Noncoding Regulatory Sequences Research Articles

Deletion upstream of MAB21L2 highlights the importance of evolutionarily conserved non-coding sequences for eye development

Anophthalmia, microphthalmia and coloboma (AMC) comprise a spectrum of developmental eye disorders, accounting for approximately 20% of childhood visual impairment. While non-coding regulatory sequences are increasingly recognised as contributing to disease burden, characterising their impact on gene function and phenotype remains challenging. Furthermore, little is known of the nature and extent of their contribution to AMC phenotypes. We report two families with variants in or near MAB21L2, a gene where genetic variants are known to cause AMC in humans and animal models. The first proband, presenting with microphthalmia and coloboma, has a likely pathogenic missense variant (c.338 G > C; p.[Trp113Ser]), segregating within the family. The second individual, presenting with microphthalmia, carries an ~ 113.5 kb homozygous deletion 19.38 kb upstream of MAB21L2. Modelling of the deletion results in transient small lens and coloboma as well as midbrain anomalies in zebrafish, and microphthalmia and coloboma in Xenopus tropicalis. Using conservation analysis, we identify 15 non-coding conserved elements (CEs) within the deleted region, while ChIP-seq data from mouse embryonic stem cells demonstrates that two of these (CE13 and 14) bind Otx2, a protein with an established role in eye development. Targeted disruption of CE14 in Xenopus tropicalis recapitulates an ocular coloboma phenotype, supporting its role in eye development. Together, our data provides insights into regulatory mechanisms underlying eye development and highlights the importance of non-coding sequences as a source of genetic diagnoses in AMC.

A Kernelized Classification Approach for Cancer Recognition Using Markovian Analysis of DNA Structure Patterns as Feature Mining.

Nucleotide-based molecules called DNA and RNA are essential for several biological processes that affect both normal and cancerous cells. They contain the critical genetic material needed for normal cell growth and functioning. The DNA structure patterns that make up the genetic code affect cells' growth, behavior, and control. Different DNA structure patterns indicate different physiological effects in the cell. Knowledge of these patterns is necessary to identify the molecular origins of cancer and other disorders. Analyzing these patterns can help in the early detection of diseases, which is essential for the effectiveness of cancer research and therapy. The novelty of this study is to examine the patterns of dinucleotide structure in many genomic regions, including the non-coding region sequence (N-CDS), coding region sequence (CDS), and whole raw DNA sequence (W.R. sequence). It provides an in-depth discussion of dinucleotide patterns related to these diverse genetic environments and contains malignant and non-malignant DNA sequences. The Markovian modeling that predicts dinucleotide probabilities also reduces feature complexity and minimizes computational costs compared to the approaches of Kernelized Logistic Regression (KLR) and Support Vector Machine (SVM). This technique is effectively evaluated in essential case studies, as indicated by accuracy metrics and 10-fold cross-validation. The classifier and feature reduction, which are generated by Markovian probability, operate well together and can help predict cancer. Our findings successfully distinguish DNA sequences related to cancer from those diagnostics of non-cancerous diseases by analyzing the W.R. DNA sequence as well as its CDS and N-CDS regions.

M-F noncoding region sequences of H1 genotype measles virus provide higher resolution for virus transmission tracing

As countries and regions move toward measles elimination, extended sequence window including noncoding region located between the matrix and fusion protein genes (M − F NCR) was considered to be used in molecular surveillance. The molecular resolution of M − F NCR was evaluated with 192 genotype H1 strains circulating during 2011–2018 in China. Phylogenetic analyses of the N450 and M − F NCR targets indicated that both two targets could confirm epi-linked outbreak, while M − F NCR target could further improve resolution of the molecular characterization: (1) it could differentiate the strains with identical N450 circulated in one county within one month of disease onset; (2) different transmission chains could be distinguished for strains with identical N450; (3) better spatial-temporal consistency with topology could be provided among sporadic cases with inconsistent N450. Accordingly, M − F NCR could be used to complement the information from N450 to address the specific questions in tracking the virus transmission chains.

Deep learning the cis-regulatory code for gene expression in selected model plants

Elucidating the relationship between non-coding regulatory element sequences and gene expression is crucial for understanding gene regulation and genetic variation. We explored this link with the training of interpretable deep learning models predicting gene expression profiles from gene flanking regions of the plant species Arabidopsis thaliana, Solanum lycopersicum, Sorghum bicolor, and Zea mays. With over 80% accuracy, our models enabled predictive feature selection, highlighting e.g. the significant role of UTR regions in determining gene expression levels. The models demonstrated remarkable cross-species performance, effectively identifying both conserved and species-specific regulatory sequence features and their predictive power for gene expression. We illustrated the application of our approach by revealing causal links between genetic variation and gene expression changes across fourteen tomato genomes. Lastly, our models efficiently predicted genotype-specific expression of key functional gene groups, exemplified by underscoring known phenotypic and metabolic differences between Solanum lycopersicum and its wild, drought-resistant relative, Solanum pennellii.

Genetic analysis of Octopus cyanea reveals high gene flow in the South-West Indian Ocean.

Octopus cyanea (Gray, 1849), abundant in the South-West Indian Ocean (SWIO), constitutes a vital resource for both subsistence and commercial fisheries. However, despite this socioeconomic importance, and recent indications of overfishing, little is known about the population structure of O. cyanea in the region. To inform sustainable management strategies, this study assessed the spatio-temporal population structure and genetic variability of O. cyanea at 20 sites in the SWIO (Kenya, Tanzania, Mozambique, Madagascar, Mauritius, Rodrigues, and the Seychelle Islands) by complementary analysis of mitochondrial DNA (mtDNA) noncoding region (NCR) sequences and microsatellite markers. MtDNA analysis revealed a shallow phylogeny across the region, with demographic tests suggesting historic population fluctuations that could be linked to glacial cycles. Contrary to expectations, NCR variation was comparable to other mtDNA regions, indicating that the NCR is not a hypervariable region. Both nuclear and mtDNA marker types revealed a lack of genetic structure compatible with high gene flow throughout the region. As adults are sedentary, this gene flow likely reflects connectivity by paralarval dispersal. All samples reported heterozygote deficits, which, given the overall absence of structure, likely reflect ephemeral larval recruitment variability. Levels of mtDNA and nuclear variability were similar at all locations and congruent with those previously reported for harvested Octopodidae, implying resilience to genetic erosion by drift, providing current stock sizes are maintained. However, as O. cyanea stocks in the SWIO represent a single, highly connected population, fisheries may benefit from additional management measures, such as rotational closures aligned with paralarval ecology and spanning geopolitical boundaries.

Systematic characterization of the HOXA9 downstream targets in MLL-r leukemia by noncoding CRISPR screens

Accumulating evidence indicates that HOXA9 dysregulation is necessary and sufficient for leukemic transformation and maintenance. However, it remains largely unknown how HOXA9, as a homeobox transcriptional factor, binds to noncoding regulatory sequences and controls the downstream genes. Here, we conduct dropout CRISPR screens against 229 HOXA9-bound peaks identified by ChIP-seq. Integrative data analysis identifies reproducible noncoding hits, including those located in the distal enhancer of FLT3 and intron of CDK6. The Cas9-editing and dCas9-KRAB silencing of the HOXA9-bound sites significantly reduce corresponding gene transcription and impair cell proliferation in vitro, and in vivo by transplantation into NSG female mice. In addition, RNA-seq, Q-PCR analysis, chromatin accessibility change, and chromatin conformation evaluation uncover the noncoding regulation mechanism of HOXA9 and its functional downstream genes. In summary, our work improves our understanding of how HOXA9-associated transcription programs reconstruct the regulatory network specifying MLL-r dependency.

Mouse genome rewriting and tailoring of three important disease loci

Genetically engineered mouse models (GEMMs) help us to understand human pathologies and develop new therapies, yet faithfully recapitulating human diseases in mice is challenging. Advances in genomics have highlighted the importance of non-coding regulatory genome sequences, which control spatiotemporal gene expression patterns and splicing in many human diseases1,2. Including regulatory extensive genomic regions, which requires large-scale genome engineering, should enhance the quality of disease modelling. Existing methods set limits on the size and efficiency of DNA delivery, hampering the routine creation of highly informative models that we call genomically rewritten and tailored GEMMs (GREAT-GEMMs). Here we describe ‘mammalian switching antibiotic resistance markers progressively for integration’ (mSwAP-In), a method for efficient genome rewriting in mouse embryonic stem cells. We demonstrate the use of mSwAP-In for iterative genome rewriting of up to 115 kb of a tailored Trp53 locus, as well as for humanization of mice using 116 kb and 180 kb human ACE2 loci. The ACE2 model recapitulated human ACE2 expression patterns and splicing, and notably, presented milder symptoms when challenged with SARS-CoV-2 compared with the existing K18-hACE2 model, thus representing a more human-like model of infection. Finally, we demonstrated serial genome writing by humanizing mouse Tmprss2 biallelically in the ACE2 GREAT-GEMM, highlighting the versatility of mSwAP-In in genome writing.

Identification and characterization of transcribed enhancers during cerebellar development through enhancer RNA analysis

BackgroundThe development of the brain requires precise coordination of molecular processes across many cell-types. Underpinning these events are gene expression programs which require intricate regulation by non-coding regulatory sequences known as enhancers. In the context of the developing brain, transcribed enhancers (TEs) regulate temporally-specific expression of genes critical for cell identity and differentiation. Transcription of non-coding RNAs at active enhancer sequences, known as enhancer RNAs (eRNAs), is tightly associated with enhancer activity and has been correlated with target gene expression. TEs have been characterized in a multitude of developing tissues, however their regulatory role has yet to be described in the context of embryonic and early postnatal brain development. In this study, eRNA transcription was analyzed to identify TEs active during cerebellar development, as a proxy for the developing brain. Cap Analysis of Gene Expression followed by sequencing (CAGE-seq) was conducted at 12 stages throughout embryonic and early postnatal cerebellar development.ResultsTemporal analysis of eRNA transcription identified clusters of TEs that peak in activity during either embryonic or postnatal times, highlighting their importance for temporally specific developmental events. Functional analysis of putative target genes identified molecular mechanisms under TE regulation revealing that TEs regulate genes involved in biological processes specific to neurons. We validate enhancer activity using in situ hybridization of eRNA expression from TEs predicted to regulate Nfib, a gene critical for cerebellar granule cell differentiation.ConclusionsThe results of this analysis provide a valuable dataset for the identification of cerebellar enhancers and provide insight into the molecular mechanisms critical for brain development under TE regulation. This dataset is shared with the community through an online resource (https://goldowitzlab.shinyapps.io/trans-enh-app/).

DNA:RNA Hybrids Are Major Dinoflagellate Minicircle Molecular Types.

Peridinin-containing dinoflagellate plastomes are predominantly encoded in nuclear genomes, with less than 20 essential chloroplast proteins carried on "minicircles". Each minicircle generally carries one gene and a short non-coding region (NCR) with a median length of approximately 400-1000 bp. We report here differential nuclease sensitivity and two-dimensional southern blot patterns, suggesting that dsDNA minicircles are in fact the minor forms, with substantial DNA:RNA hybrids (DRHs). Additionally, we observed large molecular weight intermediates, cell-lysate-dependent NCR secondary structures, multiple bidirectional predicted ssDNA structures, and different southern blot patterns when probed with different NCR fragments. In silico analysis suggested the existence of substantial secondary structures with inverted repeats (IR) and palindrome structures within the initial ~650 bp of the NCR sequences, in accordance with conversion event(s) outcomes with PCR. Based on these findings, we propose a new transcription-templating-translation model, which is associated with cross-hopping shift intermediates. Since dinoflagellate chloroplasts are cytosolic and lack nuclear envelope breakdown, the dynamic DRH minicircle transport could have contributed to the spatial-temporal dynamics required for photosystem repair. This represents a paradigm shift from the previous understanding of "minicircle DNAs" to a "working plastome", which will have significant implications for its molecular functionality and evolution.

Preclinical development of RAG1-40-31L: A novel small activating RNA-lipid conjugate targeting tumor suppressor gene p21 for treatment of non-muscle invasive bladder cancer.

e16620 Background: Loss-of-function of tumor suppressor genes are the dominant driving force in tumorigenesis. Restoration in function and/or expression of these genes holds tremendous therapeutic potential in cancer treatment. Bladder cancer is the 9th leading cause of cancer-related deaths in the United States in which ~75% of all newly diagnosed cases are non-muscle invasive bladder cancer (NMIBC). Standard-of-care includes intravesical installation of Bacillus Calmette-Guerin following tumor resection with an expected failure rate of ~50% within 6 months for patients with high-grade tumors. RNA activation (RNAa) is a mechanism in which short RNA duplexes termed small activating RNA (saRNA) induce gene transcription by targeting non-coding regulatory sequence ( i.e., promoters) embedded in chromatin. Thus, saRNA-induced overexpression of p21WAF1/CIP1 (p21) – a tumor suppressor of several anti-growth pathways – may hold therapeutic potential in bladder cancer. Through conjugation of a novel lipid ( i.e., C5X5), we have created a p21-targeting saRNA drug candidate referred to as RAG01-40-31L for delivery to bladder cancer cells in vivo. The aim of this work was to characterize the intravesical administration of RAG01-40-31L on p21 induction and its anti-tumor potential in NMBIC models. Methods: In vitro expression analyses were performed to investigate p21 induction via saRNA in KU7 and T24 bladder cancer cell lines by RT-qPCR and immunoblot analysis. Cell cycle analysis and tumorigenicity assays examined impact of RAG1-40-31L on cancer cell growth. Orthotopic human bladder tumors were established in female BALB/c nude mice using the recombinant cell line KU7 engineered to overexpress luciferase reporter. Tumor growth was monitored in live animals via luciferase bioluminescence using an in vivo imaging system. Plasma and tissue were harvested for drug exposure and expression analytics. Results: In vitro analyses indicated RAG1-40-31L activated p21 expression by approximately 6-fold and inhibited bladder cancer cell growth ( i.e., cell cycle arrest, apoptosis, and senescence) in a dose-dependent manner with low nanomolar potency. Intravesical administration of RAG1-40-31L (3 times per week for 2 weeks) inhibited growth of orthotopic tumors by 65% in mouse bladder models. Single-dose pharmacokinetics demonstrated a half-life (t1/2) of ~114 h with minimal systemic exposure (~0.05% of that of bladder tissue). Conclusions: These data constitute a preclinical proof-of-concept for saRNA as a novel p21-targeting modality in the treatment of cancer. The C5X5 lipid conjugate appears to be a viable approach to enhance oligonucleotide delivery and activity in bladder cancer. Preclinical safety assessment studies to enable clinical trials of RAG01-40-31L are currently underway.

Health care-associated measles outbreak in pediatric wards in a tertiary care hospital: Challenges and Swiss cheese model enforcement for patient safety

IntroductionMeasles is one of the most contagious of all infectious diseases, for example, up to 9 out of 10 susceptible people with close contact to a measles patient will develop measles. In countries where measles is rare, transmissions in health care facilities have been a key factor in amplifying outbreaks ObjectivesDescribe the hospital transmission of measles among unvaccinated children in pediatric service, challenges faced and recommendations for health care settings by applying the Swiss cheese model. MethodBetween December 2019 and January 2020; multiple exposures to measles cases occurred. The incident and factors that led to the outbreak are described. The matrix and fusion genes, non-coding region sequence analysis was also conducted on the 3 strains isolated from the cases. ResultsThe outbreak extended from December 2019 to January 2020, which resulted in 110 exposed individuals (85 health care workers and 25 patients). Eleven (44%) children exposed were vaccinated, 14 (56%) were not yet vaccinated, and the measles status of 10 (11.8%) HCWs was not known at the time of the outbreak. Two infants acquired measles in the hospital, and both required ICU care. Three infants and one HCW received immunoglobulin. The phylogenetic tree of the matrix and fusion genes, non-coding region sequencing confirmed that all three cases had 100% identical measles strain. ConclusionsIn countries where measles elimination goals are achieved, a multifaceted approach to prevent measles transmission in health care is vital to maintain patient safety.

Cis-Acting Element at the 5' Noncoding Region of Tacaribe Virus S RNA Modulates Genome Replication.

Tacaribe virus (TCRV) is the prototype of New World mammarenaviruses, a group that includes several members that cause hemorrhagic fevers in humans. The TCRV genome comprises two RNA segments, named S (small) and L (large). Both genomic segments contain noncoding regions (NCRs) at their 5' and 3' ends. While the 5'- and 3'-terminal 19-nucleotide sequences are known to be essential for promoter function, the role of their neighboring internal noncoding region (iNCR) sequences remains poorly understood. To analyze the relevance of the 5' and 3' iNCRs in TCRV S RNA synthesis, mutant S-like minigenomes and miniantigenomes were generated. Using a minireplicon assay, Northern blotting, and reverse transcription-quantitative PCR, we demonstrated that the genomic 5' iNCR is specifically engaged in minigenome replication yet is not directly involved in minigenome transcription, and we showed that the S genome 3' iNCR is barely engaged in this process. Analysis of partial deletions and point mutations, as well as total or partial substitution of the 5' iNCR sequence, led us to conclude that the integrity of the whole genomic 5' iNCR is essential and that a local predicted secondary structure or RNA-RNA interactions between the 5' and 3' iNCRs are not strictly required for viral S RNA synthesis. Furthermore, we employed a TCRV reverse genetic approach to ask whether manipulation of the S genomic 5' iNCR sequence may be suitable for viral attenuation. We found that mutagenesis of the 5' promoter-proximal subregion slightly impacted recombinant TCRV virulence in vivo. IMPORTANCE The Mammarenavirus genus of the Arenaviridae family includes several members that cause severe hemorrhagic fevers associated with high morbidity and mortality rates, for which no FDA-approved vaccines and limited therapeutic resources are available. We provide evidence demonstrating the specific involvement of the TCRV S 5' noncoding sequence adjacent to the viral promoter in replication. In addition, we examined the relevance of this region in the context of an in vivo infection. Our findings provide insight into the mechanism through which this 5' viral RNA noncoding region assists the L polymerase for efficient viral S RNA synthesis. Also, these findings expand our understanding of the effect of genetic manipulation of New World mammarenavirus sequences aimed at the rational design of attenuated recombinant virus vaccine platforms.

The Use of Next-Generation Sequencing in Pharmacogenomics.

Next-generation sequencing (NGS) methods have become more commonly performed in clinical and research laboratories. This review summarizes the current laboratory NGS-based diagnostic approaches in pharmacogenomics including targeted multi-gene panel sequencing, whole-exome sequencing (WES), and whole-genome sequencing (WGS). Clinical laboratories perform multiple non-uniform types of pharmacogenetic panels, which can reduce the overall number of single-gene tests to be more cost-efficient. Compared to the targeted multi-gene panels, which are not typically designed to detect novel variants, WES and WGS have a greater potential to identify secondary pharmacogenomic findings, which might be predictive for the pharmacotherapy outcome of different patient settings. WGS overcomes the limitations of WES enabling a more accurate exome-sequencing at appropriate coverage and the sequencing of non-coding regions. Different NGS-based study designs with different test strategies and study populations, varying sample sizes, and distinct analytical and interpretation procedures lead to different identification results of pharmacogenomic variants. The rapid progress in gene sequencing technologies will overcome the clinical and laboratory challenges of WES and WGS. Further high throughput NGS-based pharmacogenomics studies in different populations and patient settings are necessary to expand knowledge about rare functional variants and to enhance translation in clinical practice.

Systematically Interrogating Downstream Regulation Mechanisms of HOXA9 in MLL-r Leukemia Via Functional Noncoding CRISPR Screens

HOXA9 overexpression is observed in 50-70% of human acute myeloid leukemia (AML) and a subset of acute lymphoblastic leukemia (ALL) and positively correlates with poor patient outcomes. Leukemia subtypes with hallmark overexpression of HOXA9 include those carrying MLL gene rearrangements (MLL-r), NPM1c mutations, and other genetic alterations. Frequent genetic translation of NUP98-HOXA9 retained the DNA binding domain of HOXA9, suggesting the transcription factor function is essential for leukemia initiation and maintenance. Accumulating evidence indicates that HOXA9 dysregulation is sufficient and necessary for leukemic transformation. However, HOXA9 protein itself is a poor therapeutic target as it lacks targetable binding domains. Therefore, understanding HOXA9's functional downstream targets will provide alternative therapeutic targets. However, it remains largely unknown how HOXA9, as a homeobox transcriptional factor, binds to noncoding regulatory sequences and controls the downstream genes in MLL-r leukemia and across leukemias of other genetic subtypes. In this study, we have successfully established a HOXA9-miniAID expressing MLL-r B-ALL cell line to execute acute HOXA9 degradation in the same isogenic cell line background upon auxin treatment. Compared with conventional loss-of-function strategies, our AID cellular model allows the investigation of immediate downstream targets controlled by HOXA9. We have therefore identified about 1,800 reproducible peaks bound by HOXA9 at a genome-wide scale. About 80% of HOXA9 binding peaks were co-bound by HOXA9's binding partner MEIS1, and motif enrichment confirmed that more than 75% of peaks contained a typical HOXA9 consensus motif. Interestingly, >80% binding peaks are located in non-promoter cis-regulator elements. Given the essential role of HOXA9 in regulating MLL-r leukemia cell survival and differentiation, we reasoned that targeting specific HOXA9-bound peaks will affect downstream gene expression leading to a similar survival crisis seen in HOXA9 knockout cells. Based on this rationale, combinatorial CRISPR screens were performed in three biological replicates on the MLL-r SEM cell line stably expressing Cas9 and base editor (ABE8.0), followed by time-course dropout selection on days 7, 14, and 21. Integrative CRISPR screen analysis identified six reproducible noncoding hits, including a positive control located in the distal enhancer of FLT3. Functional validation by targeting these six noncoding segments with Cas9, dCas9-KRAB in additional MLL-r leukemia cell lines MOLM13, MV4,11 confirmed the survival essential of these HOXA9-bound regions. No cellular phenotype was observed in non-MLL-r leukemia cell lines, including NALM6, JURKAT, or OCI-AML2. Transplanting SEM cells targeted with sgHOXA9-in-FLT3 into NSG mice, significant growth retardation was monitored by flow analysis of peripheral blood. In addition, RNA-seq and Q-PCR analysis further identified the functional relevant downstream genes upon CRISPR editing of these HOXA9-bound noncoding segments, including FLT3, XBP1, JUN, BAHCC1, and CCDC200. Chromatin conformation characterization by Capture-C further confirmed the long-range interaction between HOXA9 bound enhancers and corresponding gene promoters in MLL-r SEM cells. In summary, using state-of-art research tools and newly established cell models, we have conducted a systematic functional screen and mechanism study of an undocumented downstream transcriptional network of HOXA9 in MLL-r leukemia cells. The work is significant as it will advance our understanding of how HOXA9-associated transcription programs reconstruct the regulatory network specifying MLL-r dependency. Moreover, our study will promote the future development of alternative therapeutic targets in HOXA9-driven (including HOXA9 and possibly NUP98-HOXA9 subtype) leukemia in patients. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Identification of Apiaceae using ITS, ITS2 and psba-trnH barcodes.

Apiaceae plants are used as medicinal herbs, pesticides, spices, and vegetables; thus, accurately identifying Apiaceae species is important. The grassland ecosystem of Heilongjiang Province in northern China has huge reserves of wild Apiaceae plants, but few reports have systematically documented their diversity. In this study, 275 Apiaceae plants of 23 species in 18 genera were collected from this area. We identified Apiaceae species by using nuclear internal transcribed spacer (ITS/ITS2) and psbA-trnH (chloroplast non-coding region) sequences based on experimental data. The identification efficiency of ITS, ITS2 and psbA-trnH sequences was determined and evaluated by sequence alignment and analysis, intraspecific and interspecific genetic distance analyses, and phylogenetic tree construction. ITS, ITS2 could distinguish 21 species from 17 genera of Apiaceae with good identification effect. When identifying species in the Apiaceae family, ITS2 can be used as the core barcode and psbA-trnH can be used as the supplementary barcode. These results can enrich the reference Apiaceae DNA barcode database.

Evolution of transcription factor binding through sequence variations and turnover of binding sites.

Variations in noncoding regulatory sequences play a central role in evolution. Interpreting such variations, however, remains difficult even in the context of defined attributes such as transcription factor (TF) binding sites. Here, we systematically link variations in cis-regulatory sequences to TF binding by profiling the allele-specific binding of 27 TFs expressed in a yeast hybrid, in which two related genomes are present within the same nucleus. TFs localize preferentially to sites containing their known consensus motifs but occupy only a small fraction of the motif-containing sites available within the genomes. Differential binding of TFs to the orthologous alleles was well explained by variations that alter motif sequence, whereas differences in chromatin accessibility between alleles were of little apparent effect. Motif variations that abolished binding when present in only one allele were still bound when present in both alleles, suggesting evolutionary compensation, with a potential role for sequence conservation at the motif's vicinity. At the level of the full promoter, we identify cases of binding-site turnover, in which binding sites are reciprocally gained and lost, yet most interspecific differences remained uncompensated. Our results show the flexibility of TFs to bind imprecise motifs and the fast evolution of TF binding sites between related species.

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.

Machine Learning Prediction of Non-Coding Variant Impact in Human Retinal cis-Regulatory Elements.

PurposePrior studies have demonstrated the significance of specific cis-regulatory variants in retinal disease; however, determining the functional impact of regulatory variants remains a major challenge. In this study, we utilized a machine learning approach, trained on epigenomic data from the adult human retina, to systematically quantify the predicted impact of cis-regulatory variants.MethodsWe used human retinal DNA accessibility data (ATAC-seq) to determine a set of 18.9k high-confidence, putative cis-regulatory elements. Eighty percent of these elements were used to train a machine learning model utilizing a gapped k-mer support vector machine–based approach. In silico saturation mutagenesis and variant scoring was applied to predict the functional impact of all potential single nucleotide variants within cis-regulatory elements. Impact scores were tested in a 20% hold-out dataset and compared to allele population frequency, phylogenetic conservation, transcription factor (TF) binding motifs, and existing massively parallel reporter assay data.ResultsWe generated a model that distinguishes between human retinal regulatory elements and negative test sequences with 95% accuracy. Among a hold-out test set of 3.7k human retinal CREs, all possible single nucleotide variants were scored. Variants with negative impact scores correlated with higher phylogenetic conservation of the reference allele, disruption of predicted TF binding motifs, and massively parallel reporter expression.ConclusionsWe demonstrated the utility of human retinal epigenomic data to train a machine learning model for the purpose of predicting the impact of non-coding regulatory sequence variants. Our model accurately scored sequences and predicted putative transcription factor binding motifs. This approach has the potential to expedite the characterization of pathogenic non-coding sequence variants in the context of unexplained retinal disease.Translational RelevanceThis workflow and resulting dataset serve as a promising genomic tool to facilitate the clinical prioritization of functionally disruptive non-coding mutations in the retina.

The evolution, evolvability and engineering of gene regulatory DNA.

Mutations in non-coding regulatory DNA sequences can alter gene expression, organismal phenotype and fitness1-3. Constructing complete fitness landscapes, in which DNA sequences are mapped to fitness, is a long-standing goal in biology, but has remained elusive because it is challenging to generalize reliably to vast sequence spaces4-6. Here we build sequence-to-expression models that capture fitness landscapes and use them to decipher principles of regulatory evolution. Using millions of randomly sampled promoter DNA sequences and their measured expression levels in the yeast Saccharomyces cerevisiae, we learn deep neural network models that generalize with excellent prediction performance, and enable sequence design for expression engineering. Using our models, we study expression divergence under genetic drift and strong-selection weak-mutation regimes to find that regulatory evolution is rapid and subject to diminishing returns epistasis; that conflicting expression objectives in different environments constrain expression adaptation; and that stabilizing selection on gene expression leads to the moderation of regulatory complexity. We present an approach for using suchmodels to detect signatures of selection on expression from natural variation in regulatory sequences and use it to discover an instance of convergent regulatory evolution. We assess mutational robustness, finding that regulatory mutation effect sizes follow a power law, characterize regulatory evolvability, visualize promoter fitness landscapes, discover evolvability archetypes and illustrate the mutational robustness of natural regulatory sequence populations. Our work provides a general framework for designing regulatorysequences andaddressing fundamental questions in regulatory evolution.

Two ovarian candidate enhancers, identified by time series enhancer RNA analyses, harbor rare genetic variations identified in ovarian insufficiency.

The genetic regulation of ovarian development remains largely unclear. Indeed, in most cases of impaired ovarian development-such as 46,XX disorders of sex development (DSD) without SRY, and premature ovarian insufficiency (POI)-the genetic causes have not been identified, and the vast majority of disease-associated sequence variants could lie within non-coding regulatory sequences. In this study, we aimed to identify enhancers of five ovarian genes known to play key roles in early ovarian development, basing our analysis on the expression of enhancer derived transcripts (eRNAs), which are considered to characterize active enhancers. Temporal expression profile changes in mouse WT1-positive ovarian cells were obtained from cap analysis of gene expression at E13.5, E16.5 and P0. We compared the chronological expression profiles of ovarian-specific eRNA with expression profiles for each of the ovarian-specific genes, yielding two candidate sequences for enhancers of Wnt4 and Rspo1. Both sequences are conserved between mouse and human, and we confirmed their enhancer activities using transient expression assays in murine granulosa cells. Furthermore, by sequencing the region in patients with impaired ovarian development in 24 patients, such as POI, gonadal dysgenesis and 46,XX DSD, we identified rare single nucleotide variants in both sequences. Our results demonstrate that combined analysis of the temporal expression profiles of eRNA and mRNA of target genes presents a powerful tool for locating cis-element enhancers, and a means of identifying disease-associated sequence variants that lie within non-coding regulatory sequences, thus advancing an important unmet need in forward human genetics.