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Clockwise from top: Rosa gallica ‘Versicolor’ (Rosa Mundi), Mme. Isaac Pereire, Maiden’s Blush, Rosa gallica ‘Officinalis’ (Apothecary’s Rose); center: Baron Girod de l’Ain.
To celebrate the Rosa genomes, we invite you to imagine ways to make rosy data as well loved as the roses themselves. This is an opportunity for data modeling and new discoveries from reanalysis, as well as for data display to feed public interest in the science and culture of flowers.
Roses have held an attraction for people all over the world as ornamental plants. Now genome sequencing of the highly heterozygous Rosa chinensis and resequencing of major genotypes open the door to a greater understanding of rose evolutionary history and the regulatory mechanisms determining rose flower color and scent.
High-quality genome assembly of diploid Rosa chinensis and resequencing of major genotypes highlights the origin of modern rose cultivars and provides insights into color biosynthesis and scent pathways.
A meta-analysis of 139,555 Europeans identifies 68 new genomic loci associated with intraocular pressure. Incorporating these new findings into genetic models improves risk prediction for primary open-angle glaucoma.
Shortening of mRNA 3′ UTRs is often observed in cancer. A combination of model-based analysis and experiments suggests that 3′ UTR shortening disrupts competing endogenous RNA crosstalk, thus influencing tumor-suppressor expression in trans.
Comprehensive fecal metabolic profiling in 786 individuals from TwinsUK provides insights into the influence of host genetics and gut microbial composition on metabolites that may mediate microbiome-associated phenotypes.
The authors report an improved genome assembly of G. arboretum and resequencing of 243 diploid cotton accessions. GWAS and QTL-seq identify a number of candidate loci that associate with seed oil content, disease resistance and yield traits in cotton.
The authors resequence a core collection of upland cotton (Gossypium hirsutum) comprising 419 accessions. They analyze genomic variation and conduct a genome-wide association study for 13 fiber quality and yield traits in 12 different environments.
ARLNC1 is a newly discovered lncRNA that is induced by androgen receptor (AR) and maintains AR signaling by stabilizing the AR transcript. Knockdown of ARLNC1 suppresses AR expression, AR signaling and prostate cancer growth in vitro and in vivo.
Integration of single-cell RNA sequencing with genome-wide association data implicates specific brain cell types in schizophrenia. Gene sets previously associated with schizophrenia implicate the same cell types, which include pyramidal cells and medium spiny neurons.
Transancestral GWAS meta-analysis in 160,420 individuals identifies 139 loci associated with refractive error, including myopia. Newly identified genes implicate pathways involved in eye growth and light signaling cascades.
Genomic analysis of Mycobacterium tuberculosis (Mtb) isolated from tuberculosis patients identifies the transmission dynamics of Mtb in Vietnam including frequent transmission of Beijing lineage and positive selection for EsxW Beijing variant.
Genome-wide cross-trait analysis shows a strong genetic correlation between asthma and allergic diseases. Shared susceptibility loci are enriched for genes involved in immune and inflammatory responses and genes expressed in epithelial tissues.
CLASSY chromatin remodeling factors (CLSY 1–4) are shown to regulate DNA methylation in Arabidopsis, both globally and in a locus-specific manner. CLSYs and RNA polymerase IV control the production of 24-nucleotide siRNAs, which guide DNA methylation.
VAMP-seq is a scalable assay that measures the effects of missense variants on intracellular protein abundance. Applying VAMP-seq to thousands of PTEN and TPMT variants helps to classify them as pathogenic or benign.
This study shows that UTX (KDM6A) suppresses myeloid leukemogenesis through noncatalytic functions. UTX loss leads to alterations in H3K27ac, H3K4me1 and chromatin accessibility, and in gene-regulatory programs mediated by ETS and GATA transcription factors.
This analysis uses computational modeling of clonal selection to measure evolutionary dynamics in primary human cancers. The method employs high-throughput sequencing data and simultaneously measures the selective advantage and time of appearance of subclones.