Modeling the 3D Genome Using Hi-C and Nuclear Lamin-Genome Contacts.

The three-dimensional (3D) organization of the genome is shaped by interactions with multiple structures within the nucleus, affecting gene expression outcomes. Technological breakthroughs in recent years have generated vast data reflecting various aspects of nuclear genome architecture in space and time. Integrating these datasets into comprehensive 3D genome models can reveal new insights into genome structure and regulation in normal and disease states. In this chapter, we provide a step-by-step guide on how to generate publication-ready integrated 3D genome models from (raw) Hi-C data and from lamin-genome (LAD) contacts.

A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons.

BACKGROUND: Midbrain dopaminergic neurons (MDN) represent 0.0005% of the brain's neuronal population and mediate cognition, food intake, and metabolism. MDN are also posited to underlay the neurobiological dysfunction of schizophrenia (SCZ), a severe neuropsychiatric disorder that is characterized by psychosis as well as multifactorial medical co-morbidities, including metabolic disease, contributing to markedly increased morbidity and mortality. Paradoxically, however, the genetic risk sequences of psychosis and traits associated with metabolic disease, such as body mass, show very limited overlap. METHODS: We investigated the genomic interaction of SCZ with medical conditions and traits, including body mass index (BMI), by exploring the MDN's "spatial genome," including chromosomal contact landscapes as a critical layer of cell type-specific epigenomic regulation. Low-input Hi-C protocols were applied to 5-10 × 103 dopaminergic and other cell-specific nuclei collected by fluorescence-activated nuclei sorting from the adult human midbrain. RESULTS: The Hi-C-reconstructed MDN spatial genome revealed 11 "Euclidean hot spots" of clustered chromatin domains harboring risk sequences for SCZ and elevated BMI. Inter- and intra-chromosomal contacts interconnecting SCZ and BMI risk sequences showed massive enrichment for brain-specific expression quantitative trait loci (eQTL), with gene ontologies, regulatory motifs and proteomic interactions related to adipogenesis and lipid regulation, dopaminergic neurogenesis and neuronal connectivity, and reward- and addiction-related pathways. CONCLUSIONS: We uncovered shared nuclear topographies of cognitive and metabolic risk variants. More broadly, our PsychENCODE sponsored Hi-C study offers a novel genomic approach for the study of psychiatric and medical co-morbidities constrained by limited overlap of their respective genetic risk architectures on the linear genome.