27 papers · ranked by Valyu relevance
Parul Tyagi, Deeksha Singh, Shivangi Mathur, Ayushi Singh + 1 more
'Rajiv Ranjan'] Transcriptome sequencing or RNA-Sequencing is a high-resolution, sensitive and high-throughput next-generation sequencing (NGS) approach used to study non-model plants and other organisms. In other words, it is an assembly of RNA transcripts from individual or whole samples of functional and…
Nunzio D’Agostino, Wenli Li, Dapeng Wang
High-throughput transcriptomics has revolutionised the field of transcriptome research by offering a cost-effective and powerful screening tool. Standard bulk RNA sequencing (RNA-Seq) enables characterisation of the average expression profiles for individual samples and facilitates identification of the molecular…
Stephen B. Montgomery, Jonathan A. Bernstein, Matthew T. Wheeler
In the past 5 years transcriptome or RNA-sequencing (RNA-seq) has steadily emerged as a complementary assay for rare disease diagnosis and discovery. In this perspective, we summarize several recent developments and challenges in the use of RNA-seq for rare disease investigation. Using an accessible patient sample…
Tamer Butto, Stefan Pastore, Max Müller, Kaushik Viswanathan Iyer + 6 more
Nanopore technology offers real-time sequencing opportunities, providing rapid access to sequenced data and allowing researchers to manage the sequencing process efficiently, resulting in cost-effective strategies. Here, we present focused case studies demonstrating the versatility of real-time transcriptomics analysis…
Tanner Stokes, Haoning Howard Cen, Philipp Kapranov, Iain J Gallagher + 7 more
'Iain J Gallagher' 'Andrew A. Pitsillides' 'Claude‐Henry Volmar' 'William E Kraus' 'James D. Johnson' 'Stuart M. Phillips' 'Claes Wahlestedt' 'James A. Timmons'] Title: Abstract Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug…
Cristian D. Gutierrez Reyes, Gerardo Alejo-Jacuinde, Benjamin Perez Sanchez, Jesus Chavez Reyes + 7 more
'Benjamin Perez Sanchez' 'Jesus Chavez Reyes' 'Sherifdeen Onigbinde' 'Damir Mogut' 'Irma Hernández-Jasso' 'Denisse Calderón-Vallejo' 'J. Luis Quintanar' 'Yehia Mechref' 'Madhav Bhatia'] Traditional methodologies often fall short in addressing the complexity of biological systems. In this regard, system biology omics…
Sai Guna Ranjan Gurazada, H Kennedy, Richard D. Braatz, Steven J. Mehrman + 2 more
adeno-associated virus (rAAV) gene therapy manufacturing Authors: ['Sai Guna Ranjan Gurazada' 'H Kennedy' 'Richard D. Braatz' 'Steven J. Mehrman' 'Shawn W. Polson' 'Irene Rombel'] Gene therapy is poised to transition from niche to mainstream medicine, with recombinant adeno-associated virus (rAAV) as the vector of…
Hyeongseon Jeon, Juan Xie, Yeseul Jeon, Kyeong Joo Jung + 3 more
'Arkobrato Gupta' 'Won Chang' 'Dongjun Chung'] Gene expression profiling technologies have been used in various applications such as cancer biology. The development of gene expression profiling has expanded the scope of target discovery in transcriptomic studies, and each technology produces data with distinct…
Isaac Adeyemi Babarinde, Andrew Paul Hutchins
Investigating the functions and activities of genes requires proper annotation of the transcribed units. However, transcript assembly efforts have produced a surprisingly large variation in the number of transcripts, and especially so for noncoding transcripts. The heterogeneity of the assembled transcript sets might…
Jonathan S. Abebe, Yasmine Alwie, Erik Fuhrmann, Jonas Leins + 5 more
High-resolution annotations of transcriptomes from all domains of life are essential for many sequencing-based RNA analyses, including Nanopore direct RNA sequencing (DRS), which would otherwise be hindered by misalignments and other analysis artefacts. DRS allows the capture and full-length sequencing of native RNAs…
Ya-Hui Lin, Jennifer E. Dodd, Luisa Cutillo, Lydia M. Castelli + 14 more
Transcriptomes and translatomes measure genome-wide levels of total and ribosome-associated RNAs. A few hundred translatomes were reported over >250,000 transcriptomes highlighting the challenges of identifying translating RNAs. Here, we used a human isogenic inducible model of TDP-43-linked amyotrophic lateral…
David Murphy, Mina Ryten, Nicholas W. Wood, Emil K. Gustavsson
Long-read RNA sequencing has expanded our understanding of the transcriptome, revealing unannotated transcripts. However, interpreting their functional relevance remains challenging. To address this, we developed TX2P, a user-friendly tool that integrates transcriptomic and proteomic data to link RNA discoveries with…
Ihab Bendidi, Shawn Whitfield, Kian Kenyon-Dean, Hanene Ben Yedder + 3 more
: one PCA still rules them all Authors: ['Ihab Bendidi' 'Shawn Whitfield' 'Kian Kenyon-Dean' 'Hanene Ben Yedder' 'Yassir El Mesbahi' 'Emmanuel Noutahi' 'Alisandra K. Denton'] Understanding the relationships among genes, compounds, and their interactions in living organisms remains limited due to technological…
Elena A. Ponomarenko, George S. Krasnov, Olga I. Kiseleva, Polina A. Kryukova + 7 more
'Polina A. Kryukova' 'Viktoriia A. Arzumanian' 'Georgii V. Dolgalev' 'Ekaterina V. Ilgisonis' 'Andrey V. Lisitsa' 'Ekaterina V. Poverennaya' 'Jinghua Zhao' 'Jiadong Ji'] Transcriptomics methods (RNA-Seq, PCR) today are more routine and reproducible than proteomics methods, i.e., both mass spectrometry and…
Shuo Shuo Liu, Shikun Wang, Yuxuan Chen, Anil K. Rustgi + 2 more
'Jianhua Hu'] Background: Spatial transcriptomics have emerged as a powerful tool in biomedical research because of its ability to capture both the spatial contexts and abundance of the complete RNA transcript profile in organs of interest. However, limitations of the technology such as the relatively low resolution…
Jeremy W. Prokop, Stephanie M. Bilinovich, Ember Tokarski, Sangeetha Vishweswaraiah + 27 more
Although single-cell RNA sequencing advances cellular discovery, spatial RNA sequencing promises to refine our tissue physiology and disease knowledge (189, 190). The complex anatomy of cells within any biological tissue has long been appreciated through histology, and dating back to 1987, groups have advanced the…
Dian Meng, Bao-Cai Xing, Xinlei Huang, Yanran Liu + 4 more
Test-Time Training layers Authors: ['Dian Meng' 'Bao-Cai Xing' 'Xinlei Huang' 'Yanran Liu' 'Yijun Zhou' 'Yujie Xiao' 'Zitong Yu' 'Xubin Zheng'] Single-cell multi-omics (scMulti-omics) refers to the paired multimodal data, such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), where the…
Ihab Bendidi, Yassir El Mesbahi, Alisandra K. Denton, Karush Suri + 3 more
'Kian Kenyon-Dean' 'Auguste Genovesio' 'Emmanuel Noutahi'] Understanding cellular responses to stimuli is crucial for biological discovery and drug development. Transcriptomics provides interpretable, gene-level insights, while microscopy imaging offers rich predictive features but is harder to interpret. Weakly paired…
Vighnesh Ghatpande, Uma Paul, MacKenzie A Howard, Can Cenik
In the last decade, an unexpectedly large number of translated regions (translons) have been discovered using ribosome profiling and proteomics. Translons can regulate mRNA translation and encode micropeptides that contribute to multiprotein complex formation, Ca^2+^ regulation in muscle, and signaling during embryonic…
Meriem Hadjer Hamadou, Laura Alunno, Tecla Venturelli, Samuel Valentini + 20 more
Relatively few studies have examined the link between SNPs and mRNA translation, despite the established importance of translational regulation in shaping cell phenotypes. We developed a pipeline analyzing the allelic imbalance in total and polysome-bound mRNAs from paired RNA-seq data of HCT116 cells and identified 40…
Janet Sasso, Barbara Ambrose, Rumiana Tenchov, Ruchira Datta + 3 more
In the last decade, there has been a shift in research, clinical development, and commercial activity to exploit the many roles of RNA in physiology for use in medicine. With the rapid success in the development of lipid-RNA nanoparticles for mRNA vaccines against COVID-19 and with several approved RNA-based drugs, RNA…
Authors not listed
Mass spectrometry (MS) is a cornerstone technology in modern molecular biology, powering diverse applications across proteomics, metabolomics, lipidomics, glycomics, and beyond. As the field continues to evolve, rapid advancements in instrumentation, acquisition strategies, machine learning, and scalable computing have…
Juerg Straubhaar, Alexandria D’Souza, Zachary Niziolek, Bogdan Budnik
Single-cell analysis has clearly established itself in biology and biomedical fields as an invaluable tool that allows one to comprehensively understand the relationship between cells, including their types, states, transitions, trajectories, and spatial position. Scientific methods such as fluorescence labeling…
Michael Lanzillotti, Jennifer Brodbelt
Recent progress in top-down mass spectrometry analysis of progressively larger nucleic acids has enabled in-depth characterization of intact, modified RNA molecules. Development of methods for desalting and MS/MS fragmentation allows rapid acquisition of high-quality top-down MS/MS spectra of nucleic acids up to 100…
Michael Lanzillotti, Jennifer Brodbelt
Mass spectrometry has proven to be a highly effective tool for characterization of RNA post-transcriptional modifications. For both synthetic RNAs and ones from biological sources, mass spectrometry can interrogate multiple, co-occurring covalent modifications at the nucleotide level simultaneously. To expand the…
Ulrich Pabst
The idea of peptide mass fingerprinting (PMF) was first introduced in 1989, when protein research was facing a serious issue with automated Edman-degradation taking nearly one hour per reaction cycle. There was a dire need for more streamlined and fast ways to analyse proteins and peptides. Since the first steps…
Authors not listed
Machine learning holds significant promise for accelerating biomarker discovery in clinical proteomics, yet its real-world impact remains limited by widespread methodological pitfalls and unrealistic expectations. In this perspective, we critically examine the integration of machine learning into clinical proteomics…