Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × ∼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Thlaspi arvense (field pennycress) is being domesticated as a winter annual oilseed crop capable of improving ecosystems and intensifying agricultural productivity without increasing land use. It is a selfing diploid with a short life cycle and is amenable to genetic manipulations, making it an accessible field-based model species for genetics and epigenetics. The availability of a high-quality reference genome is vital for understanding pennycress physiology and for clarifying its evolutionary history within the Brassicaceae. Here, we present a chromosome-level genome assembly of var. MN106-Ref with improved gene annotation and use it to investigate gene structure differences between two accessions (MN108 and Spring32-10) that are highly amenable to genetic transformation. We describe non-coding RNAs, pseudogenes and transposable elements, and highlight tissue-specific expression and methylation patterns. Resequencing of forty wild accessions provided insights into genome-wide genetic variation, and QTL regions were identified for a seedling colour phenotype. Altogether, these data will serve as a tool for pennycress improvement in general and for translational research across the Brassicaceae.

Combining integrative genomics and systems biology approaches has revealed new and conserved features in the genome of human herpesvirus 6.

Human herpesvirus-6 (HHV-6) A and B are ubiquitous betaherpesviruses, infecting the majority of the human population. They encompass large genomes and our understanding of their protein coding potential is far from complete. Here, we employ ribosome-profiling and systematic transcript-analysis to experimentally define HHV-6 translation products. We identify hundreds of new open reading frames (ORFs), including upstream ORFs (uORFs) and internal ORFs (iORFs), generating a complete unbiased atlas of HHV-6 proteome. By integrating systematic data from the prototypic betaherpesvirus, human cytomegalovirus, we uncover numerous uORFs and iORFs conserved across betaherpesviruses and we show uORFs are enriched in late viral genes. We identified three highly abundant HHV-6 encoded long non-coding RNAs, one of which generates a non-polyadenylated stable intron appearing to be a conserved feature of betaherpesviruses. Overall, our work reveals the complexity of HHV-6 genomes and highlights novel features conserved between betaherpesviruses, providing a rich resource for future functional studies.

Genome annotation remains a fundamental effort in modern biology. With reducing costs and new forms of sequencing technologies, annotations specific to tissue type and experimental conditions are continually being generated (e.g., histone methylation marks). Computing the statistical significance of overlap between two different annotations is key to many biological findings but has not been systematically addressed previously. We formalize the problem as follows: let I and If each describe a collection of n and m intervals of a genome with particular annotation. Under the null hypothesis that genomic intervals in I are randomly arranged with respect to If, what is the significance of k of m intervals of If intersecting with intervals in I? We describe a tool iSTAT that implements a combinatorial algorithm to accurately compute p values. We applied iSTAT to simulated and real datasets to obtain precise estimates and contrasted them against previous results using permutation or parametric tests.