Omics A Journal of Integrative Biology最新文献

Role of N-Glycosylation in Gastrointestinal Cancers. N 型糖基化在胃肠道癌症中的作用

IF 2.2 3区生物学

Omics A Journal of Integrative Biology Pub Date : 2024-11-08 DOI: 10.1089/omi.2024.0174

Ruirui Xu, Lois Balmer, Gengzhen Chen, Manshu Song

{"title":"Role of N-Glycosylation in Gastrointestinal Cancers.","authors":"Ruirui Xu, Lois Balmer, Gengzhen Chen, Manshu Song","doi":"10.1089/omi.2024.0174","DOIUrl":"https://doi.org/10.1089/omi.2024.0174","url":null,"abstract":"Gastrointestinal cancers pose a significant global health challenge. N-glycosylation modulates various cellular processes, including key cancer-related mechanisms. Elucidating its involvement in the onset and advancement of these cancers can offer critical insights for enhancing diagnostic and therapeutic approaches. This review outlines the core process of protein N-glycosylation and highlights its contribution to the progression of gastrointestinal cancers, encompassing cell proliferation, survival, invasion, metastasis, and immune evasion, mainly through its impact on critical signaling pathways. Notably, aberrant N-glycosylation patterns have emerged as crucial biomarkers for the diagnosis and prognosis of various gastrointestinal cancers, providing the foundation for more personalized therapeutic approaches. Therapeutic strategies targeting N-glycosylation, such as glycosyltransferase inhibitors and glycoengineering, show significant promise in mitigating tumor aggressiveness and enhancing immune recognition. However, the clinical implementation of N-glycosylation biomarkers requires the standardization of glycosylation analysis techniques and solutions to challenges in sample processing and data interpretation. Future research efforts should concentrate on overcoming these obstacles to unlock the full potential of N-glycosylation in enhancing cancer management and advancing patient outcomes.","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142605851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unique and Shared Molecular Mechanisms of Alcoholic and Non-Alcoholic Liver Cirrhosis Identified Through Transcriptomics Data Integration. 通过转录组学数据整合发现酒精性和非酒精性肝硬化的独特和共同分子机制

IF 2.2 3区生物学

Omics A Journal of Integrative Biology Pub Date : 2024-11-01 Epub Date: 2024-10-17 DOI: 10.1089/omi.2024.0168

Ki-Hoon Park, Hwajin Lee, Ji Hyun Lee, Dong Keon Yon, Young-Il Choi, Hyung-Joo Chung, Junyang Jung, Na Young Jeong

{"title":"Unique and Shared Molecular Mechanisms of Alcoholic and Non-Alcoholic Liver Cirrhosis Identified Through Transcriptomics Data Integration.","authors":"Ki-Hoon Park, Hwajin Lee, Ji Hyun Lee, Dong Keon Yon, Young-Il Choi, Hyung-Joo Chung, Junyang Jung, Na Young Jeong","doi":"10.1089/omi.2024.0168","DOIUrl":"10.1089/omi.2024.0168","url":null,"abstract":"Liver cirrhosis is a severe chronic disease that results from various etiological factors and leads to substantial morbidity and mortality. Alcoholic cirrhosis (AC) and non-AC (NAC) arise from prolonged and excessive consumption of alcohol and metabolic syndromes, respectively. Precise molecular mechanisms of AC and NAC are yet to be comprehensively understood for diagnostics and therapeutic advances to materialize. This study reports novel findings to this end by utilizing high-throughput RNA sequencing and microarray data from the Gene Expression Omnibus (GEO). We performed a meta-analysis of transcriptomics data to identify the differentially expressed genes specific to AC and NAC. Functional enrichment and protein-protein interaction network analyses uncovered novel hub genes and transcription factors (TFs) critical to AC and NAC. We found that AC is primarily driven by metabolic dysregulation and oxidative stress, with key TFs such as RELA, NFKB1, and STAT3. NAC was characterized by fibrosis and tissue remodeling associated with metabolic dysfunction, with TFs including USF1, MYCN, and HIF1A. Key hub genes such as ESR1, JUN, FOS, and PKM in AC, and CD8A, MAPK3, CCND1, and CXCR4 in NAC were identified, along with their associated TFs, pointing to potential therapeutic targets. Our results underscore the unique and shared molecular mechanisms that underlie AC and NAC and inform the efforts toward precision medicine and improved patient outcomes in liver cirrhosis.","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142471535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Autism Spectrum Disorder and Atypical Brain Connectivity: Novel Insights from Brain Connectivity-Associated Genes by Combining Random Forest and Support Vector Machine Algorithm. 自闭症谱系障碍与非典型性脑连接：结合随机森林和支持向量机算法，从大脑连接性相关基因中获得新见解

IF 2.2 3区生物学

Omics A Journal of Integrative Biology Pub Date : 2024-11-01 Epub Date: 2024-10-17 DOI: 10.1089/omi.2024.0167

Pelin Gelmez, Talha Emir Karakoc, Ozlem Ulucan

{"title":"Autism Spectrum Disorder and Atypical Brain Connectivity: Novel Insights from Brain Connectivity-Associated Genes by Combining Random Forest and Support Vector Machine Algorithm.","authors":"Pelin Gelmez, Talha Emir Karakoc, Ozlem Ulucan","doi":"10.1089/omi.2024.0167","DOIUrl":"10.1089/omi.2024.0167","url":null,"abstract":"It is estimated that approximately one in every 100 children is diagnosed with autism spectrum disorder (ASD) around the globe. Currently, there are no curative pharmacological treatments for ASD. Discoveries on key molecular mechanisms of ASD are essential for precision medicine strategies. Considering that atypical brain connectivity patterns have been observed in individuals with ASD, this study examined the brain connectivity-associated genes and their putatively distinct expression patterns in brain samples from individuals diagnosed with ASD and using an iterative strategy based on random forest and support vector machine algorithms. We discovered a potential gene signature capable of differentiating ASD from control samples with a 92% accuracy. This gene signature comprised 14 brain connectivity-associated genes exhibiting enrichment in synapse-related terms. Of these genes, 11 were previously associated with ASD in varying degrees of evidence. Notably, NFKBIA, WNT10B, and IFT22 genes were identified as ASD-related for the first time in this study. Subsequent clustering analysis revealed the existence of two distinct ASD subtypes based on our gene signature. The expression levels of signature genes have the potential to influence brain connectivity patterns, potentially contributing to the manifestation of ASD. Further studies on the omics of ASD are called for so as to elucidate the molecular basis of ASD and for diagnostic and therapeutic innovations. Finally, we underscore that advances in ASD research can benefit from integrative bioinformatics and data science approaches.","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142471615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Alterations in Hurler-Scheie Syndrome Revealed by Mass Spectrometry-Based Proteomics and Phosphoproteomics Analysis. 基于质谱的蛋白质组学和磷蛋白组学分析揭示了赫勒-谢伊综合征的变化

IF 2.2 3区生物学

Omics A Journal of Integrative Biology Pub Date : 2024-11-01 Epub Date: 2024-10-29 DOI: 10.1089/omi.2024.0171

Madan Gopal Ramarajan, K T Shreya Parthasarathy, Kiran Bharat Gaikwad, Neha Joshi, Kishore Garapati, Richard K Kandasamy, Jyoti Sharma, Akhilesh Pandey

{"title":"Alterations in Hurler-Scheie Syndrome Revealed by Mass Spectrometry-Based Proteomics and Phosphoproteomics Analysis.","authors":"Madan Gopal Ramarajan, K T Shreya Parthasarathy, Kiran Bharat Gaikwad, Neha Joshi, Kishore Garapati, Richard K Kandasamy, Jyoti Sharma, Akhilesh Pandey","doi":"10.1089/omi.2024.0171","DOIUrl":"10.1089/omi.2024.0171","url":null,"abstract":"Hurler-Scheie syndrome (MPS IH/S), also known as mucopolysaccharidosis type I-H/S (MPS IH/S), is a lysosomal storage disorder caused by deficiency of the enzyme alpha-L-iduronidase (IDUA) leading to the accumulation of glycosaminoglycans (GAGs) in various tissues, resulting in a wide range of symptoms affecting different organ systems. Postgenomic omics technologies offer the promise to understand the changes in proteome, phosphoproteome, and phosphorylation-based signaling in MPS IH/S. Accordingly, we report here a large dataset and the proteomic and phosphoproteomic analyses of fibroblasts derived from patients with MPS IH/S (n = 8) and healthy individuals (n = 8). We found that protein levels of key lysosomal enzymes such as cathepsin D, prosaposin, arylsulfatases (arylsulfatase A and arylsulfatase B), and IDUA were downregulated. We identified 16,693 unique phosphopeptides, corresponding to 4,605 proteins, in patients with MPS IH/S. We found that proteins related to the cell cycle, mitotic spindle assembly, apoptosis, and cytoskeletal organization were differentially phosphorylated in MPS IH/S. We identified 12 kinases that were differentially phosphorylated, including hyperphosphorylation of cyclin-dependent kinases 1 and 2, hypophosphorylation of myosin light chain kinase, and calcium/calmodulin-dependent protein kinases. Taken together, the findings of the present study indicate significant alterations in proteins involved in cytoskeletal changes, cellular dysfunction, and apoptosis. These new observations significantly contribute to the current understanding of the pathophysiology of MPS IH/S specifically, and the molecular mechanisms involved in the storage of GAGs in MPS more generally. Further translational clinical omics studies are called for to pave the way for diagnostics and therapeutics innovation for patients with MPS IH/S.","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142522605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Phytochemicals Neogitogenin and Samogenin Hold Potentials for Hepatocyte Growth Factor Receptor-Targeted Cancer Treatment. 植物化学物质 Neogitogenin 和 Samogenin 具有以肝细胞生长因子受体为靶点治疗癌症的潜力。

IF 2.2 3区生物学

Omics A Journal of Integrative Biology Pub Date : 2024-11-01 Epub Date: 2024-10-10 DOI: 10.1089/omi.2024.0169

Abdelbaset Mohamed Elasbali, Farah Anjum, Bodour Ali Al-Ghabban, Alaa Shafie, Taj Mohammad, Md Imtaiyaz Hassan

{"title":"Phytochemicals Neogitogenin and Samogenin Hold Potentials for Hepatocyte Growth Factor Receptor-Targeted Cancer Treatment.","authors":"Abdelbaset Mohamed Elasbali, Farah Anjum, Bodour Ali Al-Ghabban, Alaa Shafie, Taj Mohammad, Md Imtaiyaz Hassan","doi":"10.1089/omi.2024.0169","DOIUrl":"10.1089/omi.2024.0169","url":null,"abstract":"Protein kinases are key targets for cancer therapies, with the c-Met receptor tyrosine kinase (MET) and its ligand, hepatocyte growth factor, playing a role in various cancers, including non-small cell lung cancer, gastric cancer, and hepatocellular carcinoma. Although small-molecule inhibitors have been designed to target MET, the development of drug resistance remains a significant challenge to advancing therapeutic strategies. In this study, we employed virtual screening of plant-based compounds sourced from the IMPPAT 2.0 databank to identify potent inhibitors of MET. Preliminary filtering based on the physicochemical parameters following Lipinski's rule of five and pan-assay interference compounds criteria were applied to prioritize hits. Subsequent molecular docking, pharmacokinetic evaluation, prediction of activity spectra for biologically active substances, and specificity assessments facilitated the identification of two promising phytochemicals, neogitogenin and samogenin. Both phytochemicals exhibited considerable drug-like properties with notable binding affinity and selectivity toward MET. Molecular dynamics simulation studies showed the conformational stability of MET with neogitogenin and samogenin. Taken together, these findings suggest that neogitogenin and samogenin hold potential as lead molecules for the development of MET-targeted therapeutics. We call for further evaluations of these phytochemicals in preclinical and experimental studies for anticancer drug discovery and development.","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142471534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Next-Generation Cancer Phenomics: A Transformative Approach to Unraveling Lung Cancer Complexity and Advancing Precision Medicine. 下一代癌症表型组学：揭示肺癌复杂性和推进精准医疗的变革性方法》（Next-Generation Cancer Phenomics: A Transformative Approach to Unraveling Lung Cancer Complexity and Advancing Precision Medicine）。

IF 2.2 3区生物学

Omics A Journal of Integrative Biology Pub Date : 2024-10-22 DOI: 10.1089/omi.2024.0175

Sanjukta Dasgupta

{"title":"Next-Generation Cancer Phenomics: A Transformative Approach to Unraveling Lung Cancer Complexity and Advancing Precision Medicine.","authors":"Sanjukta Dasgupta","doi":"10.1089/omi.2024.0175","DOIUrl":"https://doi.org/10.1089/omi.2024.0175","url":null,"abstract":"Lung cancer remains one of the leading causes of cancer-related deaths globally, with its complexity driven by intricate and intertwined genetic, epigenetic, and environmental factors. Despite advances in genomics, transcriptomics, and proteomics, understanding the phenotypic diversity of lung cancer has lagged behind. Next-generation phenomics, which integrates high-throughput phenotypic data with multiomics approaches and digital technologies such as artificial intelligence (AI), offers a transformative strategy for unraveling the complexity of lung cancer. This approach leverages advanced imaging, single-cell technologies, and AI to capture dynamic phenotypic variations at cellular, tissue, and whole organism levels and in ways resolved in temporal and spatial contexts. By mapping the high-throughput and spatially and temporally resolved phenotypic profiles onto molecular alterations, next-generation phenomics provides deeper insights into the tumor microenvironment, cancer heterogeneity, and drug efficacy, safety, and resistance mechanisms. Furthermore, integrating phenotypic data with genomic and proteomic networks allows for the identification of novel biomarkers and therapeutic targets in ways informed by biological structure and function, fostering precision medicine in lung cancer treatment. This expert review examines and places into context the current advances in next-generation phenomics and its potential to redefine lung cancer diagnosis, prognosis, and therapy. It highlights the emerging role of AI and machine learning in analyzing complex phenotypic datasets, enabling personalized therapeutic interventions. Ultimately, next-generation phenomics holds the promise of bridging the gap between molecular alterations and clinical and population health outcomes, providing a holistic understanding of lung cancer biology that could revolutionize its management and improve patient survival rates.","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142471533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How Do You Start a Revolution for Systems Medicine in a Health Innovation Ecosystem? Think Orthogonally and Change Assumptions. 如何在健康创新生态系统中掀起一场系统医学革命？正向思考，改变假设。

IF 2.2 3区生物学

Omics A Journal of Integrative Biology Pub Date : 2024-10-01 Epub Date: 2024-09-18 DOI: 10.1089/omi.2024.0173

Vural Özdemir

{"title":"How Do You Start a Revolution for Systems Medicine in a Health Innovation Ecosystem? Think Orthogonally and Change Assumptions.","authors":"Vural Özdemir","doi":"10.1089/omi.2024.0173","DOIUrl":"10.1089/omi.2024.0173","url":null,"abstract":"This paper defines a revolution as an orthogonal change in direction, a 90-degree perpendicular turn from the status quo ways of thinking, being and doing, so as to create a complete break, an abolitionist rupture with current and past ways of producing knowledge. David Bowie was a relatable example of a revolutionary and orthogonal innovator who completely and courageously broke with the past and the present and opened up new vistas in music and performing arts. The late anthropologist and public intellectual David Graeber also argued that a revolution fundamentally changes the assumptions in a given field of inquiry. Changing the entrenched assumptions that are long ossified, outdated or uncritically internalized by a knowledge community and profession can have multiplying revolutionary effects on downstream knowledge production. Thinking orthogonally to change the prevailing assumptions is indeed a revolutionary act. Orthogonal innovation as described in this paper is not a repackaging of an innovation in a different field. An orthogonal innovation is proposed as coalescence of ideas drawn from orthogonal domains, e.g., epistemologically speaking as in medicine and political theory, with an eye to pave the way for unprecedented social change and innovation. Grounding systems medicine in political determinants of planetary health, to link two fields of inquiry that have remained isolated and orthogonal since the 17th century, is nothing short of a revolution and orthogonal innovation in the making. For systems medicine to be a truly revolutionary field, it ought to acknowledge that there is no single-issue health nor single-issue politics.","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142292696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning-Aided Ultra-Low-Density Single Nucleotide Polymorphism Panel Helps to Identify the Tharparkar Cattle Breed: Lessons for Digital Transformation in Livestock Genomics. 机器学习辅助的超低密度单核苷酸多态性面板有助于识别塔帕卡尔牛品种：家畜基因组学数字化转型的启示。

IF 2.2 3区生物学

Omics A Journal of Integrative Biology Pub Date : 2024-10-01 Epub Date: 2024-09-20 DOI: 10.1089/omi.2024.0153

Harshit Kumar, Manjit Panigrahi, Dongwon Seo, Sunghyun Cho, Bharat Bhushan, Triveni Dutt

{"title":"Machine Learning-Aided Ultra-Low-Density Single Nucleotide Polymorphism Panel Helps to Identify the Tharparkar Cattle Breed: Lessons for Digital Transformation in Livestock Genomics.","authors":"Harshit Kumar, Manjit Panigrahi, Dongwon Seo, Sunghyun Cho, Bharat Bhushan, Triveni Dutt","doi":"10.1089/omi.2024.0153","DOIUrl":"10.1089/omi.2024.0153","url":null,"abstract":"Cattle breed identification is crucial for livestock research and sustainable food systems, and advances in genomics and artificial intelligence present new opportunities to address these challenges. This study investigates the identification of the Tharparkar cattle breed using genomics tools combined with machine learning (ML) techniques. By leveraging data from the Bovine SNP 50K chip, we developed a breed-specific panel of single nucleotide polymorphisms (SNPs) for Tharparkar cattle and integrated data from seven other Indian cattle populations to enhance panel robustness. Genome-wide association studies (GWAS) and principal component analysis were employed to identify 500 SNPs, which were then refined using ML models-AdaBoost, bagging tree, gradient boosting machines, and random forest-to determine the minimal number of SNPs needed for accurate breed identification. Panels of 23 and 48 SNPs achieved accuracy rates of 95.2-98.4%. Importantly, the identified SNPs were associated with key productive and adaptive traits, thus attesting to the value and potentials of digital transformation in livestock genomics. The ML-aided ultra-low-density SNP panel approach reported here not only facilitates breed identification but also contributes to preserving genetic diversity and guiding future breeding programs.","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142292697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DeepGenomeScan of 15 Worldwide Bovine Populations Detects Spatially Varying Positive Selection Signals. 对全球 15 个牛种群的 DeepGenomeScan 检测到空间上不同的正向选择信号。

IF 2.2 3区生物学

Omics A Journal of Integrative Biology Pub Date : 2024-10-01 Epub Date: 2024-09-24 DOI: 10.1089/omi.2024.0154

Harshit Kumar, Xinghu Qin, Bharat Bhushan, Triveni Dutt, Manjit Panigrahi

{"title":"DeepGenomeScan of 15 Worldwide Bovine Populations Detects Spatially Varying Positive Selection Signals.","authors":"Harshit Kumar, Xinghu Qin, Bharat Bhushan, Triveni Dutt, Manjit Panigrahi","doi":"10.1089/omi.2024.0154","DOIUrl":"10.1089/omi.2024.0154","url":null,"abstract":"Identifying genomic regions under selection is essential for understanding the genetic mechanisms driving species evolution and adaptation. Traditional methods often fall short in detecting complex, spatially varying selection signals. Recent advances in deep learning, however, present promising new approaches for uncovering subtle selection signals that traditional methods might miss. In this study, we utilized the deep learning framework DeepGenomeScan to detect spatially varying selection signatures across 15 bovine populations worldwide. Our analysis uncovered novel insights into selective sweep hotspots within the bovine genome, revealing key genes associated with physiological and adaptive traits that were previously undetected. We identified significant quantitative trait loci linked to milk protein and fat percentages. By comparing the selection signatures identified in this study with those reported in the Bovine Genome Variation Database, we discovered 38 novel genes under selection that were not identified through traditional methods. These genes are primarily associated with milk and meat yield and quality. Our findings enhance our understanding of spatially varying selection's impact on bovine genomic diversity, laying a foundation for future research in genetic improvement and conservation. This is the first deep learning-based study of selection signatures in cattle, offering new insights for evolutionary and livestock genomics research.","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142308253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unlocking the Door for Precision Medicine in Rare Conditions: Structural and Functional Consequences of Missense ACVR1 Variants. 打开罕见疾病精准医疗之门：错义 ACVR1 变异的结构和功能后果

IF 3.3 3区生物学

Omics A Journal of Integrative Biology Pub Date : 2024-09-17 DOI: 10.1089/omi.2024.0140

Garima Nagar,Shradheya R R Gupta,Vanshika Rustagi,Ravindran Kumar Pramod,Archana Singh,Monika Pahuja,Indrakant Kumar Singh

{"title":"Unlocking the Door for Precision Medicine in Rare Conditions: Structural and Functional Consequences of Missense ACVR1 Variants.","authors":"Garima Nagar,Shradheya R R Gupta,Vanshika Rustagi,Ravindran Kumar Pramod,Archana Singh,Monika Pahuja,Indrakant Kumar Singh","doi":"10.1089/omi.2024.0140","DOIUrl":"https://doi.org/10.1089/omi.2024.0140","url":null,"abstract":"Rare diseases and conditions have thus far received relatively less attention in the field of precision/personalized medicine than common chronic diseases. There is a dire need for orphan drug discovery and therapeutics in ways that are informed by the precision/personalized medicine scholarship. Moreover, people with rare conditions, when considered collectively across diseases worldwide, impact many communities. In this overarching context, Activin A Receptor Type 1 (ACVR1) is a transmembrane kinase from the transforming growth factor-β superfamily and plays a critical role in modulating the bone morphogenetic protein signaling. Missense variants of the ACVR1 gene result in modifications in structure and function and, by extension, abnormalities and have been predominantly linked with two rare conditions: fibrodysplasia ossificans progressiva and diffuse intrinsic pontine glioma. We report here an extensive bioinformatic analyses assessing the pool of 50,951 variants and forecast seven highly destabilizing mutations (R206H, G356D, R258S, G328W, G328E, R375P, and R202I) that can significantly alter the structure and function of the native protein. Protein-protein interaction and ConSurf analyses revealed the crucial interactions and localization of highly deleterious mutations in highly conserved domains that may impact the binding and functioning of the protein. cBioPortal, CanSAR Black, and existing literature affirmed the association of these destabilizing mutations with posterior fossa ependymoma, uterine corpus carcinoma, and pediatric brain cancer. The current findings suggest these deleterious nonsynonymous single nucleotide polymorphisms as potential candidates for future functional annotations and validations associated with rare conditions, further aiding the development of precision medicine in rare diseases.","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142253358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0