Results 81 to 90 of about 389,403 (285)

Role of RNA Interference (RNAi) in the Moss Physcomitrella patens [PDF]

, 2013
RNA interference (RNAi) is a mechanism that regulates genes by either transcriptional (TGS) or posttranscriptional gene silencing (PTGS), required for genome maintenance and proper development of an organism.
Arif, Muhammad Asif, Frank, Wolfgang, Khraiwesh, Basel   +2 more
core   +3 more sources

Interplay between RNA‐protein interactions and RNA structures in gene regulation

FEBS Open Bio, EarlyView.
Methodological advances in mapping transcriptome‐wide RNA‐protein interactions and RNA structures have started to uncover the potential of RNP conformations in gene regulation. Competing RNA–RNA, RNA‐protein and protein–protein interactions shape the compaction and function of RNPs throughout their lifetime and may provide novel therapeutic targets in ...
Jenni Rapakko, Mauro Scaravilli, Minna‐Liisa Änkö   +2 more
wiley   +1 more source

Naked cuticle is essential for Drosophila wing development beyond Wingless signaling

FEBS Open Bio, EarlyView.
Naked cuticle (Nkd), a Wnt signaling inhibitor, assumes extensive roles in Drosophila wing development. Overexpressing Nkd causes smaller, crumpled wings, while also perturbing multiple signaling pathways and developmental genes. A specific region (R1S) is critical for Nkd's function as a signaling integrator, offering new insights for studying its ...
Rui Wang, Ping Wang
wiley   +1 more source

Defending the genome from the enemy within:mechanisms of retrotransposon suppression in the mouse germline [PDF]

, 2013
The viability of any species requires that the genome is kept stable as it is transmitted from generation to generation by the germ cells. One of the challenges to transgenerational genome stability is the potential mutagenic activity of transposable ...
A Aravin, A Dupressoir, A Dupressoir, A Dupressoir, A Fadloun, A Inagaki, A Inoue, A Inoue, A Meissner, A Prokhortchouk, A Puech, A Sookdeo, A Tsumura, A Vourekas, AA Aravin, AA Aravin, AA Aravin, AA Zabolotneva, AE Peaston, AR Muotri, AR Muotri, B Hendrich, BH Schrans-Stassen, C Chen, C Lu, C Popp, C-X Song, C-X Song, CE Nestor, CG Lian, CM Davis, CP Walsh, D Bourc’his, D Bourc’his, D Branciforte, D Guallar, D Haig, D Lucifero, D Lucifero, D Reiss, D Ribet, D Ribet, D Ribet, D Sproul, D Wolf, D Wolf, DA Kramerov, DC Hancks, DJ Lees-Murdock, DM Maatouk, Donncha S. Dunican, DS Dunican, DT Ting, E Beyret, E Beyret, E Khazina, E Li, EB Chuong, EL Kuff, ES Lander, F Santos, F Yang, FD Araujo, G Hutvagner, G Velasco, GD Evrony, H Cedar, H Cedar, H Heyn, H Kano, H Khan, H Kobayashi, H Stroud, HJ Cooke, HM Rowe, HM Rowe, HM Rowe, I Cantone, I Martín Caballero, I Suetake, IA Maksakova, Ian R. Adams, J Borgel, J Brennecke, J Chen, J Gimenez, J Lange, J Reichmann, J Reichmann, J Rossant, J Sharif, J Xiol, J-H Ng, JA Hackett, JA Hackett, JA Yoder, James H. Crichton, JD Lewis, JK Baillie, JL Garcia-Perez, JL Goodier, JN Athanikar, JO Kriegs, JP Reddington, JP Reddington, JP Thomson, JP Thomson, JV Moran, K Dennis, K Hata, K Hayashi, K Hisada, K Kurimoto, K Myant, K Zheng, K Zheng, KP Koh, L Jackson-Grusby, L Ma, L Piko, L Shen, L-Q Sun, LK Hutnick, M Abe, M Chotalia, M Denne, M Dewannieux, M Dewannieux, M Dewannieux, M Freitag, M Kaneda, M Kaneda, M Ko, M Ko, M Leeb, M Okano, M Reuter, M Reuter, M Ruggiu, M Saitou, M Shoji, M Tachibana, M Tahiliani, M Weber, M Wiench, M Xu, MA Carmell, Marie MacLennan, MC Ward, MM Dawlaty, MM Dawlaty, MM Karimi, MT Romanish, N Bannert, N Gilbert, N Lane, N Mathioudakis, N Reynolds, N Yang, N Zamudio, OH Tam, P Hajkova, P Hajkova, PJ Skene, Q Feng, Q Yan, R Brunmeir, R Burdick, R Fuente De La, R Illingworth, R Lister, R Rebollo, R Shukla, R Yaman, R Öllinger, RH Waterston, Richard R. Meehan, RJ DeBerardinis, RJA Frost, RR Meehan, S Chuma, S Fazio De, S Guibert, S Ito, S Ito, S Kagiwada, S Kaufmann, S Kuntz, S Kuramochi-Miyagawa, S Kuramochi-Miyagawa, S Kuramochi-Miyagawa, S Kuramochi-Miyagawa, S Mi, S Milutinovic, S Salle La, S Schütt, S Seisenberger, S Solyom, S Takebayashi, S Yamaguchi, S-H Lee, SA Smallwood, SA Trelogan, SB Rothbart, SFC Soper, SK Mahadevaiah, SL Martin, SL Martin, SL Martin, SL Mathias, SP Sripathy, SS Tanaka, ST Grivna, T Matsui, T Singer, T Tanaka, T Watanabe, T Watanabe, T Watanabe, T-P Gu, TS Macfarlan, UM Galli, V Chapman, VV Vagin, W Deng, W Filipowicz, W Seifarth, W Wei, W Yan, WA Pastor, X Cai, X Nan, Y Kato, Y Seki, Y Tao, Y Unhavaithaya, Y Yabuta, Y Yotsuyanagi, Y-Q Su, Z Li, ZD Smith, ZD Smith   +241 more
core   +2 more sources

Domain associated with zinc fingers‐containing NF90‐NF45 complex inhibits m6A modification of primary microRNA by suppressing METTL3/14 activity

FEBS Open Bio, EarlyView.
NF90–NF45 functions as a negative regulator of methyltransferase‐like 3/14 (METTL3/14)‐mediated N6‐methyladenosine (m6A) modification on primary microRNAs (pri‐miRNAs). NF90–NF45 binds to anti‐oncogenic pri‐miRNAs and inhibits their m6A modification, thereby suppressing the biogenesis of anti‐oncogenic miRNAs.
Takuma Higuchi, Shunsuke Morioka, Keiko Morisawa, Kazutsugu Matsukawa, Shingo Ashida, Takeshi Suzuki, Shuji Sakamoto   +6 more
wiley   +1 more source

Ibuprofen promotes p75 neurotrophin receptor expression through modifying promoter methylation and N6-methyladenosine-RNA-methylation in human gastric cancer cells [PDF]

, 2022
Haifeng Jin, Zheng Wu, Bi-Bo Tan, Zhen Liu, Zhanfei Zu, Xiaoyun Wu, Yuwang Bi, Xingmao Hu   +7 more
openalex   +1 more source

The Aging Blood: Cellular Origins, Circulating Drivers, and Therapeutic Potential

Aging and Cancer, EarlyView.
As a conduit linking all organs, the blood system both reflects and actively drives systemic aging. This review highlights how circulating pro‐aging and antiaging factors and age‐associated hematopoietic stem cell dysfunction contribute to immunosenescence and multi‐organ decline, positioning the hematopoietic system as a target for aging intervention.
Hanqing He, Jianwei Wang
wiley   +1 more source

TREEOME: A framework for epigenetic and transcriptomic data integration to explore regulatory interactions controlling transcription [PDF]

, 2015
Motivation: Predictive modelling of gene expression is a powerful framework for the in silico exploration of transcriptional regulatory interactions through the integration of high-throughput -omics data.
Budden, David M, Crampin, Edmund J, Hurley, Daniel G   +2 more
core   +2 more sources

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu, Yinjiao Fei, Jiaxuan Ding, Kexin Shi, Jinyan Luo, Yuchen Zhu, Xingjian Sun, Gefei Jiang, Yuandong Cao, Weilin Xu, Shu Zhou   +10 more
wiley   +1 more source

Depression and suicide risk prediction models using blood-derived multi-omics data [PDF]

, 2019
More than 300 million people worldwide experience depression; annually, ~800,000 people die by suicide. Unfortunately, conventional interview-based diagnosis is insufficient to accurately predict a psychiatric status. We developed machine learning models
Bhak, Jong, Bhak, Youngjune, Blazyte, Asta, Cho, Juok, Cho, Yun Sung, Gim, Jeong-An, Ham, Byung-Joo, Jeon, Sungwon, Jeon, Yeonsu, Jeong, Hyoung-oh, Kang, Wooyoung, Kim, Aram, Kim, Byung Chul, Kim, Hak-Min, Kim, Yumi, Lee, Hae-Woo, Lee, Semin, Paik, Jong-Woo, Park, Seung Gu, Shin, Eun-Seok   +19 more
core   +1 more source