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Volume 56 Issue 3, March 2024

Brassica oleracea pan-genome

De novo genome assemblies of 22 Brassica oleracea accessions and pan-genome analyses highlight the effects of structural variation on gene expression and its contribution to morphotype diversification.

See Li et al.

Image: Chang Keyong, professional photographer, Beijing, China. Cover Design: Tulsi Voralia

Research Highlights

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News & Views

  • Gestational diabetes is a complex metabolic condition thought to have a strong genetic predisposition. A large genome-wide association study of participants from Finland sheds light on the genetic contributors, opening avenues for research into mechanisms that underlie glucose regulation in pregnancy to improve the health of mothers and babies.

    • Aminata Hallimat Cissé
    • Rachel M. Freathy
    News & Views
  • A common architectural feature of the genome in many organisms is chromatin domains. A synthetic biology approach now builds chromatin domains from scratch and identifies some of the minimal components needed for their formation.

    • Theodore Busby III
    • Tom Misteli
    News & Views
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Research Briefings

  • Genome-wide CRISPR screening coupled with ATAC-see uncovered modulators that influence global chromatin accessibility. Notably, TFDP1 emerged as a pivotal modulator of chromatin accessibility that acts by controlling histone transcription. Depletion of TFDP1 induced a global elevation in accessibility, enhancing the efficiency of genome editing and iPS cell reprogramming.

    Research Briefing
  • We constructed a pan-genome using 27 high-quality representative Brassica oleracea genomes. Using this pan-genome, together with multi-omics datasets from large-scale populations, we uncovered the important role of structural variations as dosage regulators of gene expression, which drives the morphotype diversification in B. oleracea.

    Research Briefing
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Technical Reports

  • MuSiCal is a mutational signature analysis tool combining minimum-volume nonnegative matrix factorization with other algorithmic innovations. Applied to PCAWG data, MuSiCal gives more accurate results, including resolving ambiguous flat signatures.

    • Hu Jin
    • Doga C. Gulhan
    • Peter J. Park
    Technical Report Open Access
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