Identification and expression analysis of human and murine overlapping genes

Wydział BiologiiZjawisko nakładania się genów może pełnić wiele funkcji regulatorowych, a większość prowadzonych obecnie w tym temacie badań skupia się na parach genów kodujących białka, nakładających się z niekodującymi RNA. Stosunkowo mało wiadomo na temat zjawiska nakładania w przypadku dwóch genów kodujących białka. W niniejszej pracy przeanalizowano wpływ nakładania się genów kodujących białka końcami 5’ na poziom ich ekspresji. W oparciu o analizę miejsc startu transkrypcji (TSS) w 73 ludzkich i 10 mysich organach, tkankach i liniach komórkowych, zidentyfikowano 582 i 113 par genów nakładających się w przynajmniej jednej bibliotece odpowiednio u człowieka i myszy. Wykazano, że rejon nakładania jest rzadko zachowany między gatunkami i tkankami. Pokazano również, że tylko w przypadku połowy par genów, transkrypcja inicjowana była wyłącznie w rejonie nakładania. W pozostałych przypadkach inicjacja transkrypcji następowała z miejsc TSS położonych zarówno w rejonie nakładania jak i po za nim. Analizy 26 linii komórkowych gruczolakoraka płuc oparte zostały dodatkowo również o dane pochodzące z eksperymentów RNA-Seq oraz ChIP-Seq dla siedmiu typów modyfikacji histonów i aktywności polimerazy RNA II, co pozwoliło przestudiować zjawisko nakładania w kontekście interferencji transkrypcji. Kluczowe wyniki zdeponowane zostały w bazie danych, dostępnej pod adresem http://overgenedb.amu.edu.pl.Gene overlap is known to play various regulatory functions on transcriptional and post-transcriptional levels. Most of the currently held studies is focused on protein coding genes overlapping with non-protein coding counterparts. Much less is known about the role of the gene overlap in the case of two protein-coding genes. Here we have studied 5’ end protein-coding overlapping genes in human and mice genomes. We have identified 582 human and 113 mouse pairs of genes that are transcribed using overlapping promoters in at least one analyzed library. Gene pairs were identified based on the analysis of the transcription start sites (TSSs) coordinates in 73 human and 10 mouse organs, tissues and cell lines. The collected data revealed that the overlap region is rarely conserved between the studied species and tissues. The results also shown that only in the case of about 50% of overlapping genes, transcription started explicitly in the overlap regions. In remaining half, the transcription was initiated both from overlapping and non-overlapping TSSs. Analyses for 26 human lung adenocarcinoma cell lines were additionally based on RNA-Seq and ChIP-Seq data for seven histone modifications and RNA Polymerase II activity which were studied in the context of the transcriptional interference. Key results were stored in a database, accessible under http://overgenedb.amu.edu.pl

Efficient Exploration of the Space of Reconciled Gene Trees

Gene trees record the combination of gene level events, such as duplication, transfer and loss, and species level events, such as speciation and extinction. Gene tree-species tree reconciliation methods model these processes by drawing gene trees into the species tree using a series of gene and species level events. The reconstruction of gene trees based on sequence alone almost always involves choosing between statistically equivalent or weakly distinguishable relationships that could be much better resolved based on a putative species tree. To exploit this potential for accurate reconstruction of gene trees the space of reconciled gene trees must be explored according to a joint model of sequence evolution and gene tree-species tree reconciliation. Here we present amalgamated likelihood estimation (ALE), a probabilistic approach to exhaustively explore all reconciled gene trees that can be amalgamated as a combination of clades observed in a sample of trees. We implement ALE in the context of a reconciliation model, which allows for the duplication, transfer and loss of genes. We use ALE to efficiently approximate the sum of the joint likelihood over amalgamations and to find the reconciled gene tree that maximizes the joint likelihood. We demonstrate using simulations that gene trees reconstructed using the joint likelihood are substantially more accurate than those reconstructed using sequence alone. Using realistic topologies, branch lengths and alignment sizes, we demonstrate that ALE produces more accurate gene trees even if the model of sequence evolution is greatly simplified. Finally, examining 1099 gene families from 36 cyanobacterial genomes we find that joint likelihood-based inference results in a striking reduction in apparent phylogenetic discord, with 24%, 59% and 46% percent reductions in the mean numbers of duplications, transfers and losses.Comment: Manuscript accepted pending revision in Systematic Biolog

Hubungan Kadar Timbel dalam Darah dengan Kadar Hemoglobin dan Hematokrit pada Petugas Pintu Tol Jagorawi

A study on the association of lead in blood and haemoglobin and hematocrit value as a measure of anaemia among toll booth workers at Jagorawi Jakarta, has been conducted. The rational of the study is that high aerial lead content has been reported by the Jakarta environmental authority and health literature indicates that lead is toxic to human hemopoeitic system. The toll booth workers are exposed to air pollutants in their day to day work. One hundred workers, randomly selected, participated in the study. On the haemoglobin concentration, 12% of the study subjects were categorized as anaemia, while on hematocrit values 10% were considered as anaemia. Blood lead concentrations found in this study were 20,1 ± 1,1 (mean ± SD) μgr% and the maximum value was 22,9μgr%. The haemoglobin values were 15,2 ± 1,5gr% with a minimum of 9,9gr%, while the hematocrit values were 45,2 ± 4,4% with a minimum of 30%. All blood lead values were above 10μgr% including 16 women of child-bearing age. In general, no association was found between blood lead and haemoglobin and hematocrit values. This discovery is in line with other studies which found that there is no meaningful association between blood lead and anaemia when the blood lead concentrations were below 40 μgr%

Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data.

Chromatin interaction studies can reveal how the genome is organized into spatially confined sub-compartments in the nucleus. However, accurately identifying sub-compartments from chromatin interaction data remains a challenge in computational biology. Here, we present Sub-Compartment Identifier (SCI), an algorithm that uses graph embedding followed by unsupervised learning to predict sub-compartments using Hi-C chromatin interaction data. We find that the network topological centrality and clustering performance of SCI sub-compartment predictions are superior to those of hidden Markov model (HMM) sub-compartment predictions. Moreover, using orthogonal Chromatin Interaction Analysis by in-situ Paired-End Tag Sequencing (ChIA-PET) data, we confirmed that SCI sub-compartment prediction outperforms HMM. We show that SCI-predicted sub-compartments have distinct epigenetic marks, transcriptional activities, and transcription factor enrichment. Moreover, we present a deep neural network to predict sub-compartments using epigenome, replication timing, and sequence data. Our neural network predicts more accurate sub-compartment predictions when SCI-determined sub-compartments are used as labels for training

Enhanced CRISPR-based DNA demethylation by Casilio-ME-mediated RNA-guided coupling of methylcytosine oxidation and DNA repair pathways.

Here we develop a methylation editing toolbox, Casilio-ME, that enables not only RNA-guided methylcytosine editing by targeting TET1 to genomic sites, but also by co-delivering TET1 and protein factors that couple methylcytosine oxidation to DNA repair activities, and/or promote TET1 to achieve enhanced activation of methylation-silenced genes. Delivery of TET1 activity by Casilio-ME1 robustly alters the CpG methylation landscape of promoter regions and activates methylation-silenced genes. We augment Casilio-ME1 to simultaneously deliver the TET1-catalytic domain and GADD45A (Casilio-ME2) or NEIL2 (Casilio-ME3) to streamline removal of oxidized cytosine intermediates to enhance activation of targeted genes. Using two-in-one effectors or modular effectors, Casilio-ME2 and Casilio-ME3 remarkably boost gene activation and methylcytosine demethylation of targeted loci. We expand the toolbox to enable a stable and expression-inducible system for broader application of the Casilio-ME platforms. This work establishes a platform for editing DNA methylation to enable research investigations interrogating DNA methylomes

DNA methylation-calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation.

BACKGROUND: Nanopore long-read sequencing technology greatly expands the capacity of long-range, single-molecule DNA-modification detection. A growing number of analytical tools have been developed to detect DNA methylation from nanopore sequencing reads. Here, we assess the performance of different methylation-calling tools to provide a systematic evaluation to guide researchers performing human epigenome-wide studies. RESULTS: We compare seven analytic tools for detecting DNA methylation from nanopore long-read sequencing data generated from human natural DNA at a whole-genome scale. We evaluate the per-read and per-site performance of CpG methylation prediction across different genomic contexts, CpG site coverage, and computational resources consumed by each tool. The seven tools exhibit different performances across the evaluation criteria. We show that the methylation prediction at regions with discordant DNA methylation patterns, intergenic regions, low CG density regions, and repetitive regions show room for improvement across all tools. Furthermore, we demonstrate that 5hmC levels at least partly contribute to the discrepancy between bisulfite and nanopore sequencing. Lastly, we provide an online DNA methylation database ( https://nanome.jax.org ) to display the DNA methylation levels detected by nanopore sequencing and bisulfite sequencing data across different genomic contexts. CONCLUSIONS: Our study is the first systematic benchmark of computational methods for detection of mammalian whole-genome DNA modifications in nanopore sequencing. We provide a broad foundation for cross-platform standardization and an evaluation of analytical tools designed for genome-scale modified base detection using nanopore sequencing

Biological functions of natural antisense transcripts

Natural antisense transcripts (NATs) are RNA molecules that originate from opposite DNA strands of the same genomic locus (cis-NAT) or unlinked genomic loci (trans-NAT). NATs may play various regulatory functions at the transcriptional level via transcriptional interference. NATs may also regulate gene expression levels post-transcriptionally via induction of epigenetic changes or double-stranded RNA formation, which may lead to endogenous RNA interference, RNA editing or RNA masking. The true biological significance of the natural antisense transcripts remains controversial despite many years of research. Here, we summarize the current state of knowledge and discuss the sense-antisense overlap regulatory mechanisms and their potential

real_mlrec

ALEml output for real ales

real_alignments

Alignments constructed using MUSCLE and GBLOCKS for 1099 cyanobacterial gene families with from version 5 of the HOGENOM database