Complementing tissue characterization by integrating transcriptome profiling from the Human Protein Atlas and from the FANTOM5 consortium

The protein expression profile of ACE2 in human tissues

The novel SARS-coronavirus 2 (SARS-CoV-2) poses a global challenge on healthcare and society. For understanding the susceptibility for SARS-CoV-2 infection, the cell type-specific expression of the host cell surface receptor is necessary. The key protein suggested to be involved in host cell entry is angiotensin I converting enzyme 2 (ACE2). Here, we report the expression pattern of ACE2 across > 150 different cell types corresponding to all major human tissues and organs based on stringent immunohistochemical analysis. The results were compared with several datasets both on the mRNA and protein level. ACE2 expression was mainly observed in enterocytes, renal tubules, gallbladder, cardiomyocytes, male reproductive cells, placental trophoblasts, ductal cells, eye, and vasculature. In the respiratory system, the expression was limited, with no or only low expression in a subset of cells in a few individuals, observed by one antibody only. Our data constitute an important resource for further studies on SARS-CoV-2 host cell entry, in order to understand the biology of the disease and to aid in the development of effective treatments to the viral infection.

Marginal zone lymphoma expression of histidine-rich glycoprotein correlates with improved survival

Purpose

The abundant hepatocyte-expressed plasma protein histidine-rich glycoprotein (HRG) enhances antitumor immunity by polarizing inflammatory and immune cells in several mouse models, however, the clinical relevance of HRG in human cancer is poorly explored. The expression and role of HRG in human B-cell lymphomas was investigated in order to find new tools for prognosis and treatment.

Findings

Immunohistochemical (IHC) analysis and RNA hybridization of tissue microarrays showed that (i) HRG was expressed by tumor cells in marginal zone lymphoma (MZL), in 36% of 59 cases. Expression was also detected in follicular lymphoma (22%), mantle cell lymphoma (19%), and indiffuse large B-cell lymphoma (DLBCL;5%) while primary CNS lymphoma (PCNSL) lacked expression of HRG. (ii) MZL patients positive for HRG showed a superior overall survival outcome (HR = 0.086, 95% CI = 0.014-0.518, P-value = .007), indicating a protective role for HRG independent of stage, age and sex. (iii) HRG-expressing MZL displayed significantly increased transcript and protein levels of the host defense peptide alpha defensin 1. In addition, global transcript analyses showed significant changes in gene ontology terms relating to immunity and inflammation, however, infiltration of immune and inflammatory cells detected by IHC was unaffected by HRG expression.

Conclusion

HRG expression by MZL tumor cells correlates with an altered transcription profile and improved overall survival.

The protein expression profile of ACE2 in human tissues

The novel SARS-coronavirus 2 (SARS-CoV-2) poses a global challenge on healthcare and society. For understanding the susceptibility for SARS-CoV-2 infection, the cell type-specific expression of the host cell surface receptor is necessary. The key protein suggested to be involved in host cell entry is angiotensin I converting enzyme 2 (ACE2). Here, we report the expression pattern of ACE2 across > 150 different cell types corresponding to all major human tissues and organs based on stringent immunohistochemical analysis. The results were compared with several datasets both on the mRNA and protein level. ACE2 expression was mainly observed in enterocytes, renal tubules, gallbladder, cardiomyocytes, male reproductive cells, placental trophoblasts, ductal cells, eye, and vasculature. In the respiratory system, the expression was limited, with no or only low expression in a subset of cells in a few individuals, observed by one antibody only. Our data constitute an important resource for further studies on SARS-CoV-2 host cell entry, in order to understand the biology of the disease and to aid in the development of effective treatments to the viral infection.

Edgetic perturbation signatures represent known and novel cancer biomarkers

Isoform switching is a recently characterized hallmark of cancer, and often translates to the loss or gain of domains mediating protein interactions and thus, the re-wiring of the interactome. Recent computational tools leverage domain-domain interaction data to resolve the condition-specific interaction networks from RNA-Seq data accounting for the domain content of the primary transcripts expressed. Here, we used The Cancer Genome Atlas RNA-Seq datasets to generate 642 patient-specific pairs of interactomes corresponding to both the tumor and the healthy tissues across 13 cancer types. The comparison of these interactomes provided a list of patient-specific edgetic perturbations of the interactomes associated with the cancerous state. We found that among the identified perturbations, select sets are robustly shared between patients at the multi-cancer, cancer-specific and cancer sub-type specific levels. Interestingly, the majority of the alterations do not directly involve significantly mutated genes, nevertheless, they strongly correlate with patient survival. The findings (available at EdgeExplorer: “http://webclu.bio.wzw.tum.de/EdgeExplorer”) are a new source of potential biomarkers for classifying cancer types and the proteins we identified are potential anti-cancer therapy targets.

Computational annotation of miRNA transcription start sites

Motivation

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in gene regulation and phenotype development. The identification of miRNA transcription start sites (TSSs) is critical to understand the functional roles of miRNA genes and their transcriptional regulation. Unlike protein-coding genes, miRNA TSSs are not directly detectable from conventional RNA-Seq experiments due to miRNA-specific process of biogenesis. In the past decade, large-scale genome-wide TSS-Seq and transcription activation marker profiling data have become available, based on which, many computational methods have been developed. These methods have greatly advanced genome-wide miRNA TSS annotation.

Results

In this study, we summarized recent computational methods and their results on miRNA TSS annotation. We collected and performed a comparative analysis of miRNA TSS annotations from 14 representative studies. We further compiled a robust set of miRNA TSSs (RSmirT) that are supported by multiple studies. Integrative genomic and epigenomic data analysis on RSmirT revealed the genomic and epigenomic features of miRNA TSSs as well as their relations to protein-coding and long non-coding genes.

Contact

xiaoman@mail.ucf.edu, haihu@cs.ucf.edu

A comparison of gene expression and DNA methylation patterns across tissues and species

Previously published comparative functional genomic data sets from primates using frozen tissue samples, including many data sets from our own group, were often collected and analyzed using nonoptimal study designs and analysis approaches. In addition, when samples from multiple tissues were studied in a comparative framework, individuals and tissues were confounded. We designed a multitissue comparative study of gene expression and DNA methylation in primates that minimizes confounding effects by using a balanced design with respect to species, tissues, and individuals. We also developed a comparative analysis pipeline that minimizes biases attributable to sequence divergence. Thus, we present the most comprehensive catalog of similarities and differences in gene expression and DNA methylation levels between livers, kidneys, hearts, and lungs, in humans, chimpanzees, and rhesus macaques. We estimate that overall, interspecies and inter-tissue differences in gene expression levels can only modestly be accounted for by corresponding differences in promoter DNA methylation. However, the expression pattern of genes with conserved inter-tissue expression differences can be explained by corresponding interspecies methylation changes more often. Finally, we show that genes whose tissue-specific regulatory patterns are consistent with the action of natural selection are highly connected in both gene regulatory and protein–protein interaction networks.

Alternative Strategy To Explore Missing Proteins with Low Molecular Weight

Identifying more missing proteins (MPs) is an important mission of C-HPP. With the number of identified MPs being attenuated year by year (2,949 to 2,129 MPs from 2016 to 2019), we have realized that the difficulty of exploring the remaining MPs is a challenge in technique. Herein, we propose a comprehensive strategy to effectively enrich, separate, and identify proteins with low molecular weights, aiming at the discovery of MPs. Basically, a protein extract from human placenta was passed through a C18 SPE column, and the bound proteins that were eluted were further separated with an SDS-PAGE gel or a 50 kDa cutoff filter. The separated proteins were subjected to trypsin digestion, and the MS/MS signals were searched against data sets with two different digestion modes (full-trypsin and semitrypsin). The strategy was adopted, resulting in the identification of 4 MPs with 8 unique peptides (≥2 non-nested unique peptides with ≥9 amino acids). Importantly, the identification of 6 out of 8 of the unique peptides derived from the MPs was further supported by parallel reaction monitoring, which confirmed the identification of 3 MPs from human placenta tissues (Q6NT89: TMF-regulated nuclear protein 1; A0A183: late cornified envelope protein 6A; and Q6UWQ7: insulin growth factor-like family member 2, mapped to chromosomes 1, 1, and 19, respectively). The three proteins ranged in length from 80 aa to 227 aa. The study not only establishes a feasible strategy for analyzing proteins with low molecular weights but also fills a small part of a large gap in the list of MPs. The data obtained in this study are available via ProteomeXchange (PXD014083) and PeptideAtlas (PASS01389).

Human Antigen Leucocyte (HLA)-G and HLA-E are differentially expressed in pancreatic disorders

BACKGROUND

Little information is available regarding the expression of the immunomodulatory Human Leukocyte Antigen (HLA)-G and -E molecules in pancreatic disorders.

AIM

To analyze HLA-G and -E expression in specimens of alcoholic chronic pancreatitis (ACP), idiopathic chronic pancreatitis (ICP), type 1 (T1D) and type 2 diabetes (T2D) and in histologically normal pancreas (HNP).

METHODS

HLA-G and -E expression (ACP = 30, ICP = 10, T1D = 10, T2D = 30 and HNP = 20) was evaluated by immunohistochemistry in three different areas (acini, islets and inflammatory infiltrate).

RESULTS

Acini and islets from HNP specimens exhibited higher HLA-G and -E expression compared to corresponding areas from all other patient groups. In inflammatory infiltrate, HLA-G and -E expression was observed only among the pancreatic disorders. We observed higher HLA-G and -E expression in acini from T2D compared to ACP, as well as higher HLA-G expression compared to ICP.

CONCLUSION

The decreased expression of HLA-G and -E in islets and acini together with the expression of these molecules in the inflammatory infiltrating cells were shared features among chronic inflammatory and autoimmune pancreatic disorders evaluated in this study, possibly reflecting tissue damage.

Molecular Pathogenesis of Membranous Nephropathy

Membranous nephropathy is a noninflammatory autoimmune disease of the kidney glomerulus, characterized by the formation of immune deposits, complement-mediated proteinuria, and risk of renal failure. Considerable advances in understanding the molecular pathogenesis have occurred with the identification of several antigens [neutral endopeptidase, phospholipase A2 receptor (PLA₂R), thrombospondin domain-containing 7A (THSD7A)] in cases arising from the neonatal period to adulthood and the characterization of antibody-binding domains (that is, epitopes). Immunization against PLA2R occurs in 70% to 80% of adult cases. The development of highly specific and sensitive assays of circulating antibodies has induced a paradigm shift in diagnosis and treatment monitoring. In addition, several interacting loci in HLA-DQ, HLA-DR, and PLA2R1, as well as classical human leukocyte antigen (HLA)-D alleles have been identified as being risk factors, depending on a patient's ethnicity. Additionally, mechanisms of antibody pathogenicity and pathways of complement activation are now better understood. Further research is mandatory for designing new therapeutic strategies, including the identifying triggering events, the molecular bases of remission and progression, and the T cell epitopes involved.

MAPCap allows high-resolution detection and differential expression analysis of transcription start sites

The position, shape and number of transcription start sites (TSS) are critical determinants of gene regulation. Most methods developed to detect TSSs and study promoter usage are, however, of limited use in studies that demand quantification of expression changes between two or more groups. In this study, we combine high-resolution detection of transcription start sites and differential expression analysis using a simplified TSS quantification protocol, MAPCap (Multiplexed Affinity Purification of Capped RNA) along with the software icetea. Applying MAPCap on developing Drosophila melanogaster embryos and larvae, we detected stage and sex-specific promoter and enhancer activity and quantify the effect of mutants of maleless (MLE) helicase at X-chromosomal promoters. We observe that MLE mutation leads to a median 1.9 fold drop in expression of X-chromosome promoters and affects the expression of several TSSs with a sexually dimorphic expression on autosomes. Our results provide quantitative insights into promoter activity during dosage compensation.

The position, shape and number of transcription start sites (TSS) regulate gene expression. Here authors present MAPCap, a method for high-resolution detection and differential expression analysis of TSS, and apply MAPCap to early fly development, detecting stage and sex-specific promoter and enhancer activity.

Complete Inactivation of Sebum-Producing Genes Parallels the Loss of Sebaceous Glands in Cetacea

Genomes are dynamic biological units, with processes of gene duplication and loss triggering evolutionary novelty. The mammalian skin provides a remarkable case study on the occurrence of adaptive morphological innovations. Skin sebaceous glands (SGs), for instance, emerged in the ancestor of mammals serving pivotal roles, such as lubrication, waterproofing, immunity, and thermoregulation, through the secretion of sebum, a complex mixture of various neutral lipids such as triacylglycerol, free fatty acids, wax esters, cholesterol, and squalene. Remarkably, SGs are absent in a few mammalian lineages, including the iconic Cetacea. We investigated the evolution of the key molecular components responsible for skin sebum production: Dgat2l6, Awat1, Awat2, Elovl3, Mogat3, and Fabp9. We show that all analyzed genes have been rendered nonfunctional in Cetacea species (toothed and baleen whales). Transcriptomic analysis, including a novel skin transcriptome from blue whale, supports gene inactivation. The conserved mutational pattern found in most analyzed genes, indicates that pseudogenization events took place prior to the diversification of modern Cetacea lineages. Genome and skin transcriptome analysis of the common hippopotamus highlighted the convergent loss of a subset of sebum-producing genes, notably Awat1 and Mogat3. Partial loss profiles were also detected in non-Cetacea aquatic mammals, such as the Florida manatee, and in terrestrial mammals displaying specialized skin phenotypes such as the African elephant, white rhinoceros and pig. Our findings reveal a unique landscape of “gene vestiges” in the Cetacea sebum-producing compartment, with limited gene loss observed in other mammalian lineages: suggestive of specific adaptations or specializations of skin lipids.

Expression profile and functional role of S100A14 in human cancer

S100A14 is one of the new members of the multi-functional S100 protein family. Expression of S100A14 is highly heterogeneous among normal human tissues, suggesting that the regulation of S100A14 expression and its function may be tissue- and context-specific. Compared to the normal counterparts, S100A14 mRNA and protein levels have been found to be deregulated in several cancer types, indicating a functional link between S100A14 and malignancies. Accordingly, S100A14 is functionally linked with a number of key signaling molecules such as p53, p21, MMP1, MMP9, MMP13, RAGE, NF-kB, JunB, actin and HER2. Of interest, S100A14 seems to have seemingly opposite functions in malignancies arising from the gastrointestional tract (tissues rich in epithelial components) compared to cancers in the other parts of the body (tissues rich in mesenchymal components). The underlying mechanism for these observations are currently unclear and may be related to the relative abundance and differences in the type of interaction partners (effector protein) in different cancer types and tissues. In addition, several studies indicate that the expression pattern of S100A14 has a potential to be clinically useful as prognostic biomarker in several cancer types. This review attempts to provide a comprehensive summary on the expression pattern and functional roles/related molecular pathways in different cancer types. Additionally, the prognostic potential of S100A14 in the management of human malignancies will be discussed.

Altered Expression and Localization of Tumor Suppressive E3 Ubiquitin Ligase SMURF2 in Human Prostate and Breast Cancer

SMURF2, an E3 ubiquitin ligase and suggested tumor suppressor, operates in normal cells to prevent genomic instability and carcinogenesis. However, the mechanisms underlying SMURF2 inactivation in human malignancies remain elusive, as SMURF2 is rarely found mutated or deleted in cancers. We hypothesized that SMURF2 might have a distinct molecular biodistribution in cancer versus normal cells and tissues. The expression and localization of SMURF2 were analyzed in 666 human normal and cancer tissues, with primary focus on prostate and breast tumors. These investigations were accompanied by SMURF2 gene expression analyses, subcellular fractionation and biochemical studies, including SMURF2’s interactome analysis. We found that while in normal cells and tissues SMURF2 has a predominantly nuclear localization, in prostate and aggressive breast carcinomas SMURF2 shows a significantly increased cytoplasmic sequestration, associated with the disease progression. Mechanistic studies showed that the nuclear export machinery was not involved in cytoplasmic accumulation of SMURF2, while uncovered that its stability is markedly increased in the cytoplasmic compartment. Subsequent interactome analyses pointed to 14-3-3s as SMURF2 interactors, which could potentially affect its localization. These findings link the distorted expression of SMURF2 to human carcinogenesis and suggest the alterations in SMURF2 localization as a potential mechanism obliterating its tumor suppressor activities.

The role of IRAK1 in breast cancer patients treated with neoadjuvant chemotherapy

Background

IRAK1 has been shown to be abnormally expressed in a set of tumors leading to tumorigenesis and progression. IRAK1 is a therapeutic target that drives breast cancer metastasis and resistance to paclitaxel. However, the exact role of IRAK1 in neoadjuvant chemotherapy (NCT) for breast cancer remains unclear. The aim of this study was to investigate the relationship between the expression of IRAK1 and the clinicopathological parameters and survival prognosis of breast cancer patients treated with NCT.

Patients and methods

Based on the clinical data and mRNA microarray data from 1,085 breast cancer patients in The Cancer Genome Atlas, the correlation between IRAK1 expression and clinicopathological parameters of breast cancer was analyzed. Immunohistochemistry was performed to evaluate the expression of IRAK1. The Human Protein Atlas and the String database were used to analyze the expression of IRAK1 protein and its interaction with altered neighboring proteins in breast cancer. IRAK1 alteration was analyzed in cBioPortal database. GEO enrichment of IRAK1 was performed using WEB-based Gene SeT AnaLysis Toolkit.

Results

The expression of IRAK1 was significantly downregulated following NCT. The decreased expression of IRAK1 following NCT was positively correlated with reduced tumor size. Finally, survival analysis confirmed that a shorter survival period was correlated to higher expression of IRAK1 both before and after NCT.

Conclusion

These findings advanced our understanding about the expression pattern of IRAK1 in breast cancer, especially in those patients who were treated with NCT, suggesting that IRAK1 could be used as a prognostic indicator, as well as a potential indicator for evaluating NCT efficacy for breast cancer patients.

The Transcriptomic Landscape of Yaks Reveals Molecular Pathways for High Altitude Adaptation

Yak is one of the largest native mammalian species at the Himalayas, the highest plateau area in the world with an average elevation of >4,000 m above the sea level. Yak is well adapted to high altitude environment with a set of physiological features for a more efficient blood flow for oxygen delivery under hypobaric hypoxia. Yet, the genetic mechanism underlying its adaptation remains elusive. We conducted a cross-tissue, cross-altitude, and cross-species study to characterize the transcriptomic landscape of domestic yaks. The generated multi-tissue transcriptomic data greatly improved the current yak genome annotation by identifying tens of thousands novel transcripts. We found that among the eight tested tissues (lung, heart, kidney, liver, spleen, muscle, testis, and brain), lung and heart are two key organs showing adaptive transcriptional changes and >90% of the cross-altitude differentially expressed genes in lung display a nonlinear regulation. Pathways related to cell survival and proliferation are enriched, including PI3K-Akt, HIF-1, focal adhesion, and ECM–receptor interaction. These findings, in combination with the comprehensive transcriptome data set, are valuable to understanding the genetic mechanism of hypoxic adaptation in yak.

Local genetic ancestry in CDKN2B-AS1 is associated with primary open-angle glaucoma in an African American cohort extracted from de-identified electronic health records

BACKGROUND

Glaucoma is a leading cause of blindness in developed countries. Primary open-angle glaucoma (POAG), the most prevalent clinical subtype of glaucoma in the United States, affects African Americans at a higher rate compared with European Americans. Risk factors identified for POAG include increased age and family history, which coupled with heritability estimates, suggest this complex condition is associated with genetic and environmental factors. To date, several genome-wide studies have identified loci significantly associated with POAG risk, but most of these studies were performed in populations of European-descent.

METHODS

To identify population-specific and trans-population genetic associations for POAG, we genotyped 11,521 African Americans using the Illumina Metabochip as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study accessing BioVU, the Vanderbilt University Medical Center's biorepository linked to de-identified electronic health records. Among this study population, we identified 138 cases of POAG and 1376 controls and performed Metabochip-wide tests of association. We also estimated local genetic ancestry at CDKN2B-AS1, a POAG-associated locus established in European-descent populations.

RESULTS

Overall, we did not identify significant single SNP-POAG associations after adjusting for multiple testing. We did, however, detect a significant association between POAG risk and local African genetic ancestry at CDKN2B-AS1, where on average cases were of 90% African descent compared with controls at 58% (p = 2 × 10- 6).

CONCLUSIONS

These data suggest that CDKN2B-AS1 is an important locus for POAG risk among African Americans, warranting further investigation to identify the variants underlying this association.

CTCF maintains regulatory homeostasis of cancer pathways

BACKGROUND

CTCF binding to DNA helps partition the mammalian genome into discrete structural and regulatory domains. Complete removal of CTCF from mammalian cells causes catastrophic genome dysregulation, likely due to widespread collapse of 3D chromatin looping and alterations to inter- and intra-TAD interactions within the nucleus. In contrast, Ctcf hemizygous mice with lifelong reduction of CTCF expression are viable, albeit with increased cancer incidence. Here, we exploit chronic Ctcf hemizygosity to reveal its homeostatic roles in maintaining genome function and integrity.

RESULTS

We find that Ctcf hemizygous cells show modest but robust changes in almost a thousand sites of genomic CTCF occupancy; these are enriched for lower affinity binding events with weaker evolutionary conservation across the mouse lineage. Furthermore, we observe dysregulation of the expression of several hundred genes, which are concentrated in cancer-related pathways, and are caused by changes in transcriptional regulation. Chromatin structure is preserved but some loop interactions are destabilized; these are often found around differentially expressed genes and their enhancers. Importantly, the transcriptional alterations identified in vitro are recapitulated in mouse tumors and also in human cancers.

CONCLUSIONS

This multi-dimensional genomic and epigenomic profiling of a Ctcf hemizygous mouse model system shows that chronic depletion of CTCF dysregulates steady-state gene expression by subtly altering transcriptional regulation, changes which can also be observed in primary tumors.

N-α-acetyltransferase 10 (NAA10) in development: the role of NAA10

N-α-acetyltransferase 10 (NAA10) is a subunit of N^α-terminal protein acetyltransferase that plays a role in many biological processes. Among the six N-α-acetyltransferases (NATs) in eukaryotes, the biological significance of the N-terminal acetyl-activity of Naa10 has been the most studied. Recent findings in a few species, including humans, indicate that loss of N-terminal acetylation by NAA10 is associated with developmental defects. However, very little is known about the role of NAA10, and more research is required in relation to the developmental process. This review summarizes recent studies to understand the function of NAA10 in the development of multicellular organisms.

Further investigations are needed into the role of a key enzyme in biological development and its encoding gene. The enzyme N-α-acetyltransferase 10 (NAA10), encoded by the NAA10 gene, plays a role in multiple biological processes. While the function of NAA10 has been studied in cancer, less is known about the roles of the gene and the enzyme during development, according to a review by Goo Taeg Oh and co-workers at the Ewha Womans University in Seoul, South Korea. Mutations in NAA10 are found in patients with developmental delay, cardiac problems and skeletal abnormalities, while reduced enzyme activity is associated with developmental defects. Mouse studies suggest a role for NAA10 in neuronal development, bone formation and healthy sperm generation. The impact of variable NAA10 expression in different organs at different developmental stages needs clarification.

Liver-enriched Genes are Associated with the Prognosis of Patients with Hepatocellular Carcinoma

Tissue-enriched genes are highly expressed in one particular tissue type and represent distinct physiological processes. The dynamic profile of tissue-enriched genes during tumorigenesis and progression remains largely unstudied. Here, we identified tissue-enriched genes from 12 tissue types based on RNA sequencing data from the Cancer Genome Atlas (TCGA), and found that the liver had the largest number of such genes among the 12 tissue types. The characteristics of liver-enriched genes were further investigated. Most liver-enriched genes were downregulated and metabolism-related genes, which were associated with pathological stage and dedifferentiation in patients with hepatocellular carcinoma (HCC). Hypermethylation might be a mechanism underlying the downregulation of liver-enriched genes. We constructed a liver-enriched gene set and demonstrated that it is associated with the prognosis of the patients with HCC both in the TCGA cohort and the Gene Expression Omnibus (GEO) datasets. Moreover, we discovered that the degree of the dissimilarity between tumors and normal tissues was correlated with the prognosis of patients with HCC and the biological behaviours of the tumors. These results will help identify prognostic biomarkers of patients with HCC, and enhance our understanding of the molecular mechanisms of hepatocarcinogenesis and progression.

Systems biology in hepatology: approaches and applications

Detailed insights into the biological functions of the liver and an understanding of its crosstalk with other human tissues and the gut microbiota can be used to develop novel strategies for the prevention and treatment of liver-associated diseases, including fatty liver disease, cirrhosis, hepatocellular carcinoma and type 2 diabetes mellitus. Biological network models, including metabolic, transcriptional regulatory, protein-protein interaction, signalling and co-expression networks, can provide a scaffold for studying the biological pathways operating in the liver in connection with disease development in a systematic manner. Here, we review studies in which biological network models were used to integrate multiomics data to advance our understanding of the pathophysiological responses of complex liver diseases. We also discuss how this mechanistic approach can contribute to the discovery of potential biomarkers and novel drug targets, which might lead to the design of targeted and improved treatment strategies. Finally, we present a roadmap for the successful integration of models of the liver and other human tissues with the gut microbiota to simulate whole-body metabolic functions in health and disease.

Inferring the effect of genomic variation in the new era of genomics

Accurate and detailed understanding of the effects of variants in the coding and noncoding regions of the genome is the next big challenge in the new genomic era of personalized medicine, especially to tackle newer findings of genetic and phenotypic heterogeneity of diseases. This is necessary to resolve the gene-variant-disease relationship, the pathogenic variant spectrum of genes, pathogenic variants with variable clinical consequences, and multiloci diseases. In turn, this will facilitate patient recruitment for relevant clinical trials. In this review, we describe the trends in research at the intersection of basic and clinical genomics aiming to (a) overcome molecular diagnostic challenges and increase the clinical utility of next-generation sequencing (NGS) platforms, (b) elucidate variants associated with disease, (c) determine overall genomic complexity including epistasis, complex inheritance patterns such as "synergistic heterozygosity," digenic/multigenic inheritance, modifier effect, and rare variant load. We describe the newly emerging field of integrated functional genomics, in vivo or in vitro large-scale functional approaches, statistical bioinformatics algorithms that support NGS genomics data to interpret variants for timely clinical diagnostics and disease management. Thus, facilitating the discovery of new therapeutic or biomarker options, and their roles in the future of personalized medicine.

Quantitative mapping of genetic similarity in human heritable diseases by shared mutations

Many genetic diseases exhibit considerable epidemiological comorbidity and common symptoms, which provokes debate about the extent of their etiological overlap. The rapid growth in the number of known disease-causing mutations in the Human Gene Mutation Database (HGMD) has allowed us to characterize genetic similarities between diseases by ascertaining the extent to which identical genetic mutations are shared between diseases. Using this approach, we show that 41.6% of disease pairs in all possible pairs (42, 083) exhibit a significant sharing of mutations (P value < 0.05). These mutation-related disease pairs are in agreement with heritability-based disease-disease relations in 48 neurological and psychiatric disease pairs (Spearman's correlation coefficient = 0.50; P value = 3.4 × 10^-5 ), and share over-expressed genes significantly more often than unrelated disease pairs (1.5-1.8-fold higher; P value ≤ 1.6 × 10^-4 ). The usefulness of mutation-related disease pairs was further demonstrated for predicting novel mutations and identifying individuals susceptible to Crohn disease. Moreover, the mutation-based disease network concurs closely with that based on phenotypes.

A liver-specific gene expression panel predicts the differentiation status of in vitro hepatocyte models

Alternative cell sources, such as three-dimensional organoids and induced pluripotent stem cell-derived cells, might provide a potentially effective approach for both drug development applications and clinical transplantation. For example, the development of cell sources for liver cell-based therapy has been increasingly needed, and liver transplantation is performed for the treatment for patients with severe end-stage liver disease. Differentiated liver cells and three-dimensional organoids are expected to provide new cell sources for tissue models and revolutionary clinical therapies. However, conventional experimental methods confirming the expression levels of liver-specific lineage markers cannot provide complete information regarding the differentiation status or degree of similarity between liver and differentiated cell sources. Therefore, in this study, to overcome several issues associated with the assessment of differentiated liver cells and organoids, we developed a liver-specific gene expression panel (LiGEP) algorithm that presents the degree of liver similarity as a "percentage." We demonstrated that the percentage calculated using the LiGEP algorithm was correlated with the developmental stages of in vivo liver tissues in mice, suggesting that LiGEP can correctly predict developmental stages. Moreover, three-dimensional cultured HepaRG cells and human pluripotent stem cell-derived hepatocyte-like cells showed liver similarity scores of 59.14% and 32%, respectively, although general liver-specific markers were detected.

CONCLUSION

Our study describes a quantitative and predictive model for differentiated samples, particularly liver-specific cells or organoids; and this model can be further expanded to various tissue-specific organoids; our LiGEP can provide useful information and insights regarding the differentiation status of in vitro liver models. (Hepatology 2017;66:1662-1674).

The human protein atlas: A spatial map of the human proteome

The correct spatial distribution of proteins is vital for their function and often mis-localization or ectopic expression leads to diseases. For more than a decade, the Human Protein Atlas (HPA) has constituted a valuable tool for researchers studying protein localization and expression in human tissues and cells. The centerpiece of the HPA is its unique antibody collection for mapping the entire human proteome by immunohistochemistry and immunocytochemistry. By these approaches, more than 10 million images showing protein expression patterns at a single-cell level were generated and are publicly available at www.proteinatlas.org. The antibody-based approach is combined with transcriptomics data for an overview of global expression profiles. The present article comprehensively describes the HPA database functions and how users can utilize it for their own research as well as discusses the future path of spatial proteomics.

A high resolution atlas of gene expression in the domestic sheep (Ovis aries)

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

FARNA: knowledgebase of inferred functions of non-coding RNA transcripts

Non-coding RNA (ncRNA) genes play a major role in control of heterogeneous cellular behavior. Yet, their functions are largely uncharacterized. Current available databases lack in-depth information of ncRNA functions across spectrum of various cells/tissues. Here, we present FARNA, a knowledgebase of inferred functions of 10,289 human ncRNA transcripts (2,734 microRNA and 7,555 long ncRNA) in 119 tissues and 177 primary cells of human. Since transcription factors (TFs) and TF co-factors (TcoFs) are crucial components of regulatory machinery for activation of gene transcription, cellular processes and diseases in which TFs and TcoFs are involved suggest functions of the transcripts they regulate. In FARNA, functions of a transcript are inferred from TFs and TcoFs whose genes co-express with the transcript controlled by these TFs and TcoFs in a considered cell/tissue. Transcripts were annotated using statistically enriched GO terms, pathways and diseases across cells/tissues based on guilt-by-association principle. Expression profiles across cells/tissues based on Cap Analysis of Gene Expression (CAGE) are provided. FARNA, having the most comprehensive function annotation of considered ncRNAs across widest spectrum of human cells/tissues, has a potential to greatly contribute to our understanding of ncRNA roles and their regulatory mechanisms in human. FARNA can be accessed at: http://cbrc.kaust.edu.sa/farna

PLA2R and THSD7A: Disparate Paths to the Same Disease?

The phospholipase A2 receptor (PLA2R) and thrombospondin type-1 domain-containing 7A (THSD7A) are the two major autoantigens in primary membranous nephropathy (MN), and define two molecular subclasses of this disease. Both proteins are large transmembrane glycoproteins expressed by the podocyte, and both induce IgG4-predominant humoral immune responses that produce circulating autoantibodies that can be used clinically for diagnostic and monitoring purposes. The biologic roles of these proteins remain speculative, although several features of THSD7A suggest a role in adhesion. PLA2R-associated MN was initially found to associate with risk alleles within HLA-DQA1, but subsequent studies have shifted the focus to the HLA-DRB locus. Three distinct humoral epitope-containing regions have been defined within the extracellular portion of PLA2R, and it appears that the number of targeted epitopes may determine disease severity. Although similar information is not yet available for THSD7A-associated MN, this form of MN may have a unique association with malignancy. Finally, it appears likely that other autoantigens in primary MN exist. Although protocols similar to those that identified PLA2R and THSD7A may be successful in the identification of novel antigenic targets in MN, newer techniques such as laser-capture mass spectrometry or protein arrays may be helpful as well.

Relevance of tissue specific subunit expression in channelopathies

Channelopathies are a diverse group of human disorders that are caused by mutations in genes coding for ion channels or channel-regulating proteins. Several dozen channelopathies have been identified that involve both non-excitable cells as well as electrically active tissues like brain, skeletal and smooth muscle or the heart. In this review, we start out from the general question which ion channel genes are expressed tissue-selectively. We mined the human gene expression database Human Protein Atlas (HPA) for tissue-enriched ion channel genes and found 85 genes belonging to the ion channel families. Most of these genes were enriched in brain, testis and muscle and a complete list of the enriched ion channel genes is provided. We further focused on the tissue distribution of voltage-gated calcium channel (VGCC) genes including different brain areas and the retina based on the human gene expression from the FANTOM5 dataset. The expression data is complemented by an overview of the tissue-dependent aspects of L-type calcium channel (LTCC) function, dysfunction and pharmacology, as well as of their splice variants. Finally, we focus on the pathology of tissue-restricted LTCC channelopathies and their treatment options. This article is part of the Special Issue entitled 'Channelopathies.'

A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq

The mouse has been widely used as a model organism for studying human diseases and for evaluating drug safety and efficacy. Many diseases and drug effects exhibit tissue specificity that may be reflected by tissue-specific gene-expression profiles. Here we construct a comprehensive mouse transcriptomic BodyMap across 17 tissues of six-weeks old C57BL/6JJcl mice using RNA-seq. We find different expression patterns between protein-coding and non-coding genes. Liver expressed the least complex transcriptomes, that is, the smallest number of genes detected in liver across all 17 tissues, whereas testis and ovary harbor more complex transcriptomes than other tissues. We report a comprehensive list of tissue-specific genes across 17 tissues, along with a list of 4,781 housekeeping genes in mouse. In addition, we propose a list of 27 consistently and highly expressed genes that can be used as reference controls in expression-profiling analysis. Our study provides a unique resource of mouse gene-expression profiles, which is helpful for further biomedical research.

The FANTOM5 Computation Ecosystem: Genomic Information Hub for Promoters and Active Enhancers

The Functional Annotation of the Mammalian Genome 5 (FANTOM5) project conducted transcriptome analysis of various mammalian cell types and provided a comprehensive resource to understand transcriptome and transcriptional regulation in individual cellular states encoded in the genome.FANTOM5 used cap analysis of gene expression (CAGE) with single-molecule sequencing to map transcription start sites (TSS) and measured their expression in a diverse range of samples. The main results from FANTOM5 were published as a promoter-level mammalian expression atlas and an atlas of active enhancers across human cell types. The FANTOM5 dataset is composed of raw experimental data and the results of bioinformatics analyses. In this chapter, we give a detailed description of the content of the FANTOM5 dataset and elaborate on different computing applications developed to publish the data and enable reproducibility and discovery of new findings. We present use cases in which the FANTOM5 dataset has been reused, leading to new findings.

Transcriptomics resources of human tissues and organs

Quantifying the differential expression of genes in various human organs, tissues, and cell types is vital to understand human physiology and disease. Recently, several large‐scale transcriptomics studies have analyzed the expression of protein‐coding genes across tissues. These datasets provide a framework for defining the molecular constituents of the human body as well as for generating comprehensive lists of proteins expressed across tissues or in a tissue‐restricted manner. Here, we review publicly available human transcriptome resources and discuss body‐wide data from independent genome‐wide transcriptome analyses of different tissues. Gene expression measurements from these independent datasets, generated using samples from fresh frozen surgical specimens and postmortem tissues, are consistent. Overall, the different genome‐wide analyses support a distribution in which many proteins are found in all tissues and relatively few in a tissue‐restricted manner. Moreover, we discuss the applications of publicly available omics data for building genome‐scale metabolic models, used for analyzing cell and tissue functions both in physiological and in disease contexts.