Genetics Virtual Week 2021

COVID-19 is a severe disease that has caused >1 million deaths in under one year. As this disease is novel, the molecular and cellular underpinnings of the progressive tissue injury are poorly understood, as is the role of direct versus indirect viral-induced injury. This study compared spatially-resolved gene expression in fixed lung tissue from autopsies of COVID-19 patients with high and low viral loads to those who suffered from other respiratory diseases – flu or non-viral acute respiratory distress syndrome (ARDS) – and normal lung tissue. We used the DreamPrep™ NAP workstation to extract RNA and DNA to profile 735 COVID-19 patients. Using normal samples as a reference, there was an enrichment of genes involved in antigen presentation and interferon response in high and low viral load patients. Between COVID-19 cohorts, there was an overall upregulation of individual interferon-stimulating genes in COVID-high patients, and an increase in collagen genes found in COVID-low patients. Pathway analysis revealed enrichment in interferon alpha/beta and gamma signaling in COVID-19 samples compared to normal, and this enrichment scaled with viral load. COVID-high patients showed enrichment in these pathways compared to flu and ARDS patients, while COVID-low patients had enrichment of collagen-related pathways compared to flu and ARDS.

NanoCellect will discuss the importance of cell sample preparation in order to obtain good quality sequencing data with 3’ RNA-Seq as well as cell sample preparation in order to obtain optimal sequencing results for 10x Genomics applications. We will review:

• The challenges in obtaining high quality data for Single-Cell 3’RNA-seq and single cell genomic applications

• Why low-pressure cell sorting can help preserve cell viability and reduce background noise in    sequencing results

• How cell sorting can dramatically improve the quality of your sequencing results. We will highlight an example for PBMCs and iPSCs

Learning Objectives:

1. The challenges in obtaining high quality data for Single-Cell 3’RNA-seq and single cell genomic applications

2. Why low-pressure cell sorting can help preserve cell viability and reduce background noise in sequencing results

3. How cell sorting can dramatically improve the quality of your sequencing results. We will highlight an example for PBMCs and iPSCs

Structural variants (SVs) are essential in human evolution and genetic disease but remain understudied. This is especially the case for non-Caucasian ethnicities. We report, for the first time, a comprehensive study of SVs across the genomes of 499 Han Chinese, the largest ethnicity group, using ~15x Oxford Nanopore technology. We identify a total of 81,752 SVs, of which 46.86% are novel when compared to the SV calls in the dbVar and many can be successfully genotyped in short read data. Using these we were able to identify and compare Han Chinese specific SV hotspots across the genome and identified novel sequences that can be place in the human genome.  We found that SV hotspots not only affected the well-known amylase locus, but also seven carbohydrate metabolic processes in the Han Chinese genomes. Further, we uncovered 355 unreported natural knockout genes in the Han Chinese genomes. These data provide the first sequence map of structural variation map of Han Chinese and are a valuable resource for both the population genetics and medical communities.

Learning Objectives:

1. Attendees will learn about variability and complexity of SV across the Han Chinese population and its implication on phenotypes

2. Attendees will learn about what we are missing on GRCH38/37 and why ethnicity specific reference/ pan genomes are necessary

3. We will review approaches and sequencing technologies to scale up the study of hundreds to thousands of long read genomes

Recently, long-read sequencing with high accuracy has become a reality. Previous technologies allowed for the detection of particular classes of genetic variation and/or have focused on pre-defined regions of the genome. De novo assembly of an individual’s complete genome has also been difficult and time-intensive with the drastically shorter reads that have been the standard in our field. Long-read sequencing is a ground-breaking advance that enables us to perform analyses to assemble genomes within one day and to detect nearly all forms of variation in one single technology. In this talk, I will discuss the application of Pacific Biosciences (PacBio) HiFi long-read sequencing to human genetics. First, I will describe our analysis workflow for long-read sequencing that includes de novo assembly and mapping-based strategies to detect variation in a single individual. Second, I will detail the utility of public long-read sequencing data for filtering of variation detected within individuals. This approach helps narrow into relevant rare variation within an individual and is necessary for variation not detected by previous technologies. Third, I will discuss the benefit of long-read sequencing for phasing of variation regarding detection of compound heterozygous variants. Finally, I will show examples of our utilization of long-read sequencing to understand complex structural variation in individuals we have assessed in our lab. Overall, my talk will introduce the concept of long-read sequencing and its application in human genetics.

Learning Objectives:

1. Understand the concept of long-read sequencing

2. Learn applications of long-read sequencing to human genetics

Traumatic brain injury (TBI) is best characterized as brain dysfunction caused by an outside force, usually a violent blow to the head, often occurring as a result of a severe sports injury or car accident. It is a major global health concern, affecting 69 million people worldwide per year, and is one of the most common causes of disability and death in adults. Nearly 50% of TBI patients experience long term cognitive impairment, linked to hippocampal neuronal damage and death. At the same time a deregulation of the hippocampal neurogenic processes is observed which impedes possible functional recovery of the brain. In particular, immunohistochemistry in mouse hippocampus has shown that cortical TBI affects neural stem and progenitor cells (NSPCs) residing in sub-granular zone of dendrite gyrus. Moreover, severe changes in the states of astrocytes, cells regulating axonal growth and synaptogenesis, has been observed throughout hippocampus. Here, in a collaborative project between VIB-KU Leuven, University of Amsterdam and the Bioinformatics CRO, we explore the cellular response in hippocampus following cortical TBI, exploiting cutting edge single cell RNA sequencing (10X Genomics) and highly multiplexed in situ hybridization (Resolve Biosciences) technologies. We systematically assess the sensitivity of NSPCs, immature astrocytes and immature neurons located in the sub-granular layer of dentate gyrus to TBI-induced pathology at the molecular level. We further characterize molecular changes within the hippocampus and the surrounding tissue, providing a spatial map of gene expression changes with single cell resolution.

Learning Objectives:

1. Single cell and spatial transcriptomics to investigate cell type heterogeneity at the highest resolution.

2. The impact of cortical traumatic brain injury on hippocampus and the surrounding tissue.

3. Effects of traumatic brain injury on neural stem and progenitor cells.

Somatic mutations that arise during development are increasingly recognized as contributors to neurodevelopmental disease. One challenge has been to determine how mosaic mutations contribute to cell lineages and affect the function of individual cells, which could have implications for disease manifestation. We integrated high-throughput single-cell 3’-RNA-sequencing with targeted Iso-Seq long-read RNA sequencing on the PacBio Sequel II platform to overlay single-cell genotype with cell-type and gene expression analyses. We applied this strategy to study the contribution of somatic mutations to developmental brain malformations in surgically-resected patient brain tissue.

Learning objectives:

1. Understand how long-read sequencing can be useful for haplotype phasing of variants.

2. Understand how long-read sequencing can be integrated with single-cell 3’-RNA-sequencing.

The ability of single-cell RNA-Seq (scRNA-Seq) to measure the transcriptional basis of heterogeneity between individual cells is transforming biomedical research. It enables the precise ‘molecular dissection’ of the multiple cell types present within a complex tissue. This makes it possible to determine how a pathology affects each cell type, rather than just the overall effect upon the bulk tissue. As the technology matures and the range and scope of analytical tools expands, ever greater insights into cellular characteristics and their relationships to one another are becoming possible. However, each biological system presents unique challenges and customised experimental design and analyses are required. In this presentation I will outline recent and ongoing projects from my lab and collaborators which are applying scRNA-Seq to investigate the basis of the major eye diseases Diabetic Retinopathy, Age-related Macular Degeneration and Glaucoma. This work employs both in vivo models of the retina and in vitro cell culture systems with retinal endothelial, retinal pigment epithelial and lamina cribrosa cells. The results from a range of analytical approaches will be described, with examples chosen to help others maximise the pertinent information gained from their own experiments.

Learning Objectives:

1. Evaluate the potential of alternative technical and analytical single cell RNA-Seq approaches to provide relevant biological insights into a given model system.

2. Provide examples of how single cell RNA-Seq is being applied in vision science to understand the basis of eye diseases.

The recent explosion in the sample sizes and diversity of omics assays has created exciting new opportunities for biomedical scientists. However, connecting these omics data types in an interpretable way remains a challenge, especially when the data come from different sources and cohorts. One approach to this problem is to build regulatory networks that reflect the support of the data. In this talk, I will discuss a new method for estimating the effects of germline genetic variants on transcription factor (TF) regulatory events. This method, EGRET, integrates an individual's genotype with regulatory data to produce an individual-specific regulatory network. When we applied EGRET to RNA-seq and genotype data collected from 119 individuals in three cell types, we find TF regulatory disruptions that are disease-specific and occur only in the cell type relevant to the disease. Together this suggests that EGRET provides valuable insight into regulatory processes influencing disease.

Learning Objectives:

1. Describe the effect size distribution and typical genomic locations of GWAS variants

2. Explain which data types the EGRET method uses as input

In mammals, DNA methylation is an epigenetic mark that regulates gene expression by serving as a maintainable mark whose absence marks promoters and enhancers. Recent epidemiological studies demonstrate that DNA methylation levels are associated with aspects of biological aging in humans. We present universal mammalian epigenetic clocks that lend themselves for measuring age across mammalian species. We demonstrate that DNA methylation levels are strongly associated with maximum lifespan. These epigenetic clocks are expected to be useful for in vitro studies, animals models, and ultimately human clinical trials.

Learning Objectives:

1. Define the concept of an epigenetic clock

2. Review evidence that epigenetic clocks are indicators of epigenetic age in mammals

3. Explain what is meant by universal mammalian clock

Biological systems are comprised of numerous cell types, intricately organized to form functional tissues and organs. Cell atlas initiatives with single-cell RNA sequencing have begun to characterize cell types based on their RNA expression profiles. However, the tissue organization is lost when cells are dissociated for single-cell sequencing, making it difficult to study how the cellular heterogeneity is contributing to the function of the tissue. Multiplexed error robust in situ hybridization (MERFISH) technology  enables the direct profiling of the spatial organization of intact tissue with genomic-scale throughput. Through combinatorial labeling, sequential imaging, and error-robust barcoding, MERFISH technology provides the highest detection efficiency and resolution available for spatial genomics. In a single experiment, hundreds of thousands of cells can be spatially profiled with subcellular resolution with high accuracy and reproducibility. In this presentation, we used the technology to profile gene expression in situ across large tissue areas in mouse brain and human colon cancer, discover and map cell types in complex tissue in response to external stimuli in animal models, and analyze the intracellular organization of transcriptome with sub-cellular resolution in individual cells.

Learning Objectives:

1. Learn about the benefits of spatially resolved, single-cell transcriptomics for further characterizing cell types based on their RNA expression profiles.

2. Learn about different research applications of MERFISH technology for the direct profiling of the spatial organization of intact tissues with genome-scale throughput.

Alternative RNA isoforms are defined by promoter choice, alternative splicing, and polyA site selection. Although differential isoform expression is known to play a large regulatory role in eukaryotes, it has proved challenging to study with standard short-read RNA-seq because of uncertainties it leaves about the full-length structure and precise termini of transcripts. The rise in throughput and quality of long-read sequencing now offers the possibility to unambiguously identify most transcript isoforms from beginning to end. However, the application of long-read sequencing to single-cell RNA-seq in particular remains limited by low throughput and high expense. Here, we develop and characterize long-read Split-seq (LR-Split-seq), which utilizes a combinatorial barcoding-based method for sequencing single cells and nuclei with long reads. We demonstrate that LR-Split-seq can associate isoforms to cell types with relative economy. We characterize LR-Split-seq for whole cells and nuclei by using the well-studied mouse C2C12 system in which mononucleated myoblast cells differentiate and fuse into multinucleated myotubes. We show that the overall results are consistent with existing knowledge of the system and are reproducible when comparing long- and short-read data from the same cell or nuclear samples. We find substantial evidence of differential isoform expression during differentiation including alternative transcription start site (TSS) usage. Moreover, we validate our known and novel isoforms by integration of isoform expression dynamics with snATAC-seq chromatin accessibility at their TSSs. LR-Split-seq provides an affordable method for identifying cluster-specific isoforms in single cells that can be matched to short-read sequencing of an expanded pool of the same cells as well as integrated with additional single-cell omics data modalities.

Learning Objectives:

1. Demonstrate the utility of long-read RNA-sequencing in studying alternative isoforms

2. Define the long-Split-seq approach to profiling the transcriptomes of single-cells

Precise diagnosis of neurodevelopmental disorders (NDDs), which often have genetic causes, is a challenging and important problem.  Here we describe the results of a recent pilot study using PacBio CCS sequencing reads, which are both long and accurate the basepair level, to analyze 6 proband-parent trios affected by an NDD that remains undiagnosed after extensive testing, including short-read genome sequencing.  Our results suggest that long-read genomes may reveal biologically and clinically relevant information in many families affected by unexplained NDDs.

Learning Objectives:

1. Understand the role of genome sequencing for neurodevelopmental disorder diagnosis

2. Define the types of genetic variation that can be uncovered more effectively by long reads than short reads

Microbial communities include distinct lineages of closely related organisms which have proved challenging to separate in metagenomic assembly. Challenges include the existence of highly related organisms that exist the same environment, or several species that exist at very low abundances and are therefore inconsistently sampled. Many of these challenges are exacerbated by limitations in DNA sequencing technologies, where some platforms produce reads that are too short or reads that have too many errors. The advent of long, accurate “HiFi” reads presents a possible means to address the challenge of metagenome assembly by disambiguating individual reads or contigs within metagenomic bins.  We present a metagenomic assembly of a complex microbial community from parasite-infested sheep fecal material.  We found that assemblies made from HiFi reads were able to properly assemble low abundance species in our sample, and could often assemble microbial genomes into single, circular contigs.  Taking advantage of the low error rates of HiFi reads, we developed a method that can track linked single nucleotide polymorphisms (SNPs), which is termed “phasing,” and identify individual SNP haplotypes that indicate subpopulations of microbes in a sample. This method is sensitive and scalable, and was able to phase haplotypes as long as 309 SNPs across hundreds of thousands of bases in the microbial genome.  We also report successful characterization of multiple, closely-related microbes within a sample with potential to improve precision in assigning mobile genetic elements to candidate host genomes within complex microbial communities.

Learning Objectives:

1. Identify the challenges of metagenome assembly

2. Quantify the benefits of low error rate long reads on metagenome sequencing and assembly

3. Understand concepts such as “phasing” and “haplotyping” as it relates to metagenome assembly

Nanopore sequencing has enormous potential in epigenetic applications; unlike traditional sequencing-by-synthesis technologies, it can distinguish covalently modified nucleotides directly through their modulation of the electrolytic current. We can take advantage of the long read lengths generated by nanopore sequencing to precisely call methylation patterns, and to obtain phased methylation information across the genome. The promise of nanopore sequencing has already been demonstrated by the accurate calling of 5-methylcytosine in a CG context using hidden Markov models (nanopolish) and neural networks (Megalodon). We have now trained our models on other modified (non-canonical) nucleotides, focussing here on dam-mediated adenosine methylation (N6-mA). Methylated adenosine sequencing has applications in bacterial epigenetics as well as exogenous labeling in mammalian systems. In particular, the DamID method uses a dam enzyme fused to a protein of interest, e.g. nuclear lamina, resulting in labeling DNA proximal to the protein. We are able to detect this N6-mA modification simultaneously with 5mC, providing two distinct epigenetic signatures along long single DNA molecules. We applied this to mammalian cells treated by DamID to characterize lamin-associated domains (LADs). LADs showed on average significantly higher methylation profiles than other regions in our pipeline. Applying this model we can simultaneously measure phased nuclear positioning information (LADs) with DNA cytosine methylation (5-mC) using long reads. With this method, we have explored CTCF binding sites and CpG islands on the border of LADs to investigate their mechanism.

Learning Objectives:

1. Base modification detection using nanopore sequencing

2. Simultaneous profiling of DNA methylation and lamina-associated domains

Traditional genomics approaches look at bulk signatures from often heterogeneous samples or tissues. These approaches do not have the requisite resolution to fully uncover the true complexity of biology. Single cell and spatial transcriptomics approaches provide the ability to build a more comprehensive multidimensional understanding of complex biological systems. In order to fully utilize such technologies, there are several key experimental design and sample preparation considerations that when followed will help lead to success.  Both single cell and spatial transcriptomics provide high resolution views, and we will discuss how combining both of these technologies work synergistically to uncover an even greater understanding.

Learning Obejctives:

1. Understand the key requirements for sample preparation in a single cell and/or spatial transcriptomics experiment

2. Learn the synergies between a combined single cell and spatial transcriptomics approach

Telomere length (TL) is widely considered a molecular/cellular hallmark of the aging process with implications for multiple diseases. While there has been success in epidemiology and genomewide association studies (GWAS) to understanding telomere biology and genetics, there is a gross under-representation of minority and admixed populations in these efforts, limiting our understanding of health disparities pertaining to diseases related to aging, inflammation, and cellular senescence that are related to TL. High throughput technologies with decreasing sequencing cost per sample has enabled the generation of whole genome sequencing (WGS) at an unprecedented scale with large, well-phenotyped resources of subjects having WGS in epidemiology, precision medicine and biobank endeavors nationally and internationally. With large and well-powered sample sizes, multi-ethnic representation, and WGS data, we have an unprecedented opportunity address critical gaps in TL genetics through NHLBI's Trans-Omics for Precision Medicine (TOPMed) Program on heart, lung, blood, and sleep disorders. Similar to the novel gains in focusing on this ‘functionally relevant’ part of the dynamic human genome, is the added value of calling clonal hematopoiesis from the same genomes, and exploring relationships between the two. This talk will focus on the opportunities from of out-of-the-box and non-traditional approaches to leveraging pre-existing data and the opportunities at scale from large multi-ethnic resources such as TOPMed to bridge major gaps with health disparities research within a Precision Medicine framework.

Learning objectives:

1. Calling variation corresponding to the dynamic genome - CHIP and telomere length

2. The importance of multi-ethnic representation in large Precision Medicine Efforts

Sex and gender differences are apparent in health and disease and aduring aging. Chronic obstructive pulmonary disease is a leading cause of death with pronounced sex and gender differences associated with disease susceptibility and severity. Studying genetics and (epi)genomics will allow the development of holistic approaches to modeling the molecular differences that may be further exacerbated for COPD as a disease of accelerated aging. The hope is that big data and sex and gender aware systems and network medicine approaches will inform innovations for diagnostic, therapeutic and preventative approaches to COPD as a disease of aging.

Learning Objectives:

1. Overview associations with sex/ gender and lung disease

2. Note a role for the (epi)genome in sex differeneccs in the lung

3. Propose a role for Networks to integrate sex and gender differences in understanding COPD

Most human protein-coding genes are regulated by multiple, distinct promoters, suggesting that the choice of promoter is as important as its level of transcriptional activity. While the role of promoters as driver elements in cancer has been recognized, the contribution of alternative promoters to regulation of the cancer transcriptome remains largely unexplored. Here I will present how active promoters can be identified using RNA-Seq data, enabling the analysis of promoter activity in more than 18,000 samples. In order to study novel promoters, we generated long read RNA-Seq data in 10 different gastric cancer cell lines. Our results show that alternative promoters are frequently used, that they are predictive of patient survival, and that promoters are a major contribution to the diversity of isoforms in cancer.

Learning Objectives:

1. Learn about alternative promoters and their role in cancer

2. Learn how long read RNA-Seq helps to study the transcriptome

We are entering into an exciting era of genomics where truly complete, high-quality assemblies of human chromosomes are available end-to-end, or from ‘telomere-to-telomere’ (T2T). Recently, the Telomere-to-Telomere (T2T) consortium announced our v1.0 assembly that includes more than 150 Mbp of novel sequence compared to GRCh38, achieves near-perfect sequence accuracy, and unlocks the most complex regions of the genome to functional study. This technological advance, crediting the confluence of new assembly methods with long read sequencing technologies, offers a new opportunity to comprehensively the genomic structure and epigenetic organization in the most repeat-dense regions of our chromosomes. In particular, I will focus on the release of initial genetic and epigenetic reference of all human centromeric regions. High-resolution study of the pericentromeric sequence content and organization reveals new satellite families, sites of transposable element insertion, segmental duplications, and pericentromeric gene predictions. Using unique markers (marker-assisted method) to anchor ultra-long nanopore reads to human centromeric regions regions we report hypomethylated dips at every centromeric region, as previously described for the T2TX centromere. These sites are shown to coincide with regions enriched in centromere protein A (CENP-A) and may provide a signature of sites of kinetochore assembly genome-wide.

Learning objectives:

1. Understand the incomplete nature of the human reference genome, which sequences are missing and how that impacts our understanding for basic/translational research

2. Explain the differences in long read technologies in repeat assembly

3. Describe sequences and epigenetic patterns that are in the part of our genome that are not represented in current reference maps (e.g. GRCh38).

The complete assembly of each human chromosome is essential for understanding human biology and evolution. Using complementary long-read sequencing technologies, we complete the first linear assembly of a human autosome, chromosome 8. Our assembly resolves the sequence of five previously long-standing gaps, including a 2.08 Mbp centromeric α-satellite array, a 644 kbp β-defensin copy number polymorphism important for disease risk, and an 863 kbp variable number tandem repeat at chromosome 8q21.2 that can function as a neocentromere. We show that the centromeric α-satellite array is generally methylated except for a 73 kbp hypomethylated region of diverse higher-order α-satellite enriched with CENP-A nucleosomes, consistent with the location of the kinetochore. Additionally, we confirm the overall organization and methylation pattern of the centromere in a diploid human genome. Using a dual long-read sequencing approach, we complete high-quality draft assemblies of the orthologous chromosome 8 centromeric regions in chimpanzee, orangutan, and macaque for the first time to reconstruct its evolutionary history. Comparative and phylogenetic analyses show that the higher-order α-satellite structure evolved specifically in the great ape ancestor, and the centromeric region evolved with a layered symmetry, with more ancient higher-order repeats located at the periphery adjacent to monomeric α-satellites. Additionally, sequence and assembly of two other primate centromeres confirms the overall organization and evolution of these regions. We estimate that the mutation rate of centromeric satellite DNA is accelerated at least 2.2-fold, and this acceleration extends beyond the higher-order α-satellite into the flanking sequence.

Learning Objectives:

1. Explain why centromeres, segmental duplications, and other repeat-rich regions of the human genome have been historically challenging to resolve

2. Identify recent advances in long-read DNA sequencing technology and assembly algorithms that are now allowing scientists to accurately assemble complex regions of the genome

3. Describe genetic and epigenetic features of newly resolved regions in chromosome 8 and how the chromosome 8 centromere has evolved over the last 25 million years

The Genome in a Bottle Consortium has published benchmarks for variant calling, but some challenging medically-relevant genes have been partially or fully excluded due to mapping challenges, structural variation, and issues in the reference genomes. Here, we use a trio-based, long-read, phased diploid assembly to form phased small variant and structural variant benchmarks for 273 out of 396 autosomal genes covered <90% by mapping-based benchmarks. We curated >1000 variants to exclude errors in the assembly, mostly in homopolymers and highly homozygous regions, and to ensure the benchmark accurately identifies false positives and false negatives across call sets. The new benchmark for challenging medically relevant genes will improve the characterization of challenging variants, leading to better insights for clinical genomics in the near future.

Learning Objectives:

1. Learn about applications of long read sequencing technologies for variant detection in medical genes

2. Clarify use of Genome in a Bottle benchmarks and how a medical gene focused benchmark improves clinical application

Many diseases show sex differences in incidence or progression, suggesting that one sex has inherent biological factors that protect from or exacerbate disease. Historically the root causes of all sex differences in tissue phenotypes were thought to be the gonadal hormones. The advent of specialized mouse models has uncovered non-hormonal origins of sex bias in disease, caused by inherent inequality of XX vs. XY sex chromosomes. For example, the Four Core Genotypes and XY* models allow the investigator to compare mice with different sex chromosomes, but with the same type of gonad. Use of these mouse lines in several models of disease has now progressed far enough that specific X or Y genes have been identified that give rise to molecular cascades causing sex differences in disease. The number of X chromosomes, one vs. two, causes sex differences in models of metabolism and adiposity, of autoimmune disease, of Alzheimer’s disease, and bladder cancer. The underlying genes that cause the X chromosome effects are X-linked Kdm5c and Kdm6a, two lysine demethylases acting on H3K4 to activate or reduce gene expression elsewhere in the genome. The genes escape X inactivation and are expressed from all X chromosomes, so that XX cells express a higher dose than XY cells. This inherent inequality influences diverse tissues and diseases. Just as the discovery of gonadal hormonal sex-biasing factors, such as testosterone and estradiol, catalyzed waves of discovery of downstream mechanisms leading to sexual dimorphism in many tissues, we now expect the discovery of new sex chromosomal sex-biasing factors to lead to new research on novel pathways causing sex differences in diverse tissues related to numerous diseases. Supported by NIH grants OD026560, HD100298, HD076125, DK083561, HL1311820

Learning Objectives:

1. Understand mouse models that test inherent sex differences in X and Y gene dose that cause sex differences in disease.

2. Appreciate new evidence about specific X genes that are the origins of sex bias in the genome.