Biology subjects

Araujo, G. S.

Publications and source records attributed to Araujo, G. S..

6 recordsLinked to original sources

bioRxiv2026

SlytheRINs: using graph parameters and residue interaction networks to analyze protein dynamics and structural ensembles

Establishing the relationship between protein structure and functional behavior remains a significant challenge. The recognition that proteins are inherently dynamic, with functions often dependent on conformational changes, is increasingly accepted. Among computational approaches for elucidating protein properties, Residue Interaction Network (RIN) analysis has emerged as a powerful tool. However, conventional RIN analysis is constrained by its reliance on single, static protein structures, which fail to capture the flexibility inherent in dynamic protein folding transitions. To address these limitations, SlytheRINs is introduced as an interactive tool designed for comparative analysis of protein conformations via RINs. SlytheRINs enables dynamic ensemble analysis by decomposing interaction network data across multiple conformations of a single protein and providing detailed residue-interaction mapping across conformational changes via graph parameters in comparative plots. Applying these principles, the conformational variations of the wild-type and a pathogenic variant (G188R) of the human Glucose-6-Phosphatase (G6PC1) catalytic subunit were compared to identify fluctuations in both chemical interactions and graph features associated with conformational changes induced by the residue modification. The analyses identified key shifts in dynamic residue interactions in the protein variant that compromise substrate binding and the catalytic site, thereby elucidating the impact on G6PC1s dynamic behavior and the resulting activity loss. AvailabilityThe source code for SlytheRINs is available on GitHub (https://github.com/evomol-lab/SlytheRINs), while the web tool and documentation are available at https://slytherins.streamlit.app.

bioinformatics↗

bioRxiv2026

mtDNA-Network: a web tool to explore mitochondrial variant profiles in complex diseases

The mitochondrial genome (mtDNA) provides valuable insights into human evolution, population diversity, and disease etiology. Here, we present the mtDNA-network (https://apps.lghm.ufpa.br/mtdna/), an integrative bioinformatics database and tool for the visualization and analysis of mitochondrial variants (single-nucleotide variants and insertions/deletions). The mtDNA-network was upgraded to enable investigation of mtDNA in admixed Brazilian individuals with substantial contributions from uniparental Indigenous and African ancestries. We implement a bioinformatics pipeline to harmonize variant calling across 339 mtDNA samples. The dataset supports general genetic population analysis and variant mapping for complex diseases, including Parkinsons disease (104 cases and 75 controls), leprosy (33 cases and 37 controls), and somatic gastric cancer (40 cases and 50 controls). The mtDNA-network tool features an intuitive interface and analytical dashboards for transitions, transversions, heteroplasmy, and variant-disease networks, and serves as a strategic resource for advancing research in population genetics and precision medicine in underrepresented populations. We reinforce the critical need to expand non-European genomic representation in global databases to promote more equitable genomic diversity studies and clinically relevant discoveries.

bioinformatics↗

bioRxiv2021

NAToRA, a relatedness-pruning method to minimize the loss of dataset size in genetic and omics analyses

Genetic and omics analyses frequently require independent observations, which is not guaranteed in real datasets. When relatedness cannot be accounted for, solutions involve removing related individuals (or observations) and, consequently, a reduction of available data. We developed a network-based relatedness-pruning method that minimizes dataset reduction while removing unwanted relationships in a dataset. It uses node degree centrality metric to identify highly connected nodes (or individuals) and implements heuristics that approximate the minimal reduction of a dataset to allow its application to large datasets. NAToRA outperformed two popular methodologies (implemented in software PLINK and KING) by showing the best combination of effective relatedness-pruning, removing all relatives while keeping the largest possible number of individuals in all datasets tested and also, with similar or lesser reduction in genetic diversity. NAToRA is freely available, both as a standalone tool that can be easily incorporated as part of a pipeline, and as a graphical web tool that allows visualization of the relatedness networks. NAToRA also accepts a variety of relationship metrics as input, which facilitates its use. We also present a genealogies simulator software used for different tests performed in the manuscript.

bioinformatics↗

bioRxiv2020

From bioinformatics user to bioinformatics engineer: a report

Teaching computer programming is not a simple task and it is challenging to introduce the concepts of programming in graduate programs of other fields. Little efforts have been made on engaging students in computational development after programming trainings. An emerging need is to establish subjects of bioinformatics and programming languages in genetics and molecular biology graduate programs, when students in these degree programs are immersed in a sea of genomic and transcriptomic data, which demands proficient computational treatment. I report an empirical guideline to introduce programming languages and recommend Python as first language for graduate programs in which students were from genetics and molecular biology backgrounds. Including the development of programming solutions related to graduate students' research activities may improve programming skills and better engagement. These results suggest that the applied approach leads to enhanced learning of introductory to autonomy in highly advanced programming concepts by graduate students. This guide should be extended for other research programs.

scientific communication and education↗

bioRxiv2019

Admixture/fine-mapping in Brazilians reveals a West African associated potential regulatory variant (rs114066381) with a strong female-specific effect on body mass- and fat mass-indexes

Admixed populations are a resource to study the global genetic architecture of complex phenotypes, which is critical, considering that non-European populations are severely under-represented in genomic studies. Leveraging admixture in Brazilians, whose chromosomes are mosaics of fragments of Native American, European and African origins, we used genome-wide data to perform admixture mapping/fine-mapping of Body Mass Index (BMI) in three population-based cohorts from Northeast (Salvador), Southeast (Bambui) and South (Pelotas) of the country. We found significant associations with African-associated alleles in children from Salvador (PALD1 and ZMIZ1 genes), and in young adults from Pelotas (NOD2 and MTUS2 genes). More importantly, in Pelotas, rs114066381, mapped in a potential regulatory region, is significantly associated only in females (p= 2.76 e-06). This variant is very rare in Europeans but with frequencies of ~3% in West Africa, and has a strong female-specific effect (95%CI: 2.32-5.65 kg/m2 per each A allele). We confirmed this sex-specific association and replicated its strong effect for an adjusted fat-mass index in the same Pelotas cohort, and for BMI in another Brazilian cohort from Sao Paulo (Southeast Brazil). A meta-analysis confirmed the significant association. Remarkably, we observed that while the frequency of rs114066381-A allele ranges from 0.8 to 2.1% in the studied populations, it attains ~9% among morbidly obese women from Pelotas, Sao Paulo, and Bambui. The effect size of rs114066381 is at least five-times the effect size of the FTO SNPs rs9939609 and rs1558902, already emblematic for their high effects, and for which we replicated associations in Pelotas. We demonstrate how, after a decade of GWAS mostly performed in European-ancestry populations, non-European and admixed populations are a source of new relevant phenotype-associated genetic variants.

genetics↗

bioRxiv2019

Origins, admixture dynamics and homogenization of the African gene pool in the Americas

The Transatlantic Slave Trade transported more than 9 million Africans to the Americas between the early 16th and the mid-19th centuries. We performed genome-wide analysis of 6,267 individuals from 22 populations and observed an enrichment in West-African ancestry in northern latitudes of the Americas, whereas South/East African ancestry is more prevalent in southern South-America. This pattern results from distinct geographic and geopolitical factors leading to population differentiation. However, we observed a decrease of 68% in the African gene pool between-population diversity within the Americas when compared to the regions of origin from Africa, underscoring the importance of historical factors favoring admixture between individuals with different African origins in the New World. This is consistent with the excess of West-Central Africa ancestry (the most prevalent in the Americas) in the US and Southeast-Brazil, respect to historical-demography expectations. Also, in most of the Americas, admixture intensification occurred between 1,750 and 1,850, which correlates strongly with the peak of arrivals from Africa. This study contributes with a population genetics perspective to the ongoing social, cultural and political debate regarding ancestry, race, and admixture in the Americas.\n\nSignificance StatementDifferently from most genetic studies, that have estimated the overall African ancestry in the Americas, we perform a finer geographic analysis and infer how different African groups contributed to North-, South-American and Caribbean populations, in the context of geographic and geopolitical factors. We also perform a formal comparison of information from demographic history records of the Transatlantic Slave Trade with inferences based on genomic diversity of current populations. Our approach reveals the distinct regional African ancestry roots of different populations from North-, South-America and the Caribe and other important aspects of the historical process of mestizaje and its dynamics in the American continent.

genetics↗