased classification of single-molecular 'states' of nucleosome occupancy on individual chromatin fibres. We leverage this to estimate nucleosome regularity and spacing on single chromatin fibres genome-wide, at predicted transcription factor binding motifs, and across human epigenomic domains. Our analyses suggest that chromatin is comprised of both regular and irregular single-molecular oligonucleosome patterns that differ subtly in their relative abundance across epigenomic domains. This irregularity is particularly striking in constitutive heterochromatin, which has typically been viewed as a conformationally static entity. Our proof-of-concept study provides a powerful new methodology for studying nucleosome organization at a previously intractable resolution and offers up new avenues for modeling and visualizing higher order chromatin structure.

An Unbiased Molecular Approach Using 3′-UTRs Resolves the Avian Family-Level Tree of Life

Presumably, due to a rapid early diversification, major parts of the higher-level phylogeny of birds are still resolved controversially in different analyses or are considered unresolvable. To address this problem, we produced an avian tree of life, which includes molecular sequences of one or several species of ∼90% of the currently recognized family-level taxa (429 species, 379 genera) including all 106 family-level taxa of the nonpasserines and 115 of the passerines (Passeriformes). The unconstrained analyses of noncoding 3-prime untranslated region (3′-UTR) sequences and those of coding sequences yielded different trees. In contrast to the coding sequences, the 3′-UTR sequences resulted in a well-resolved and stable tree topology. The 3′-UTR contained, unexpectedly, transcription factor binding motifs that were specific for different higher-level taxa. In this tree, grebes and flamingos are the sister clade of all other Neoaves, which are subdivided into five major clades. All nonpasserine taxa were placed with robust statistical support including the long-time enigmatic hoatzin (Opisthocomiformes), which was found being the sister taxon of the Caprimulgiformes. The comparatively late radiation of family-level clades of the songbirds (oscine Passeriformes) contrasts with the attenuated diversification of nonpasseriform taxa since the early Miocene. This correlates with the evolution of vocal production learning, an important speciation factor, which is ancestral for songbirds and evolved convergent only in hummingbirds and parrots. As 3′-UTR-based phylotranscriptomics resolved the avian family-level tree of life, we suggest that this procedure will also resolve the all-species avian tree of life

Massively multiplex single-molecule oligonucleosome footprinting

ABSTRACTOur understanding of the beads-on-a-string arrangement of nucleosomes has been built largely on high-resolution sequence-agnostic imaging methods and sequence-resolved bulk biochemical techniques. To bridge the divide between these approaches, we present the single-molecule adenine methylated oligonucleosome sequencing assay (SAMOSA). SAMOSA is a high-throughput single-molecule sequencing method that combines adenine methyltransferase footprinting and single-molecule real-time DNA sequencing to natively and nondestructively measure nucleosome positions on individual chromatin fibres. SAMOSA data allows unbiased classification of single-molecular ‘states’ of nucleosome occupancy on individual chromatin fibres. We leverage this to estimate nucleosome regularity and spacing on single chromatin fibres genome-wide, at predicted transcription factor binding motifs, and across both active and silent human epigenomic domains. Our analyses suggest that chromatin is comprised of a diverse array of both regular and irregular single-molecular oligonucleosome patterns that differ subtly in their relative abundance across epigenomic domains. This irregularity is particularly striking in constitutive heterochromatin, which has typically been viewed as a conformationally static entity. Our proof-of-concept study provides a powerful new methodology for studying nucleosome organization at a previously intractable resolution, and offers up new avenues for modeling and visualizing higher-order chromatin structure.1-sentence summaryHigh-throughput single-molecule real-time footprinting of chromatin arrays reveals heterogeneous patterns of oligonucleosome occupancy.

Exploring functionally annotated transcriptional consensus regulatory elements with CONREL

Understanding the interaction between human genome regulatory elements and transcription factors is fundamental to elucidate the structure of gene regulatory networks. Here we present CONREL, a web application that allows for the exploration of functionally annotated transcriptional ‘consensus’ regulatory elements at different levels of abstraction. CONREL provides an extensive collection of consensus promoters, enhancers and active enhancers for 198 cell-lines across 38 tissue types, which are also combined to provide global consensuses. In addition, 1000 Genomes Project genotype data and the ‘total binding affinity’ of thousands of transcription factor binding motifs at genomic regulatory elements is fully combined and exploited to characterize and annotate functional properties of our collection. Comparison with other available resources highlights the strengths and advantages of CONREL. CONREL can be used to explore genomic loci, specific genes or genomic regions of interest across different cell lines and tissue types. The resource is freely available at https://bcglab.cibio.unitn.it/conrel.

A Multi-Layered Study on Harmonic Oscillations in Mammalian Genomics and Proteomics

Cellular, organ, and whole animal physiology show temporal variation predominantly featuring 24-h (circadian) periodicity. Time-course mRNA gene expression profiling in mouse liver showed two subsets of genes oscillating at the second (12-h) and third (8-h) harmonic of the prime (24-h) frequency. The aim of our study was to identify specific genomic, proteomic, and functional properties of ultradian and circadian subsets. We found hallmarks of the three oscillating gene subsets, including different (i) functional annotation, (ii) proteomic and electrochemical features, and (iii) transcription factor binding motifs in upstream regions of 8-h and 12-h oscillating genes that seemingly allow the link of the ultradian gene sets to a known circadian network. Our multifaceted bioinformatics analysis of circadian and ultradian genes suggests that the different rhythmicity of gene expression impacts physiological outcomes and may be related to transcriptional, translational and post-translational dynamics, as well as to phylogenetic and evolutionary components.

A Bayesian approach for correcting Tn5 transposition bias in ATAC-seq footprinting

ATAC-seq exploits the observation that the pattern of transposition of a hyperactive Tn5 transposase in native chromatin mirrors genome-wide chromatin accessibility. It has been suggested that transposition observed around transcription factor binding motifs can be used to assess their occupancy in the form of footprints. However, we show that the vast majority of footprints observed at transcription factor motifs in ATAC-seq data spuriously arise from the intrinsic sequence-dependent transposition site bias of Tn5 and are also observed in naked DNA. We demonstrate that the Tn5 transposition bias can be corrected using existing tools for sequence bias correction and a novel estimate of global occupancy in order to produce more reliable estimates of footprints.