Thank you to @monashuniversity.bsky.social, @monashbiol.bsky.social, BDI & e_Research Monash and all collaborative Institutions for support. We enjoyed bringing this work out and we hope people like it. A big thank you to @nature.com for being considerate about APC in my funding climate! (10/10)

Thank you also to my collaborators Sefi Rosenbluh (BDI Monash), Mauro D'Amato (LUM, Italy), Partha Das (BDI Monash), Yalong Guo (CAS, China), Alex Fournier-Level (Uni Melb), David Powell (e-Research, Monash) and Sridevi Sureshkumar (Biol, Monash) for their excellent support and contributions (9/10)

Hearty congratulations/thanks to Craig Dent
@ciden13.bsky.social, Stefan Prodic, Aiswarya Balakrishnan, Aaryan Chhabra, James Georges, Sourav Mukherjee @souravbiotech.bsky.social, Jordyn Coutts @jordyncoutts.bsky.social , Michael Gitonobel & Rucha Sarwade for their contributions (8/10)

Mutational impacts of known diseases could be explained based on the impacts of the hexamers as the example of CFTR gene in cystic fibrosis (7/10)

There is a correlation in the rankings of the hexamers, which appear to reflect phylogenetic relationships arguing for a shared logic across eukaryotes (6/10)

This pattern appears to hold true across eukaryotes and this shared logic of stronger hexamers being able to compete with weaker ones to determine splicing outcomes. The frequency at splice sites is correlated with with their strength rather than genomic prevalence (5/10)

By carrying out 130000 GWAS along with millions of splice-site usage measures, we could infer that hexamer sequences surrounding the splice-sites form a rank order that could mostly explain the choices! By chaning hexamers, we could modify introns for desirable outcomes (4/10)

Here, we used these quantifications to map genetic variation associated with splice-site usage in GWAS (SpliSER-GWAS), which really worked like magic (3/10)

This works builds on our earlier work, where we described SpliSER, a method that allows accurate and empirical quantifications of splice-site usage as a method to analyse splicing (2/10)

academic.oup.com/nargab/artic...

Review: Dispersed components drive temperature sensing and response in plants
www.science.org/doi/10.1126/...

Avilash Yadav, Sridevi Sureshkumar, Alok Sinha & Suresh Balasubramanian review how plants integrate temperature sensing across signalling pathways and find the common themes in temperature sensing mechanisms
www.science.org/doi/10.1126/...
(5/8)

Great to see the Chinese abstract too!