Genomic context sensitizes regulatory elements to genetic disruption.

Genomic context critically modulates regulatory function but is difficult to manipulate systematically. The murine insulin-like growth factor 2 (Igf2)/H19 locus is a paradigmatic model of enhancer selectivity, whereby CTCF occupancy at an imprinting control region directs downstream enhancers to activate either H19 or Igf2. We used synthetic regulatory genomics to repeatedly replace the native locus with 157-kb payloads, and we systematically dissected its architecture. Enhancer deletion and ectopic delivery revealed previously uncharacterized long-range regulatory dependencies at the native locus. Exchanging the H19 enhancer cluster with the Sox2 locus control region (LCR) showed that the H19 enhancers relied on their native surroundings while the Sox2 LCR functioned autonomously. Analysis of regulatory DNA actuation across cell types revealed that these enhancer clusters typify broader classes of context sensitivity genome wide. These results show that unexpected dependencies influence even well-studied loci, and our approach permits large-scale manipulation of complete loci to investigate the relationship between regulatory architecture and function.

Packaging and containerization of computational methods.

Methods for analyzing the full complement of a biomolecule type, e.g., proteomics or metabolomics, generate large amounts of complex data. The software tools used to analyze omics data have reshaped the landscape of modern biology and become an essential component of biomedical research. These tools are themselves quite complex and often require the installation of other supporting software, libraries and/or databases. A researcher may also be using multiple different tools that require different versions of the same supporting materials. The increasing dependence of biomedical scientists on these powerful tools creates a need for easier installation and greater usability. Packaging and containerization are different approaches to satisfy this need by delivering omics tools already wrapped in additional software that makes the tools easier to install and use. In this systematic review, we describe and compare the features of prominent packaging and containerization platforms. We outline the challenges, advantages and limitations of each approach and some of the most widely used platforms from the perspectives of users, software developers and system administrators. We also propose principles to make the distribution of omics software more sustainable and robust to increase the reproducibility of biomedical and life science research.

Molecular Profile of Variants Potentially Associated with Severe Forms of COVID-19 in Amazonian Indigenous Populations.

Coronavirus disease 2019 (COVID-19) is an infection caused by SARS-CoV-2. Genome-wide association studies (GWASs) have suggested a strong association of genetic factors with the severity of the disease. However, many of these studies have been completed in European populations, and little is known about the genetic variability of indigenous peoples' underlying infection by SARS-CoV-2. The objective of the study is to investigate genetic variants present in the genes AQP3, ARHGAP27, ELF5L, IFNAR2, LIMD1, OAS1 and UPK1A, selected due to their association with the severity of COVID-19, in a sample of indigenous people from the Brazilian Amazon in order to describe potential new and already studied variants. We performed the complete sequencing of the exome of 64 healthy indigenous people from the Brazilian Amazon. The allele frequency data of the population were compared with data from other continental populations. A total of 66 variants present in the seven genes studied were identified, including a variant with a high impact on the ARHGAP27 gene (rs201721078) and three new variants located in the Amazon Indigenous populations (INDG) present in the AQP3, IFNAR2 and LIMD1 genes, with low, moderate and modifier impact, respectively.

Genomic investigation on genes related to mercury metabolism in Amazonian indigenous populations.

Studies have identified elevated levels of mercury in Amazonian Indigenous individuals, highlighting them as one of the most exposed to risks. In the unique context of the Brazilian Indigenous population, it is crucial to identify genetic variants with clinical significance to better understand vulnerability to mercury and its adverse effects. Currently, there is a lack of research on the broader genomic profile of Indigenous people, particularly those from the Amazon region, concerning mercury contamination. Therefore, the aim of this study was to assess the genomic profile related to the processes of mercury absorption, distribution, metabolism, and excretion in 64 Indigenous individuals from the Brazilian Amazon. We aimed to determine whether these individuals exhibit a higher susceptibility to mercury exposure. Our study identified three high-impact variants (GSTA1 rs1051775, GSTM1 rs1183423000, and rs1241704212), with the latter two showing a higher frequency in the study population compared to global populations. Additionally, we discovered seven new variants with modifier impact and a genomic profile different from the worldwide populations. These genetic variants may predispose the study population to more harmful mercury exposure compared to global populations. As the first study to analyze broader genomics of mercury metabolism pathways in Brazilian Amazonian Amerindians, we emphasize that our research aims to contribute to public policies by utilizing genomic investigation as a method to identify populations with a heightened susceptibility to mercury exposure.

Genomic context sensitizes regulatory elements to genetic disruption.

Enhancer function is frequently investigated piecemeal using truncated reporter assays or single deletion analysis. Thus it remains unclear to what extent enhancer function at native loci relies on surrounding genomic context. Using the Big-IN technology for targeted integration of large DNAs, we analyzed the regulatory architecture of the murine Igf2/H19 locus, a paradigmatic model of enhancer selectivity. We assembled payloads containing a 157-kb functional Igf2/H19 locus and engineered mutations to genetically direct CTCF occupancy at the imprinting control region (ICR) that switches the target gene of the H19 enhancer cluster. Contrasting activity of payloads delivered at the endogenous Igf2/H19 locus or ectopically at Hprt revealed that the Igf2/H19 locus includes additional, previously unknown long-range regulatory elements. Exchanging components of the Igf2/H19 locus with the well-studied Sox2 locus showed that the H19 enhancer cluster functioned poorly out of context, and required its native surroundings to activate Sox2 expression. Conversely, the Sox2 locus control region (LCR) could activate both Igf2 and H19 outside its native context, but its activity was only partially modulated by CTCF occupancy at the ICR. Analysis of regulatory DNA actuation across different cell types revealed that, while the H19 enhancers are tightly coordinated within their native locus, the Sox2 LCR acts more independently. We show that these enhancer clusters typify broader classes of loci genome-wide. Our results show that unexpected dependencies may influence even the most studied functional elements, and our synthetic regulatory genomics approach permits large-scale manipulation of complete loci to investigate the relationship between locus architecture and function.

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.

Molecular Profile of Variants in CDH1, TP53, PSCA, PRKAA1, and TTN Genes Related to Gastric Cancer Susceptibility in Amazonian Indigenous Populations.

Gastric Cancer is a disease associated with environmental and genetic changes, becoming one of the most prevalent cancers around the world and with a high incidence in Brazil. However, despite being a highly studied neoplastic type, few efforts are aimed at populations with a unique background and genetic profile, such as the indigenous peoples of the Brazilian Amazon. Our study characterized the molecular profile of five genes associated with the risk of developing gastric cancer by sequencing the complete exome of 64 indigenous individuals belonging to 12 different indigenous populations in the Amazon. The analysis of the five genes found a total of 207 variants, of which 15 are new in our indigenous population, and among these are two with predicted high impact, present in the TTN and CDH1 genes. In addition, at least 20 variants showed a significant difference in the indigenous population in comparison with other world populations, and three are already associatively related to some type of cancer. Our study reaffirms the unique genetic profile of the indigenous population of the Brazilian Amazon and allows us to contribute to the conception of early diagnosis of complex diseases such as cancer, improving the quality of life of individuals potentially suffering from the disease.

Epidemiological-molecular profile of variants associated with type 2 diabetes mellitus in indigenous populations from the Brazilian Amazon.

AIMS: While lifestyle factors are strongly associated with Type 2 diabetes (T2DM), genetic characteristics also play a role. However, much of the research on T2DM genetics focuses on European and Asian populations, leaving underrepresented groups, such as indigenous populations with high diabetes prevalence, understudied. METHODS: We characterized the molecular profile of 10 genes involved in T2DM risk through complete exome sequencing of 64 indigenous individuals belonging to 12 different Amazonian ethnic groups. RESULTS: The analysis revealed 157 variants, including four exclusive variants in the indigenous population located in the NOTCH2 and WFS1 genes with a modifier or moderate impact on protein effectiveness. Furthermore, a high impact variant in NOTCH2 was also found. Additionally, the frequency of 10 variants in the indigenous group showed significant differences when compared to other global populations that were evaluated. CONCLUSION: Our study identified 4 novel variants associated with T2DM in the NOTCH2 and WFS1 genes in the Amazonian indigenous populations we studied. In addition, a variant with a high predicted impact in NOTCH2 was also observed. These findings represent a valuable starting point for conducting further association and functional studies, which could help to improve our understanding of the unique characteristics of this population.

Synthetic regulatory genomics uncovers enhancer context dependence at the Sox2 locus.

Sox2 expression in mouse embryonic stem cells (mESCs) depends on a distal cluster of DNase I hypersensitive sites (DHSs), but their individual contributions and degree of interdependence remain a mystery. We analyzed the endogenous Sox2 locus using Big-IN to scarlessly integrate large DNA payloads incorporating deletions, rearrangements, and inversions affecting single or multiple DHSs, as well as surgical alterations to transcription factor (TF) recognition sequences. Multiple mESC clones were derived for each payload, sequence-verified, and analyzed for Sox2 expression. We found that two DHSs comprising a handful of key TF recognition sequences were each sufficient for long-range activation of Sox2 expression. By contrast, three nearby DHSs were entirely context dependent, showing no activity alone but dramatically augmenting the activity of the autonomous DHSs. Our results highlight the role of context in modulating genomic regulatory element function, and our synthetic regulatory genomics approach provides a roadmap for the dissection of other genomic loci.

Incidence of Hereditary Gastric Cancer May Be Much Higher than Reported.

Hereditary gastric cancers (HGCs) are supposed to be rare and difficult to identify. Nonetheless, many cases of young patients with gastric cancer (GC) fulfill the clinical criteria for considering this diagnosis but do not present the defined pathogenic mutations necessary to meet a formal diagnosis of HGC. Moreover, GC in young people is a challenging medical situation due to the usual aggressiveness of such cases and the potential risk for their relatives when related to a germline variant. Aiming to identify additional germline alterations that might contribute to the early onset of GC, a complete exome sequence of blood samples from 95 GC patients under 50 and 94 blood samples from non-cancer patients was performed and compared in this study. The number of identified germline mutations in GC patients was found to be much higher than that from individuals without a cancer diagnosis. Specifically, the number of high functional impact mutations, including those affecting genes involved in medical diseases, cancer hallmark genes, and DNA replication and repair processes, was much higher, strengthening the hypothesis of the potential causal role of such mutations in hereditary cancers. Conversely, classically related HGC mutations were not found and the number of mutations in genes in the CDH1 pathway was not found to be relevant among the young GC patients, reinforcing the hypothesis that existing alternative germline contributions favor the early onset of GC. The LILRB1 gene variants, absent in the world's cancer datasets but present in high frequencies among the studied GC patients, may represent essential cancer variants specific to the Amerindian ancestry's contributions. Identifying non-reported GC variants, potentially originating from under-studied populations, may pave the way for additional discoveries and translations to clinical interventions for GC management. The newly proposed approaches may reduce the discrepancy between clinically suspected and molecularly proven hereditary GC and shed light on similar inconsistencies among other cancer types. Additionally, the results of this study may support the development of new blood tests for evaluating cancer risk that can be used in clinical practice, helping physicians make decisions about strategies for surveillance and risk-reduction interventions.

Triple-Negative Breast Cancer circRNAome Reveals Hsa_circ_0072309 as a Potential Risk Biomarker.

Circular RNAs (circRNAs) are a class of long non-coding RNAs that have the ability to sponge RNA-Binding Proteins (RBPs). Triple-negative breast cancer (TNBC) has very aggressive behavior and poor prognosis for the patient. Here, we aimed to characterize the global expression profile of circRNAs in TNBC, in order to identify potential risk biomarkers. For that, we obtained RNA-Seq data from TNBC and control samples and performed validation experiments using FFPE and frozen tissues of TNBC patients and controls, followed by in silico analyses to explore circRNA-RBP interactions. We found 16 differentially expressed circRNAs between TNBC patients and controls. Next, we mapped the RBPs that interact with the top five downregulated circRNAs (hsa_circ_0072309, circ_0004365, circ_0006677, circ_0008599, and circ_0009043) and hsa_circ_0000479, resulting in a total of 16 RBPs, most of them being enriched to pathways related to cancer and gene regulation (e.g., AGO1/2, EIF4A3, ELAVL1, and PTBP1). Among the six circRNAs, hsa_circ_0072309 was the one that presented the most confidence results, being able to distinguish TNBC patients from controls with an AUC of 0.78 and 0.81, respectively. This circRNA may be interacting with some RBPs involved in important cancer-related pathways and is a novel potential risk biomarker of TNBC.

Identification of Genomic Variants Associated with the Risk of Acute Lymphoblastic Leukemia in Native Americans from Brazilian Amazonia.

A number of genomic variants related to native American ancestry may be associated with an increased risk of developing Acute Lymphoblastic Leukemia (ALL), which means that Latin American and hispanic populations from the New World may be relatively susceptible to this disease. However, there has not yet been any comprehensive investigation of the variants associated with susceptibility to ALL in traditional Amerindian populations from Brazilian Amazonia. We investigated the exomes of the 18 principal genes associated with susceptibility to ALL in samples of 64 Amerindians from this region, including cancer-free individuals and patients with ALL. We compared the findings with the data on populations representing five continents available in the 1000 Genomes database. The variation in the allele frequencies found between the different groups was evaluated using Fisher's exact test. The analyses of the exomes of the Brazilian Amerindians identified 125 variants, seven of which were new. The comparison of the allele frequencies between the two Amerindian groups analyzed in the present study (ALL patients vs. cancer-free individuals) identified six variants (rs11515, rs2765997, rs1053454, rs8068981, rs3764342, and rs2304465) that may be associated with susceptibility to ALL. These findings contribute to the identification of genetic variants that represent a potential risk for ALL in Amazonian Amerindian populations and might favor precision oncology measures.

Pharmacogenomic Profile of Amazonian Amerindians.

Given the role of pharmacogenomics in the large variability observed in drug efficacy/safety, an assessment about the pharmacogenomic profile of patients prior to drug prescription or dose adjustment is paramount to improve adherence to treatment and prevent adverse drug reaction events. A population commonly underrepresented in pharmacogenomic studies is the Native American populations, which have a unique genetic profile due to a long process of geographic isolation and other genetic and evolutionary processes. Here, we describe the pharmacogenetic variability of Native American populations regarding 160 pharmacogenes involved in absorption, distribution, metabolism, and excretion processes and biological pathways of different therapies. Data were obtained through complete exome sequencing of individuals from 12 different Amerindian groups of the Brazilian Amazon. The study reports a total of 3311 variants; of this, 167 are exclusive to Amerindian populations, and 1183 are located in coding regions. Among these new variants, we found non-synonymous coding variants in the DPYD and the IFNL4 genes and variants with high allelic frequencies in intronic regions of the MTHFR, TYMS, GSTT1, and CYP2D6 genes. Additionally, 332 variants with either high or moderate (disruptive or non-disruptive impact in protein effectiveness, respectively) significance were found with a minimum of 1% frequency in the Amazonian Amerindian population. The data reported here serve as scientific basis for future design of specific treatment protocols for Amazonian Amerindian populations as well as for populations admixed with them, such as the Northern Brazilian population.

The Genomic Profile Associated with Risk of Severe Forms of COVID-19 in Amazonian Native American Populations.

Genetic factors associated with COVID-19 disease outcomes are poorly understood. This study aimed to associate genetic variants in the SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6, XCR1, and ABO genes with the risk of severe forms of COVID-19 in Amazonian Native Americans, and to compare the frequencies with continental populations. The study population was composed of 64 Amerindians from the Amazon region of northern Brazil. The difference in frequencies between the populations was analyzed using Fisher's exact test, and the results were significant when p ≤ 0.05. We investigated 64 polymorphisms in 7 genes; we studied 47 genetic variants that were new or had impact predictions of high, moderate, or modifier. We identified 15 polymorphisms with moderate impact prediction in 4 genes (ABO, CXCR6, FYCO1, and SLC6A20). Among the variants analyzed, 18 showed significant differences in allele frequency in the NAM population when compared to others. We reported two new genetic variants with modifier impact in the Amazonian population that could be studied to validate the possible associations with COVID-19 outcomes. The genomic profile of Amazonian Native Americans may be associated with protection from severe forms of COVID-19. This work provides genomic data that may help forthcoming studies to improve COVID-19 outcomes.

Genomic context sensitivity of insulator function.

The specificity of interactions between genomic regulatory elements and potential target genes is influenced by the binding of insulator proteins such as CTCF, which can act as potent enhancer blockers when interposed between an enhancer and a promoter in a reporter assay. But not all CTCF sites genome-wide function as insulator elements, depending on cellular and genomic context. To dissect the influence of genomic context on enhancer blocker activity, we integrated reporter constructs with promoter-only, promoter and enhancer, and enhancer blocker configurations at hundreds of thousands of genomic sites using the Sleeping Beauty transposase. Deconvolution of reporter activity by genomic position reveals distinct expression patterns subject to genomic context, including a compartment of enhancer blocker reporter integrations with robust expression. The high density of integration sites permits quantitative delineation of characteristic genomic context sensitivity profiles and their decomposition into sensitivity to both local and distant DNase I hypersensitive sites. Furthermore, using a single-cell expression approach to test the effect of integrated reporters for differential expression of nearby endogenous genes reveals that CTCF insulator elements do not completely abrogate reporter effects on endogenous gene expression. Collectively, our results lend new insight into genomic regulatory compartmentalization and its influence on the determinants of promoter-enhancer specificity.

Comprehensive analysis of germline mutations in northern Brazil: a panel of 16 genes for hereditary cancer-predisposing syndrome investigation.

BACKGROUND: Next generation sequencing (NGS) has been a handy tool in clinical practice, mainly due to its efficiency and cost-effectiveness. It has been widely used in genetic diagnosis of several inherited diseases, and, in clinical oncology, it may enhance the discovery of new susceptibility genes and enable individualized care of cancer patients. In this context, we explored a pan-cancer panel in the investigation of germline variants in Brazilian patients presenting clinical criteria for hereditary cancer syndromes or familial history. METHODS: Seventy-one individuals diagnosed or with familial history of hereditary cancer syndromes were submitted to custom pan-cancer panel including 16 high and moderate penetrance genes previously associated with hereditary cancer syndromes (APC, BRCA1, BRCA2, CDH1, CDKN2A, CHEK2, MSH2, MSH6, MUTYH, PTEN, RB1, RET, TP53, VHL, XPA and XPC). All pathogenic variants were validated by Sanger sequencing. RESULTS: We identified a total of eight pathogenic variants among 12 of 71 individuals (16.9%). Among the mutation-positive subjects, 50% were diagnosed with breast cancer and had mutations in BRCA1, CDH1 and MUTYH. Notably, 33.3% were individuals diagnosed with polyposis or who had family cases and harbored pathogenic mutations in APC and MUTYH. The remaining individuals (16.7%) were gastric cancer patients with pathogenic variants in CDH1 and MSH2. Overall, 54 (76.05%) individuals presented at least one variant uncertain significance (VUS), totalizing 81 VUS. Of these, seven were predicted to have disease-causing potential. CONCLUSION: Overall, analysis of all these genes in NGS-panel allowed the identification not only of pathogenic variants related to hereditary cancer syndromes but also of some VUS that need further clinical and molecular investigations. The results obtained in this study had a significant impact on patients and their relatives since it allowed genetic counselling and personalized management decisions.

Can miRNA Indicate Risk of Illness after Continuous Exposure to M. tuberculosis?

The role of regulatory elements such as small ncRNAs and their mechanisms are poorly understood in infectious diseases. Tuberculosis is one of the oldest infectious diseases of humans and it is still a challenge to prevent and treat. Control of the infection, as well as its diagnosis, are still complex and current treatments used are linked to several side effects. This study aimed to identify possible biomarkers for tuberculosis by applying NGS techniques to obtain global miRNA expression profiles from 22 blood samples of infected patients with tuberculosis (n = 9), their respective healthy physicians (n = 6) and external healthy individuals as controls (n = 7). Samples were run through a pipeline consisting of differential expression, target genes, gene set enrichment and miRNA-gene network analyses. We observed 153 altered miRNAs, among which only three DEmiRNAs (hsa-let-7g-5p, hsa-miR-486-3p and hsa-miR-4732-5p) were found between the investigated patients and their respective physicians. These DEmiRNAs are suggested to play an important role in granuloma regulation and their immune physiopathology. Our results indicate that miRNAs may be involved in immune modulation by regulating gene expression in cells of the immune system. Our findings encourage the application of miRNAs as potential biomarkers for tuberculosis.

Systematic analysis of binding of transcription factors to noncoding variants.

Many sequence variants have been linked to complex human traits and diseases1, but deciphering their biological functions remains challenging, as most of them reside in noncoding DNA. Here we have systematically assessed the binding of 270 human transcription factors to 95,886 noncoding variants in the human genome using an ultra-high-throughput multiplex protein-DNA binding assay, termed single-nucleotide polymorphism evaluation by systematic evolution of ligands by exponential enrichment (SNP-SELEX). The resulting 828 million measurements of transcription factor-DNA interactions enable estimation of the relative affinity of these transcription factors to each variant in vitro and evaluation of the current methods to predict the effects of noncoding variants on transcription factor binding. We show that the position weight matrices of most transcription factors lack sufficient predictive power, whereas the support vector machine combined with the gapped k-mer representation show much improved performance, when assessed on results from independent SNP-SELEX experiments involving a new set of 61,020 sequence variants. We report highly predictive models for 94 human transcription factors and demonstrate their utility in genome-wide association studies and understanding of the molecular pathways involved in diverse human traits and diseases.

ACE2 polymorphisms as potential players in COVID-19 outcome.

The clinical condition COVID-19, caused by SARS-CoV-2, was declared a pandemic by the WHO in March 2020. Currently, there are more than 5 million cases worldwide, and the pandemic has increased exponentially in many countries, with different incidences and death rates among regions/ethnicities and, intriguingly, between sexes. In addition to the many factors that can influence these discrepancies, we suggest a biological aspect, the genetic variation at the viral S protein receptor in human cells, ACE2 (angiotensin I-converting enzyme 2), which may contribute to the worse clinical outcome in males and in some regions worldwide. We performed exomics analysis in native and admixed South American populations, and we also conducted in silico genomics databank investigations in populations from other continents. Interestingly, at least ten polymorphisms in coding, noncoding and regulatory sites were found that can shed light on this issue and offer a plausible biological explanation for these epidemiological differences. In conclusion, there are ACE2 polymorphisms that could influence epidemiological discrepancies observed among ancestry and, moreover, between sexes.

Exome Sequencing of Native Populations From the Amazon Reveals Patterns on the Peopling of South America.

Studies on the peopling of South America have been limited by the paucity of sequence data from Native Americans, especially from the east part of the Amazon region. Here, we investigate the whole exome variation from 58 Native American individuals (eight different populations) from the Amazon region and draw insights into the peopling of South America. By using the sequence data generated here together with data from the public domain, we confirmed a strong genetic distinction between Andean and Amazonian populations. By testing distinct demographic models, our analysis supports a scenario of South America occupation that involves migrations along the Pacific and Atlantic coasts. Occupation of the southeast part of South America would involve migrations from the north, rather than from the west of the continent.