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By integrating spatially resolved single-cell RNA sequencing (scRNA-seq) and Stereo-seq data, two studies in this issue characterize molecular signatures of liver cell types and their interactions in homeostasis, damage, repair and regeneration.
Two low-input tagmentation-based long-read sequencing methods, single-molecule real-time sequencing by tagmentation (SMRT-Tag), which identifies genetic variation and CpG methylation, and single-molecule adenine-methylated oligonucleosome sequencing assay by tagmentation (SAMOSA-Tag), which detects chromatin accessibility, are presented. Application of SAMOSA-Tag to prostate cancer patient-derived xenograft samples identifies metastasis-associated epigenomic alterations.
The authors develop and harness a suite of epigenome editing tools to explore the role of different epigenetic marks in modulating transcription. In particular, H3K4me3 deposition on promoter sequences is shown to directly promote transcription activation in mouse embryonic stem cells.
Genomic and epigenomic techniques identify a new variation type causing Mendelian disease by altering the non-coding regulatory network in thyroid cells — solving a hidden cause linked for 20 years.
Short tandem repeat mutations in a primate Alu element on chromosome 15q cause activation of a thyroid-specific enhancer, upregulating MIR7-2/MIR1179. This results in defective thyroid proliferation and thyrotropin resistance.
A high-quality reference genome assembly of cauliflower C-8 (V2) and genomic analyses of 971 diverse accessions and their relatives reveal the stepwise domestication and the genetic mechanism of curd biogenesis.
Noncoding variants in a TTTG microsatellite on 15q26.1 are identified in Japanese patients with childhood and adult-onset thyroid abnormalities. Functional analyses suggest that these variants affect the role of the microsatellite as a potential regulator of thyroid cell growth.
Defining minimal standards for data collection is key to creating interoperative, searchable genomic and clinical databases. We highlight here the 1+Million Genomes Minimal Dataset for Cancer, encompassing 140 items in 8 domains to foster the collection of cancer data, inform transnational cooperation and advance precision cancer medicine.
Genome assemblies of four filamentous Zygnematophyceae and co-expression network analyses shed light on the evolutionary roots of the mechanism for balancing environmental responses and multicellular growth.
Genome-wide association analysis in over one million individuals of European ancestry identifies 2,103 independent genetic signals (including 113 new loci) associated with blood pressure traits.
SBayesRC integrates genome-wide association summary statistics with functional annotations to improve polygenic prediction of complex traits. Functional partitioning highlights a major contribution of evolutionarily constrained regions to prediction accuracy.
The recently launched Egyptian Genome Project aims to sequence genomic variants of 100,000 apparently healthy Egyptian adults, with around 8,000 individuals suspected to have a genetic disease, as well as 200 ancient Egyptian mummies. The project will provide the first comprehensive genomic dataset from Egypt and North Africa.
We construct a chromosome-level genome assembly of the acorn barnacle Amphibalanus amphitrite. Using this genome together with multi-omics datasets and functional evidence, we reveal the evolution and function of two lineage-specific genes, bcs-6 and bsf, that help A. amphitrite adapt to a sessile lifestyle.
Long-read sequencing identifies a GGC-repeat expansion in the coding region of ZFHX3 as the cause of spinocerebellar ataxia type 4. The expansion encodes polyglycine and results in intranuclear aggregates and abnormal autophagy.
Multiple domestication-related traits in cultivated soybeans are pleiotropic effects of a locus composed of two tandemly duplicated long noncoding RNAs that act via sRNA repression of MYB transcription factors.
A multi-ancestry genome-wide association meta-analysis of kidney cancer identifies 63 regions associated with disease susceptibility including one locus that was associated with increased risk in individuals with African ancestry.
BEAN is a Bayesian approach for analyzing base editing screens with improved effect size quantification and variant classification. Applied to low-density lipoprotein (LDL)-associated common variants and saturation base editing of LDLR, BEAN identifies new LDL uptake genes and offers insights into variant structure–pathogenicity mechanisms.