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Linking genetic variants to kidney disease via the epigenome

The largest GWAS for kidney function so far provided the starting point for integrated multi-stage annotation of genetic loci. Whole kidney and single-cell epigenomic information is crucial for translating GWAS information to the identification of causal genes and pathogenetic (and potentially targetable) cellular and molecular mechanisms of kidney disease.

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Graph pangenomes find missing heritability

The use of association studies to identify candidate genes for complex biological traits in plants has been challenging due to a reliance on single reference genomes, leading to missing heritability. Graphical pangenomes and the identification of causal variants help overcome this and provide an important advance for crop breeding.

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Single-cell analyses define a continuum of cell state and composition changes in the malignant transformation of polyps to colorectal cancer

Single-cell ATAC-seq and RNA-seq profiling traces the transformation of healthy colon to precancerous adenomas to colorectal cancer (CRC). A large proportion of polyp and CRC cells show a stem-like phenotype.

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Epigenomic and transcriptomic analyses define core cell types, genes and targetable mechanisms for kidney disease

Genome-wide analyses identify hundreds of loci associated with kidney function. Integrated analyses of expression, methylation and single-cell open chromatin and expression data derived from human kidney samples prioritize genes and mechanisms underlying renal disease.

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