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Transcriptome landscape of the human placenta
Jinsil Kim, Keyan Zhao, Peng Jiang, Zhi-xiang Lu, Jinkai Wang, Jeffrey C Murray, Yi Xing
BMC Genomics , 2012, DOI: 10.1186/1471-2164-13-115
Abstract: We have conducted a deep RNA sequencing (RNA-Seq) study on three tissue components (amnion, chorion, and decidua) of 5 human placentas from normal term pregnancies. We compared the placental RNA-Seq data to that of 16 other human tissues and observed a wide spectrum of transcriptome differences both between placenta and other human tissues and between distinct compartments of the placenta. Exon-level analysis of the RNA-Seq data revealed a large number of exons with differential splicing activities between placenta and other tissues, and 79% (27 out of 34) of the events selected for RT-PCR test were validated. The master splicing regulator ESRP1 is expressed at a proportionately higher level in amnion compared to all other analyzed human tissues, and there is a significant enrichment of ESRP1-regulated exons with tissue-specific splicing activities in amnion. This suggests an important role of alternative splicing in regulating gene function and activity in specific placental compartments. Importantly, genes with differential expression or splicing in the placenta are significantly enriched for genes implicated in placental abnormalities and preterm birth. In addition, we identified 604-1007 novel transcripts and 494-585 novel exons expressed in each of the three placental compartments.Our data demonstrate unique aspects of gene expression and splicing in placental tissues that provide a basis for disease investigation related to disruption of these mechanisms. These data are publicly available providing the community with a rich resource for placental physiology and disease-related studies.Pregnancy and parturition require an intricate interplay between maternal and fetal factors, orchestrated by the placenta, which lies at the interface between mother and fetus. The placenta performs multiple functions critical for fetal survival, growth, and development, including transport of gases, nutrients, and waste products, hormone production, protection of the fetus from
The hepatic transcriptome in human liver disease
Nicholas A Shackel, Devanshi Seth, Paul S Haber, Mark D Gorrell, Geoffrey W McCaughan
Comparative Hepatology , 2006, DOI: 10.1186/1476-5926-5-6
Abstract: The sequencing of the human and other genomes has heralded the age of functional genomics. Although an invaluable resource in understanding human biology and disease, the frequent lack of sequence correlation with a defined tissue or disease phenotype has led to the genomic sequence databases being huge reservoirs of knowledge that mostly aid but do not direct research. We have the start of the map for human disease but only limited understanding of how it unfolds. Moreover, this genomic "gene map" is invariant across an entire organism and it is the expression of messenger RNA (mRNA) gene transcripts and resultant protein expression that defines normal molecular homeostasis and pathobiology. Functional genomics studies attempt to correlate gene mRNA transcript expression with a characterised phenotype thereby inferring function.The entire mRNA transcript pool within a cell or tissue has been labelled the transcriptome [1-3]. Similarly, the proteome refers to the entire protein pool. Understanding the regulation and expression of transcriptomes or proteomes in a disease specific context is pivotal to understanding human disease. Further, although proteins are the mediators of molecular pathobiology proteome expression is ultimately controlled by the transcriptome. Approaches aimed at understanding the relationship between mRNA and protein expression are complementary and important in understanding disease [1,2]. No single approach or methodology to examine the transcriptome is "best" or "correct" and one of the central goals of this review is to highlight the benefits and deficiencies of many current approaches being utilized to examine transciptomes (Table 1). Additionally, understanding the relationship between the transcriptome and proteome is essential in interpreting functional genomic studies.Organ specific research has lagged behind the understanding of general biological processes. However, most human disease is defined by unique changes to organ specific tr
Transcriptome coexpression map of human embryonic stem cells
Huai Li, Ying Liu, Soojung Shin, Yu Sun, Jeanne F Loring, Mark P Mattson, Mahendra S Rao, Ming Zhan1
BMC Genomics , 2006, DOI: 10.1186/1471-2164-7-103
Abstract: We report the first transcriptome coexpression map of the human ES cell and the earliest stage of ES differentiation, the embryoid body (EB), for the analysis of how transcriptional regulation interacts with genomic structure during ES self-renewal and differentiation. We determined the gene expression profiles from multiple ES and EB samples and identified chromosomal domains showing coexpression of adjacent genes on the genome. The coexpression domains were not random, with significant enrichment in chromosomes 8, 11, 16, 17, 19, and Y in the ES state, and 6, 11, 17, 19 and 20 in the EB state. The domains were significantly associated with Giemsa-negative bands in EB, yet showed little correlation with known cytogenetic structures in ES cells. Different patterns of coexpression were revealed by comparative transcriptome mapping between ES and EB.The findings and methods reported in this investigation advance our understanding of how genome organization affects gene expression in human ES cells and help to identify new mechanisms and pathways controlling ES self-renewal or differentiation.Large-scale transcriptional profiling and the availability of the complete genome sequences have made it possible for transcriptome mapping analysis in various organisms [1]. Transcriptome maps showing the density of expressed genes along the chromosome have revealed genomic regions that correspond to known amplicons of human tumors [2-4]. Regional similarity of expression on the chromosome have been observed in the yeast Saccharomyces cerevisiae [1], nematode Caenorhabditis elegans [5], fruit fly Drosophila melanogaster[1,6,7], and human [2,8]. Transcriptome maps showing regional similarities illustrate the existence of chromosomal domains of gene coexpression and transcriptional regulation operating at the local chromosome level. Transcriptome mapping analyses have been based on data generated from a variety of experimental techniques, including Expressed Sequence Tags [9], Seri
High-Resolution Transcriptome of Human Macrophages  [PDF]
Marc Beyer, Michael R. Mallmann, Jia Xue, Andrea Staratschek-Jox, Daniela Vorholt, Wolfgang Krebs, Daniel Sommer, Jil Sander, Christina Mertens, Andrea Nino-Castro, Susanne V. Schmidt, Joachim L. Schultze
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0045466
Abstract: Macrophages are dynamic cells integrating signals from their microenvironment to develop specific functional responses. Although, microarray-based transcriptional profiling has established transcriptional reprogramming as an important mechanism for signal integration and cell function of macrophages, current knowledge on transcriptional regulation of human macrophages is far from complete. To discover novel marker genes, an area of great need particularly in human macrophage biology but also to generate a much more thorough transcriptome of human M1- and M1-like macrophages, we performed RNA sequencing (RNA-seq) of human macrophages. Using this approach we can now provide a high-resolution transcriptome profile of human macrophages under classical (M1-like) and alternative (M2-like) polarization conditions and demonstrate a dynamic range exceeding observations obtained by previous technologies, resulting in a more comprehensive understanding of the transcriptome of human macrophages. Using this approach, we identify important gene clusters so far not appreciated by standard microarray techniques. In addition, we were able to detect differential promoter usage, alternative transcription start sites, and different coding sequences for 57 gene loci in human macrophages. Moreover, this approach led to the identification of novel M1-associated (CD120b, TLR2, SLAMF7) as well as M2-associated (CD1a, CD1b, CD93, CD226) cell surface markers. Taken together, these data support that high-resolution transcriptome profiling of human macrophages by RNA-seq leads to a better understanding of macrophage function and will form the basis for a better characterization of macrophages in human health and disease.
Spin-Glass: An Unfinished Story  [PDF]
J. R. L. de Almeida,S. Coutinho
Physics , 1994,
Abstract: In this work a short overview of the development of spin glass theories, mainly long and short range Ising models, are presented.
Analysis of a human brain transcriptome map
Ping Qiu, Lawrence Benbow, Suxing Liu, Jonathan R Greene, Luquan Wang
BMC Genomics , 2002, DOI: 10.1186/1471-2164-3-10
Abstract: Examination of ESTs derived from brain tissues (excluding brain tumor tissues) suggests that these genes are distributed on chromosomes in a non-random fashion. Some regions on the genome are dense with brain-enriched genes while some regions lack brain-enriched genes, suggesting a significant correlation between distribution of genes along the chromosome and tissue type. ESTs from brain tumor tissues have also been mapped to the human genome working draft. We reveal that some regions enriched in brain genes show a significant decrease in gene expression in brain tumors, and, conversely that some regions lacking in brain genes show an increased level of gene expression in brain tumors.This report demonstrates a novel approach for tissue specific transcriptome mapping using EST-based quantitative assessment.Sequencing of Expressed Sequence Tags (ESTs) has resulted in the rapid identification of expressed genes [1]. ESTs are single-pass, partial sequences of cDNA clones from a large number of disease and normal tissue libraries. ESTs have been used extensively for gene discovery and for transcript mapping of genes from a wide number of organisms [2-4]. Even with the finished working draft of the human genome, the generation of a complete and non-redundant catalog of human genes is still a big challenge facing the genome research community. Full-length cDNA data are currently available for only 10,000 human genes [5], less than one-third of the total using the most conservative recent estimates of human gene numbers [6,7]. Evidence of differential expression is one of the most important criteria in prioritizing the exploitation of genes in both academic and pharmaceutical research [8-10].While identifying individual differentially expressed genes attracts most of the interest, a genome wide transcriptome map may not only provide a tool to identify candidate genes that are over-expressed or silenced in certain disease tissue, but may also help to understand the structur
Transcriptome Complexity and Riboregulation in the Human Pathogen Helicobacter pylori  [PDF]
Sandy R. Pernitzsch,Cynthia M. Sharma
Frontiers in Cellular and Infection Microbiology , 2012, DOI: 10.3389/fcimb.2012.00014
Abstract: The Gram-negative Epsilonproteobacterium Helicobacter pylori is considered as one of the major human pathogens and many studies have focused on its virulence mechanisms as well as genomic diversity. In contrast, only very little is known about post-transcriptional regulation and small regulatory RNAs (sRNAs) in this spiral-shaped microaerophilic bacterium. Considering the absence of the common RNA chaperone Hfq, which is a key-player in post-transcriptional regulation in enterobacteria, H. pylori was even regarded as an organism without riboregulation. However, analysis of the H. pylori primary transcriptome using RNA-seq revealed a very complex transcriptional output from its small genome. Furthermore, the identification of a wealth of sRNAs as well as massive antisense transcription indicates that H. pylori uses riboregulation for its gene expression control. The ongoing functional characterization of sRNAs along with the identification of associated RNA binding proteins will help to understand their potential roles in Helicobacter virulence and stress response. Moreover, research on riboregulation in H. pylori will provide new insights into its virulence mechanisms and will also help to shed light on post-transcriptional regulation in other Epsilonproteobacteria, including widespread and emerging pathogens such as Campylobacter.
The Human Blood Metabolome-Transcriptome Interface  [PDF]
J?rg Bartel?,Jan Krumsiek?,Katharina Schramm?,Jerzy Adamski?,Christian Gieger?,Christian Herder?,Maren Carstensen?,Annette Peters?,Wolfgang Rathmann?,Michael Roden
PLOS Genetics , 2015, DOI: 10.1371/journal.pgen.1005274
Abstract: Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the ‘human blood metabolome-transcriptome interface’ (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease.
Probabilistic analysis of the human transcriptome with side information  [PDF]
Leo Lahti
Computer Science , 2011,
Abstract: Understanding functional organization of genetic information is a major challenge in modern biology. Following the initial publication of the human genome sequence in 2001, advances in high-throughput measurement technologies and efficient sharing of research material through community databases have opened up new views to the study of living organisms and the structure of life. In this thesis, novel computational strategies have been developed to investigate a key functional layer of genetic information, the human transcriptome, which regulates the function of living cells through protein synthesis. The key contributions of the thesis are general exploratory tools for high-throughput data analysis that have provided new insights to cell-biological networks, cancer mechanisms and other aspects of genome function. A central challenge in functional genomics is that high-dimensional genomic observations are associated with high levels of complex and largely unknown sources of variation. By combining statistical evidence across multiple measurement sources and the wealth of background information in genomic data repositories it has been possible to solve some the uncertainties associated with individual observations and to identify functional mechanisms that could not be detected based on individual measurement sources. Statistical learning and probabilistic models provide a natural framework for such modeling tasks. Open source implementations of the key methodological contributions have been released to facilitate further adoption of the developed methods by the research community.
A transcriptome anatomy of human colorectal cancers
Bingjian Lü, Jing Xu, Maode Lai, Hao Zhang, Jian Chen
BMC Cancer , 2006, DOI: 10.1186/1471-2407-6-40
Abstract: In this study, we clustered human colorectal normal mucosa (N), inflammatory bowel disease (IBD), adenoma (A) and cancer (T) related expression sequence tags (EST) into UniGenes via an in-house GetUni software package and analyzed the transcriptome overview of these libraries by GOTree Machine (GOTM). Additionally, we downloaded UniGene based cDNA libraries of colon and analyzed them by Xprofiler to cross validate the efficiency of GetUni. Semi-quantitative RT-PCR was used to validate the expression of β-catenin and. 7 novel genes in colorectal cancers.The efficiency of GetUni was successfully validated by Xprofiler and RT-PCR. Genes in library N, IBD and A were all found in library T. A total of 14,879 genes were identified with 2,355 of them having at least 2 transcripts. Differences in gene enrichment among these libraries were statistically significant in 50 signal transduction pathways and Pfam protein domains by GOTM analysis P < 0.01 Hypergeometric Test). Genes in two metabolic pathways, ribosome and glycolysis, were more enriched in the expression profiles of A and IBD than in N and T. Seven transmembrane receptor superfamily genes were typically abundant in cancers.Colorectal cancers are genetically heterogeneous. Transcription variants are common in them. Aberrations of ribosome and glycolysis pathway might be early indicators of precursor lesions in colon cancers. The electronic gene expression profile could be used to highlight the integral molecular events in colorectal cancers.Worldwide, the incidence of colorectal cancer has been rising nowadays. It is the second mortality caused by cancers in western countries and the third or fourth in China [1]. Many tumor suppressor genes, oncogenes, and growth factor genes have been demonstrated to be involved in the carcinogenesis of colon and rectum, for example, k-ras, APC, p53 and TGFβ. A molecular genetic model of multiple genes and steps was proposed by Vogelstein in 1990 [2]. Two paralleling molecular path
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