[Next-Generation Sequencing Book]

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  • [Photo] Editor • January 31, 2026
    A new deep learning model called AlphaGenome, developed by researchers at Google DeepMind, analyzes up to one million base pairs of DNA sequence to forecast thousands of functional genomic features at single-base resolution. These predictions span 11 modalities, from gene expression and RNA splicing to chromatin accessibility, histone modifications, transcription factor binding, and spatial chromatin contacts, drawing on extensive human and mouse datasets. In benchmark tests, the model equals or surpasses leading alternatives on 25 out of 26 variant effect prediction tasks, including those for expression quantitative trait loci (eQTLs), splicing changes, and chromatin interactions. AlphaGenome also reconstructs the regulatory mechanisms behind clinically significant variants near the TAL1 oncogene.

    ARTICLE

    Avsec Ž, Latysheva N, Cheng J, Novati G, Taylor KR, Ward T, et al. Advancing regulatory variant effect prediction with AlphaGenome. Nature. 2026;649(8099):1206-1218. https://doi.org/10.1038/s41586-025-10014-0.

    AVAILABILITY

    AlphaGenome's primary website is hosted by Google DeepMind at https://deepmind.google.com/science/alphagenome

    It is also on GitHub. There are two key repositories:

    https://github.com/google-deepmind/alphagenome – This provides the Python SDK and programmatic access to the hosted API.
    https://github.com/google-deepmind/alphagenome_research – This contains the model source code, weights, variant scoring tools, and related research materials, as stated in the Nature paper.

    Additional resources include detailed documentation at https://www.alphagenomedocs.com and a community forum.
  • [Photo] Elsa Dubar • January 28, 2026
    August 31 - September 4, 2026
    Geneva, Switzerland
    https://eccb2026.org

    The city of Geneva hosts the 25th European Conference on Computational Biology (ECCB), from 31 August until 4 September 2026, under the theme "Biodiversity, AI & Health: computational biology to address the challenges of our time".

    The conference will explore how computational biology and bioinformatics contribute to understanding biological diversity, advancing health research, and addressing global societal challenges through data-driven approaches.

    Organized by the SIB Swiss Institute of Bioinformatics, ECCB 2026 will bring together 1,000-1,200 experts from around the world, including bioinformaticians, computational biologists, developers, biocurators, and clinicians from academia, industry, and public healthcare.

    CALL FOR PROCEEDINGS

    The ECCB 2026 Scientific Committee welcomes the submission of full manuscripts describing original and previously unpublished work in computational biology. Accepted papers will be presented as 15-minute talks during the conference and published in a supplementary issue (online-only and open access) of the Bioinformatics journal (Oxford University Press).

    Deadline to submit: 5 March 2026.

    More info : https://eccb2026.org/call-proceedings

    CALL FOR HIGHLIGHT TALKS & POSTERS

    ECCB 2026 also welcomes abstract submissions for highlight talks on significant advances in one of the conference's five scientific areas in computational biology and bioinformatics, published in a scientific journal on or after 1 March 2025 or accepted for publication in a scientific journal and available online as a preprint.

    Posters can also be submitted across all areas of computational biology and bioinformatics.

    Accepted contributions (highlight talks and posters) will be presented in person at the conference. Highlight talks will be delivered as 15-minute presentations followed by 3 minutes of discussion.

    Deadline to submit: 20 April 2026.

    More info: https://eccb2026.org/call-highlight-talk-poster
  • [Photo] Editor • January 22, 2026
    Adults who reach their eighties and nineties while keeping memory sharp enough to match much younger people often have a distinct profile in their APOE gene. SuperAgers, as researchers call them, carry the APOE-ε4 allele less frequently than those diagnosed with Alzheimer's dementia, and the APOE-ε2 allele more often. This pattern emerged clearly from analyses of over 18,000 participants in several major cohorts. Among non-Hispanic White individuals, SuperAgers differed significantly from both dementia patients and age-matched peers with average cognitive aging. In a smaller sample of non-Hispanic Black SuperAgers, the trends pointed in the same direction: lower APOE-ε4 and somewhat elevated APOE-ε2 compared with dementia cases, although some differences versus cognitively normal controls did not meet the threshold for strong statistical significance. The results suggest APOE genotype plays a role in maintaining cognitive function late in life. Larger studies focused on Black participants would help determine whether these associations hold similarly across racial or ethnic groups.

    ARTICLE

    Durant A, Mukherjee S, Lee ML, et al. Evaluating the association of apolipoprotein E genotype and cognitive resilience in SuperAgers. Alzheimers Dement. 2026;22(1):e71024. https://doi.org/10.1002/alz.71024
  • [Photo] Editor • January 8, 2026
    Genomics teams often rely on static cloud tags (e.g., project, pipeline_run) and service-level metrics to monitor compute costs. These signals provide limited visibility into how workloads behave at the execution-layer. There's no default mapping from a pipeline task to an EC2 process, it is difficult to determine whether slowdowns are caused by application logic or infrastructure constraints such as disk or network I/O.

    This guide analyzes a real-world RNA-seq pipeline that was initially assumed to be memory- or compute-bound. By correlating pipeline run identifiers with kernel-level execution data, the team identified a different root cause: sustained disk and network I/O saturation. The pipeline consistently ran for more than three hours per sample. Cloud metrics showed high memory reservations, leading the team to vertically scale the infrastructure:
    • Baseline: r6i.8xlarge (256 GB RAM, EBS-backed)
    • Scaled: r6i.16xlarge (512 GB RAM, EBS-backed)
    Costs doubled, but runtime did not improve. By correlating the specific pipeline_run ID to kernel-level traces, using Tracer (https://www.tracer.cloud), the team isolated the following metrics:
    • CPU utilization remained below ~25%
    • Peak memory usage stayed well below requested limits
    • Disk and network throughput were saturated for large portions of the run
    • STAR frequently stalled while waiting on data rather than compute
    The team evaluated newer, memory-optimized instance families with improved CPU generation, memory bandwidth, and network characteristics:
    • r7a.12xlarge: ~33% faster runtime at ~37% lower cost
    • r8i.8xlarge: near-baseline runtime at ~61% lower cost
    After the change:
    • Runtime decreased from 3+ hours to ~2 hours (~30% faster)
    • Cost per pipeline dropped by 36-60%, depending on configuration
    Effective optimization needs more signals. Tracing execution from pipeline-level identifiers down to kernel behavior, helps teams avoid paying for unused resources and select infrastructure that matches how workloads actually run.
  • [Photo] Prashanth N Suravajhala • January 3, 2026
    A comprehensive European study examining the impacts of open science practices, such as publishing articles in open access formats and sharing data or software freely, confirms certain advantages while revealing limited evidence for broader effects. Open-access papers earn more citations from other research and appear in patent applications more often, citizen scientists gain knowledge through participation, and reused open resources during the COVID-19 pandemic correlated with increased industry collaborations in some cases. Users of shared databases like UniProt save substantial time compared to the effort required to maintain them. Yet the analysis, which combined quantitative data, literature reviews, and case studies, identifies sparse causal proof linking these practices to accelerated scientific discovery, economic growth, or widespread societal benefits, underscoring challenges in measuring long-term outcomes.

    Source: https://www.science.org/content/article/open-science-delivering-benefits-major-study-finds-proof-sparse

    Prash
  • [Photo] J.W. Bizzaro • December 14, 2025
    Rare diseases sometimes open windows into everyday biology that we otherwise miss. Take Sedaghatian-type spondylometaphyseal dysplasia (SSMD) as an example. It's a condition so rare it affects only a handful of families worldwide. Tragically, most affected infants die soon after birth, but a few linger long enough to show something striking: their brains deteriorate at breakneck speed in a pattern that echoes severe dementia in the elderly. The entire process traces back to one defective gene: GPX4.

    Source: https://scitechdaily.com/a-tiny-enzyme-flaw-may-explain-how-dementia-begins/

    GPX4 codes for the enzyme glutathione peroxidase 4, which is embedded in neuronal membranes. Its job is to disarm lipid peroxides before they can harm the cell. When the enzyme fails, either because of an inherited mutation or because levels drop over a lifetime, those peroxides multiply unchecked. Membranes essentially oxidize in a runaway chain reaction. The result is ferroptosis: iron-driven cell death where the neuron balloons, bursts, and spills damaging contents that inflame nearby cells. Apoptosis, by comparison, looks tidy – this is messy and can spread.

    Findings like these push us to reconsider Alzheimer's disease itself. For years the field has argued over which protein misfolds first, amyloid-beta plaques or tau tangles, and which one truly drives the damage. Yet the terminal event that kills the neuron may not depend on either. Emerging evidence suggests that ferroptosis could represent a common endpoint, potentially contributing to neurodegeneration. Different insults can start the trouble, but they often finish by wrecking membranes the same way.

    If we interrupt ferroptosis, the cell holds together no matter what sparked the crisis. Work in laboratory animals using agents such as the iron-binding drug deferoxamine or the experimental compound J147 shows this clearly. Neurons stop dying explosively, regain metabolic stability, kick autophagy back into gear, and begin clearing junk while rebuilding connections. Preserving the neuron becomes the priority; tracing the exact upstream culprit matters less once the cell survives.

    RELEVANT DRUGS AND TRIALS

    The "Synthetic Shields" (Geroneuroprotectors):
    • J147 (Curcumin derivative):
      • Mechanism: Targets mitochondrial ATP synthase to reduce oxidative stress (ROS) and boosts BDNF to repair synapses.
      • Status: Has completed FDA Phase 1 (safety) trials in humans; Phase 2 efficacy trials for Alzheimer's are the next step.
    • CMS121 (Fisetin derivative):
      • Mechanism: Inhibits fatty acid synthase (FASN) to alter cell membrane composition, making lipids resistant to peroxidation.
      • Status: In active clinical development (Phase 1 safety profile established); moving toward efficacy testing.
    The Iron Chelators (The "Sledgehammers"):
    • Deferoxamine (Desferal):
      • Mechanism: Physically removes excess iron to stop the reaction that triggers ferroptosis.
      • Trial History: The 1991 Crapper McLachlan study (intramuscular injections) showed a 50% reduction in cognitive decline.
      • Status: Since deferoxamine can no longer be patented, complex delivery methods are being actively investigated.
    • Deferiprone:
      • Mechanism: An oral iron chelator that crosses the blood-brain barrier more easily than deferoxamine.
      • Status: Deferiprone was tested in the "3D Study", which ran from 2018 to 2023. The study authors and subsequent editorial commentaries concluded that the drug failed not because it didn't work, but because it caused "Functional Iron Deficiency" within the neurons.
  • [Photo] Editor • December 10, 2025
    The US Defense Advanced Research Projects Agency (DARPA) has launched Generative Optogenetics (GO), a program that aims to let living cells write their own DNA and RNA on demand using beams of light. Instead of synthesizing genetic material in distant factories and then inserting it, scientists plan to engineer microbes and human cells to assemble precise nucleic-acid sequences inside the body whenever specific wavelengths strike them. DARPA's Biological Technologies Office describes the effort as a shift from today's slow, lab-bound gene synthesis to rapid, programmable biology that operates directly within organisms. Program manager Matthew Pava leads the initiative, which remains in early exploratory stages with no public milestones yet announced.

    Source: https://www.darpa.mil/research/programs/go
    YouTube video: https://www.youtube.com/watch?v=RtpZhZcbQXQ
  • [Photo] Editor • November 29, 2025
    A new fluorescence-based sensor now lets researchers watch DNA repair unfold in real time inside living cells. When both strands of the DNA helix snap – a lethal lesion if left unrepaired – the sensor signals the arrival of the MRN complex (MRE11, RAD50, and NBS1 proteins) within seconds. High-resolution movies reveal MRN rapidly resecting the broken ends, generating single-stranded DNA overhangs up to 1,000 nucleotides long in under ten minutes to prepare the site for homologous recombination. Tracking hundreds of individual breaks showed striking variation: some sites resect smoothly and complete repair, while others stall at intermediate steps, hinting that local chromatin environment or break complexity governs outcome. Published in Nature Communications, the work provides the first direct view of this key genome-maintenance process in action.

    ARTICLE

    da Silva RC, Eleftheriou K, Recchia DC, et al. Engineered chromatin readers track damaged chromatin dynamics in live cells and animals. Nat Commun. 2025;16(1):10127. https://doi.org/10.1038/s41467-025-65706-y

    Via: https://scitechdaily.com/this-new-sensor-shows-dna-repair-in-real-time-video/
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