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Journal articles on the topic 'Genomics and transcriptomics'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Carpenter, Seren, and R. Steven Conlan. "Clinical Functional Genomics." Cancers 13, no. 18 (September 15, 2021): 4627. http://dx.doi.org/10.3390/cancers13184627.

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Functional genomics is the study of how the genome and its products, including RNA and proteins, function and interact to affect different biological processes. The field of functional genomics includes transcriptomics, proteomics, metabolomics and epigenomics, as these all relate to controlling the genome leading to expression of particular phenotypes. By studying whole genomes—clinical genomics, transcriptomes and epigenomes—functional genomics allows the exploration of the diverse relationship between genotype and phenotype, not only for humans as a species but also in individuals, allowing an understanding and evaluation of how the functional genome ‘contributes’ to different diseases. Functional variation in disease can help us better understand that disease, although it is currently limited in terms of ethnic diversity, and will ultimately give way to more personalized treatment plans.

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2

Kiechle, Frederick L., and Carol A. Holland-Staley. "Genomics, Transcriptomics, Proteomics, and Numbers." Archives of Pathology & Laboratory Medicine 127, no. 9 (September 1, 2003): 1089–97. http://dx.doi.org/10.5858/2003-127-1089-gtpan.

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Abstract Objective.—To review the advances in clinically useful molecular biologic techniques and to identify their applications in clinical practice, as presented at the 11th Annual William Beaumont Hospital DNA Symposium. Data Sources.—The 8 manuscripts submitted were reviewed, and their major findings were compared with literature on the same or related topics. Study Selection.—Manuscripts address the use of molecular techniques in microbiology to evaluate infectious disease and epidemiology; molecular microbiology methods, including rapid-cycle real-time polymerase chain reaction; peroxisome proliferator–activated receptor γ as a potential therapeutic target in inflammatory bowel disease or colon cancer; the effect of nonapoptotic doses of the bisbenizamide dye Hoechst 33342 on luciferase expression in plasmid-transfected BC3H-1 myocytes; the routine use of cystic fibrosis screening and its challenges; and the use of flow cytometry and/or chromosomal translocation in the diagnostic evaluation of hematopoietic malignancies. Data Synthesis.—Three current issues related to the use of molecular tests in clinical laboratories are (1) the restriction on introducing new tests secondary to existing patents or licenses; (2) the preanalytic variables for the different specimen types currently in use, including whole blood, plasma, serum, fresh or frozen tissues, and free-circulating DNA; and (3) the interpretation of studies evaluating the association of complex diseases with a single mutation or single-nucleotide polymorphism. Molecular methods have had a major impact on infectious disease through the rapid identification of organisms, the evaluation of outbreaks, and the characterization of drug resistance when compared with standard culture techniques. The activation of peroxisome proliferator–activated receptor γ stimulated by thiazolidinedione is useful in the treatment of type II diabetes mellitus and may have value in preventing inflammatory bowel disease or colon cancer. Hoechst 33342 binding to adenine-thymine–rich regions in the minor groove of DNA is a fluorescent stain for DNA and initiates apoptosis at >10 μg/mL. Lower doses of Hoechst 33342 promote luciferase expression by a mechanism that may involve binding to cryptic promoters facilitated by dye-associated misalignment of the tertiary structure of DNA. The routine use of cystic fibrosis screening is complicated by the more than 1000 mutations associated with the disease. The use of 4-color flow cytometry and the detection of chromosomal translocation are both invaluable aids in establishing the diagnosis of lymphoid or myeloid hematopoietic malignancies. Conclusions.—The current postgenomic era will continue to emphasize the use of microarrays and database software for genomic, transcriptomic, and proteomic screening in the search for useful clinical assays. The number of molecular pathologic techniques will expand as additional disease-associated mutations are defined.

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3

Cooper, Edwin L. "JECM: TMU Proteomics Genomics Transcriptomics." Journal of Experimental & Clinical Medicine 2, no. 2 (April 2010): 43–46. http://dx.doi.org/10.1016/s1878-3317(10)60007-1.

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4

Kawai, J., P. Carninci, and Y. Hayashizaki. "Transcriptomics resources for functional genomics." Briefings in Functional Genomics and Proteomics 6, no. 3 (August 20, 2007): 171–79. http://dx.doi.org/10.1093/bfgp/elm024.

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5

Schaechter, M., J. L. Ingraham, and J. Soler. "What limits genomics, proteomics, transcriptomics?" International Microbiology 5, no. 2 (May 29, 2002): 51–52. http://dx.doi.org/10.1007/s10123-002-0065-0.

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Tzika, Athanasia C., Asier Ullate-Agote, Djordje Grbic, and Michel C. Milinkovitch. "Reptilian Transcriptomes v2.0: An Extensive Resource for Sauropsida Genomics and Transcriptomics." Genome Biology and Evolution 7, no. 6 (June 2015): 1827–41. http://dx.doi.org/10.1093/gbe/evv106.

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7

Wang, W., and J. Messing. "Status of duckweed genomics and transcriptomics." Plant Biology 17 (July 4, 2014): 10–15. http://dx.doi.org/10.1111/plb.12201.

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8

Dopazo, Joaquin. "Genomics and transcriptomics in drug discovery." Drug Discovery Today 19, no. 2 (February 2014): 126–32. http://dx.doi.org/10.1016/j.drudis.2013.06.003.

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9

Liu, Tiancheng, Lin Yu, Lei Liu, Hong Li, and Yixue Li. "Comparative Transcriptomes and EVO-DEVO Studies Depending on Next Generation Sequencing." Computational and Mathematical Methods in Medicine 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/896176.

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High throughput technology has prompted the progressive omics studies, including genomics and transcriptomics. We have reviewed the improvement of comparative omic studies, which are attributed to the high throughput measurement of next generation sequencing technology. Comparative genomics have been successfully applied to evolution analysis while comparative transcriptomics are adopted in comparison of expression profile from two subjects by differential expression or differential coexpression, which enables their application in evolutionary developmental biology (EVO-DEVO) studies. EVO-DEVO studies focus on the evolutionary pressure affecting the morphogenesis of development and previous works have been conducted to illustrate the most conserved stages during embryonic development. Old measurements of these studies are based on the morphological similarity from macro view and new technology enables the micro detection of similarity in molecular mechanism. Evolutionary model of embryo development, which includes the “funnel-like” model and the “hourglass” model, has been evaluated by combination of these new comparative transcriptomic methods with prior comparative genomic information. Although the technology has promoted the EVO-DEVO studies into a new era, technological and material limitation still exist and further investigations require more subtle study design and procedure.

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Mubarak, Ghada, and Farah R. Zahir. "Recent Major Transcriptomics and Epitranscriptomics Contributions toward Personalized and Precision Medicine." Journal of Personalized Medicine 12, no. 2 (February 1, 2022): 199. http://dx.doi.org/10.3390/jpm12020199.

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With the advent of genome-wide screening methods—beginning with microarray technologies and moving onto next generation sequencing methods—the era of precision and personalized medicine was born. Genomics led the way, and its contributions are well recognized. However, “other-omics” fields have rapidly emerged and are becoming as important toward defining disease causes and exploring therapeutic benefits. In this review, we focus on the impacts of transcriptomics, and its extension—epitranscriptomics—on personalized and precision medicine efforts. There has been an explosion of transcriptomic studies particularly in the last decade, along with a growing number of recent epitranscriptomic studies in several disease areas. Here, we summarize and overview major efforts for cancer, cardiovascular disease, and neurodevelopmental disorders (including autism spectrum disorder and intellectual disability) for transcriptomics/epitranscriptomics in precision and personalized medicine. We show that leading advances are being made in both diagnostics, and in investigative and landscaping disease pathophysiological studies. As transcriptomics/epitranscriptomics screens become more widespread, it is certain that they will yield vital and transformative precision and personalized medicine contributions in ways that will significantly further genomics gains.

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Pujol-Gualdo, Natàlia, Cristina Sánchez-Mora, Josep Antoni Ramos-Quiroga, Marta Ribasés, and María Soler Artigas. "Integrating genomics and transcriptomics: Towards deciphering ADHD." European Neuropsychopharmacology 44 (March 2021): 1–13. http://dx.doi.org/10.1016/j.euroneuro.2021.01.002.

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12

Brzuszkiewicz, Elzbieta, January Weiner, Antje Wollherr, Andrea Thürmer, Jennifer Hüpeden, Hans B. Lomholt, Mogens Kilian, et al. "Comparative Genomics and Transcriptomics of Propionibacterium acnes." PLoS ONE 6, no. 6 (June 27, 2011): e21581. http://dx.doi.org/10.1371/journal.pone.0021581.

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13

Horgan, Richard P., and Louise C. Kenny. "‘Omic’ technologies: genomics, transcriptomics, proteomics and metabolomics." Obstetrician & Gynaecologist 13, no. 3 (July 2011): 189–95. http://dx.doi.org/10.1576/toag.13.3.189.27672.

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14

Wilson, Ian D., Gary L. A. Barker, Richard W. Beswick, Sophie K. Shepherd, Chungui Lu, Jane A. Coghill, David Edwards, et al. "A transcriptomics resource for wheat functional genomics." Plant Biotechnology Journal 2, no. 6 (September 21, 2004): 495–506. http://dx.doi.org/10.1111/j.1467-7652.2004.00096.x.

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15

Kalinowski, J., C. Rückert, R. Szczepanowski, and A. Pühler. "Advanced Genomics and Transcriptomics of Industrial Microorganisms." Chemie Ingenieur Technik 82, no. 9 (August 27, 2010): 1518–19. http://dx.doi.org/10.1002/cite.201050335.

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16

Andrade-Navarro, Miguel A. "The Dictionary of Genomics, Transcriptomics, and Proteomics." BioEssays 31, no. 12 (December 2009): 1367–69. http://dx.doi.org/10.1002/bies.200900121.

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Puccio, Ava M., and Sheila Alexander. "Genomics, Transcriptomics, and Epigenomics in Traumatic Brain Injury Research." Annual Review of Nursing Research 33, no. 1 (May 2015): 75–109. http://dx.doi.org/10.1891/0739-6686.33.75.

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The long-term effects and significant impact of the full spectrum of traumatic brain injury (TBI) has received increased attention in recent years. Despite increased research efforts, there has been little movement toward improving outcomes for the survivors of TBI. TBI is a heterogeneous condition with a complex biological response, and significant variability in human recovery contributes to the difficulty in identifying therapeutics that improve outcomes. Personalized medicine, identifying the best course of treatment for a given individual based on individual characteristics, has great potential to improve recovery for TBI survivors. The advances in medical genetics and genomics over the past 20 years have increased our understanding of many biological processes. A substantial amount of research has focused on the genomic, transcriptomic, and epigenomic profiles in many health and disease states, including recovery from TBI. The focus of this review chapter is to describe the current state of the science in genomic, transcriptomic, and epigenomic research in the TBI population. There have been some advancements toward understanding the genomic, transcriptomic, and epigenomic processes in humans, but much of this work remains at the preclinical stage. This current evidence does improve our understanding of TBI recovery, but also serves as an excellent platform upon which to build further study toward improved outcomes for this population.

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Nahum, Laila A., Marina M. Mourão, and Guilherme Oliveira. "New Frontiers inSchistosomaGenomics and Transcriptomics." Journal of Parasitology Research 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/849132.

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Schistosomes are digenean blood flukes of aves and mammals comprising 23 species. Some species are causative agents of human schistosomiasis, the second major neglected disease affecting over 230 million people worldwide. Modern technologies including the sequencing and characterization of nucleic acids and proteins have allowed large-scale analyses of parasites and hosts, opening new frontiers in biological research with potential biomedical and biotechnological applications. Nuclear genomes of the three most socioeconomically important species (S. haematobium,S. japonicum, andS. mansoni) have been sequenced and are under intense investigation. Mitochondrial genomes of sixSchistosomaspecies have also been completely sequenced and analysed from an evolutionary perspective. Furthermore, DNA barcoding of mitochondrial sequences is used for biodiversity assessment of schistosomes. Despite the efforts in the characterization ofSchistosomagenomes and transcriptomes, many questions regarding the biology and evolution of this important taxon remain unanswered. This paper aims to discuss some advances in the schistosome research with emphasis on genomics and transcriptomics. It also aims to discuss the main challenges of the current research and to point out some future directions in schistosome studies.

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19

Pandey, Kamal, Eunbyeol Lee, Nahee Park, Jin Hur, Young Bin Cho, Nar Bahadur Katuwal, Seung Ki Kim, et al. "Deregulated Immune Pathway Associated with Palbociclib Resistance in Preclinical Breast Cancer Models: Integrative Genomics and Transcriptomics." Genes 12, no. 2 (January 25, 2021): 159. http://dx.doi.org/10.3390/genes12020159.

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Recently, cyclin-dependent kinase (CDK) 4/6 inhibitors have been widely used to treat advanced hormone receptor-positive breast cancer. Despite promising clinical outcomes, almost all patients eventually acquire resistance to CDK4/6 inhibitors. Here, we screened genes associated with palbociclib resistance through genomics and transcriptomics in preclinical breast cancer models. Palbociclib-resistant cells were generated by exposing hormone receptor-positive breast cancer cell lines to palbociclib. Whole-exome sequencing (WES) and a mRNA microarray were performed to compare the genomic and transcriptomic landscape between both palbociclib-sensitive and resistant cells. Microarray analysis revealed 651 differentially expressed genes (DEGs), while WES revealed 107 clinically significant mutated genes. Furthermore, pathway analysis of both DEGs and mutated genes revealed immune pathway deregulation in palbociclib-resistant cells. Notably, DEG annotation revealed activation of type I interferon pathway, activation of immune checkpoint inhibitory pathway, and suppression of immune checkpoint stimulatory pathway in palbociclib-resistant cells. Moreover, mutations in NCOR1, MUC4, and MUC16 genes found in palbociclib-resistant cells were annotated to be related to the immune pathway. In conclusion, our genomics and transcriptomics analysis using preclinical model, revealed that deregulated immune pathway is an additional mechanism of CDK4/6 inhibitor resistance besides the activation of cyclin E-CDK2 pathway and loss of RB, etc. Further studies are warranted to evaluate whether immune pathways may be a therapeutic target to overcome CDK4/6 inhibitor resistance.

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20

Cho, Kang Hee, Jung Hyun Kwon, Se Hee Kim, and Ji Hae Jun. "Current status of peach genomics and transcriptomics research." Journal of Plant Biotechnology 42, no. 4 (December 31, 2015): 312–25. http://dx.doi.org/10.5010/jpb.2015.42.4.312.

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21

Pierlé, Sebastián, Michael J. Dark, Dani Dahmen, Guy H. Palmer, and Kelly A. Brayton. "Comparative genomics and transcriptomics of trait-gene association." BMC Genomics 13, no. 1 (2012): 669. http://dx.doi.org/10.1186/1471-2164-13-669.

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22

Patel, Vishal R., Kristin Eckel-Mahan, Paolo Sassone-Corsi, and Pierre Baldi. "CircadiOmics: integrating circadian genomics, transcriptomics, proteomics and metabolomics." Nature Methods 9, no. 8 (July 30, 2012): 772–73. http://dx.doi.org/10.1038/nmeth.2111.

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23

Technau, Ulrich, and Michaela Schwaiger. "Recent advances in genomics and transcriptomics of cnidarians." Marine Genomics 24 (December 2015): 131–38. http://dx.doi.org/10.1016/j.margen.2015.09.007.

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24

Madhavan, Guruprasad. "The Dictionary of Gene Technology: Genomics, Transcriptomics, Proteomics." Annals of Biomedical Engineering 33, no. 7 (July 2005): 984. http://dx.doi.org/10.1007/s10439-005-5024-4.

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25

Clarke, Paul A., and Paul Workman. "Innovative cancer drug targets: genomics, transcriptomics and clinomics." Expert Opinion on Pharmacotherapy 2, no. 6 (June 2001): 911–15. http://dx.doi.org/10.1517/14656566.2.6.911.

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26

Swanepoel, Conrad C., and Du Toit Loots. "The Use of Functional Genomics in Conjunction with Metabolomics forMycobacterium tuberculosisResearch." Disease Markers 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/124218.

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Tuberculosis (TB), caused byMycobacterium tuberculosis, is a fatal infectious disease, resulting in 1.4 million deaths globally per annum. Over the past three decades, genomic studies have been conducted in an attempt to elucidate the functionality of the genome of the pathogen. However, many aspects of this complex genome remain largely unexplored, as approaches like genomics, proteomics, and transcriptomics have failed to characterize them successfully. In turn, metabolomics, which is relatively new to the “omics” revolution, has shown great potential for investigating biological systems or their modifications. Furthermore, when these data are interpreted in combination with previously acquired genomics, proteomics and transcriptomics data, using what is termed a systems biology approach, a more holistic understanding of these systems can be achieved. In this review we discuss how metabolomics has contributed so far to characterizing TB, with emphasis on the resulting improved elucidation ofM. tuberculosisin terms of (1) metabolism, (2) growth and replication, (3) pathogenicity, and (4) drug resistance, from the perspective of systems biology.

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27

Michel, Sebastian, Christian Wagner, Tetyana Nosenko, Barbara Steiner, Mina Samad-Zamini, Maria Buerstmayr, Klaus Mayer, and Hermann Buerstmayr. "Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat." Genes 12, no. 1 (January 19, 2021): 114. http://dx.doi.org/10.3390/genes12010114.

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Genomic selection with genome-wide distributed molecular markers has evolved into a well-implemented tool in many breeding programs during the last decade. The resistance against Fusarium head blight (FHB) in wheat is probably one of the most thoroughly studied systems within this framework. Aside from the genome, other biological strata like the transcriptome have likewise shown some potential in predictive breeding strategies but have not yet been investigated for the FHB-wheat pathosystem. The aims of this study were thus to compare the potential of genomic with transcriptomic prediction, and to assess the merit of blending incomplete transcriptomic with complete genomic data by the single-step method. A substantial advantage of gene expression data over molecular markers has been observed for the prediction of FHB resistance in the studied diversity panel of breeding lines and released cultivars. An increase in prediction ability was likewise found for the single-step predictions, although this can mostly be attributed to an increased accuracy among the RNA-sequenced genotypes. The usage of transcriptomics can thus be seen as a complement to already established predictive breeding pipelines with pedigree and genomic data, particularly when more cost-efficient multiplexing techniques for RNA-sequencing will become more accessible in the future.

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Eriksen, Martina, Annelaura Bach Nielsen, Filip Mundt, Josephine Kerzel Duel, Matthias Mann, Ulrik Lassen, Christina Westmose Yde, et al. "Abstract 3254: Multiomics detect potential mechanisms of resistance to BRAF targeted therapy in patients with BRAFV600E mutated solid tumors." Cancer Research 82, no. 12_Supplement (June 15, 2022): 3254. http://dx.doi.org/10.1158/1538-7445.am2022-3254.

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Abstract Purpose: The purpose of this study was to identify mechanisms of resistance to BRAF targeted therapy using proteomics together with genomics and transcriptomics in patients with BRAFV600E mutated solid tumors. Experimental procedures: A total of nine patients with BRAFV600E mutated advanced solid tumors (5 with colorectal cancer, 2 with neuroendocrine carcinoma, 1 with cholangiocarcinoma and 1 with breast cancer) treated with BRAF targeted therapy (BRAF inhibitor in combination with either MEK inhibitor and/or EGRF antibody) as part of the Copenhagen Prospective Personalized Oncology study, were included in this study. Tumor biopsies at baseline and at disease progression were analyzed with whole exome/genome sequencing (WES/WGS), transcriptomics (RNA sequencing) and proteomics. Genomic variants were analyzed together with changes in protein expression. Three filtering steps were used to identify potential resistance mechanisms from the proteomics measurements. Proteins were filtered for 1) proteins with a high shift in abundance between baseline and progression 2) proteins with known associations to the patient’s primary cancer based on text-mining and 3) proteins in pathways where BRAF is also involved. Results: Alterations conferring resistance were identified in 2 out of 9 patients when comparing data from WES/WGS and RNA sequencing at baseline and at disease progression (one patient with PTBP2-BRAF fusion and one with NRAS mutation). Genomic or transcriptomic alterations conferring resistance were not detected in the remaining 7 patients. Notably, there was not a single protein shared between all 9 patients after our filtering, but when comparing overlap on pathway level, six pathways related to RAF and MAPK signaling were affected in all 9 patients. Particularly, paradoxical activation of RAF signaling seems to be an interesting candidate to explain resistance, where formation of RAF dimer structures happens as a response to treatment with BRAF inhibitors, selectively inhibiting BRAF monomer structures (i.e. BRAFV600E). Conclusion: With a multiomic approach using proteomics together with genomics and transcriptomics, potential mechanisms of resistance were detected in all patients at disease progression, where resistance to BRAF targeted therapies had occurred. Six mechanisms of resistance were shared independently of diagnosis and BRAF inhibitor combination regimes. The potential of integrating proteomics with genomics and transcriptomics is promising and may potentially guide therapy for future patients with treatment resistant BRAFV600E mutated solid tumors. Citation Format: Martina Eriksen, Annelaura Bach Nielsen, Filip Mundt, Josephine Kerzel Duel, Matthias Mann, Ulrik Lassen, Christina Westmose Yde, Camilla Qvortrup, Martin Højgaard, Iben Spanggaard, Kristoffer Staal Rohrberg. Multiomics detect potential mechanisms of resistance to BRAF targeted therapy in patients with BRAFV600E mutated solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3254.

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29

Uddin, Mohammed, Farah Mustafa, Tahir A. Rizvi, Tom Loney, Hanan Al Suwaidi, Ahmed H. Hassan Al-Marzouqi, Afaf Kamal Eldin, et al. "SARS-CoV-2/COVID-19: Viral Genomics, Epidemiology, Vaccines, and Therapeutic Interventions." Viruses 12, no. 5 (May 10, 2020): 526. http://dx.doi.org/10.3390/v12050526.

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The COVID-19 pandemic is due to infection caused by the novel SARS-CoV-2 virus that impacts the lower respiratory tract. The spectrum of symptoms ranges from asymptomatic infections to mild respiratory symptoms to the lethal form of COVID-19 which is associated with severe pneumonia, acute respiratory distress, and fatality. To address this global crisis, up-to-date information on viral genomics and transcriptomics is crucial for understanding the origins and global dispersion of the virus, providing insights into viral pathogenicity, transmission, and epidemiology, and enabling strategies for therapeutic interventions, drug discovery, and vaccine development. Therefore, this review provides a comprehensive overview of COVID-19 epidemiology, genomic etiology, findings from recent transcriptomic map analysis, viral-human protein interactions, molecular diagnostics, and the current status of vaccine and novel therapeutic intervention development. Moreover, we provide an extensive list of resources that will help the scientific community access numerous types of databases related to SARS-CoV-2 OMICs and approaches to therapeutics related to COVID-19 treatment.

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Ahmad, Niaz, and Brent L. Nielsen. "Plastid Transcriptomics: An Important Tool For Plastid Functional Genomics." Protein & Peptide Letters 28, no. 8 (September 10, 2021): 855–60. http://dx.doi.org/10.2174/0929866528999210128210555.

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Plastids in higher plants carry out specialized roles such as photosynthesis, nitrogen assimilation, biosynthesis of amino acids, fatty acids, isoprenoids, and various metabolites. Plastids arise from undifferentiated precursors known as proplastids, which are found in the root and shoot meristems. They are highly dynamic as they change their number, morphology, and physiology according to the tissue they are present. In addition to housing various metabolic activities, plastids also serve as a global sensor for both internal and external environmental cues including different stresses, and help plants to respond/adjust accordingly. They relay information to the nucleus, which then responds by changing the expression levels of specific genes. It has been shown that plants with impaired plastid functions exhibit abnormalities. One of the sources emanating these signals to the nucleus is plastid transcription. Normal plastid functioning is therefore critical for plant survival. Despite immense significance for plant acclimation, the plastid transcriptome is largely an unstudied research area. In this review, we discuss the importance of plastid transcriptomics for the acclimation of plants under changing environmental conditions and summarize the key literature published in this field.

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Khodadadian, Ali, Somaye Darzi, Saeed Haghi-Daredeh, Farzaneh sadat Eshaghi, Emad Babakhanzadeh, Seyed Hamidreza Mirabutalebi, and Majid Nazari. "Genomics and Transcriptomics: The Powerful Technologies in Precision Medicine." International Journal of General Medicine Volume 13 (September 2020): 627–40. http://dx.doi.org/10.2147/ijgm.s249970.

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Ye, Yongqin, Vincent Chi Hang Lui, and Paul Kwong Hang Tam. "Pathogenesis of Choledochal Cyst: Insights from Genomics and Transcriptomics." Genes 13, no. 6 (June 8, 2022): 1030. http://dx.doi.org/10.3390/genes13061030.

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Choledochal cysts (CC) is characterized by extra- and/or intra-hepatic b\ile duct dilations. There are two main theories, “pancreaticobiliary maljunction” and “congenital stenosis of bile ducts” proposed for the pathogenesis of CC. Although family cases or CC associated with other anomalies have been reported, the molecular pathogenesis of CC is still poorly understood. Recent advances in transcriptomics and genomics analysis platforms have unveiled key expression signatures/genes/signaling pathways in the pathogenesis of human diseases including CC. This review summarizes insights from genomics and transcriptomics studies into the pathogenesis of CC, with the aim to improve (i) our understanding of its underlying complex pathomechanisms, and (ii) clinical management of different subtypes of CC, in particular their associated hepatic fibrotic change and their risk of malignancy transformation.

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33

Dircksen, Heinrich, Susanne Neupert, Reinhard Predel, Peter Verleyen, Jurgen Huybrechts, Johannes Strauss, Frank Hauser, et al. "Genomics, Transcriptomics, and Peptidomics ofDaphnia pulexNeuropeptides and Protein Hormones." Journal of Proteome Research 10, no. 10 (October 7, 2011): 4478–504. http://dx.doi.org/10.1021/pr200284e.

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34

Zhuang, Xiaowei. "Spatially resolved single-cell genomics and transcriptomics by imaging." Nature Methods 18, no. 1 (January 2021): 18–22. http://dx.doi.org/10.1038/s41592-020-01037-8.

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35

Larsson, Ludvig, Jonas Frisén, and Joakim Lundeberg. "Spatially resolved transcriptomics adds a new dimension to genomics." Nature Methods 18, no. 1 (January 2021): 15–18. http://dx.doi.org/10.1038/s41592-020-01038-7.

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BLAXTER, M., S. KUMAR, G. KAUR, G. KOUTSOVOULOS, and B. ELSWORTH. "Genomics and transcriptomics across the diversity of the Nematoda." Parasite Immunology 34, no. 2-3 (February 2012): 108–20. http://dx.doi.org/10.1111/j.1365-3024.2011.01342.x.

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37

Sepulveda, Jorge L. "Using R and Bioconductor in Clinical Genomics and Transcriptomics." Journal of Molecular Diagnostics 22, no. 1 (January 2020): 3–20. http://dx.doi.org/10.1016/j.jmoldx.2019.08.006.

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Waterer, Grant. "Community-Acquired Pneumonia: Genomics, Epigenomics, Transcriptomics, Proteomics, and Metabolomics." Seminars in Respiratory and Critical Care Medicine 33, no. 03 (June 2012): 257–65. http://dx.doi.org/10.1055/s-0032-1315637.

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Bianchi, Diana W. "Turner syndrome: New insights from prenatal genomics and transcriptomics." American Journal of Medical Genetics Part C: Seminars in Medical Genetics 181, no. 1 (January 31, 2019): 29–33. http://dx.doi.org/10.1002/ajmg.c.31675.

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40

Spreafico, Roberto, Leah B. Soriaga, Johannes Grosse, Herbert W. Virgin, and Amalio Telenti. "Advances in Genomics for Drug Development." Genes 11, no. 8 (August 15, 2020): 942. http://dx.doi.org/10.3390/genes11080942.

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Drug development (target identification, advancing drug leads to candidates for preclinical and clinical studies) can be facilitated by genetic and genomic knowledge. Here, we review the contribution of population genomics to target identification, the value of bulk and single cell gene expression analysis for understanding the biological relevance of a drug target, and genome-wide CRISPR editing for the prioritization of drug targets. In genomics, we discuss the different scope of genome-wide association studies using genotyping arrays, versus exome and whole genome sequencing. In transcriptomics, we discuss the information from drug perturbation and the selection of biomarkers. For CRISPR screens, we discuss target discovery, mechanism of action and the concept of gene to drug mapping. Harnessing genetic support increases the probability of drug developability and approval.

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(Lonneke), A., and H. M. van der Geest. "Seed genomics: germinating opportunities." Seed Science Research 12, no. 3 (September 2002): 145–53. http://dx.doi.org/10.1079/ssr2002106.

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With the sequencing of theArabidopsis thalianagenome, the field of plant biology has made a quantum leap. The sequence information available to the community has greatly facilitated the identification of genes responsible for mutant phenotypes and the large-scale analysis of gene expression inArabidopsis. High-throughput laboratory tools for DNA sequencing (genomics), mutant analysis (functional genomics), mRNA quantification (transcriptomics) and protein analysis (proteomics) are being used to scrutinize this model plant. For seed physiologists, the challenge lies in translating this information into physiological processes in seeds from other plant species. Combining more traditional seed biology with the new high-throughput molecular tools should yield breakthroughs in seed science.

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Shembekar, Nachiket, Chawaree Chaipan, Ramesh Utharala, and Christoph A. Merten. "Droplet-based microfluidics in drug discovery, transcriptomics and high-throughput molecular genetics." Lab on a Chip 16, no. 8 (2016): 1314–31. http://dx.doi.org/10.1039/c6lc00249h.

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Balilashaki, Khosro, Hedayat Zakizadeh, Jamal Ali Olfati, Maryam Vahedi, Anuj Kumar, and Meera Indracanti. "Recent Advances in Phalaenopsis Orchid Improvement using Omics Approaches." Plant Tissue Culture and Biotechnology 29, no. 1 (June 26, 2019): 133–49. http://dx.doi.org/10.3329/ptcb.v29i1.41986.

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With recent advances in high-throughput sequencing (HTS) technologies to improve plants, there is a need to release orchid specific genomic resources and platforms that are crucial for managing omics elements in systematic manner. Authors provide details about the recent developments in biotechnological techniques, genomics, transcriptomics, proteomics, metabolomics and their applications for the industrial production, propagation, conservation and manipulation of Phalaenopsis orchid. Plant Tissue Cult. & Biotech. 29(1): 133-149, 2019 (June)

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Thomas, Luke, and Stephen R. Palumbi. "The genomics of recovery from coral bleaching." Proceedings of the Royal Society B: Biological Sciences 284, no. 1865 (October 25, 2017): 20171790. http://dx.doi.org/10.1098/rspb.2017.1790.

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Ecological damage from periodic environmental extremes is often repaired in resilient ecosystems, but the rate of return to a non-damaged state is critical. Measures of recovery of communities include biomass, productivity and diversity, while measures of recovery of individuals tend to focus on physiological conditions and the return to normal metabolic functioning. Transcriptomics offers a window into the entire physiology of the organism under stress and can represent a holistic view of organismal recovery. In this study, we track the recovery of seven colonies of Acropora hyacinthus following a natural bleaching event. We identified a large environmental stress response in the field that involved approximately 20% of the host transcriptome. The transcriptome remained largely perturbed for at least six months after temperatures had cooled and four months after symbiont populations had recovered. Moreover, a small set of genes did not recover to previous expression levels even 12 months after the event, about the time that normal growth rates resumed. This study is among the first to incorporate transcriptomics into a longitudinal dataset of recovery from environmental stress. The data demonstrate large and lasting effects on coral physiology long after environmental conditions return to normal and symbiont populations recover.

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Kataoka, Kosuke, Yuki Togawa, Ryuto Sanno, Toru Asahi, and Kei Yura. "Dissecting cricket genomes for the advancement of entomology and entomophagy." Biophysical Reviews 14, no. 1 (January 21, 2022): 75–97. http://dx.doi.org/10.1007/s12551-021-00924-4.

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AbstractSignificant advances in biophysical methods such as next-generation sequencing technologies have now opened the way to conduct evolutionary and applied research based on the genomic information of greatly diverse insects. Crickets belonging to Orthoptera (Insecta: Polyneoptera), one of the most flourishing groups of insects, have contributed to the development of multiple scientific fields including developmental biology and neuroscience and have been attractive targets in evolutionary ecology for their diverse ecological niches. In addition, crickets have recently gained recognition as food and feed. However, the genomic information underlying their biological basis and application research toward breeding is currently underrepresented. In this review, we summarize the progress of genomics of crickets. First, we outline the phylogenetic position of crickets in insects and then introduce recent studies on cricket genomics and transcriptomics in a variety of fields. Furthermore, we present findings from our analysis of polyneopteran genomes, with a particular focus on their large genome sizes, chromosome number, and repetitive sequences. Finally, how the cricket genome can be beneficial to the food industry is discussed. This review is expected to enhance greater recognition of how important the cricket genomes are to the multiple biological fields and how basic research based on cricket genome information can contribute to tackling global food security.

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Rosenthal, Sara Brin, Hao Wang, Da Shi, Cin Liu, Ruben Abagyan, Linda K. McEvoy, and Chi-Hua Chen. "Mapping the gene network landscape of Alzheimer’s disease through integrating genomics and transcriptomics." PLOS Computational Biology 18, no. 2 (February 25, 2022): e1009903. http://dx.doi.org/10.1371/journal.pcbi.1009903.

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Integration of multi-omics data with molecular interaction networks enables elucidation of the pathophysiology of Alzheimer’s disease (AD). Using the latest genome-wide association studies (GWAS) including proxy cases and the STRING interactome, we identified an AD network of 142 risk genes and 646 network-proximal genes, many of which were linked to synaptic functions annotated by mouse knockout data. The proximal genes were confirmed to be enriched in a replication GWAS of autopsy-documented cases. By integrating the AD gene network with transcriptomic data of AD and healthy temporal cortices, we identified 17 gene clusters of pathways, such as up-regulated complement activation and lipid metabolism, down-regulated cholinergic activity, and dysregulated RNA metabolism and proteostasis. The relationships among these pathways were further organized by a hierarchy of the AD network pinpointing major parent nodes in graph structure including endocytosis and immune reaction. Control analyses were performed using transcriptomics from cerebellum and a brain-specific interactome. Further integration with cell-specific RNA sequencing data demonstrated genes in our clusters of immunoregulation and complement activation were highly expressed in microglia.

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Tounta, Vivian, Yi Liu, Ashleigh Cheyne, and Gerald Larrouy-Maumus. "Metabolomics in infectious diseases and drug discovery." Molecular Omics 17, no. 3 (2021): 376–93. http://dx.doi.org/10.1039/d1mo00017a.

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Chen, Xin, Anjun Ma, Adam McDermaid, Hanyuan Zhang, Chao Liu, Huansheng Cao, and Qin Ma. "RECTA: Regulon Identification Based on Comparative Genomics and Transcriptomics Analysis." Genes 9, no. 6 (May 30, 2018): 278. http://dx.doi.org/10.3390/genes9060278.

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Hacquard, Stéphane, Benjamin Petre, Pascal Frey, Arnaud Hecker, Nicolas Rouhier, and Sébastien Duplessis. "The Poplar-Poplar Rust Interaction: Insights from Genomics and Transcriptomics." Journal of Pathogens 2011 (2011): 1–11. http://dx.doi.org/10.4061/2011/716041.

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Poplars are extensively cultivated worldwide, and their susceptibility to the leaf rust fungusMelampsora larici-populinaleads to considerable damages in plantations. Despite a good knowledge of the poplar rust life cycle, and particularly the epidemics on poplar, the perennial status of the plant host and the obligate biotrophic lifestyle of the rust fungus are bottlenecks for molecular investigations. Following the completion of bothM. larici-populinaandPopulus trichocarpagenome sequences, gene families involved in poplar resistance or in rust fungus virulence were investigated, allowing the identification of key genetic determinants likely controlling the outcome of the interaction. Specific expansions of resistance and defense-related genes in poplar indicate probable innovations in perennial species in relation with host-pathogen interactions. The genome ofM. Larici-populinacontains a strikingly high number of genes encoding small secreted proteins (SSPs) representing hundreds of candidate effectors. Transcriptome analyses of interacting partners in compatible and incompatible interactions revealed conserved set of genes involved in poplar defense reactions as well as timely regulated expression of SSP transcripts during host tissues colonisation. Ongoing functional studies of selected candidate effectors will be achieved mainly on the basis of recombinant protein purification and subsequent characterisation.

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KALLIONIEMI, OLLI. "Functional genomics and transcriptomics of prostate cancer: promises and limitations." BJU International 96, s2 (December 2005): 10–15. http://dx.doi.org/10.1111/j.1464-410x.2005.05941.x.

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