BMAL1 is a core circadian transcription factor that also regulates stem cell fate, yet its role in human embryonic stem cell neurodifferentiation remains incompletely understood. Circadian disruption is associated with adverse neurodevelopmental outcomes, while N6 methyladenosine (m6A) RNA modification is a key regulator of early development. How BMAL1 interfaces with m6A dependent regulation during neural differentiation is unclear. Using CRISPR-Cas9 mediated genome editing, we generate BMAL1-deficient human embryonic stem cells and characterize their differentiation toward neural stem cells. Loss of BMAL1 does not compromise pluripotency but markedly impairs neurodifferentiation, resulting in defective neural rosette formation and suppression of neural lineage gene programs. Transcriptomic and CUT&Tag analyses reveal that BMAL1 directly regulates genes involved in embryonic development and neurogenesis. Integrated m6A profiling demonstrates altered m6A distribution in BMAL1-deficient cells, particularly reduced m6A enrichment near transcription end sites of downregulated genes. Notably, BMAL1 loss leads to a pronounced reduction in the m6A reader YTHDF2 at the protein level. Mechanistically, BMAL1 binds to an E-box motif in the YTHDF2 promoter and regulates alternative splicing of YTHDF2 transcripts, favoring a variant with a highly structured 5′ untranslated region and reduced translational efficiency. Genetic disruption of this E-box phenocopies BMAL1 deficiency. Functional rescue experiments show that YTHDF2 overexpression partially restores neural differentiation defects caused by BMAL1 loss. These findings identify a BMAL1-m6A-YTHDF2 regulatory axis that integrates transcriptional and post-transcriptional control to govern early human neural differentiation, providing mechanistic insight into how circadian disruption may contribute to neurodevelopmental disorders.
Some claim that especially in the field of agile software development the research lags years behind of the practice. In this paper, we characterize the status and main challenges for research on agile software development, and propose a preliminary roadmap, focusing on providing more empirical research, primarily on e...
Torgeir Dingsøyr, T. Dybå, P. Abrahamsson· Agile Conference· 92 citations· ⚡7
The results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains, and 219 factors representing causes of unhappiness while developing software are identified.
D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.· International Conference on...· 84 citations· ⚡6
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
Agile methods continue to gain popularity. In particular, the Scrum method appears to be on the verge of becoming a de-facto standard in the industry, leading the so called Agile movement. While there are success stories and recommendations, there is little scientifically valid evidence of the challenges in the adoptio...
A. Marchenko, P. Abrahamsson· Agile Conference· 59 citations· ⚡11
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.