genomics

Researchers report that artificial intelligence has identified a hidden DNA code that marks enhancers — genetic elements that regulate gene activity — consistently across different species. The finding suggests that regulatory sequences share common patterns that machine learning models can detect, offering new insight into how gene expression is controlled throughout evolution. The work could help scientists better understand genetic diseases linked to regulatory mutations.

A new deep learning tool can read RNA poly(A) tails directly from nanopore sequencing signals, bypassing the need for traditional basecalling and secondary analysis steps. Reported by Bioengineer.org, the method promises faster and potentially more accurate measurement of RNA modifications, which play key roles in gene regulation. Researchers in genomics are expected to take interest in the approach for transcriptomics workflows.

A landmark nationwide trial has found that genome sequencing outperforms standard testing in diagnosing developmental disorders, according to coverage by Bioengineer.org. The results could push doctors to adopt genomic testing earlier for children with unexplained developmental delays, shortening what is often a long diagnostic journey. The findings are being discussed as a potential turning point in how these conditions are diagnosed.

GRETA is a new database designed to turn vast quantities of genome sequencing data into searchable, usable science. The announcement comes amid growing frustration among researchers that enormous sequencing datasets remain difficult to query and exploit. By indexing genomic information, GRETA could accelerate work in medicine, biology and biodiversity. Details about its developers, scope and availability remain limited so far.

Researchers are reporting important advances in next-generation genome editing tools aimed at Huntington's disease, a fatal inherited neurodegenerative disorder caused by a single faulty gene. The news was highlighted by HDBuzz, a science communication outlet covering Huntington's research. The development fuels hope that gene-editing approaches could one day correct or silence the disease-causing mutation, though clinical application likely remains some distance away.

Two biotech holdings in Cathie Wood's ARK Genomic Revolution ETF (ARKG) have surged nearly six times in value this year, making the genomics fund the strongest performer among ARK Invest's lineup of ETFs. The outsized gains from the two biotech positions are driving the fund's advantage over her other products, drawing attention to Wood's high-conviction bets in genomics.

Researchers have introduced a graph transformer model designed to improve RNA velocity predictions in single-cell genomics. RNA velocity estimates the future state of individual cells, but existing methods struggle with noisy data and complex cell trajectories. By applying transformer-based deep learning to gene regulatory graphs, the new approach aims to produce more accurate predictions of how cells develop and differentiate. If validated, it could strengthen research in developmental biology and disease studies, areas where precise modeling of cell dynamics matters.

A new resource of induced pluripotent stem cells has been developed using long-read genome sequencing, providing researchers with deeply characterized cell lines for laboratory disease modeling. The combination of long-read technology, which captures complex genomic regions that shorter methods miss, with iPSC lines aims to give scientists a more complete genetic picture for studying disease in the lab.