AlleleHMM: a data-driven method to identify allele specific differences in distributed functional genomic marks.

How DNA sequence variation influences gene expression remains poorly understood. Diploid organisms have two homologous copies of their DNA sequence in the same nucleus, providing a rich source of information about how genetic variation affects a wealth of biochemical processes. However, few computational methods have been developed to discover allele specific differences in functional genomic data. Existing methods either treat each SNP independently, limiting statistical power, or combine SNPs across gene annotations, preventing the discovery of allele specific differences in unexpected genomic regions. Here we introduce AlleleHMM, a new computational method to identify blocks of neighboring SNPs that share similar allele specific differences in mark abundance. AlleleHMM uses a hidden Markov model to divide the genome into three hidden states based on allele frequencies in genomic data: a symmetric state (state S) which shows no difference between alleles, and regions with a higher signal on the maternal (state M) or paternal (state P) allele. AlleleHMM substantially outperformed naive methods using both simulated and real genomic data, particularly when input data had realistic levels of overdispersion. Using global run-on sequencing (GRO-seq) data, AlleleHMM identified thousands of allele specific blocks of transcription in both coding and non-coding genomic regions. AlleleHMM is a powerful tool for discovering allele specific regions in functional genomic datasets.

Chromatin run-on sequencing analysis finds that ECM remodeling plays an important role in canine hemangiosarcoma pathogenesis.

BACKGROUND: Canine visceral hemangiosarcoma (HSA) is a highly aggressive cancer of endothelial origin that closely resembles visceral angiosarcoma in humans, both clinically and histopathologically. Currently there is an unmet need for new diagnostics and therapies for both forms of this disease. The goal of this study was to utilize Chromatin run-on sequencing (ChRO-seq) and immunohistochemistry (IHC) to identify gene and protein expression signatures that may be important drivers of HSA progression. RESULTS: ChRO-seq was performed on tissue isolated from 17 HSA samples and 4 normal splenic samples. Computational analysis was then used to identify differentially expressed genes and these factors were subjected to gene ontology analysis. ChRO-seq analysis revealed over a thousand differentially expressed genes in HSA tissue compared with normal splenic tissue (FDR < 0.005). Interestingly, the majority of genes overexpressed in HSA tumor tissue were associated with extracellular matrix (ECM) remodeling. This observation correlated well with our histological analysis, which found that HSA tumors contain a rich and complex collagen network. Additionally, we characterized the protein expression patterns of two highly overexpressed molecules identified in ChRO-seq analysis, podoplanin (PDPN) and laminin alpha 4 (LAMA4). We found that the expression of these two ECM-associated factors appeared to be largely limited to transformed endothelial cells within the HSA lesions. CONCLUSION: Outcomes from this study suggest that ECM remodeling plays an important role in HSA progression. Additionally, our study identified two potential novel biomarkers of HSA, PDPN and LAMA4. Interestingly, given that function-blocking anti-PDPN antibodies have shown anti-tumor effects in mouse models of canine melanoma, our studies raise the possibility that these types of therapeutic strategies could potentially be developed for treating canine HSA.

Integrated proteomic and transcriptomic analysis of the Aedes aegypti eggshell.

BACKGROUND: Mosquito eggshells show remarkable diversity in physical properties and structure consistent with adaptations to the wide variety of environments exploited by these insects. We applied proteomic, transcriptomic, and hybridization in situ techniques to identify gene products and pathways that participate in the assembly of the Aedes aegypti eggshell. Aedes aegypti population density is low during cold and dry seasons and increases immediately after rainfall. The survival of embryos through unfavorable periods is a key factor in the persistence of their populations. The work described here supports integrated vector control approaches that target eggshell formation and result in Ae. aegypti drought-intolerant phenotypes for public health initiatives directed to reduce mosquito-borne diseases. RESULTS: A total of 130 proteins were identified from the combined mass spectrometric analyses of eggshell preparations. CONCLUSIONS: Classification of proteins according to their known and putative functions revealed the complexity of the eggshell structure. Three novel Ae. aegypti vitelline membrane proteins were discovered. Odorant-binding and cysteine-rich proteins that may be structural components of the eggshell were identified. Enzymes with peroxidase, laccase and phenoloxidase activities also were identified, and their likely involvements in cross-linking reactions that stabilize the eggshell structure are discussed.

Genetic dissection of the RNA polymerase II transcription cycle.

How DNA sequence affects the dynamics and position of RNA Polymerase II (Pol II) during transcription remains poorly understood. Here, we used naturally occurring genetic variation in F1 hybrid mice to explore how DNA sequence differences affect the genome-wide distribution of Pol II. We measured the position and orientation of Pol II in eight organs collected from heterozygous F1 hybrid mice using ChRO-seq. Our data revealed a strong genetic basis for the precise coordinates of transcription initiation and promoter proximal pause, allowing us to redefine molecular models of core transcriptional processes. Our results implicate DNA sequence, including both known and novel DNA sequence motifs, as key determinants of the position of Pol II initiation and pause. We report evidence that initiation site selection follows a stochastic process similar to Brownian motion along the DNA template. We found widespread differences in the position of transcription termination, which impact the primary structure and stability of mature mRNA. Finally, we report evidence that allelic changes in transcription often affect mRNA and ncRNA expression across broad genomic domains. Collectively, we reveal how DNA sequences shape core transcriptional processes at single nucleotide resolution in mammals.

Prediction of histone post-translational modification patterns based on nascent transcription data.

The role of histone modifications in transcription remains incompletely understood. Here, we examine the relationship between histone modifications and transcription using experimental perturbations combined with sensitive machine-learning tools. Transcription predicted the variation in active histone marks and complex chromatin states, like bivalent promoters, down to single-nucleosome resolution and at an accuracy that rivaled the correspondence between independent ChIP-seq experiments. Blocking transcription rapidly removed two punctate marks, H3K4me3 and H3K27ac, from chromatin indicating that transcription is required for active histone modifications. Transcription was also required for maintenance of H3K27me3, consistent with a role for RNA in recruiting PRC2. A subset of DNase-I-hypersensitive sites were refractory to prediction, precluding models where transcription initiates pervasively at any open chromatin. Our results, in combination with past literature, support a model in which active histone modifications serve a supportive, rather than an essential regulatory, role in transcription.

Uncovering transcriptional dark matter via gene annotation independent single-cell RNA sequencing analysis.

Conventional scRNA-seq expression analyses rely on the availability of a high quality genome annotation. Yet, as we show here with scRNA-seq experiments and analyses spanning human, mouse, chicken, mole rat, lemur and sea urchin, genome annotations are often incomplete, in particular for organisms that are not routinely studied. To overcome this hurdle, we created a scRNA-seq analysis routine that recovers biologically relevant transcriptional activity beyond the scope of the best available genome annotation by performing scRNA-seq analysis on any region in the genome for which transcriptional products are detected. Our tool generates a single-cell expression matrix for all transcriptionally active regions (TARs), performs single-cell TAR expression analysis to identify biologically significant TARs, and then annotates TARs using gene homology analysis. This procedure uses single-cell expression analyses as a filter to direct annotation efforts to biologically significant transcripts and thereby uncovers biology to which scRNA-seq would otherwise be in the dark.

Discovering Transcriptional Regulatory Elements From Run-On and Sequencing Data Using the Web-Based dREG Gateway.

Transcription is a chromatin mark that can be used effectively to identify the location of active enhancers and promoters, collectively known as transcriptional regulatory elements (TREs). We recently introduced dREG, a tool for the identification of TREs using run-on and sequencing (RO-seq) assays, including global run-on and sequencing (GRO-seq), precision run-on and sequencing (PRO-seq), and chromatin run-on and sequencing (ChRO-seq). In this protocol, we present step-by-step instructions for running dREG on an arbitrary run-on and sequencing dataset. Users provide dREG with bigWig files (in which each read is represented by a single base) representing the location of RNA polymerase in a cell or tissue sample of interest, and dREG returns a list of genomic regions that are predicted to be active TREs. Finally, we demonstrate the use of dREG regions in discovering transcription factors controlling response to a stimulus and predicting their target genes. Together, this protocol provides detailed instructions for running dREG on arbitrary run-on and sequencing data. © 2018 by John Wiley & Sons, Inc.

Virome Diversity Correlates with Intestinal Microbiome Diversity in Adult Monozygotic Twins.

The virome is one of the most variable components of the human gut microbiome. Within twin pairs, viromes have been shown to be similar for infants, but not for adults, indicating that as twins age and their environments and microbiomes diverge, so do their viromes. The degree to which the microbiome drives the vast virome diversity is unclear. Here, we examine the relationship between microbiome and virome diversity in 21 adult monozygotic twin pairs selected for high or low microbiome concordance. Viromes derived from virus-like particles are unique to each individual, are dominated by Caudovirales and Microviridae, and exhibit a small core that includes crAssphage. Microbiome-discordant twins display more dissimilar viromes compared to microbiome-concordant twins, and the richer the microbiomes, the richer the viromes. These patterns are driven by bacteriophages, not eukaryotic viruses. Collectively, these observations support a strong role of the microbiome in patterning for the virome.

Functional characterization of cellulases identified from the cow rumen fungus Neocallimastix patriciarum W5 by transcriptomic and secretomic analyses.

BACKGROUND: Neocallimastix patriciarum is one of the common anaerobic fungi in the digestive tracts of ruminants that can actively digest cellulosic materials, and its cellulases have great potential for hydrolyzing cellulosic feedstocks. Due to the difficulty in culture and lack of a genome database, it is not easy to gain a global understanding of the glycosyl hydrolases (GHs) produced by this anaerobic fungus. RESULTS: We have developed an efficient platform that uses a combination of transcriptomic and proteomic approaches to N. patriciarum to accelerate gene identification, enzyme classification and application in rice straw degradation. By conducting complementary studies of transcriptome (Roche 454 GS and Illumina GA IIx) and secretome (ESI-Trap LC-MS/MS), we identified 219 putative GH contigs and classified them into 25 GH families. The secretome analysis identified four major enzymes involved in rice straw degradation: ß-glucosidase, endo-1,4-ß-xylanase, xylanase B and Cel48A exoglucanase. From the sequences of assembled contigs, we cloned 19 putative cellulase genes, including the GH1, GH3, GH5, GH6, GH9, GH18, GH43 and GH48 gene families, which were highly expressed in N. patriciarum cultures grown on different feedstocks. CONCLUSIONS: These GH genes were expressed in Pichia pastoris and/or Saccharomyces cerevisiae for functional characterization. At least five novel cellulases displayed cellulytic activity for glucose production. One ß-glucosidase (W5-16143) and one exocellulase (W5-CAT26) showed strong activities and could potentially be developed into commercial enzymes.