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There has been a significant increase in the use of assisted reproductive therapies (ARTs) over the past several decades, allowing many couples with infertility to conceive. Despite the achievements in this field, a mounting body of evidence concerning the epigenetic risks associated with ART interventions such as ovarian hormonal stimulation, intracytoplasmic sperm injection (ICSI), and

Male infertility is a disorder of the reproductive system with a highly complex genetic landscape. In most cases, the reason for male infertility remains unknown; however, the importance of genetic abnormalities in the diagnosis of subfertility/infertility is becoming increasingly recognized. Several syndromes include impaired male fertility in the clinical picture, although a comprehensive analysis of genetic causes of the syndromology perspective of male reproduction is not yet available.(1) To develop a catalog of syndromes and corresponding genes associated with impaired male fertility and (2) to visualize an up-to-date genome-phenome network of syndromic male subfertility.Published literature was retrieved from the Online Mendelian Inheritance in Man, Orphanet, Human Phenotype Ontology and PubMed databases using keywords "male infertility," "syndrome," "gene," and "case report"; time period from 1980 to September, 2021. Retrieved data were organized as a catalog and complemented with identification numbers of syndromes (MIM ID) and genes (Gene ID). The genome-phenome network and the phenome network were visualized using Cytoscape and Gephi software platforms. Protein-protein interaction analysis was performed using STRING tool.Retrieved syndromes were presented as (1) a catalog containing 63 syndromes and 93 associated genes, (2) a genome-phenome network including CHD7 and WT1 genes and Noonan and Kartagener syndromes, and (3) a phenome network including 63 syndromes, and 25 categories of clinical features.The developed catalog will contribute to the advances and translational impact toward understanding the factors of syndromic male infertility. Visualized networks provide simple, flexible tools for clinicians and researchers to quickly generate hypotheses and gain a deeper understanding of underlying mechanisms affecting male reproduction.Recognition of the significance of genome-phenome visualization as part of network medicine can help expedite efforts toward unravelling molecular mechanisms and enable advances personal/precision medicine of male reproduction and other complex traits.

In this perspective analysis, we strive to answer the following question: how can we advance integrative biology research in the 21st century with lessons from animal science? At the University of Ljubljana, Biotechnical Faculty, Department of Animal Science, we share here our three lessons learned in the two decades from 2002 to 2022 that we believe could inform integrative biology, systems science, and animal science scholarship in other countries and geographies. Cultivating multiomics knowledge through a conceptual lens of integrative biology is crucial for life sciences research that can stand the test of diverse biological, clinical, and ecological contexts. Moreover, in an era of the current COVID-19 pandemic, animal nutrition and animal science, and the study of their interactions with human health (and vice versa) through integrative biology approaches hold enormous prospects and significance for systems medicine and ecosystem health.

STUDY QUESTION Are de novo mutations in the human genome associated with male infertility? SUMMARY ANSWER We identified de novo mutations in five candidate genes: SEMA5A, NEURL4, BRD2, CD1D, and CD63. WHAT IS KNOWN ALREADY Epidemiological and genetic studies have consistently indicated contribution of genetic factors to the etiology of male infertility, suggesting that more than 1500 genes are involved in spermatogenesis. STUDY DESIGN, SIZE, DURATION First, we searched for de novo mutations in patients with idiopathic azoospermia with whole-exome sequencing (WES). To evaluate the potential functional impact of de novo identified mutations, we analyzed their expression differences on independent testis samples with normal and impaired spermatogenesis. In the next step, we tested additional group of azoospermic patients for mutations in identified genes with de novo mutations. In addition to the analysis of de novo mutations in patients with idiopathic azoospermia, we considered other models of inheritance and searched for candidate genes harboring rare maternally inherited variants and biallelic autosomal and X-chromosome hemizygous variants. PARTICIPANTS/MATERIALS, SETTING, METHODS We performed WES in 13 infertile males with idiopathic azoospermia and their parents. Potential functional impact of de novo identified mutations was evaluated by global gene expression profiling on 20 independent testis samples. To replicate the results, we performed WES in further 16 independent azoospermic males, which were screened for the variants in the same genes. Library preparation was performed with Nextera Coding Exome Capture Kit (Illumina), with subsequent sequencing on Illumina HiSeq 2500 platform. MAIN RESULTS AND THE ROLE OF CHANCE We identified 11 de novo mutations in 10 genes of which 5 were considered potentially associated with azoospermia: SEMA5A, NEURL4, BRD2, CD1D, and CD63. All candidate genes showed significant differential expression in testis samples composed of patients with severely impaired and normal spermatogenesis. Additionally, we identified rare, potentially pathogenic mutations in the genes previously implicated in male infertility-a maternally inherited heterozygous frameshift variant in FKBPL gene and inframe deletion in UPF2 gene, homozygous frameshift variant in CLCA4 gene, and a heterozygous missense variant NR0B1 gene, which represent promising candidates for further clinical implication. LIMITATIONS OF THE STUDY, REASONS FOR CAUTION We provided limited functional support for involvement of de novo identified genes in pathogenesis of male infertility, based on expression analysis. Additionally, the sample size was limited. WIDER IMPLICATIONS OF THE FINDINGS We provide support that de novo mutations might contribute to male infertility and propose five genes as potentially implicated in its pathogenesis.

Leukemias are a group of malignancies of the blood and bone marrow. Multiple types of leukemia are known, however reliable treatments have not been developed for most leukemia types. Furthermore, even relatively reliable treatments can result in relapses. MicroRNAs (miRNAs) are a class of short, noncoding RNAs responsible for epigenetic regulation of gene expression and have been proposed as a source of potential novel therapeutic targets for leukemias. In order to identify central miRNAs for leukemia, we conducted data synthesis using two databases: miRTarBase and DISNOR. A total of 137 unique miRNAs associated with 16 types of leukemia were retrieved from miRTarBase and 86 protein-coding genes associated with leukemia were retrieved from the DISNOR database. Based on these data, we formed a visual network of 248 miRNA-target interactions (MTI) between leukemia-associated genes and miRNAs associated with ≥4 leukemia types. We then manually reviewed the literature describing these 248 MTIs for interactions identified in leukemia studies. This manually curated data was then used to visualize a network of 64 MTIs identified in leukemia patients, cell lines and animal models. We also formed a visual network of miRNA-leukemia associations. Finally, we compiled leukemia clinical trials from the ClinicalTrials database. miRNAs with the highest number of MTIs were miR-125b-5p, miR-155-5p, miR-181a-5p and miR-19a-3p, while target genes with the highest number of MTIs were TP53, BCL2, KIT, ATM, RUNX1 and ABL1. The analysis of 248 MTIs revealed a large, highly interconnected network. Additionally, a large MTI subnetwork was present in the network visualized from manually reviewed data. The interconnectedness of the MTI subnetwork suggests that certain miRNAs represent central disease molecules for multiple leukemia types. Additional studies on miRNAs, their target genes and associated biological pathways are required to elucidate the therapeutic potential of miRNAs in leukemia.

Circular RNAs (circRNAs) are increasingly recognized as having a role in cancer development. Their expression is modified in numerous cancers, including hepatocellular carcinoma (HCC), however, little is known about the mechanisms of their regulation. The aim of this study was to identify regulators of circRNAome expression in HCC. Using publicly available datasets, we identified RNA binding proteins (RBPs) with enriched motifs around the splice sites of differentially expressed circRNAs in HCC. We confirmed the binding of some of the candidate RBPs using ChIP-seq and eCLIP datasets in the ENCODE database. Several of the identified RBPs were found to be differentially expressed in HCC and/or correlated with the overall survival of HCC patients. According to our bioinformatics analyses and published evidence, we propose that NONO, PCPB2, PCPB1, ESRP2, and HNRNPK are candidate regulators of circRNA expression in HCC. We confirmed that the knocking down the epithelial splicing regulatory protein 2 (ESRP2), known to be involved in the maintenance of the adult liver phenotype, significantly changed the expression of candidate circRNAs in a model HCC cell line. By understanding the systemic changes in transcriptome splicing, we can identify new proteins involved in the molecular pathways leading to HCC development and progression.

Endothelial PAS domain-containing protein 1 (EPAS1), also HIF2α, is an alpha subunit of hypoxia-inducible transcription factor (HIF), which mediates cellular and systemic response to hypoxia. EPAS1 has an important role in the transcription of many hypoxia-responsive genes, however, it has been less researched than HIF1α. The aim of this study was to integrate an increasing number of data on EPAS1 into a map of diverse OMICs elements. Publications, databases, and bioinformatics tools were examined, including Ensembl, MethPrimer, STRING, miRTarBase, COSMIC, and LOVD. The EPAS1 expression, stability, and activity are tightly regulated on several OMICs levels to maintain complex oxygen homeostasis. In the integrative EPAS1 map we included: 31 promoter-binding proteins, 13 interacting miRNAs and one lncRNA, and 16 post-translational modifications regulating EPAS1 protein abundance. EPAS1 has been associated with various cancer types and other diseases. The development of neuroendocrine tumors and erythrocytosis was shown to be associated with 11 somatic and 20 germline variants. The integrative map also includes 12 EPAS1 target genes and 27 interacting proteins. The study introduced the first integrative map of diverse genomics, transcriptomics, proteomics, regulomics, and interactomics data associated with EPAS1, to enable a better understanding of EPAS1 activity and regulation and support future research.

Multiomics study designs have significantly increased understanding of complex biological systems. The multiomics literature is rapidly expanding and so is their heterogeneity. However, the intricacy and fragmentation of omics data are impeding further research. To examine current trends in multiomics field, we reviewed 52 articles from PubMed and Web of Science, which used an integrated omics approach, published between March 2006 and January 2021. From studies, data regarding investigated loci, species, omics type, and phenotype were extracted, curated, and streamlined according to standardized terminology, and summarized in a previously developed graphical summary. Evaluated studies included 21 omics types or applications of omics technology such as genomics, transcriptomics, metabolomics, epigenomics, environmental omics, and pharmacogenomics, species of various phyla including human, mouse, Arabidopsis thaliana, Saccharomyces cerevisiae, and various phenotypes, including cancer and COVID-19. In the analyzed studies, diverse methods, protocols, results, and terminology were used and accordingly, assessment of the studies was challenging. Adoption of standardized multiomics data presentation in the future will further buttress standardization of terminology and reporting of results in systems science. This shall catalyze, we suggest, innovation in both science communication and laboratory medicine by making available scientific knowledge that is easier to grasp, share, and harness toward medical breakthroughs.

Background Women with uterine adenomyosis seeking assisted reproduction have been associated with compromised endometrial receptivity to embryo implantation. To understand the mechanisms involved in this process, we aimed to compare endometrial transcriptome profiles during the window of implantation (WOI) between women with and without adenomyosis. Methods We obtained endometrial biopsies LH-timed to the WOI from women with sonographic features of adenomyosis (n=10) and controls (n=10). Isolated RNA samples were subjected to RNA sequencing (RNA-seq) by the Illumina NovaSeq 6000 platform and endometrial receptivity classification with a molecular tool for menstrual cycle phase dating (beREADY®, CCHT). The program language R and Bioconductor packages were applied to analyse RNA-seq data in the setting of the result of accurate endometrial dating. To suggest robust candidate pathways, the identified differentially expressed genes (DEGs) associated with the adenomyosis group in the receptive phase were further integrated with 151, 173 and 42 extracted genes from published studies that were related to endometrial receptivity in healthy uterus, endometriosis and adenomyosis, respectively. Enrichment analyses were performed using Cytoscape ClueGO and CluePedia apps. Results Out of 20 endometrial samples, 2 were dated to the early receptive phase, 13 to the receptive phase and 5 to the late receptive phase. Comparison of the transcriptomics data from all 20 samples provided 909 DEGs (p Conclusions Accurate endometrial dating and RNA-seq analysis resulted in the identification of altered response to IFN signalling as the most promising candidate of impaired uterine receptivity in adenomyosis.

Hypoxia-inducible factor (HIF) family of transcription factors (HIF1A, EPAS1, and HIF3A) are regulators of the cellular response to hypoxia. They have been shown to be involved in development of various diseases such as cancer, diabetes, and erythrocytosis. A complete map of connections between HIF family of genes with various omics types has not yet been developed. The main aim of the present analysis was to construct the integrative map of genomic elements associated with HIF1A gene and prioritize potentially deleterious variants. Various genomic databases and bioinformatics tools were used, including Ensembl, MirTarBase, STRING, Cytoscape, MethPrimer, CADD, SIFT, and UALCAN. Integrative HIF1A gene map was visualized and includes transcriptional and post-transcriptional regulators, downstream targets, and genetic variants. One CpG island overlaps transcription start site of the HIF1A gene. Out of over 450 missense variants, four have predicted deleterious effect on protein function by at least five bioinformatics tools. Currently there are 85 miRNAs reported to target HIF1A. HIF1A downstream targets include protein-coding genes, long noncoding RNAs, and microRNAs (hypoxamiRs). The study presents the first integration of heterogeneous molecular interactions associated with HIF1A gene enabling a holistic view of the gene and lays the groundwork for supplementing the data in the future.

In a digital society, shall we be the authors of our own experience, not only during our lifetime but also after we die? We ask this question because dying and bereavement have become even harder, and much less private, in the digital age. New big data-driven digital industries and technologies are on the rise, with promises of interactive 3D avatars and storage of digital memories of the deceased, so they can continue to exist online as the "living dead" in a digital afterlife. Famous rock and roll icons like Roy Orbison, Frank Zappa, Ronnie James Dio, and Amy Winehouse have famously been turned into holograms that can once again give "live" performances on the touring circuit, often pulling in large audiences. Death studies, dying, and grief have become virtual in the 21st century. We live in truly unprecedented times for human-computer interactions. Thanatology is the scientific study of death, dying, loss, and grief. In contrast to the biological study of biological aging (cellular senescence) and programmed cell death (apoptosis), thanatology employs multiple professional lenses, medical, psychological, physical, spiritual, ethical, descriptive, and normative. In 1997, Carla Sofka introduced the term thanatechnology as "technological mechanisms such as interactive videodiscs and computer programs that are used to access information or aid in learning about thanatology topics." Onward to 2021, the advent of social media, the Internet of Things, and sensors that digitize and archive nearly every human movement and experience are taking thanatechnology, and by extension, digital transformation, to new heights. For example, what happens to digital remains of persons once they cease to exist physically? This article offers a critical study and snapshot of this nascent field, and the "un-disciplinary" sociotechnical issues digital thanatechnologies raise in relation to big data. We also discuss how best to critically govern this new frontier in systems science and the digital society. We suggest that new policy narratives such as (1) the right to nonparticipation in relation to information and communication technologies and (2) the planetary public goods deserve further attention to democratize thanatechnology and big data. To the extent that systems science often depends on data from online platforms, for example, in times of pandemics and ecological crises, "critical thanatechnology studies," introduced in this article, is a timely and essential field of scholarship with broad importance for systems science and planetary health.

Motivation Causal biological interaction networks represent cellular regulatory pathways. Their fusion with other biological data enables insights into disease mechanisms and novel opportunities for drug discovery. Results We developed Causal Network of Diseases (CaNDis), a web server for the exploration of a human causal interaction network, which we expanded with data on diseases and FDA-approved drugs, on the basis of which we constructed a disease–disease network in which the links represent the similarity between diseases. We show how CaNDis can be used to identify candidate genes with known and novel roles in disease co-occurrence and drug–drug interactions. Availabilityand implementation CaNDis is freely available to academic users at http://candis.ijs.si and http://candis.insilab.org. Supplementary information Supplementary data are available at Bioinformatics online.

Purpose of review To integrate evidence on the role of circadian rhythm in male reproduction. Several studies report on various aspects of the association between the circadian system and male reproductive function in animals and humans both in physiological condition as well as in the case of subfertility. Recent findings Epidemiological data demonstrate diurnal and seasonal changes as well as the effect of sleep/wake cycles on the quality of semen. Rare and common genetic variation in circadian clock genes in humans and animal models support the role of circadian rhythms in male fertility in humans. Summary Current data support the modest effect of the circadian clock on male reproductive potential; however, the evidence available is still fragmented and inconclusive. Additional well designed and sufficiently powered studies are needed to delineate the role of the circadian clock both in cause and potential interventional and preventive approaches in male subfertility.

Glycomics is a rapidly emerging subspecialty of system sciences that evaluates the structures and functions of glycans in biological systems. Moreover, glycomics informs allied scholarships such as systems glycobiology and personalized glycomedicine that collectively aim to explain the role of glycans in person-to-person and between-population variations in disease susceptibility and response to health interventions such as drugs, nutrition, and vaccines. For glycomics to make greater, systems-scale, contributions to biology and medical research, it is facing a new developmental challenge: transition from single omics to multiomics integrative technology platforms. A comprehensive map of all possible connections between glycomics and other omics types has not yet been developed. Glycomics aims to discover a complex interplay of molecular interactions; however, little is known about the regulatory networks controlling these complex processes. In addition, the glycomics knowledgebase is presently scattered across various publications and databases, and therefore does not enable a holistic or systems view of this study field. Therefore, researchers are not always aware, for example, that a given analyzed genetic locus is linked with glycans, and that there are also glycomics determinants of complex phenotypes in health and biology. This review presents several published examples of glycomics science in association with other omics levels, such as genomics, transcriptomics, proteomics, metabolomics, epigenomics, ncRNomics, lipidomics, and interactomics. I also highlight the salient knowledge gaps and suggest future research directions. Understanding the interconnections of glycomics with other omics technologies will facilitate multiomics science and knowledge integration, enhance development of systems glycobiology and personalized glycomedicine.

Familial erythrocytosis (FE) is a congenital disorder, defined by elevated red blood cell number, hemoglobin, and hematocrit. Among eight types of FE, type 4 is caused by variants in the EPAS1 gene. Two other hypoxia-inducible factor alpha (HIFA) subunits, HIF1A and HIF3A, have not yet been associated with medical history of FE, but have potential role in the development of erythrocytosis. To improve diagnosis, it is crucial to identify new variants in genes involved in erythrocyte production. Published literature and data from genome browsers were used to obtain HIFA sequence variants associated with erythrocytosis and to locate them on protein sequence and regulatory sites. We retrieved 24 variants from the literature: 2 in HIF1A, 20 in EPAS1 and 2 in HIF3A gene. Sixteen out of 20 variants in the EPAS1 gene are positioned in a conserved region of 13 amino acids within exon 12, next to regulatory post-translational modification and binding sites, suggesting that EPAS1 has an important role in erythropoiesis. The role of HIF1A and HIF3A in the development of erythrocytosis should be further investigated.

Vascular endothelial growth factor (VEGF) is an important regulator of angiogenesis and has been investigated as a candidate gene in a number of conditions, including diabetes and its microvascular complications (e.g., retinopathy and nephropathy). Several VEGF-related polymorphisms have been shown to contribute to nearly half of the variability in circulating VEGF levels in healthy individuals. Our aim was to assess the association between VEGF-related rs10738760 and rs6921438 polymorphisms and proliferative diabetic retinopathy (PDR) in Slovenian patients with type 2 diabetes mellitus (T2DM). We also investigated the effect of these polymorphisms on VEGF receptor 2 (VEGFR-2) expression in fibrovascular membranes (FVMs) from patients with PDR. This case-control study enrolled 505 unrelated patients with T2DM: 143 diabetic patients with PDR as a study group, and 362 patients with T2DM of >10 years duration and with no clinical signs of PDR as a control group. Patient clinical and laboratory data were obtained from their medical records. rs10738760 and rs6921438 polymorphisms were genotyped using TaqMan SNP Genotyping assay. VEGFR-2 expression was assessed by immunohistochemistry in 20 FVMs from patients with PDR, and numerical areal density of VEGFR-2-positive cells was calculated. The occurrence of PDR was 1.7 times higher in diabetic patients carrying GA genotype of rs6921438 compared to patients with GG genotype, with a borderline statistical significance (OR = 1.7, 95% CI = 1.00 – 2.86, p = 0.05). In addition, A allele of rs6921438 was associated with increased VEGFR-2 expression in FVMs from PDR patients. However, we observed no association between AA genotype of rs6921438 nor between rs10738760 variants and PDR, indicating that the two polymorphisms are not genetic risk factors for PDR.

Background Erythrocytosis is a condition with an excessive number of erythrocytes, accompanied by an elevated haemoglobin and/or haematocrit value. Congenital erythrocytosis has a diverse genetic background with several genes involved in erythropoiesis. In clinical practice, nine genes are usually examined, but in approximately 70% of patients, no causative mutation can be identified. In this study, we screened 39 genes, aiming to identify potential disease‐driving variants in the family with erythrocytosis of unknown cause. Patients and Methods Two affected family members with elevated haemoglobin and/or haematocrit and negative for acquired causes and one healthy relative from the same family were selected for molecular‐genetic analysis of 24 erythrocytosis and 15 hereditary haemochromatosis‐associated genes with targeted NGS. The identified variants were further analysed for pathogenicity using various bioinformatic tools and review of the literature. Results Of the 12 identified variants, two heterozygous variants, the missense variant c.471G>C (NM_022051.2) (p.(Gln157His)) in the EGLN1 gene and the intron variant c.2572‐13A>G (NM_004972.3) in the JAK2 gene, were classified as low‐frequency variants in European population. None of the two variants were present in a healthy family member. Variant c.2572‐13A>G has potential impact on splicing by one prediction tool. Conclusion For the first time, we included 39 genes in the erythrocytosis clinical panel and identified two potential disease‐driving variants in the Slovene family studied. Based on the reported functional in vitro studies combined with our bioinformatics analysis, we suggest further functional analysis of variant in the JAK2 gene and evaluation of a cumulative effect of both variants., The genetic analysis was conducted on family with idiopathic erythrocytosis (IE), that is, erythrocytosis of unknown cause. Affected family members were included in the study based on the inclusion criteria for congenital erythrocytosis (eg elevated haemoglobin/haematocrit, absence of variants in some other myeloproliferative neoplasm genes and absence of secondary erythrocytosis). For the first, we included 39 erythrocytosis and haemochromatosis‐associated genes in genetic analysis with targeted NGS. Based on the inheritance pattern and selection of variants with minor allele frequency below 0.05, one missense variant in the EGLN1 gene and one intron variant in the JAK2 gene were identified in the affected family members.

Paraoxonase 1 (PON1) enzyme has antioxidative properties and is present in mammalian blood and several other body fluids. In blood, PON1 is usually integrated into the high-density lipoprotein (HDL) cholesterol. PON1 is a highly versatile enzyme displaying diverse functions such as arylesterase, lactonase, and paraoxonase, among others. PON1 activities are usually investigated with artificial substrates, for example, dihydrocoumarin and thiobutyl butyrolactone for lactonase activity. The PON1 enzyme activities measured with different substrates tend to be falsely assumed as being equivalent in the literature, although there are poor or weak correlations among the PON1 enzyme activities with different substrates. In addition, and despite our knowledge of the factors influencing PON1 paraoxonase and arylesterase activities, there is little knowledge of PON1 lactonase activity variations and attendant mechanisms. This is important considering further that the lactonase activity is the native activity of PON1. We report here a multi-omics analysis of PON1 lactonase activity. The influence of genetic variations, particularly of single nucleotide polymorphisms and epigenetic, proteomic, and lipidomic variations on PON1 lactonase activity are reviewed. In addition, the influence of various environmental, clinical, and demographic variables on PON1 lactonase activity is discussed. Finally, we examine the associations between PON1 lactonase activity and health states and common complex diseases such as atherosclerosis, dementias, obesity, and diabetes. To the best of our knowledge, this is the first multi-omics analysis of PON1 lactonase activity with an eye to future applications in basic life sciences and translational medicine and the nuances of critically interpreting PON1 function with lactones as substrates.

Background: Adenomyosis is a gynaecological condition with limited evidence of negative impact to endometrial receptivity. It is commonly associated with endometriosis, which has been shown to alter endometrial expression patterns. Therefore, the candidate genes identified in endometriosis could serve as a source to study endometrial function in adenomyosis. Methods: Transcripts/proteins associated with endometrial receptivity in women with adenomyosis or endometriosis and healthy women were obtained from publications and their nomenclature was adopted according to the HUGO Gene Nomenclature Committee (HGNC). Retrieved genes were analysed for enriched pathways using Cytoscape/Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Reactome tools to prioritise candidates for endometrial receptivity. These were used for validation on women with (n = 9) and without (n = 13) adenomyosis. Results: Functional enrichment analysis of 173, 42 and 151 genes associated with endometriosis, adenomyosis and healthy women, respectively, revealed signalling by interleukins and interleukin-4 and interleukin-13 signalling pathways, from which annotated LIF, JUNB, IL6, FOS, IL10 and SOCS3 were prioritised. Selected genes showed downregulated expression levels in adenomyosis compared to the control group, but without statistical significance. Conclusion: This is the first integrative study providing putative candidate genes and pathways characterising endometrial receptivity in women with adenomyosis in comparison to healthy women and women with endometriosis.

Erythrocytosis is a blood disorder characterised by an increased red blood cell mass. The most common causes of erythrocytosis are acquired and caused by diseases and conditions that are accompanied by hypoxaemia or overproduction of erythropoietin. More rarely, erythrocytosis has a known genetic background, such as for polycythaemia vera and familial erythrocytosis. The majority of cases of polycythaemia vera are associated with acquired variants in JAK2, while familial erythrocytosis is a group of congenital disorders. Familial erythrocytosis type 1 is associated with hypersensitivity to erythropoietin (variants in EPOR), types 2–5 with defects in oxygen-sensing pathways (variants in VHL, EGLN1, EPAS1, EPO), and types 6–8 with an increased affinity of haemoglobin for oxygen (variants in HBB, HBA1, HBA2, BPGM). Due to a heterogenic genetic background, the causes of disease are not fully discovered and in more than 70% of patients the condition remains labelled idiopathic. The transfer of next-generation sequencing into clinical practice is becoming a reality enabling detection of various variants in a single rapid test. In this review, we describe the current research on erythrocytosis gene variants and the mechanisms associated with disease development, along with the currently used diagnostic tests.

Purpose To synthesise data from genome-wide studies reporting molecular signature of eutopic endometrium through the phases of the menstrual cycle in endometriosis. Methods Extraction of data from publications reporting genetic signatures characterising endometrium associated with endometriosis. The nomenclature of extracted differentially expressed transcripts and proteins was adopted according to the HUGO Gene Nomenclature Committee (HGNC). Loci were further sorted according to the different phases of the menstrual cycle, i.e. menstrual (M), proliferative (P), secretory (S), early-secretory (ES), mid-secretory (MS), late-secretory (LS), and not specified (N/S) if the endometrial dating was not available. Enrichment analysis was performed using the DAVID bioinformatics tool. Results Altered molecular changes were reported by 21 studies, including 13 performed at the transcriptomic, 6 at proteomic, and 2 at epigenomic level. Extracted data resulted in a catalogue of total 670 genetic causes with available 591 official gene symbols, i.e. M = 3, P = 188, S = 81, ES = 82, MS = 173, LS = 36, and N/S = 28. Enriched pathways included oestrogen signalling pathway, extracellular matrix organization, and endothelial cell chemotaxis. Our study revealed that knowledge of endometrium biology in endometriosis is fragmented due to heterogeneity of published data. However, 15 genes reported as dysregulated by at least two studies within the same phase and 33 significantly enriched GO-BP terms/KEGG pathways associated with different phases of the menstrual cycle were identified. Conclusions A multi-omics insight into molecular patterns underlying endometriosis could contribute towards identification of endometrial pathological mechanisms that impact fertility capacities of women with endometriosis.

Precision/personalized medicine is a hot topic in health care. Often presented with the motto "the right drug, for the right patient, at the right dose, and the right time," precision medicine is a theory for rational therapeutics as well as practice to individualize health interventions (e.g., drugs, food, vaccines, medical devices, and exercise programs) using biomarkers. Yet, an alien visitor to planet Earth reading the contemporary textbooks on diagnostics might think precision medicine requires only two biomolecules omnipresent in the literature: nucleic acids (e.g., DNA) and proteins, known as the first and second alphabet of biology, respectively. However, the precision/personalized medicine community has tended to underappreciate the third alphabet of life, the "sugar code" (i.e., the information stored in glycans, glycoproteins, and glycolipids). This article brings together experts in precision/personalized medicine science, pharmacoglycomics, emerging technology governance, cultural studies, contemporary art, and responsible innovation to critically comment on the sociomateriality of the three alphabets of life together. First, the current transformation of targeted therapies with personalized glycomedicine and glycan biomarkers is examined. Next, we discuss the reasons as to why unraveling of the sugar code might have lagged behind the DNA and protein codes. While social scientists have historically noted the importance of constructivism (e.g., how people interpret technology and build their values, hopes, and expectations into emerging technologies), life scientists relied on the material properties of technologies in explaining why some innovations emerge rapidly and are more popular than others. The concept of sociomateriality integrates these two explanations by highlighting the inherent entanglement of the social and the material contributions to knowledge and what is presented to us as reality from everyday laboratory life. Hence, we present a hypothesis based on a sociomaterial conceptual lens: because materiality and synthesis of glycans are not directly driven by a template, and thus more complex and open ended than sequencing of a finite length genome, social construction of expectations from unraveling of the sugar code versus the DNA code might have evolved differently, as being future-uncertain versus future-proof, respectively, thus potentially explaining the "sugar lag" in precision/personalized medicine diagnostics over the past decades. We conclude by introducing systems scientists, physicians, and biotechnology industry to the concept, practice, and value of responsible innovation, while glycomedicine and other emerging biomarker technologies (e.g., metagenomics and pharmacomicrobiomics) transition to applications in health care, ecology, pharmaceutical/diagnostic industries, agriculture, food, and bioengineering, among others.

Objectives Erythrocytosis is characterized by the expansion of erythrocyte compartment including elevated red blood cell number, hematocrit, and hemoglobin content. Familial erythrocytosis (FE) is a congenital disorder with different genetic background. Type 1 FE is primary FE caused by mutation in erythropoietin receptor gene (EPOR). Type 2‐5 FE are secondary FEs caused by mutations of genes involved in oxygen sensing pathway important for erythropoietin (EPO) regulation. In the present study, we summarized associations between EPOR and EPO gene variations with development of FE and searched for genetic variants located within regulatory regions. Methods Publications reporting EPOR and EPO sequence variants associated with FE or clinical features of erythrocytosis were retrieved from PubMed and WoS. In silico, sequence reanalysis was performed using Ensembl genomic browser, release 89 to screen for variants located within regulatory regions. Results To date, 28 variants of the EPOR and seven variants of the EPO gene have been associated with erythrocytosis or upper hematocrit. Sequence variants were also found to be present within regulatory regions. Conclusions Role of variants in regulatory regions of the EPO gene should be further investigated.

Cryptorchidism is a urogenital abnormality associated with increased rates of testicular neoplasia and impaired spermatogenesis. The field is facing expansion of genomics data; however, it lacks protocols for biomarker prioritization. Identification of smallest regions of overlap (SRO) presents an approach for candidate gene identification but has not yet been systematically conducted in cryptorchidism. The aim of this study was to conduct a genome-wide screening for SRO (GW-SRO) associated with cryptorchidism development. We updated the Cryptorchidism Gene Database to version 3, remapped genomic coordinates of loci from older assemblies to the GRCh38 and performed genome-wide screening for overlapping regions associated with cryptorchidism risk. A total of 73 chromosomal loci (68 involved in chromosomal mutations and five copy number variations) described in 37 studies associated with cryptorchidism risk in humans were used for SRO identification. Analysis resulted in 18 SRO, based on deletions, duplications, inversions, derivations and copy number variations. Screening for SRO was challenging owing to heterogeneous reporting of genomic locations. To our knowledge, this is the first GW-SRO study for cryptorchidism and it presents the basis for further narrowing of critical regions for cryptorchidism and planning functional experiments. The developed protocol could also be applied to other multifactorial diseases.

Asthma is a common complex disorder and has been subject to intensive omics research for disease susceptibility and therapeutic innovation. Candidate biomarkers of asthma and its precision treatment demand that they stand the test of multiomics data triangulation before they can be prioritized for clinical applications. We classified the biomarkers of asthma after a search of the literature and based on whether or not a given biomarker candidate is reported in multiple omics platforms and methodologies, using PubMed and Web of Science, we identified omics studies of asthma conducted on diverse platforms using keywords, such as asthma, genomics, metabolomics, and epigenomics. We extracted data about asthma candidate biomarkers from 73 articles and developed a catalog of 190 potential asthma biomarkers (167 human, 23 animal data), comprising DNA loci, transcripts, proteins, metabolites, epimutations, and noncoding RNAs. The data were sorted according to 13 omics types: genomics, epigenomics, transcriptomics, proteomics, interactomics, metabolomics, ncRNAomics, glycomics, lipidomics, environmental omics, pharmacogenomics, phenomics, and integrative omics. Importantly, we found that 10 candidate biomarkers were apparent in at least two or more omics levels, thus promising potential for further biomarker research and development and precision medicine applications. This multiomics catalog reported herein for the first time contributes to future decision-making on prioritization of biomarkers and validation efforts for precision medicine in asthma. The findings may also facilitate meta-analyses and integrative omics studies in the future.

miRNA regulome is whole set of regulatory elements that regulate miRNA expression or are under control of miRNAs. Its understanding is vital for comprehension of miRNA functions. Classification of miRNA-related genetic variability is challenging because miRNA interact with different genomic elements and are studied at different omics levels. In the present study, miRNA-associated genetic variability is presented at three levels: miRNA genes and their upstream regulation, miRNA silencing machinery and miRNA targets. Several types of miRNA-associated genetic variations are known, including short and structural polymorphisms and epimutations. Differential expression can also affect miRNA regulome function. Classification of miRNA-associated genetic variability presents a baseline for complementing sequence variant nomenclature, planning of experiments, protocols for multi-omics data integration and development of biomarkers.

Molecular mechanisms of Parkinson's disease (PD) have already been investigated in various different omics landscapes. We reviewed the literature about different omics approaches between November 2005 and November 2017 to depict the main pathological pathways for PD development. In total, 107 articles exploring different layers of omics data associated with PD were retrieved. The studies were grouped into 13 omics layers: genomics–DNA level, transcriptomics, epigenomics, proteomics, ncRNomics, interactomics, metabolomics, glycomics, lipidomics, phenomics, environmental omics, pharmacogenomics, and integromics. We discussed characteristics of studies from different landscapes, such as main findings, number of participants, sample type, methodology, and outcome. We also performed curation and preliminary synthesis of multiple omics data, and identified overlapping results, which could lead toward selection of biomarkers for further validation of PD risk loci. Biomarkers could support the development of targeted prognostic/diagnostic panels as a tool for early diagnosis and prediction of progression rate and prognosis. This review presents an example of a comprehensive approach to revealing the underlying processes and risk factors of a complex disease. It urges scientists to structure the already known data and integrate it into a meaningful context.

Science and its practice always had a subtext, subject to influence by scientists', funders', and other innovation actors' values and assumptions. The recent emergence of post-truth, authoritarian and populist penchants, in both developed and developing countries, has further blurred the already fluid boundaries between material scientific facts and their social construction/shaping by scientific subtext, human values, powers, and hegemony. While there are certain checks, balances, and oversight mechanisms for publication ethics, other pillars of science communication, most notably, scientific conferences and their governance, are ill prepared for post-truth science. Worrisomely, the proliferation of spam conferences is a major cause for concern for integrative biology and postgenomic science. The current gaps in conference ethics are important beyond science communication because conferences help build legitimacy of emerging technologies and frontiers of science and, thus, bestows upon the organizers, funders, enlisted scientific advisors, speakers, among others, power, which in turn needs to be checked. Denis Diderot (1713-1784), a prominent intellectual during the Enlightenment period, has aptly observed that the very act of organizing brings about power, influence, and control. If the subtext of conference practices is left unchecked, it can pave the way for hegemony, and yet more volatile and violent authoritarian governance systems in science and society. This begs for innovative solutions to increase accountability, resilience, and capacity of technology experts and scientists to discern and decode the subtext in science and its communication in the current post-truth world. We propose that the existing undergraduate and graduate programs in life and physical sciences and medicine could be redesigned to include a rotation for exposure to and training in political science. Such innovative PhD+ programs straddling technical and political science scholarship would best equip future students and citizens to grasp and respond to subtext and embedded opaque value and power systems in scientific practices in an increasingly post-truth world. Political science scholarship unpacks the inner workings, subtext, and power dynamics in science and society. Thus, knowledge of political science competency is akin to molecular biology in life sciences. Both make the invisible (e.g., cell biology versus subtext of knowledge) visible. The ability to read subtext in science and claims of post-truth knowledge is a new and essential form of societal literacy in 21st century science and integrative biology.

Epigenomics is one of the leading frontiers of postgenomics medicine. The challenges and prospects ahead in epigenomics are related not merely to technology innovation and clinical implementation but also to science communication. In this context, microRNAs (miRNAs) are an important part of the epigenomic regulatory machinery. As the number of publications reporting miRNA-target interactions (MTIs) is growing rapidly, there is an urgent need to standardize reporting. This study reports (1) an analysis of the published literature and databases reporting validated MTIs, and for the first time to the best of our knowledge (2) suggests a solution as a way forward, the minimum information required for MTI standard reporting. We retrieved the research reports from PubMed and Web of Science dating from 09/2006 to 01/2017 and downloaded information from DIANA-TarBase, miRecords, and miRTarBase. We evaluated the reporting and extracted MTI data, which we complemented with relevant genomic information. We suggest a standard minimum checklist for MTI reporting, consisting of seven pertinent data types: miRNA gene, target gene, species, experimental validation, sequence variants, associated phenotype, and additionally a PubMed identification (PMID) number in systematic reviews and meta-analyses. Our proposal reported here shall enable faster development of MTI databases and bioinformatics resources, and looking into the future, more efficient planning of experimental designs in the nascent field of epigenomics and its postgenomics applications.

Ultraconserved elements (UCEs) are among the most popular DNA markers for phylogenomic analysis. In at least three of five placental mammalian genomes (human, dog, cow, mouse, and rat), 2189 UCEs of at least 200 bp in length that are identical have been identified. Most of these regions have not yet been functionally annotated, and their associations with diseases remain largely unknown. This is an important knowledge gap in human genomics with regard to UCE roles in physiologically critical functions, and by extension, their relevance for shared susceptibilities to common complex diseases across several mammalian organisms in the event of their polymorphic variations. In the present study, we remapped the genomic locations of these UCEs to the latest human genome assembly, and examined them for documented polymorphisms in sequenced human genomes. We identified 29,983 polymorphisms within analyzed UCEs, but revealed that a vast majority exhibits very low minor allele frequencies. Notably, only 112 of the identified polymorphisms are associated with a phenotype in the Ensembl genome browser. Through literature analyses, we confirmed associations of 37 (i.e., out of the 112) polymorphisms within 23 UCEs with 25 diseases and phenotypic traits, including, muscular dystrophies, eye diseases, and cancers (e.g., familial adenomatous polyposis). Most reports of UCE polymorphism—disease associations appeared to be not cognizant that their candidate polymorphisms were actually within UCEs. The present study offers strategic directions and knowledge gaps for future computational and experimental work so as to better understand the thus far intriguing and puzzling role(s) of UCEs in mammalian genomes.

MicroRNAs (miRNAs) are short non-coding RNAs that act as important regulators of gene expression as part of the epigenetic machinery. In addition to posttranscriptional gene silencing by miRNAs, the epigenetic mechanisms also include DNA methylation, histone modifications and their crosstalk. Epigenetic modifications were reported to play an important role in many disease onsets and progressions and can be used to explain several features of complex diseases, such as late onset and fluctuation of symptoms. However, miRNAs not only function as a part of epigenetic machinery, but are also epigenetically modified by DNA methylation and histone modification like any other protein-coding gene. There is a strong connection between epigenome and miRNome, and any dysregulation of this complex system can result in various physiological and pathological conditions. In addition, miRNAs play an important role in toxicogenomics and may explain the relationship between toxicant exposure and tumorigenesis. The present review provides information on 63 miRNA genes shown to be epigenetically regulated in association with 21 diseases, including 11 cancer types: cardiac fibrosis, cardiovascular disease, preeclampsia, Hirschsprung's disease, rheumatoid arthritis, systemic sclerosis, systemic lupus erythematosus, temporal lobe epilepsy, autism, pulmonary fibrosis, melanoma, acute myeloid leukemia, chronic lymphocytic leukemia, colorectal, gastric, cervical, ovarian, prostate, lung, breast, and bladder cancer. The review revealed that hsa-miR-34a, hsa-miR-34b, and hsa-miR-34c are the most frequently reported epigenetically dysregulated miRNAs. There is a need to further study molecular mechanisms of various diseases to better understand the crosstalk between epigenetics and gene expression and to develop new therapeutic options and biomarkers.

Like many other omics types, miRNomics is the topic of increased research interest. Fast accumulation of diverse biological information generates fragmented and sometimes contradictory results. There is an urgent need for development of protocols for systematic assembling, organization and integration of accumulated genomics data. In the present study we developed a protocol for connecting microRNA (miRNA) interactions into an integrative map of miRNA regulatory elements including: upstream regulators, overlapping genomic elements and downstream targets; miRNA-target interactions (MTIs). Data integration (integromics) in miRNomics enables revealing miRNA regulatory networks, obtaining new knowledge, setting more targeted hypotheses, prioritization of candidate regions, and facilitates biomarker development.

Asthma is a common multifactorial complex disease caused by an interaction of genetic and environmental factors. There are no robust biomarkers or molecular diagnostics for asthma or its detailed phenotypic stratification in the clinic. Regulatory and epigenomic factors are priority candidates for asthma biomarker discovery and translational research because this common disease emerges in association with host/environment interactions. In this context, epigenomic molecular events such as microRNA (miRNA) silencing affect asthma susceptibility and severity. We report here an analysis of the miRNAs in the literature, their targets associated with asthma, and present the findings organized as an miRNA-target network, an miRNA regulome of asthma. The miRNA-target interactions in asthma were extracted from the PubMed and the Web of Science databases, while the miRNA-target network was visualized with the Cytoscape tool. Genomic locations of miRNA and target genes were displayed using the Ensembl Whole Genome tool. We cataloged miRNAs associated with asthma and their experimentally validated targets, retrieving 48 miRNAs associated with asthma, and 54 experimentally validated miRNA targets. Four central molecules involved in 34.5% of all interactions were identified in the network. The miRNA-target pairs were constructed as an asthma-associated miRNA-target regulatory network. The network revealed subnetworks pointing toward potential asthma biomarker candidates. The asthma miRNA regulome reported here offers a strong foundation for future translational research and systems medicine applications for asthma diagnostic and therapeutic innovation. Developed protocol for constructing miRNA regulome could now be used for biomarker development in multifactorial diseases.

Sarcoidosis is a multifactorial systemic disease characterized by granulomatous inflammation and greatly impacting on global public health. The etiology and mechanisms of sarcoidosis are not fully understood. Recent high-throughput biological research has generated vast amounts of multi-omics big data on sarcoidosis, but their significance remains to be determined. We sought to identify novel candidate regions, and genes consistently altered in heterogeneous omics studies so as to reveal the underlying molecular mechanisms. We conducted a comprehensive integrative literature analysis on global data on sarcoidosis, including genomic, transcriptomic, proteomic, and phenomic studies. We performed positional integration analysis of 38 eligible datasets originating from 17 different biological layers. Using the integration interval length of 50 kb, we identified 54 regions reaching significance value p ≤ 0.0001 and 15 regions with significance value p ≤ 0.00001, when applying more stringent criteria. Secondary literature analysis of the top 20 regions, with the most significant accumulation of signals, revealed several novel candidate genes for which associations with sarcoidosis have not yet been established, but have considerable support for their involvement based on omic data. These new plausible candidate genes include NELFE, CFB, EGFL7, AGPAT2, FKBPL, NRC3, and NEU1. Furthermore, annotated data were prepared to enable custom visualization and browsing of these sarcoidosis related omics evidence in the University of California Santa Cruz (UCSC) Genome Browser. Further multi-omics approaches are called for sarcoidosis biomarkers and diagnostic and therapeutic innovation. Our approach for harnessing multi-omics data and the findings presented herein reflect important steps toward understanding the etiology and underlying pathological mechanisms of sarcoidosis.

Genetic variations and differential expression of miRNA regulome components are associated with cancer. Thus miRNA based diagnosis and treatments have been proposed. However, to better explore these options, the molecular changes in miRNA regulome must be understood. MicroRNAs can be involved in regulation of oncogenes and tumour suppressors. As each miRNA targets broad range of genes, minor changes in miRNAs can have great effects, contributing to cell transformation. Many genetic variants of miRNA regulome have been reported to be associated with cancer, but this information needs to be systematized. Therefore, we here classify different types of genetic variations of miRNA regulome in cancer. Genetic variations are comprised of structural and short polymorphisms and changes in epigenetic landscape. Additionally, unexplained differential expression is often reported. These alterations affect miRNA genes and their regulatory elements, processing machinery, degradation machinery, and targets, leading to changes in miRNA silencing. However, miRNA regulome components are not equally explored. A systematic overview over miRNA regulome can contribute to more targeted study design and understanding of miRNA function. We also present treatments and diagnosis based on miRNA regulome genetic variability and expression.

Hypoxia-inducible factors (HIFs) belong to a family of transcription factors (TF) responsive to a low O2 availability, which is often a characteristic feature of solid tumors. The alpha subunit of the HIF heterodimer is O2 -sensitive, and once stabilized in hypoxia, it functions as a master regulator of various genes involved in hypoxia pathway. Changes in the HIF1A (hypoxia inducible factor 1, alpha subunit) nucleotide sequence or expression has been shown to be associated with the development of several diseases. Because of increasing research interest in HIF1A gene a review of association studies was needed. We here reviewed published data on single nucleotide polymorphisms (SNPs) in HIF1A in various diseases; in total, 34 SNPs were tested for an association with 49 phenotypes, and the results were visualized using the Cytoscape software. Among all collected polymorphisms 16 SNPs showed significant associations with 40 different phenotypes, including six SNPs associated with 14 cancer types. Missense SNPs (rs11549465 and rs11549467) within the oxygen-dependent degradation domain were most frequently studied. The study provides a comprehensive tool for researchers working in this area and may contribute to more accurate disease diagnosis and identification of therapeutic targets.

Discovery of potentially deleterious sequence variants is important and has wide implications for research and generation of new hypotheses in human and veterinary medicine, and drug discovery. The GenProBiS web server maps sequence variants to protein structures from the Protein Data Bank (PDB), and further to protein–protein, protein–nucleic acid, protein–compound, and protein–metal ion binding sites. The concept of a protein–compound binding site is understood in the broadest sense, which includes glycosylation and other post-translational modification sites. Binding sites were defined by local structural comparisons of whole protein structures using the Protein Binding Sites (ProBiS) algorithm and transposition of ligands from the similar binding sites found to the query protein using the ProBiS-ligands approach with new improvements introduced in GenProBiS. Binding site surfaces were generated as three-dimensional grids encompassing the space occupied by predicted ligands. The server allows intuitive visual exploration of comprehensively mapped variants, such as human somatic mis-sense mutations related to cancer and non-synonymous single nucleotide polymorphisms from 21 species, within the predicted binding sites regions for about 80 000 PDB protein structures using fast WebGL graphics. The GenProBiS web server is open and free to all users at http://genprobis.insilab.org.

Protein interactions (PI) underlie complex biological processes. Protein interaction partners include DNA, RNA, ions, small chemical compounds, and proteins (protein-protein interactions; PPI). Analysis of sequence variants within regions corresponding to experimentally validated PI sites presents novel opportunities for understanding of complex diseases. Such information has not been systematically collected due to the fact that datasets are dispersed throughout databases and publications. Sequence variants and PI regions were obtained from the UniProt database. The location of the variants was compared to start and end positions of each PPI. Associations of sequence variants with phenotype were obtained from databases including COSMIC, GAD, PharmGKB, and dbSNP. We developed a catalogue of 603 sequence variants located within regions corresponding to experimentally validated PI sites, mostly PPI regions. These sequence variants were previously associated with risk for cancer, reproduction, ageing, renal, and immune system diseases. The developed catalogue connects information from different research papers and databases, represents a new layer of information and enables designing new hypotheses. It provides a baseline for prioritization of sequence variants, which may affect protein function and binding sites. The study contributes to the development of the proteogenomics field and provides new insights for understanding molecular mechanisms underlying disease development.

Long non-coding RNAs (lncRNAs) are transcripts without protein-coding capacity; initially regarded as "transcriptional noise", lately they have emerged as essential factors in both cell biology and mechanisms of disease. In this article, we present basic knowledge of lncRNA molecular mechanisms, associated physiological processes and cancer association, as well as their diagnostic and therapeutic value in the form of a decalog: (1) Non-coding RNAs (ncRNAs) are transcripts without protein-coding capacity divided by size (short and long ncRNAs), function (housekeeping RNA and regulatory RNA) and direction of transcription (sense/antisense, bidirectional, intronic and intergenic), containing a broad range of molecules with diverse properties and functions, such as messenger RNA, transfer RNA, microRNA and long non-coding RNAs. (2) Long non-coding RNAs are implicated in many molecular mechanisms, such as transcriptional regulation, post-transcriptional regulation and processing of other short ncRNAs. (3) Long non-coding RNAs play an important role in many physiological processes such as X-chromosome inactivation, cell differentiation, immune response and apoptosis. (4) Long non-coding RNAs have been linked to hallmarks of cancer: (a) sustaining proliferative signaling; (b) evading growth suppressors; (c) enabling replicative immortality; (d) activating invasion and metastasis; (e) inducing angiogenesis; (f) resisting cell death; and (g) reprogramming energy metabolism. (5) Regarding their impact on cancer cells, lncRNAs are divided into two groups: oncogenic and tumor-suppressor lncRNAs. (6) Studies of lncRNA involvement in cancer usually analyze deregulated expression patterns at the RNA level as well as the effects of single nucleotide polymorphisms and copy number variations at the DNA level. (7) Long non-coding RNAs have potential as novel biomarkers due to tissue-specific expression patterns, efficient detection in body fluids and high stability. (8) LncRNAs serve as novel biomarkers for diagnostic, prognostic and monitoring purposes. (9) Tissue specificity of lncRNAs enables the development of selective therapeutic options. (10) Long non-coding RNAs are emerging as commercial biomarkers and therapeutic agents.

Recent data have linked hypoxia, a classic feature of the tumor microenvironment, to the function of specific microRNAs (miRNAs); however, whether hypoxia affects other types of noncoding transcripts is currently unknown. Starting from a genome-wide expression profiling, we demonstrate for the first time a functional link between oxygen deprivation and the modulation of long noncoding transcripts from ultraconserved regions, termed transcribed-ultraconserved regions (T-UCRs). Interestingly, several hypoxia-upregulated T-UCRs, henceforth named ‘hypoxia-induced noncoding ultraconserved transcripts' (HINCUTs), are also overexpressed in clinical samples from colon cancer patients. We show that these T-UCRs are predominantly nuclear and that the hypoxia-inducible factor (HIF) is at least partly responsible for the induction of several members of this group. One specific HINCUT, uc.475 (or HINCUT-1) is part of a retained intron of the host protein-coding gene, O-linked N-acetylglucosamine transferase, which is overexpressed in epithelial cancer types. Consistent with the hypothesis that T-UCRs have important function in tumor formation, HINCUT-1 supports cell proliferation specifically under hypoxic conditions and may be critical for optimal O-GlcNAcylation of proteins when oxygen tension is limiting. Our data gives a first glimpse of a novel functional hypoxic network comprising protein-coding transcripts and noncoding RNAs (ncRNAs) from the T-UCRs category.

The number of publications on research of male infertility is increasing. Technologies used in research of male infertility generate complex results and various types of data that need to be appropriately managed, arranged, and made available to other researchers for further use. In our previous study, we collected over 800 candidate loci for male fertility in seven mammalian species. However, the continuation of the work towards a comprehensive database of candidate genes associated with different types of idiopathic human male infertility is challenging due to fragmented information, obtained from a variety of technologies and various omics approaches. Results are published in different forms and usually need to be excavated from the text, which hinders the gathering of information. Standardized reporting of genetic anomalies as well as causative and risk factors of male infertility therefore presents an important issue. The aim of the study was to collect examples of diverse genomic loci published in association with human male infertility and to propose a standardized format for reporting genetic causes of male infertility. From the currently available data we have selected 75 studies reporting 186 representative genomic loci which have been proposed as genetic risk factors for male infertility. Based on collected and formatted data, we suggested a first step towards unification of reporting the genetics of male infertility in original and review studies. The proposed initiative consists of five relevant data types: 1) genetic locus, 2) race/ethnicity, number of participants (infertile/controls), 3) methodology, 4) phenotype (clinical data, disease ontology, and disease comorbidity), and 5) reference. The proposed form for standardized reporting presents a baseline for further optimization with additional genetic and clinical information. This data standardization initiative will enable faster multi-omics data integration, database development and sharing, establishing more targeted hypotheses, and facilitating biomarker discovery.

BackgroundProtein-protein interactions (PPI) play an important role in function of all organisms and enable understanding of underlying metabolic processes. Computational predictions of PPIs are an important aspect in proteomics, as experimental methods may result in high degree of false positive results and are more expensive. Although there are many databases collecting predicted PPIs, exploration of genetics information underlying PPI interactions has not been investigated thoroughly. The aim of the present study was to identify genomic locations corresponding to regions involved in predicted PPIs and to collect non-synonymous polymorphisms (nsSNPs) located within those regions; which we termed PPI-SNPs. MethodsPredicted PPIs were obtained from PiSITE database (http://pisite.hgc.jp). Non-synonymous SNPs mapped on protein structural data (PDBs) were obtained from the UCSC server. Polymorphism locations on protein structures were mapped to predicted PPI regions. DAVID tool was used for pathway enrichment and gene cluster analysis (https://david.ncifcrf.gov/). ResultsWe collected 544 polymorphisms located within predicted PPI sites that map to 197 genes. We identified 9 SNPs, previously associated with diseases, but not yet associated with PPI sites. We also found examples in which polymorphisms located within predicted PPI regions are also occurring within previously experimentally validated PPIs and within experimentally determined functional domains. ConclusionsOur study provides the first catalog of nsSNPs located within predicted PPIs. These prioritized SNPs present the basis for planning experimental validation of SNPs that cause gain or loss of PPIs. Our implementation is expandable, as datasets used are constantly updated. Display Omitted A catalog of nsSNPs within regions corresponding to protein interactions; PPI-SNPs.PPI-SNPs are located within predicted and validated protein interactions.Genes including PPI-SNPs are associated with several diseases, including cancer.PPI-SNPs might present potential for development of novel biomarkers.

Hypoxia-inducible factor-1α (HIF-1α) has crucial role in adapting cells to hypoxia through expression regulation of many genes. Identification of HIF-1α target genes (HIF-1α-TGs) is important for understanding the adapting mechanism. The aim of the present study was to collect known HIF-1α-TGs and identify their associated pathways. Targets and associated genomics data were retrieved using PubMed, WoS ( http://apps.webofknowledge.com/ ), HGNC ( http://www.genenames.org/ ), NCBI ( http://www.ncbi.nlm.nih.gov/ ), Ensemblv.84 ( http://www.ensembl.org/index.html ), DAVID Bioinformatics Resources ( https://david.ncifcrf.gov /), and Disease Ontology database ( http://disease-ontology.org/ ). From 51 papers, we collected 98 HIF-1α TGs found to be associated with 20 pathways, including metabolism of carbohydrates and pathways in cancer. Reanalysis of genomic coordinates of published HREs (hypoxia response elements) revealed six polymorphisms within HRE sites (HRE-SNPs): ABCG2, ACE, CA9, and CP. Due to large heterogeneity of results presentation in scientific literature, we also propose a first step towards reporting standardization of HIF-1α-target interactions consisting of ten relevant data types. Suggested minimal checklist for reporting will enable faster development of a complete catalog of HIF-1α-TGs, data sharing, bioinformatics analyses, and setting novel more targeted hypotheses. The proposed format for data standardization is not yet complete but presents a baseline for further optimization of the protocol with additional details, for example, regarding the experimental validation.

Cryptorchidism is a frequent urogenital abnormality that may be present at birth (congenital form) or develop later in life (acquired form). It represents 2-4% full-term male births. It has a potential effect on health; defects in testes descent usually cause impaired spermatogenesis resulting in reduced fertility and increased rates of testicular neoplasia, and testicular torsion. In our previous study, we developed a cryptorchidism gene database which consists of 217 genomic variations associated with development of cryptorchidism in seven mammalian species. The number of studies and study approaches in this field are increasing; therefore, update of the database was needed. The search of multi-omics data was performed and the updated database includes 280 genomic variations associated with cryptorchidism in seven species. The catalog has been complemented with additional data including: number of participants (patients/controls), race/ethnicity, clinical data (age period at diagnosis), congenital/acquired cryptorchidism, unilateral (left/right)/bilateral cryptorchidism, disease comorbidity, and disease ontology. Collected data revealed that cryptorchidism has been reported to be co-present with 150 comorbid conditions, including several syndromes, reproductive, cardiovascular, ophthalmologic, dermatologic, mental, and bone disorders, deafness, and cancer. However, updating the database is time-consuming because of the heterogeneity of results and methodology in scientific literature. The field lacks a standardized format for reporting associations between genotype and phenotype which would enable faster development of the database, data integration, sharing, and facilitate biomarker development. Therefore, in this study, we updated a database of cryptorchidism genes and suggested a first step toward standardization of the format for reporting results of original as well as review studies which we suggest implementing into the scientific literature that reports genotype-cryptorchidism associations.

MicroRNAs (miRNAs) are a class of noncoding RNAs (ncRNAs) and posttranscriptional gene regulators shown to be involved in pathogenesis of all types of human cancers. Their aberrant expression as tumor suppressors can lead to cancerogenesis by inhibiting malignant potential, or when acting as oncogenes, by activating malignant potential. Differential expression of miRNA genes in tumorous tissues can occur owing to several factors including positional effects when mapping to cancer-associated genomic regions, epigenetic mechanisms, and malfunctioning of the miRNA processing machinery, all of which can contribute to a complex miRNA-mediated gene network misregulation. They may increase or decrease expression of protein-coding genes, can target 3'-UTR or other genic regions (5'-UTR, promoter, coding sequences), and can function in various subcellular compartments, developmental, and metabolic processes. Because expanding research on miRNA-cancer associations has already produced large amounts of data, our main objective here was to summarize main findings and critically examine the intricate network connecting the miRNAs and coding genes in regulatory mechanisms and their function and phenotypic consequences for cancer. By examining such interactions, we aimed to gain insights for the development of new diagnostic markers as well as identification of potential venues for more selective tumor therapy. To enable efficient examination of the main past and current miRNA discoveries, we developed a Web-based miRNA timeline tool that will be regularly updated (http://www.integratomics-time.com/miRNA_timeline). Further development of this tool will be directed at providing additional analyses to clarify complex network interactions between miRNAs, other classes of ncRNAs, and protein-coding genes and their involvement in development of diseases including cancer. This tool therefore provides curated relevant information about the miRNA basic research and therapeutic application all at hand on one site to help researchers and clinicians in making informed decision about their miRNA cancer-related research or clinical practice.

MicroRNAs (miRNAs) belong to the heterogeneous class of non-coding RNAs (ncRNAs) that regulate the translation and degradation of target mRNAs, and control approximately 30% of human genes. MiRNA genes might be silenced in human tumors (oncomiRs) by aberrant hypermethylation of CpG islands that encompass or lie adjacent to miRNA genes and/or by histone modifications. We performed literature search for research articles describing epigenetically regulated miRNAs in cancer and identified 45 studies that were published between 2006 and 7/2010. The data from those papers are fragmented and methodologically heterogeneous and our work represents first systematic review towards to integration of diverse sets of information. We reviewed the methods used for detection of miRNA epigenetic regulation, which comprise bisulfite genomic sequencing PCR (BSP), bisulfite pyrosequencing, methylation specific PCR (MSP), combined bisulfite restriction analysis (COBRA), methylation sensitive single nucleotide primer extension (Ms-SNuPE), MassARRAY technique and some modifications of those methods. This integrative study revealed 122 miRNAs that were reported to be epigenetically regulated in 23 cancer types. Compared to protein coding genes, human oncomiRs showed an order of magnitude higher methylation frequency (11.6%; 122/1048 known miRNAs). Nearly half, (45%; 55/122) epigenetically regulated miRNAs were associated with different cancer types, but other 55% (67/122) miRNAs were present in only one cancer type and therefore representing cancer-specific biomarker potential. The data integration revealed miRNA epigenomic hot spots on the chromosomes 1q, 7q, 11q, 14q and 19q. CpG island analysis of corresponding miRNA precursors (pre-miRNAs) revealed that 20% (26/133) of epigenetically regulated miRNAs had a CpG island within the range of 5kb upstream, among them 14% (19/133) of miRNAs resided within the CpG island. Our integrative survey and analyses revealed candidate cancer-specific miRNA epigenetic signatures which provide the basis for new therapeutic strategies in cancer by targeting the epigenetic regulation of miRNAs.

Many biological phenomena can be represented as complex networks. Using a protein binding site comparison approach, we generated a network of ion binding sites on the scale of all known protein structures from the Protein Data Bank. We found that this ion binding site similarity network is scale-free, indicating a network in which a few ion binding site scaffolds are the network hubs, and these are connected to hundreds of nodes, whereas the vast majority of nodes have only a few neighbors. Enrichment and statistical analysis of the network components and communities yielded insights into underlying processes from the functional and the structural perspective. Largest components and communities were observed to be closely related to basic metabolic processes and some of the most common structural folds, which, from the evolutionary point of view, indicates that they may be the oldest ones. Further, we derived the first comprehensive map of ion interchangeability, based on binding site similarity. Several highly interchangeable protein-ion binding site pairs emerged (e.g., Ca2+ and Mg2+ ), as well as structurally distinct ones. The constructed network of ion binding site similarities will aid in understanding the general principles of protein-ion binding sites structure, function and evolution. We demonstrate potential uses of the network on proteins involved in cancer development and immune response, where individual ions play prominent roles in disease development.

The major parts of the coding region and promoter of the equine kappa casein (CSN3) gene were sequenced and compared among several species. Four SNPs were identified in the CSN3 gene: two in exon 1 and two in exon 4. The SNPs were genotyped in six Slovenian horse breeds using RFLP and two different PCR-based methods. The highest variation in genotype frequencies was found in the Slovenian cold-blood breed. The SNPs in exon 4 may cause a change in the amino acid sequence and may alter chemical/functional properties of the protein. Using horse-specific primers, we obtained 400 bp of exon 4 sequence from zebra and donkey. Two SNPs within the zebra exon 4 sequence were discovered; both presumably caused amino acid substitutions. Within the equine promoter sequence, 15 SNPs were found and 12 of them could be involved in the gain/loss of potential transcription factor (TF) binding sites. Using a comparative genomics approach, we obtained 1482 bp of the promoter sequence from zebra and donkey. Sequence alignment revealed highly conserved blocks of promoter sequence among nine species (sheep, goat, cow, zebra, donkey, horse, chimp, macaque and human) and clustered these species in three distinct groups. Consensus binding sites for TFs STAT5, C/EBP, NF1 and STAT6, previously demonstrated to be associated with expression, were located within conserved regions. Four promoter regions were tested for specific binding of TFs using electrophoretic mobility shift assays. Predicted binding sites for C/EBP and NF1 were confirmed and one conserved region was specifically detected by a yet-uncharacterized TF.

Background The peroxisome proliferator–activated receptor-gamma (PPARγ) gene has been recently associated with type 2 diabetes, obesity and traits depending on VEGF expression (e.g. retinopathy). The PPARγ gene and its coactivator, the peroxisome proliferator–activated receptor-gamma coactivator-1 (PPARGC1) gene, have been implicated to be involved in glucose uptake and altered lipid oxidation. We therefore hypothesized that the Gly482Ser polymorphism of the PPARGC1 gene and Pro12Ala polymorphism of the PPARγ gene might confer susceptibility to diabetic retinopathy in type 2 diabetes. The aim of this study was to investigate the association between the Pro12Ala polymorphism in the PPARγ gene and Gly482Ser polymorphism in the PPARGC1 gene and the development of diabetic retinopathy in the Slovene population (Caucasians) with type 2 diabetes. Methods One hundred and sixty subjects with type 2 diabetes and diabetic retinopathy were compared with 101 diabetic subjects without diabetic retinopathy. Chi-square test was used to compare discrete variables, and continuous clinical data were compared by unpaired students t − test. Results A significantly higher frequency of the AA genotype of the Gly482Ser polymorphism of the PPARGC1 gene was found in the patients with diabetic retinopathy compared to the patients without diabetic retinopathy (14.4% vs 5.9%; p = 0.035), whereas the Pro12Ala polymorphism of the PPARγ gene failed to yield an association with diabetic retinopathy. Conclusions The present study demonstrates that the AA genotype of the Gly482Ser polymorphism in the PPARGC1 gene might be a risk factor for diabetic retinopathy in the Slovene population (Caucasians) with type 2 diabetes (odds ratio 2.7, 95% confidence interval 1.0–6.8), whereas the Pro12Ala polymorphism of the PPARγ gene failed to confer susceptibility to diabetic retinopathy. Copyright © 2005 John Wiley & Sons, Ltd.