DNA sequencing

A new market report projects steady expansion of the global high-fidelity DNA polymerase market through 2035, driven by rising demand for next-generation sequencing and synthetic biology applications. High-fidelity enzymes are essential for accurate DNA amplification in research, diagnostics and biomanufacturing, and suppliers are positioning for growth as genomics workflows scale up worldwide.

A new DNA annotation model, Carbon-A, has been used to identify 566 million previously unrecorded gene candidates, according to an announcement from Hugging Face's biology team. The tool is designed to annotate genomes and flag potential new genes across GenBank sequence data, a scale of discovery that would be impractical with manual curation.

Researchers have used artificial intelligence to decipher how CTCF, a key protein that organizes the genome into functional loops, binds DNA. The AI revealed hidden 'grammar' rules in the DNA sequences CTCF recognizes, offering new insight into how gene expression is regulated and how mutations may disrupt it. The work could help explain genetic diseases and advance genomic research.

A new market report projects steady expansion of the global endonuclease enzymes market through 2035, driven by rising demand for gene editing technologies and biopharmaceutical production. Endonucleases, which cut DNA at specific sequences, are core tools in CRISPR-based editing and biologics manufacturing. Industry analysts say biotech investment and growing therapeutic pipelines are the main forces behind the forecast growth.

Researchers using low-coverage genome sequencing have identified hidden clonal seed formation in relatives of the apple, a reproductive phenomenon where seeds produce genetic copies of the mother plant instead of the usual mix of parental DNA. The finding sheds light on how some apple relatives reproduce asexually through seeds, with potential implications for breeding and understanding plant reproduction more broadly.

A report in Nature describes progress in mapping sugars at the level of individual cells. Unlike DNA or proteins, glycans on cell surfaces are hard to sequence, and new methods aim to detect which sugar structures each cell carries. Researchers say this could clarify how cells communicate and how diseases like cancer alter their surface chemistry.

Scientists stumbled upon a microscopic organism whose genetic code violates a rule long considered nearly universal in biology. The discovery came by accident while the team was testing a new DNA sequencing technique. The finding is generating interest among geneticists and biologists, as exceptions to the standard genetic code are rare and could reshape understanding of how the code works and evolves.

A feature piece on the human genome examines DNA sequencing and what our genetic code reveals about human biology. The article covers how sequencing works and its relevance to understanding health and heredity. Coverage of genome science continues as sequencing becomes cheaper and more widely used in medicine and research.

Researchers have introduced a new computational tool that detects traces of human DNA hidden within microbiome sequencing data and uses them to predict a sample's biological sex. The approach taps genetic material that is typically discarded as contamination in microbiome studies, potentially aiding forensic and biomedical research while raising privacy questions about what sensitive information can be extracted from such datasets.

Scientists report that DNA sequence from a human brain gene has been found within a virus, a striking example of genetic material crossing between human hosts and viruses. Such findings shed light on how viruses and human genomes exchange genes over evolutionary time, and researchers are now examining what the incorporated sequence might do and how it got there.

A new analysis by Epoch AI finds the cost of achieving a given level of AI model performance has dropped roughly 13-fold per year over the past five years. That decline is faster than historical cost curves for computing hardware, lithium batteries, DNA sequencing and electricity. The authors caution, however, that these steep efficiency gains may not continue indefinitely, prompting discussion about how long such rapid deflation in AI costs can last.