ABSTRACT. The past 5 years have borne witness to significant discoveries of common genetic variants that underlie the heritable component of alcohol, tobacco, cannabis and opioid use and use disorder. In addition to identifying new variants, genes and pathways, human genome-wide association studies (hGWAS) have also highlighted key distinctions between substance use and use disorder, especially with respect to their comorbidity with physical and mental health, and brought attention to the role of a common and specific genetic architecture underlying various substances. This presentation will provide an overview of current findings from hGWAS of substance use disorders, support for a common genetic liability, and distinctions from substance use patterns. As we fine tune genetic signals for substance use disorders, opportunities to weave connections from genes to brain and behavior are rapidly emerging. The presentation will therefore also highlight efforts to link polygenic addiction liability to brain imaging data and the contribution of such research to the debate surrounding the causal and neurotoxic effects of drugs versus shared predispositional pathways.

Arpana Agrawal 1Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110, USA

Funding Support: National Institutes of Health; R01DA54869, K02DA32573

ABSTRACT. The teleost medaka (Oryzias latipes) is a well-established vertebrate model system, with a long history of genetic research, a high tolerance to inbreeding, and multiple high-quality reference genomes available for several inbred strains. We Oxford Nanopore Technologies (ONT) long read sequencing to investigate the genomic and epigenomic landscapes of 12 lines from the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel. Nanopore sequencing allows us to identify a large variety of high-quality structural variants, and to explore the use of a pan-genome graph representations. This graph-based reference MIKK panel genome reveals novel differences between the MIKK panel lines and standard linear reference genomes We present a detailed analysis of the MIKK panel genomes using long and short read sequence technologies, creating a MIKK panel-specific pan genome reference dataset allowing for investigation of novel variation types that would be elusive using standard approaches. Additionally, we investigate line-specific CpG methylation by performing differential DNA methylation analysis across these 12 inbred lines.

Tomas Fitzgerald European Molecular Biology Laboratory, DE

ABSTRACT. Differences in transcript structure (i.e., alternative splicing and transcription start and stop sites) can have a significant impact on the translated protein and RNA stability/localization. To obtain a better rat transcriptome, we used long read single molecule RNA sequencing (Iso-Seq), which provides insight into potential splicing and initiation/termination sites. We have collected Iso-Seq data from brain and liver of 4 inbred rat strains from the Hybrid Rat Diversity Panel and combined this information with deep short read RNA-Seq data from these same strains. The Iso-Seq data produced almost 140,000 unique transcripts that aligned to the RN6 version of the genome with 83% possessing an open reading frame. Very few (<4%) matched an annotated Ensembl transcript perfectly (same splice junctions and start/stop sites within 100 base pairs of annotation) but the majority (>68%) of Iso-Seq transcripts included at least one annotated splice junction, i.e., most transcripts are variants of Ensembl annotated genes. Short-read RNA-Seq data was aligned to the Iso-Seq transcriptome for quantifying RNA expression. Not only did the alignment rate significantly improve compared to the protein-coding Ensembl transcriptome, but we could further distinguish ‘high-quality’ transcripts based on stringent criteria related to expression above background and heritability of expression levels. The vast majority of these ‘high-quality’ transcripts were novel transcripts of annotated genes. Iso-Seq provides an improved scaffold to quantitate RNA expression levels of individual transcripts in our deep short-read RNA-Seq databases and allows for further detail regarding the role of splicing in systems genetics analyses of complex traits.

Samuel Rosean1, Harry Smith1, Spencer Mahaffey1, Paula Hoffman1,2, Boris Tabakoff1, Laura Saba1

1Department of Pharmaceutical Sciences, 2Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA

Funding Support: NIAAA R24 AA013162, NIDA P30 DA044223

ABSTRACT. Standard methods in genomics relate genomes to a single common reference sequence. Our understanding of sequence evolution and variation can be distorted by reference bias---wherein genomes appear more similar to the reference than they actually are, and variation that is distinct from the reference is ignored. We have pioneered the development of pangenome variation graphs that allow for the simultaneous relationship of many genomes in the same data structure. Variation graphs are an attempt to resolve a fundamental theoretical problem in bioinformatics: how to compare many genomes to each other in a single alignment model that represents all possible kinds of variation. Methods based on this model will not be reference biased, and will allow us to simulatenously consider all kinds of variation, from SNPs to SVs to translocations.

To demonstrate the power of this approach, we present results from the human pangenome reference consortium (HPRC) year 1 freeze. This 90-haplotype human pangenome represents the first large pangenome for a model species. By applying the PanGenome Graph Builder (PGGB) to these haplotype-resolved assemblies, we obtain a unified variation graph model that allows us to untangle complex patterns of variation at diverse medically-relevant loci. Our approach presents a way forward for understanding variation in large collections of whole genome assemblies.

Erik Garrison University of Tennessee Health Science Center

ABSTRACT. The mouse reference genome of the C57BL/6J strain has been the cornerstone for mouse genetics and genomics for over twenty years. It enabled genetic screens in mice to be performed on an unprecedented scale, it facilitated the task of creating a complete set of null alleles for all genes, and it accelerated the discovery of mouse sequence diversity. However modern laboratory mouse strains are derived from three primary subspecies and used to model hundreds of human diseases, study genetic contributions of complex traits, and offer a unique system to study the evolution of haplotypes. In recent years, genome-wide variation catalogs (single nucleotide polymorphisms (SNPs), short indels, and structural variation) for 52 laboratory mouse strains were generated. However, reliance on mapping sequencing reads to C57BL/6J has meant that the true extent of strain-specific haplotype variation is largely unknown. At some loci, the genetic difference between the reference and sequenced strain genomes is comparable to that between humans and chimpanzees, making it hard to distinguish whether a read is mismapped or forms part of a highly divergent haplotype. In 2018, we reported the first draft de novo genome assemblies for 16 widely used inbred mouse strains and identified and characterised 2,567 regions on the current mouse reference genome exhibiting the greatest sequence diversity. These regions are enriched for genes involved in pathogen defence and immunity and exhibit enrichment of transposable elements and signatures of recent retrotransposition events. For a selected number of loci, we were able to observe combinations of alleles and genes unique to an individual strain, reflecting distinct strain phenotypes. However our efforts were hampered by the draft quality of the genomes. We are now completing long read based reference quality genomes for 17 strains, which will enable us to examine the true extent of mouse haplotype diversity. These genomes will address a major limitation in non-B6J mouse genetics studies, enabling researchers to choose the most appropriate mouse reference genome (or set of) for their studies.

Thomas M. Keane1, Mohab Helmy1, Anu Shivalikanjli1, David J. Adams2, Elizabeth Anderson2

1European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK, 2Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, U

ABSTRACT. Small neuronal subpopulations, and even individual neurons, can have profound effects on behavior. In order to manipulate small, specific subpopulations of neurons, we need better tools that allow for highly precise interventions. To determine whether it is possible to generate such novel and precise tools in a targeted fashion, as opposed to screening through vast libraries of randomly expressed reporter transgenes, we have applied ATAC-seq to determine accessible chromatin from all neurons in the fly head. Comparing accessible DNA regions from neurons to accessible DNA from the rest of the body revealed many neuron-enriched accessible DNA regions/peaks. We cloned 11 of these peaks and generated transgenic animals where the peak DNA drives reporter gene expression. Peaks more accessible in body tissue drive expression preferentially in the body and occasionally in very few neurons. Peak-transgenes more accessible in neurons resulted in preferentially neuronal expression, albeit in distinct sets of neurons from one peak-transgene to the next. One such peak-transgene, 3R579, is expressed in ~250 central brain neurons, and activating 3R579 neurons results in a significant delay in sleep latency. To determine whether we can refine the behaviorally-relevant neurons targeted by 3R579 expression, we performed a second round of ATAC seq from 3R579 neurons specifically and determined the accessible chromatin in 3R579 neurons vs. all neurons. Seven DNA regions, 2°peaks, were more accessible in 3R579 neurons and were cloned in front of FLP recombinase. Genetically intersecting 3R579 neurons AND 2°peak-FLP neurons resulted in expression in specific subsets of 3R579 neurons that were distinct between the 7 2°peak-FLP lines. Furthermore, only two out of seven 3R579 AND 2°peak-FLP combinations showed a sleep latency phenotype, suggesting that this iterative ATAC-seq approach allows for data-driven homing in on behaviorally-relevant neuronal subpopulations. Our approach is translatable to any set of neurons, tissues, and species and could be widely applied to determine subsets of functionally relevant cell populations.

Collin B. Merrill1, Iris Titos2, Alejandro M. Pabon2, Austin B. Montgomery2, Aylin R. Rodan2,3,4, and Adrian Rothenfluh1,3,4,5

1 Department of Psychiatry, Huntsman Mental Health Institute, 2 Molecular Medicine Program, 3 Division of Nephrology, Department of Internal Medicine, 4 Department of Human Genetics, 5 Department of Neurobiology, University of Utah, Salt Lake City, UT 84112, USA.