Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.

Neurofibrillary tangles (NFT) and β-amyloid plaques are the neurological hallmarks of both Alzheimer's disease and an unusual paralytic illness suffered by Chamorro villagers on the Pacific island of Guam. Many Chamorros with the disease suffer dementia, and in some villages one-quarter of the adults perished from the disease. Like Alzheimer's, the causal factors of Guamanian amyotrophic lateral sclerosis/parkinsonism dementia complex (ALS/PDC) are poorly understood. In replicated experiments, we found that chronic dietary exposure to a cyanobacterial toxin present in the traditional Chamorro diet, β-N-methylamino-l-alanine (BMAA), triggers the formation of both NFT and β-amyloid deposits similar in structure and density to those found in brain tissues of Chamorros who died with ALS/PDC. Vervets (Chlorocebus sabaeus) fed for 140 days with BMAA-dosed fruit developed NFT and sparse β-amyloid deposits in the brain. Co-administration of the dietary amino acid l-serine with l-BMAA significantly reduced the density of NFT. These findings indicate that while chronic exposure to the environmental toxin BMAA can trigger neurodegeneration in vulnerable individuals, increasing the amount of l-serine in the diet can reduce the risk.

Single-cell DNA methylome profiling has enabled the study of epigenomic heterogeneity in complex tissues and during cellular reprogramming. However, broader applications of the method have been impeded by the modest quality of sequencing libraries. Here we report snmC-seq2, which provides improved read mapping, reduced artifactual reads, enhanced throughput, as well as increased library complexity and coverage uniformity compared to snmC-seq. snmC-seq2 is an efficient strategy suited for large scale single-cell epigenomic studies.

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Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.