Jack Gemayel, Alain Chebly, Hampig Kourie, Colette Hanna, Kayane Mheidly, Melissa Mhanna, Farah Karam, Daniel Ghoussaini, Paula El Najjar, Charbel Khalil
{"title":"Genome Engineering as a Therapeutic Approach in Cancer Therapy: A Comprehensive Review","authors":"Jack Gemayel, Alain Chebly, Hampig Kourie, Colette Hanna, Kayane Mheidly, Melissa Mhanna, Farah Karam, Daniel Ghoussaini, Paula El Najjar, Charbel Khalil","doi":"10.1002/ggn2.202300201","DOIUrl":"10.1002/ggn2.202300201","url":null,"abstract":"<p>Cancer is one of the foremost causes of mortality. The human genome remains stable over time. However, human activities and environmental factors have the power to influence the prevalence of certain types of mutations. This goes to the excessive progress of xenobiotics and industrial development that is expanding the territory for cancers to develop. The mechanisms involved in immune responses against cancer are widely studied. Genome editing has changed the genome-based immunotherapy process in the human body and has opened a new era for cancer treatment. In this review, recent cancer immunotherapies and the use of genome engineering technology are largely focused on.</p>","PeriodicalId":72071,"journal":{"name":"Advanced genetics (Hoboken, N.J.)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ggn2.202300201","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139864999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Plant Functional Genomics Based on High-Throughput CRISPR Library Knockout Screening: A Perspective","authors":"Jianjie He, Can Zeng, Maoteng Li","doi":"10.1002/ggn2.202300203","DOIUrl":"https://doi.org/10.1002/ggn2.202300203","url":null,"abstract":"<p>Plant biology studies in the post-genome era have been focused on annotating genome sequences’ functions. The established plant mutant collections have greatly accelerated functional genomics research in the past few decades. However, most plant genome sequences' roles and the underlying regulatory networks remain substantially unknown. Clustered, regularly interspaced short palindromic repeat (CRISPR)-associated systems are robust, versatile tools for manipulating plant genomes with various targeted DNA perturbations, providing an excellent opportunity for high-throughput interrogation of DNA elements’ roles. This study compares methods frequently used for plant functional genomics and then discusses different DNA multi-targeted strategies to overcome gene redundancy using the CRISPR-Cas9 system. Next, this work summarizes recent reports using CRISPR libraries for high-throughput gene knockout and function discoveries in plants. Finally, this work envisions the future perspective of optimizing and leveraging CRISPR library screening in plant genomes' other uncharacterized DNA sequences.</p>","PeriodicalId":72071,"journal":{"name":"Advanced genetics (Hoboken, N.J.)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ggn2.202300203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140063864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Deep Learning-Assisted Design of Novel Promoters in Escherichia coli","authors":"Xinglong Wang, Kangjie Xu, Yameng Tan, Shangyang Yu, Xinyi Zhao, Jingwen Zhou","doi":"10.1002/ggn2.202300184","DOIUrl":"https://doi.org/10.1002/ggn2.202300184","url":null,"abstract":"<p>Deep learning (DL) approaches have the ability to accurately recognize promoter regions and predict their strength. Here, the potential for controllably designing active <i>Escherichia coli</i> promoter is explored by combining multiple deep learning models. First, “DRSAdesign,” which relies on a diffusion model to generate different types of novel promoters is created, followed by predicting whether they are real or fake and strength. Experimental validation showed that 45 out of 50 generated promoters are active with high diversity, but most promoters have relatively low activity. Next, “Ndesign,” which relies on generating random sequences carrying functional −35 and −10 motifs of the sigma70 promoter is introduced, and their strength is predicted using the designed DL model. The DL model is trained and validated using 200 and 50 generated promoters, and displays Pearson correlation coefficients of 0.49 and 0.43, respectively. Taking advantage of the DL models developed in this work, possible 6-mers are predicted as key functional motifs of the sigma70 promoter, suggesting that promoter recognition and strength prediction mainly rely on the accommodation of functional motifs. This work provides DL tools to design promoters and assess their functions, paving the way for DL-assisted metabolic engineering.</p>","PeriodicalId":72071,"journal":{"name":"Advanced genetics (Hoboken, N.J.)","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ggn2.202300184","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138578122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Insight into the Causal Relationship between Gut Microbiota and Back Pain: A Two Sample Bidirectional Mendelian Randomization Study","authors":"Jingni Hui, Yujing Chen, Chun'e Li, Yifan Gou, Ye Liu, Ruixue Zhou, Meijuan Kang, Chen Liu, Bingyi Wang, Panxing Shi, Shiqiang Cheng, Xuena Yang, Chuyu Pan, Yumeng Jia, Bolun Cheng, Huan Liu, Yan Wen, Feng Zhang","doi":"10.1002/ggn2.202300192","DOIUrl":"10.1002/ggn2.202300192","url":null,"abstract":"<p>Observational studies have shown that alterations in gut microbiota composition are associated with low back pain. However, it remains unclear whether the association is causal. To reveal the causal association between gut microbiota and low back pain, a two-sample bidirectional Mendelian randomization (MR) analysis is performed. The inverse variance weighted regression (IVW) is performed as the principal MR analysis. MR-Egger and Weighted Median is further conducted as complementary analysis to validate the robustness of the results. Finally, a reverse MR analysis is performed to evaluate the possibility of reverse causation. The inverse variance weighted (IVW) method suggests that <i>Peptostreptococcaceae</i> (odds ratio [OR] 1.056, 95% confidence interval [CI] [1.015–1.098], <i>P</i><sub>IVW</sub> = 0.010), and <i>Lactobacillaceae</i> (OR 1.070, 95% CI [1.026–1.115], <i>P</i><sub>IVW</sub> = 0.003) are positively associated with back pain. The <i>Ruminococcaceae</i> (OR 0.923, 95% CI [0.849–0.997], <i>P</i><sub>IVW</sub> = 0.033), <i>Butyricicoccus</i> (OR 0.920, 95% CI [0.868 - 0.972], <i>P</i><sub>IVW</sub> = 0.002), and <i>Lachnospiraceae</i> (OR 0.948, 95% CI [0.903–0.994], <i>P</i><sub>IVW</sub> = 0.022) are negatively associated with back pain. In this study, underlying causal relationships are identified among gut microbiota and low back pain. Notably, further research is needed on the biological mechanisms by which gut microbiota influences low back pain.</p>","PeriodicalId":72071,"journal":{"name":"Advanced genetics (Hoboken, N.J.)","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ggn2.202300192","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135391598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Host Genetic Impact on Infectious Diseases among Different Ethnic Groups","authors":"Lisa Naidoo, Thilona Arumugam, Veron Ramsuran","doi":"10.1002/ggn2.202300181","DOIUrl":"10.1002/ggn2.202300181","url":null,"abstract":"<p>Infectious diseases such as malaria, tuberculosis (TB), human immunodeficiency virus (HIV), and the coronavirus disease of 2019 (COVID-19) are problematic globally, with high prevalence particularly in Africa, attributing to most of the death rates. There have been immense efforts toward developing effective preventative and therapeutic strategies for these pathogens globally, however, some remain uncured. Disease susceptibility and progression for malaria, TB, HIV, and COVID-19 vary among individuals and are attributed to precautionary measures, environment, host, and pathogen genetics. While studying individuals with similar attributes, it is suggested that host genetics contributes to most of an individual's susceptibility to disease. Several host genes are identified to associate with these pathogens. Interestingly, many of these genes and polymorphisms are common across diseases. This paper analyzes genes and genetic variations within host genes associated with HIV, TB, malaria, and COVID-19 among different ethnic groups. The differences in host–pathogen interaction among these groups, particularly of Caucasian and African descent, and which gene polymorphisms are prevalent in an African population that possesses protection or risk to disease are reviewed. The information in this review could potentially help develop personalized treatment that could effectively combat the high disease burden in Africa.</p>","PeriodicalId":72071,"journal":{"name":"Advanced genetics (Hoboken, N.J.)","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ggn2.202300181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135725050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Editorial Board: (Advanced Genetics 3/04)","authors":"","doi":"10.1002/ggn2.202370032","DOIUrl":"https://doi.org/10.1002/ggn2.202370032","url":null,"abstract":"Nadav Ahituv, University of California, San Francisco, San Francisco, CA USA Nir Barzilai, Albert Einstein College of Medicine, Bronx, NY USA Jacqueline Batley, University of Western Australia, Perth, Australia Touati Benoukraf,Memorial University of Newfoundland, St. John’s, NL, Canada Ewan Birney, EMBL-EBI, Cambridge, UK Catherine A. Brownstein, Boston Children’s Hospital, Boston, MA USA Stephen J. Chanock, National Cancer Institute, Bethesda, MD USA George Church, Harvard Medical School, Boston, MA USA Francesco Cucca, University of Sassari, Sassari, Sardinia, Italy Marcella Devoto, Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Cagliari, Italy Roland Eils, Berlin Institue of Health, Berlin, Germany Jeanette Erdmann, Institute for Cardiogenetics, University of Lubeck, Lubeck, Germany Andrew Feinberg, Johns Hopkins University, Baltimore, MD USA Claudio Franceschi, University of Bologna, Bologna, Italy Paul W. Franks, Lund University, Malmö, Sweden Rachel Freathy, University of Exeter, Exeter, UK Jingyuan Fu, University Medical Center Groningen, Groningen, The Netherlands Eileen Furlong, European Molecular Biology Laboratory, Heidelberg, Germany Tom Gilbert, University of Copenhagen, The Globe Institute, Copenhagen, Denmark Joseph G. Gleeson, University of California, San Diego, Howard Hughes Medical Institute for Genomic Medicine, La Jolla, CA USA Erica Golemis, Fox Chase Cancer Center, Philadelphia, PA USA Sarah Hearne, International Maize and Wheat Improvement Centre (CIMMYT), Texcoco, Mexico Agnar Helgason, deCODE Genetics, Reykjavik, Iceland Kristina Hettne, Leiden University Libraries, Leiden, The Netherlands Sanwen Huang, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China Youssef Idaghdour, New York University, Abu Dhabi, Abu Dhabi, UAE Rosalind John, Cardiff University, Cardiff, UK Moien Kanaan, Bethlehem University, Bethlehem, Palestine Beat Keller, University of Zurich, Zurich, Switzerland Tuuli Lappalainen, New York Genome Center, Columbia University, New York, NY USA Luis F. Larrondo, Pontifica Universidad Catolica de Chile, Santiago, Chile Suet-Yi Leung, The University of Hong Kong, Hong Kong, China Ryan Lister, The University of Western Australia, Perth, Australia Jianjun Liu, Genome Institute Singapore, Singapore Naomichi Matsumoto, Yokohama City University, Yokohama, Japan Rachel S. Meyer, University of California, Los Angeles, Los Angeles, CA USA Nicola Mulder, University of Cape Town, Cape Town, South Africa Seishi Ogawa, Kyoto University, Kyoto, Japan Guilherme Oliveira, Vale Institute of Technology, Belem, Brazil Qiang Pan-Hammarstrom, Karolinska Institute, Stockholm, Sweden Len A. Pennacchio, Joint Genome Institute, Walnut Creek, CA USA Martin Pera, Jackson Lab, Bar Harbor, ME USA Danielle Posthuma, VU University Amsterdam, Amsterdam, The Netherlands Michael Purugganan, New York University, New York, NY USA Maanasa Raghavan, University of Chic","PeriodicalId":72071,"journal":{"name":"Advanced genetics (Hoboken, N.J.)","volume":"4 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ggn2.202370032","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50144419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A New Epigenetic Crosstalk: Chemical Modification Information Flow","authors":"Hongwoo Lee, Young-Joon Park, Pil Joon Seo","doi":"10.1002/ggn2.202200033","DOIUrl":"10.1002/ggn2.202200033","url":null,"abstract":"<p>Central dogma is the most fundamental hypothesis in the field of molecular biology and explains the genetic information flow from DNA to protein. Beyond residue-by-residue transmission of sequential information, chemical modifications of DNA, RNA, and protein are also relayed in the course of gene expression. Here, this work presents recent evidence supporting bidirectional interplay between chromatin modifications and RNA modifications. Furthermore, several RNA modifications likely affect chemical modifications of proteins. The relay of chemical modifications occurs co-transcriptionally or co-translationally, ensuring crosstalk among chemical modifications at the DNA, RNA, and protein levels. Overall, this work proposes a hypothetical framework that represents transmission of chemical modification information among chromatin, RNA, and proteins.</p>","PeriodicalId":72071,"journal":{"name":"Advanced genetics (Hoboken, N.J.)","volume":"4 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ggn2.202200033","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41177564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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