Non-coding Regions Of Genome Research Articles

Comparative epigenomics reveals the impact of ruminant-specific regulatory elements on complex traits.

Insights into the genetic basis of complex traits and disease in both human and livestock species have been achieved over the past decade through detection of genetic variants in genome-wide association studies(GWAS). A majority of such variants were found located in noncoding genomic regions, and though the involvement of numerous regulatory elements (REs) has been predicted across multiple tissues in domesticated animals, their evolutionary conservation and effects on complex traits have not been fully elucidated, particularly in ruminants. Here, we systematically analyzed 137 epigenomic and transcriptomic datasets of six mammals, including cattle, sheep, goats, pigs, mice, and humans, and then integrated them with large-scale GWAS of complex traits. Using 40 ChIP-seq datasets of H3K4me3 and H3K27ac, we detected 68,479, 58,562, 63,273, 97,244, 111,881, and 87,049 REs in the liver of cattle, sheep, goats, pigs, humans and mice, respectively. We then systematically characterized the dynamic functional landscapes of these REs by integrating multi-omics datasets, including gene expression, chromatin accessibility, and DNA methylation. We identified a core set (n = 6359) of ruminant-specific REs that are involved in liver development, metabolism, and immune processes. Genes with more complex cis-REs exhibited higher gene expression levels and stronger conservation across species. Furthermore, we integrated expression quantitative trait loci (eQTLs) and GWAS from 44 and 52 complex traits/diseases in cattle and humans, respectively. These results demonstrated that REs with different degrees of evolutionary conservation across species exhibited distinct enrichments for GWAS signals of complex traits. We systematically annotated genome-wide functional REs in liver across six mammals and demonstrated the evolution of REs and their associations with transcriptional output and conservation. Detecting lineage-specific REs allows us to decipher the evolutionary and genetic basis of complex phenotypes in livestock and humans, which may benefit the discovery of potential biomedical models for functional variants and genes of specific human diseases.

Pan-Cancer Analysis Identifies MNX1 and Associated Antisense Transcripts as Biomarkers for Cancer.

The identification of diagnostic and prognostic biomarkers is a major objective in improving clinical outcomes in cancer, which has been facilitated by the availability of high-throughput gene expression data. A growing interest in non-coding genomic regions has identified dysregulation of long non-coding RNAs (lncRNAs) in several malignancies, suggesting a potential use as biomarkers. In this study, we leveraged data from large-scale sequencing projects to uncover the expression patterns of the MNX1 gene and its associated lncRNAs MNX1-AS1 and MNX1-AS2 in solid tumours. Despite many reports describing MNX1 overexpression in several cancers, limited studies exist on MNX1-AS1 and MNX1-AS2 and their potential as biomarkers. By employing clustering methods to visualise multi-gene relationships, we identified a discriminative power of the three genes in distinguishing tumour vs. normal samples in several cancers of the gastrointestinal tract and reproductive systems, as well as in discerning oesophageal and testicular cancer histological subtypes. Notably, the expressions of MNX1 and its antisenses also correlated with clinical features and endpoints, uncovering previously unreported associations. This work highlights the advantages of using combinatory expression patterns of non-coding transcripts of differentially expressed genes as clinical evaluators and identifies MNX1, MNX1-AS1, and MNX1-AS2 expressions as robust candidate biomarkers for clinical applications.

Abstract 15608: Validation of Enhancer/Silencer Activity of the Intracranial Aneurysm-Associated SNP at SOX17 in Primary Human Endothelia

Introduction: GWAS have identified multiple SNPs that occur more commonly in those with intracranial aneurysms. Many SNPs are located in noncoding genomic regions, suggesting that genetic risk may operate on functional regulatory elements that influence gene expression. However, regulatory elements are most often only indirectly identified through methods such as DNAse hypersensitivity without direct assessment of activity. Hypothesis: We hypothesize CRISPR mediated ablation of putative regulatory elements located within intergenic loci associated with IA will result in mRNA transcript modulation of genes located within the respective topology associated domain. Methods: We investigated a SNP within a haplotype block near SOX17. The haplotype was predicted to have active enhance activity, and to mediate SOX17 expression, based on assessment of its topologically associated domain. Lentiviral constructs (each with unique antibiotic resistance and fluorescent protein reporters) for the expression of Cas9 nuclease and two gRNAs flanking a putative element located at chr8:54412191-54413910 were transfected into the Lenti-X viral propagating cell line (Figure, left). Viral supernatants were transduced into primary HUVEC cells by spinfection with 5 ug/mL polybrene. After antibiotic selection and fluorescence validation, mRNA was isolated, and transcripts quantified through PCR. Results: Lentiviral transduction of HUVECs resulted in CRISPR-mediated removal of the enhancer element located within the haplotype block chr8:54397171-54415556 and resulted in a substantial increase of the SOX17 gene mRNA located within its topology associated domain (Figure, right). Conclusions: CRISPR mediated ablation was used to efficiently remove and validate a genomic element with putative regulatory activity in HUVECs. The methods will be employed to study additional regulatory elements with IA associations as well as other primary vascular cells.

Magnitude and genotype of hepatitis delta virus among chronic hepatitis B carriers with a spectrum of liver diseases in Ethiopia

Introduction and ObjectivesChronic hepatitis D infection contributes substantially to the progression of chronic liver disease, especially in most low and middle-income countries, where hepatitis B virus-related chronic liver disease is endemic. Therefore, this study aimed to determine the magnitude and genotype of hepatitis delta virus (HDV) among patients with chronic hepatitis B (CHB)-related liver diseases in Ethiopia. Patients and MethodsIn this cross-sectional study, 323 known HBsAg positive individuals comprising 220 patients with CHB-related liver diseases [121 advanced liver diseases (hepatocellular carcinoma /HCC/ and non-HCC) and 99 chronic hepatitis (CH)], and 103 symptomless blood donors (BD) were enrolled. An ELISA kit was employed to determine HDV infection, and quantitative real-time PCR was used to detect HDV RNA. In addition, a non-coding genomic RNA region was sequenced for genotyping and phylogenetic analysis. ResultsIrrespective of the stage of liver disease, the overall magnitude of HDV was 7.7% (25/323). The frequency of anti-HDV increases with the severity of liver disease, 1.9%, 4%, 10%, and 21.3% among BD, CH, non-HCC, and HCC patients, respectively. HDV RNA has been detected in 1.54 %(5/323) cases with a mean viral load of 4,010,360 IU/ml. All isolates were found to be HDV genotype 1. ConclusionsThe magnitude of HDV infection increased with the severity of liver disease, indicating HDV infection is more common among patients with CHB-related liver diseases in Ethiopia.

A primary hierarchically organized patient-derived model enables in depth interrogation of stemness driven by the coding and non-coding genome

Many cancers are organized as cellular hierarchies sustained by cancer stem cells (CSC), whose eradication is crucial for achieving long-term remission. Difficulties to isolate and undertake in vitro and in vivo experimental studies of rare CSC under conditions that preserve their original properties currently constitute a bottleneck for identifying molecular mechanisms involving coding and non-coding genomic regions that govern stemness. We focussed on acute myeloid leukemia (AML) as a paradigm of the CSC model and developed a patient-derived system termed OCI-AML22 that recapitulates the cellular hierarchy driven by leukemia stem cells (LSC). Through classical flow sorting and functional analyses, we established that a single phenotypic population is highly enriched for LSC. The LSC fraction can be easily isolated and serially expanded in culture or in xenografts while faithfully recapitulating functional, transcriptional and epigenetic features of primary LSCs. A novel non-coding regulatory element was identified with a new computational approach using functionally validated primary AML LSC fractions and its role in LSC stemness validated through efficient CRISPR editing using methods optimized for OCI-AML22 LSC. Collectively, OCI-AML22 constitutes a valuable resource to uncover mechanisms governing CSC driven malignancies.

Identifying enhancer properties associated with genetic risk for complex traits using regulome-wide association studies.

Genetic risk for complex traits is strongly enriched in non-coding genomic regions involved in gene regulation, especially enhancers. However, we lack adequate tools to connect the characteristics of these disruptions to genetic risk. Here, we propose RWAS (Regulome Wide Association Study), a new application of the MAGMA software package to identify the characteristics of enhancers that contribute to genetic risk for disease. RWAS involves three steps: (i) assign genotyped SNPs to cell type- or tissue-specific regulatory features (e.g., enhancers); (ii) test associations of each regulatory feature with a trait of interest for which genome-wide association study (GWAS) summary statistics are available; (iii) perform enhancer-set enrichment analyses to identify quantitative or categorical features of regulatory elements that are associated with the trait. These steps are implemented as a novel application of MAGMA, a tool originally developed for gene-based GWAS analyses. Applying RWAS to interrogate genetic risk for schizophrenia, we discovered a class of risk-associated AT-rich enhancers that are active in the developing brain and harbor binding sites for multiple transcription factors with neurodevelopmental functions. RWAS utilizes open-source software, and we provide a comprehensive collection of annotations for tissue-specific enhancer locations and features, including their evolutionary conservation, AT content, and co-localization with binding sites for hundreds of TFs. RWAS will enable researchers to characterize properties of regulatory elements associated with any trait of interest for which GWAS summary statistics are available.

Comparative chloroplast genome analyses of 23 species in Swertia L. (Gentianaceae) with implications for its phylogeny.

Swertia L. is a large genus in the family Gentianaceae. Different chloroplast gene segments have been used to study systematic evolutionary relationships between species of Swertia L. However, as gene fragment–based phylogenies lack sufficient resolution, the systematic evolutionary relationships between Swertia L. species have remained unclear. We sequenced and annotated the complete chloroplast genomes of four Swertia species, namely, S. bifolia, S. tetraptera, S. franchetian, and S. przewalskii, using next generation sequencing and the plastid genome annotator tool. The chloroplast genome sequences of 19 additional species of Swertia L. were downloaded from the NCBI database and also assessed. We found that all 23 Swertia L. species had a similar genetic structure, that is, a ring tetrad structure, but with some clear differences. The chloroplast genomes of the 23 Swertia L. species were 149036–153691 bp long, averaging 152385 bp; the genomes contained 134 functional genes: 38 tRNA, eight rRNA, and 88 protein-encoding genes. A comparative analysis showed that chloroplasts genome of Swertia was conserved in terms of genome structure, codon preference, and repeat sequences, but it differed in terms of genome sizes, gene contents, and SC/IR boundary. Using Swertia wolfangiana as a reference, we found clear divergences in most of the non-coding and intergenic regions of the complete chloroplast genomes of these species; we also found that rpoC1, ccsA, ndhI, ndhA, and rps15 protein-coding genes had large variations. These highly variable hotspots will be useful for future phylogenetic and population genetic studies. Phylogenetic analysis with high bootstrap support showed that Swertia L. was not monophyletic. The classification of subgen. Swertia and subgen. Ophelia was supported by molecular data, which also partly supported the division of sect. Ophelia, sect. Platynema, sect. Poephila, sect. Swertia, and sect. Macranthos. However, the systematic positions of other groups and species require further exploration. The Swertia L formed at 29.60 Ma. Speciation of 10 species occurred in succession after 12 Ma and 13 species occurred in succession after 2.5 Ma. Our analysis provides insight into the unresolved evolutionary relationships of Swertia L. species.

Genetic identification of tissues and cell types underlying attention-deficit/hyperactivity disorder.

BackgroundGenome-wide association studies (GWASs) have identified numerous genetic variants associated with attention-deficit/hyperactivity disorder (ADHD), which is considered highly genetically heritable. However, because most of the variants located in the non-coding region of the human genome, the onset of ADHD requires further exploration.MethodsThe risk genes involved in ADHD were identified by integrating GWAS summary data and expression quantitative trait locus (eQTL) data using summary-data-based Mendelian randomization (SMR) method. We then used a stratified linkage disequilibrium score regression (LDSR) method to estimate the contribution of ADHD-relevant tissues to its heritability to screen out disease-relevant tissues. To determine the ADHD-relevant cell types, we used an R package for expression-weighted cell type enrichment (EWCE) analysis.ResultsBy integrating the brain eQTL data and ADHD GWAS data using SMR, we identified 247 genes associated with ADHD. The LDSR applied to specifically expressed genes results showed that the ADHD risk genes were mainly enriched in brain tissue, especially in the mesencephalon, visual cortex, and frontal lobe regions. Further cell-type-specific analysis suggested that ADHD risk genes were highly expressed in excitatory neurons.ConclusionThe study showed that the etiology of ADHD is associated with excitatory neurons in the midbrain, visual cortex, and frontal lobe regions.

Comparative analysis of chloroplast genomes of three medicinal Carpesium species: Genome structures and phylogenetic relationships.

Carpesium (Asteraceae) is a genus that contains many plant species with important medicinal values. However, the lack of chloroplast genome research of this genus has greatly hindered the study of its molecular evolution and phylogenetic relationship. This study used the Illumina sequencing platform to sequence three medicinal plants of the Carpesium genus: Carpesium abrotanoides, Carpesium cernuum, and Carpesium faberi, obtaining three complete chloroplast genome sequences after assembly and annotation. It was revealed that the three chloroplast genomes were typical quadripartite structures with lengths of 151,389 bp (C. abrotanoides), 151,278 bp (C. cernuum), and 151,250 bp (C. faberi), respectively. A total of 114 different genes were annotated, including 80 protein-coding genes, 30 tRNA genes, and 4 rRNA genes. Abundant SSR loci were detected in all three chloroplast genomes, with most composed of A/T. The expansion and contraction of the IR region indicate that the boundary regions of IR/SC are relatively conserved for the three species. Using C. abrotanoides as a reference, most of the non-coding regions of the chloroplast genomes were significantly different among the three species. Five different mutation hot spots (trnC-GCA-petN, psaI, petA-psbJ, ndhF, ycf1) with high nucleotide variability (Pi) can serve as potential DNA barcodes of Carpesium species. Additionally, phylogenetic evolution analysis of the three species suggests that C. cernuum has a closer genetic relationship to C. faberi than C. abrotanoides. Simultaneously, Carpesium is a monophyletic group closely related to the genus Inula. Complete chloroplast genomes of Carpesium species can help study the evolutionary and phylogenetic relationships and are expected to provide genetic marker assistance to identify Carpesium species.

AthEDL: Identifying Enhancers in Arabidopsis thaliana Using an Attention-based Deep Learning Method

Background: Enhancers are key cis-function elements of DNA structure that are crucial in gene regulation and the function of a promoter in eukaryotic cells. Availability of accurate identification of the enhancers would facilitate the understanding of DNA functions and their physiological roles. Previous studies have revealed the effectiveness of computational methods for identifying enhancers in other organisms. To date, a huge number of enhancers remain unknown, especially in the field of plant species. Objective: In this study, the aim is to build an efficient attention-based neural network model for the identification of Arabidopsis thaliana enhancers. Method: A sequence-based model using convolutional and recurrent neural networks was proposed for the identification of enhancers. The input DNA sequences are represented as feature vectors by 4-mer. A neural network model consists of CNN and Bi-RNN as sequence feature extractors, and the attention mechanism is suggested to improve the prediction performance. Results: We implemented an ablation study on validation set to select and evaluate the effectiveness of our proposed model. Moreover, our model showed remarkable performance on the test set achieving the Mcc of 0.955, the AUPRC of 0.638, and the AUROC of 0.837, which are significantly higher than state-of-the-art methods, respectively. Conclusion: The proposed computational framework aims at solving similar problems in non-coding genomic regions, thereby providing valuable insights into the prediction about the enhancers of plants.

The pharmacogenomics of selective serotonin reuptake inhibitors.

Antidepressant medications are frequently used as the first line of treatment for depression. However, their effectiveness is highly variable and influenced by genetic factors. Recently, pharmacogenetic studies, including candidate-gene, genome-wide association studiesor polygenic risk scores, have attempted to uncover the genetic architecture of antidepressant response. Genetic variants in at least 27 genes arelinked to antidepressant treatment response in both coding and non-coding genomic regions, but evidence is largely inconclusive due to the high polygenicity of the trait and limited cohort sizes in published studies. Future studies should increase the number and diversity of participants to yield sufficient statistical power to characterize the genetic underpinnings and biological mechanisms of treatment response, improve results generalizabilityand reduce racial health-related inequities.

Comprehensive analysis of complete chloroplast genome and phylogenetic aspects of ten Ficus species

BackgroundThe large genus Ficus comprises approximately 800 species, most of which possess high ornamental and ecological values. However, its evolutionary history remains largely unknown. Plastome (chloroplast genome) analysis had become an essential tool for species identification and for unveiling evolutionary relationships between species, genus and other rank groups. In this work we present the plastomes of ten Ficus species.ResultsThe complete chloroplast (CP) genomes of eleven Ficus specimens belonging to ten species were determined and analysed. The full length of the Ficus plastome was nearly 160 kbp with a similar overall GC content, ranging from 35.88 to 36.02%. A total of 114 unique genes, distributed in 80 protein-coding genes, 30 tRNAs, and 4 rRNAs, were annotated in each of the Ficus CP genome. In addition, these CP genomes showed variation in their inverted repeat regions (IR). Tandem repeats and mononucleotide simple sequence repeat (SSR) are widely distributed across the Ficus CP genome. Comparative genome analysis showed low sequence variability. In addition, eight variable regions to be used as potential molecular markers were proposed for future Ficus species identification. According to the phylogenetic analysis, these ten Ficus species were clustered together and further divided into three clades based on different subgenera. Simultaneously, it also showed the relatedness between Ficus and Morus.ConclusionThe chloroplast genome structure of 10 Ficus species was similar to that of other angiosperms, with a typical four-part structure. Chloroplast genome sizes vary slightly due to expansion and contraction of the IR region. And the variation of noncoding regions of the chloroplast genome is larger than that of coding regions. Phylogenetic analysis showed that these eleven sampled CP genomes were divided into three clades, clustered with species from subgenus Urostigma, Sycomorus, and Ficus, respectively. These results support the Berg classification system, in which the subgenus Ficus was further decomposed into the subgenus Sycomorus. In general, the sequencing and analysis of Ficus plastomes, especially the ones of species with no or limited sequences available yet, contribute to the study of genetic diversity and species evolution of Ficus, while providing useful information for taxonomic and phylogenetic studies of Ficus.

Systematic Integration of Epigenomic Landscapes in Human and Mouse Blood Cells to Predict Activity and Targets of Regulatory Elements

Thousands of genome‐wide epigenetic (epigenomic) datasets determined in the past decade have generated maps of chromatin accessibility, histone modifications, and binding by transcription factors and structural proteins in a large number of cell types in humans and model species. Such maps have revealed many informative associations between groups of epigenetic features and different classes of cis‐regulatory elements (CREs), and they enable a prediction of the locations of candidate CREs (cCREs) in many genomes. The actuation (opening of chromatin) and epigenetic state (combination of features such as histone modifications) acquired at specific cCREs has been associated with specific gene activation. However, despite the large number and rich variety of available epigenomic datasets, it is difficult for researchers to effectively utilize all the data relevant to their projects. Furthermore, comprehensive rules and catalogs have not been established for which CREs regulate specific target genes and how. Integrative analysis can help meet these needs, and our VISION project provides a ValIdated Systematic IntegratiONof epigenomic data in hematopoiesis in human and mouse blood cells. After careful curation and normalization of epigenomic data from many sources, we systematically integrated these data to generate a comprehensive view of the regulatory landscape (epigenetic states) and predicted cCREs in differentiating hematopoietic cell types jointly in both mouse and human. Multiple machine learning approaches reveal target genes predicted to be regulated by each element in different cell types. These approaches include predicting the regulatory impact of each element on targets by regression models, finding linkages between distinctive clusters of elements and potential target genes from self‐organizing maps, and visual overlays of chromatin interaction maps. Directed mutation and expression analysis around selected genes supports the utility of the assignments. These catalogs of highly annotated regulatory elements are useful for many applications, including interpretation of the phenotypic impact of genetic variants in noncoding genomic regions. Resources from the VISION project are available at our website usevision.org.

Cis-regulatory elements (CREs) in spinal solitary fibrous tumours (SFT)

Spinal Solitary Fibrous Tumour is a rare soft tissue neoplasm. Although a lot of genes are involved in Spinal Solitary Fibrous Tumour progression, survival and metastasis, NGFI-A binding protein 2 (NAB2) - signal transducer and activator of transcription 6 (STAT6) gene fusion is one of the most commonly occurring genetic abnormalities in all types of Solitary Fibrous Tumours (SFT). The interaction of STAT6 (Early Growth Response (EGR) transcriptional activator) and NAB2 (EGR transcriptional repressor) activates the conversion of the transcription repressor to the transcriptional activator and promotes EGR-induced promoter activity. EGR has shown to plays a role in the regulation of cell survival, proliferation and cell death. Cis-regulatory elements (CREs) are genomic sequences in non-coding regions of the genomic DNA which binds with the transcription factors, and they play an essential role in precise control of gene expression. CREs composed of enhancers, suppressors and insulators play pivotal roles in gene expression throughout life and development. They have important role in maintaining the normal homeostasis, preventing organogenesis, tumourigenesis and teratoma formation. In this study, we investigate the non-coding regions in the human genome to detect enhancers and suppressors present in different tissue samples of Spinal SFT using Encyclopedia of DNA Elements (ENCODE). The study of these enhancers and suppressors may be used to develop newer diagnostic and treatment strategies. A total of 75 genes and immunohistochemistry (IHC) markers expressed in Spinal SFT were obtained from PubMed and Google Scholar. CREs were identified using the ENCODE consortium. Protein interaction network was obtained using String v11.0 using the proteins corresponding to these 75 genes. Results obtained from ENCODE were enumerated and web-hosted for public access to design a treatment strategy. This may enable the wet lab scientist design CREs specific for Spinal SFT using the in silico results obtained.

Functional genomics and the future of iPSCs in disease modeling.

SummaryInduced pluripotent stem cells (iPSCs) are valuable in disease modeling because of their potential to expand and differentiate into virtually any cell type and recapitulate key aspects of human biology. Functional genomics are genome-wide studies that aim to discover genotype-phenotype relationships, thereby revealing the impact of human genetic diversity on normal and pathophysiology. In this review, we make the case that human iPSCs (hiPSCs) are a powerful tool for functional genomics, since they provide an in vitro platform for the study of population genetics. We describe cutting-edge tools and strategies now available to researchers, including multi-omics technologies, advances in hiPSC culture techniques, and innovations in drug development. Functional genomics approaches based on hiPSCs hold great promise for advancing drug discovery, disease etiology, and the impact of genetic variation on human biology.

Systematic annotation of conservation states provides insights into regulatory regions in rice

Plant genomes contain a large fraction of noncoding sequences. The discovery and annotation of conserved noncoding sequences (CNSs) in plants is an ongoing challenge. Here we report the application of comparative genomics to systematically identify CNSs in 50 well-annotated Gramineae genomes using rice (Oryza sativa) as the reference. We conduct multiple-way whole-genome alignments to the rice genome. The rice genome is annotated as 20 conservation states (CSs) at single-nucleotide resolution using a multivariate hidden Markov model (ConsHMM) based on the multiple-genome alignments. Different states show distinct enrichments for various genomic features, and the conservation scores of CSs are highly correlated with the level of associated chromatin accessibility. We find that at least 33.5% of the rice genome is highly under selection, with more than 70% of the sequence lying outside of coding regions. A catalog of 855,366 regulatory CNSs is generated, and they significantly overlapped with putative active regulatory elements such as promoters, enhancers, and transcription factor binding sites. Collectively, our study provides a resource for elucidating functional noncoding regions of the rice genome and an evolutionary aspect of regulatory sequences in higher plants.

Regulation of the Late Onset alzheimer's Disease Associated HLA-DQA1/DRB1 Expression.

(Genome-wide Association Studies) GWAS have identified ∼42 late-onset Alzheimer's disease (LOAD)-associated loci, each of which contains multiple single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) and most of these SNPs are in the non-coding region of human genome. However, how these SNPs regulate risk gene expression remains unknown. In this work, by using a set of novel techniques, we identified 6 functional SNPs (fSNPs) rs9271198, rs9271200, rs9281945, rs9271243, and rs9271247 on the LOAD-associated HLA-DRB1/DQA1 locus and 42 proteins specifically binding to five of these 6 fSNPs. As a proof of evidence, we verified the allele-specific binding of GATA2 and GATA3, ELAVL1 and HNRNPA0, ILF2 and ILF3, NFIB and NFIC, as well as CUX1 to these five fSNPs, respectively. Moreover, we demonstrate that all these nine proteins regulate the expression of both HLA-DQA1 and HLA-DRB1 in human microglial cells. The contribution of HLA class II to the susceptibility of LOAD is discussed.

Chromosome-scale Echinococcus granulosus (genotype G1) genome reveals the Eg95 gene family and conservation of the EG95-vaccine molecule

Cystic echinococcosis is a socioeconomically important parasitic disease caused by the larval stage of the canid tapeworm Echinococcus granulosus, afflicting millions of humans and animals worldwide. The development of a vaccine (called EG95) has been the most notable translational advance in the fight against this disease in animals. However, almost nothing is known about the genomic organisation/location of the family of genes encoding EG95 and related molecules, the extent of their conservation or their functions. The lack of a complete reference genome for E. granulosus genotype G1 has been a major obstacle to addressing these areas. Here, we assembled a chromosomal-scale genome for this genotype by scaffolding to a high quality genome for the congener E. multilocularis, localised Eg95 gene family members in this genome, and evaluated the conservation of the EG95 vaccine molecule. These results have marked implications for future explorations of aspects such as developmentally-regulated gene transcription/expression (using replicate samples) for all E. granulosus stages; structural and functional roles of non-coding genome regions; molecular ‘cross-talk’ between oncosphere and the immune system; and defining the precise function(s) of EG95. Applied aspects should include developing improved tools for the diagnosis and chemotherapy of cystic echinococcosis of humans.

CRISPR/Cas-Mediated Resistance against Viruses in Plants.

CRISPR/Cas9 provides a robust and widely adaptable system with enormous potential for genome editing directed towards generating useful products. It has been used extensively to generate resistance against viruses infecting plants with more effective and prolonged efficiency as compared with previous antiviral approaches, thus holding promise to alleviate crop losses. In this review, we have discussed the reports of CRISPR/Cas-based virus resistance strategies against plant viruses. These strategies include approaches targeting single or multiple genes (or non-coding region) in the viral genome and targeting host factors essential for virus propagation. In addition, the utilization of base editing has been discussed to generate transgene-free plants resistant to viruses. This review also compares the efficiencies of these approaches. Finally, we discuss combinatorial approaches, including multiplexing, to increase editing efficiency and bypass the generation of escape mutants.

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

BackgroundNumerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging.ResultsIn this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants.ConclusionsOur results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.