Archaic Introgression Shaped Human Circadian Traits.

When the ancestors of modern Eurasians migrated out of Africa and interbred with Eurasian archaic hominins, namely, Neanderthals and Denisovans, DNA of archaic ancestry integrated into the genomes of anatomically modern humans. This process potentially accelerated adaptation to Eurasian environmental factors, including reduced ultraviolet radiation and increased variation in seasonal dynamics. However, whether these groups differed substantially in circadian biology and whether archaic introgression adaptively contributed to human chronotypes remain unknown. Here, we traced the evolution of chronotype based on genomes from archaic hominins and present-day humans. First, we inferred differences in circadian gene sequences, splicing, and regulation between archaic hominins and modern humans. We identified 28 circadian genes containing variants with potential to alter splicing in archaics (e.g., CLOCK, PER2, RORB, and RORC) and 16 circadian genes likely divergently regulated between present-day humans and archaic hominins, including RORA. These differences suggest the potential for introgression to modify circadian gene expression. Testing this hypothesis, we found that introgressed variants are enriched among expression quantitative trait loci for circadian genes. Supporting the functional relevance of these regulatory effects, we found that many introgressed alleles have associations with chronotype. Strikingly, the strongest introgressed effects on chronotype increase morningness, consistent with adaptations to high latitude in other species. Finally, we identified several circadian loci with evidence of adaptive introgression or latitudinal clines in allele frequency. These findings identify differences in circadian gene regulation between modern humans and archaic hominins and support the contribution of introgression via coordinated effects on variation in human chronotype.

Sequence-based machine learning reveals 3D genome differences between bonobos and chimpanzees.

Phenotypic divergence between closely related species, including bonobos and chimpanzees (genus Pan), is largely driven by variation in gene regulation. The 3D structure of the genome mediates gene expression; however, genome folding differences in Pan are not well understood. Here, we apply machine learning to predict genome-wide 3D genome contact maps from DNA sequence for 56 bonobos and chimpanzees, encompassing all five extant lineages. We use a pairwise approach to estimate 3D divergence between individuals from the resulting contact maps in 4,420 1 Mb genomic windows. While most pairs were similar, ∼17% were predicted to be substantially divergent in genome folding. The most dissimilar maps were largely driven by single individuals with rare variants that produce unique 3D genome folding in a region. We also identified 89 genomic windows where bonobo and chimpanzee contact maps substantially diverged, including several windows harboring genes associated with traits implicated in Pan phenotypic divergence. We used in silico mutagenesis to identify 51 3D-modifying variants in these bonobo-chimpanzee divergent windows, finding that 34 or 66.67% induce genome folding changes via CTCF binding motif disruption. Our results reveal 3D genome variation at the population-level and identify genomic regions where changes in 3D folding may contribute to phenotypic differences in our closest living relatives.

Cross-tissue patterns of DNA hypomethylation reveal genetically distinct histories of cell development.

BACKGROUND: Establishment of DNA methylation (DNAme) patterns is essential for balanced multi-lineage cellular differentiation, but exactly how these patterns drive cellular phenotypes is unclear. While > 80% of CpG sites are stably methylated, tens of thousands of discrete CpG loci form hypomethylated regions (HMRs). Because they lack DNAme, HMRs are considered transcriptionally permissive, but not all HMRs actively regulate genes. Unlike promoter HMRs, a subset of non-coding HMRs is cell type-specific and enriched for tissue-specific gene regulatory functions. Our data further argues not only that HMR establishment is an important step in enforcing cell identity, but also that cross-cell type and spatial HMR patterns are functionally informative of gene regulation. RESULTS: To understand the significance of non-coding HMRs, we systematically dissected HMR patterns across diverse human cell types and developmental timepoints, including embryonic, fetal, and adult tissues. Unsupervised clustering of 126,104 distinct HMRs revealed that levels of HMR specificity reflects a developmental hierarchy supported by enrichment of stage-specific transcription factors and gene ontologies. Using a pseudo-time course of development from embryonic stem cells to adult stem and mature hematopoietic cells, we find that most HMRs observed in differentiated cells (~ 60%) are established at early developmental stages and accumulate as development progresses. HMRs that arise during differentiation frequently (~ 35%) establish near existing HMRs (≤ 6 kb away), leading to the formation of HMR clusters associated with stronger enhancer activity. Using SNP-based partitioned heritability from GWAS summary statistics across diverse traits and clinical lab values, we discovered that genetic contribution to trait heritability is enriched within HMRs. Moreover, the contribution of heritability to cell-relevant traits increases with both increasing HMR specificity and HMR clustering, supporting the role of distinct HMR subsets in regulating normal cell function. CONCLUSIONS: Our results demonstrate that the entire HMR repertoire within a cell-type, rather than just the cell type-specific HMRs, stores information that is key to understanding and predicting cellular phenotypes. Ultimately, these data provide novel insights into how DNA hypo-methylation provides genetically distinct historical records of a cell's journey through development, highlighting HMRs as functionally distinct from other epigenomic annotations.

Comparing chromatin contact maps at scale: methods and insights.

Comparing chromatin contact maps is an essential step in quantifying how three-dimensional (3D) genome organization shapes development, evolution, and disease. However, no gold standard exists for comparing contact maps, and even simple methods often disagree. In this study, we propose novel comparison methods and evaluate them alongside existing approaches using genome-wide Hi-C data and 22,500 in silico predicted contact maps. We also quantify the robustness of methods to common sources of biological and technical variation, such as boundary size and noise. We find that simple difference-based methods such as mean squared error are suitable for initial screening, but biologically informed methods are necessary to identify why maps diverge and propose specific functional hypotheses. We provide a reference guide, codebase, and benchmark for rapidly comparing chromatin contact maps at scale to enable biological insights into the 3D organization of the genome.

Comparing chromatin contact maps at scale: methods and insights.

Comparing chromatin contact maps is an essential step in quantifying how three-dimensional (3D) genome organization shapes development, evolution, and disease. However, no gold standard exists for comparing contact maps, and even simple methods often disagree. In this study, we propose novel comparison methods and evaluate them alongside existing approaches using genome-wide Hi-C data and 22,500 in silico predicted contact maps. We also quantify the robustness of methods to common sources of biological and technical variation, such as boundary size and noise. We find that simple difference-based methods such as mean squared error are suitable for initial screening, but biologically informed methods are necessary to identify why maps diverge and propose specific functional hypotheses. We provide a reference guide, codebase, and benchmark for rapidly comparing chromatin contact maps at scale to enable biological insights into the 3D organization of the genome.

Linking rare and common disease vocabularies by mapping between the human phenotype ontology and phecodes.

Enabling discovery across the spectrum of rare and common diseases requires the integration of biological knowledge with clinical data; however, differences in terminologies present a major barrier. For example, the Human Phenotype Ontology (HPO) is the primary vocabulary for describing features of rare diseases, while most clinical encounters use International Classification of Diseases (ICD) billing codes. ICD codes are further organized into clinically meaningful phenotypes via phecodes. Despite their prevalence, no robust phenome-wide disease mapping between HPO and phecodes/ICD exists. Here, we synthesize evidence using diverse sources and methods-including text matching, the National Library of Medicine's Unified Medical Language System (UMLS), Wikipedia, SORTA, and PheMap-to define a mapping between phecodes and HPO terms via 38 950 links. We evaluate the precision and recall for each domain of evidence, both individually and jointly. This flexibility permits users to tailor the HPO-phecode links for diverse applications along the spectrum of monogenic to polygenic diseases.

Archaic Introgression Shaped Human Circadian Traits.

Introduction: When the ancestors of modern Eurasians migrated out of Africa and interbred with Eurasian archaic hominins, namely Neanderthals and Denisovans, DNA of archaic ancestry integrated into the genomes of anatomically modern humans. This process potentially accelerated adaptation to Eurasian environmental factors, including reduced ultra-violet radiation and increased variation in seasonal dynamics. However, whether these groups differed substantially in circadian biology, and whether archaic introgression adaptively contributed to human chronotypes remains unknown. Results: Here we traced the evolution of chronotype based on genomes from archaic hominins and present-day humans. First, we inferred differences in circadian gene sequences, splicing, and regulation between archaic hominins and modern humans. We identified 28 circadian genes containing variants with potential to alter splicing in archaics (e.g., CLOCK, PER2, RORB, RORC), and 16 circadian genes likely divergently regulated between present-day humans and archaic hominins, including RORA. These differences suggest the potential for introgression to modify circadian gene expression. Testing this hypothesis, we found that introgressed variants are enriched among eQTLs for circadian genes. Supporting the functional relevance of these regulatory effects, we found that many introgressed alleles have associations with chronotype. Strikingly, the strongest introgressed effects on chronotype increase morningness, consistent with adaptations to high latitude in other species. Finally, we identified several circadian loci with evidence of adaptive introgression or latitudinal clines in allele frequency. Conclusions: These findings identify differences in circadian gene regulation between modern humans and archaic hominins and support the contribution of introgression via coordinated effects on variation in human chronotype.

Machine learning reveals the diversity of human 3D chromatin contact patterns.

Understanding variation in chromatin contact patterns across human populations is critical for interpreting non-coding variants and their ultimate effects on gene expression and phenotypes. However, experimental determination of chromatin contacts at a population-scale is prohibitively expensive. To overcome this challenge, we develop and validate a machine learning method to quantify the diversity 3D chromatin contacts at 2 kilobase resolution from genome sequence alone. We then apply this approach to thousands of diverse modern humans and the inferred human-archaic hominin ancestral genome. While patterns of 3D contact divergence genome-wide are qualitatively similar to patterns of sequence divergence, we find that 3D divergence in local 1-megabase genomic windows does not follow sequence divergence. In particular, we identify 392 windows with significantly greater 3D divergence than expected from sequence. Moreover, 26% of genomic windows have rare 3D contact variation observed in a small number of individuals. Using in silico mutagenesis we find that most sequence changes to do not result in changes to 3D chromatin contacts. However in windows with substantial 3D divergence, just one or a few variants can lead to divergent 3D chromatin contacts without the individuals carrying those variants having high sequence divergence. In summary, inferring 3D chromatin contact maps across human populations reveals diverse contact patterns. We anticipate that these genetically diverse maps of 3D chromatin contact will provide a reference for future work on the function and evolution of 3D chromatin contact variation across human populations.

Engaging the next generation of physician-informaticians through early exposure to the field: successes and challenges associated with starting a novel clinical informatics interest group.

Clinical informatics remains underappreciated among medical students in part due to a lack of integration into undergraduate medical education (UME). New developments in the study and practice of medicine are traditionally introduced via formal integration into undergraduate medical curricula. While this path has certain advantages, curricular changes are slow and may fail to showcase the breadth of clinical informatics activities. Less formal and more flexible approaches can circumvent these drawbacks. Interest groups (IGs), which are organized through the Association of American Medical College Careers in Medicine (CiM) program, exemplify the informal approach. CiM IGs are student-led groups that provide exposure to different specialty options, acting as an adjunct to the traditional medical curriculum. While the primary purpose of these groups is to assist students applying to residency programs, we took a novel approach of using an IG to increase student exposure to an area of medicine that had not yet been formally integrated at our institution. IGs provide unique advantages to formal integration into a curriculum as they can be more easily setup and can quickly respond to student interests. Furthermore, IGs can act synergistically with UME, acting as proving grounds for ideas that can lead to new courses. We believe that the lessons and takeaways from our experience can act as a guide for those interested in starting similar organizations at their own schools.

Genome-wide association study of musical beat synchronization demonstrates high polygenicity.

Moving in synchrony to the beat is a fundamental component of musicality. Here we conducted a genome-wide association study to identify common genetic variants associated with beat synchronization in 606,825 individuals. Beat synchronization exhibited a highly polygenic architecture, with 69 loci reaching genome-wide significance (P < 5 × 10-8) and single-nucleotide-polymorphism-based heritability (on the liability scale) of 13%-16%. Heritability was enriched for genes expressed in brain tissues and for fetal and adult brain-specific gene regulatory elements, underscoring the role of central-nervous-system-expressed genes linked to the genetic basis of the trait. We performed validations of the self-report phenotype (through separate experiments) and of the genome-wide association study (polygenic scores for beat synchronization were associated with patients algorithmically classified as musicians in medical records of a separate biobank). Genetic correlations with breathing function, motor function, processing speed and chronotype suggest shared genetic architecture with beat synchronization and provide avenues for new phenotypic and genetic explorations.

Quantifying the contribution of Neanderthal introgression to the heritability of complex traits.

Eurasians have ~2% Neanderthal ancestry, but we lack a comprehensive understanding of the genome-wide influence of Neanderthal introgression on modern human diseases and traits. Here, we quantify the contribution of introgressed alleles to the heritability of more than 400 diverse traits. We show that genomic regions in which detectable Neanderthal ancestry remains are depleted of heritability for all traits considered, except those related to skin and hair. Introgressed variants themselves are also depleted for contributions to the heritability of most traits. However, introgressed variants shared across multiple Neanderthal populations are enriched for heritability and have consistent directions of effect on several traits with potential relevance to human adaptation to non-African environments, including hair and skin traits, autoimmunity, chronotype, bone density, lung capacity, and menopause age. Integrating our results, we propose a model in which selection against introgressed functional variation was the dominant trend (especially for cognitive traits); however, for a few traits, introgressed variants provided beneficial variation via uni-directional (e.g., lightening skin color) or bi-directional (e.g., modulating immune response) effects.

Topologically associating domain boundaries that are stable across diverse cell types are evolutionarily constrained and enriched for heritability.

Topologically associating domains (TADs) are fundamental units of three-dimensional (3D) nuclear organization. The regions bordering TADs-TAD boundaries-contribute to the regulation of gene expression by restricting interactions of cis-regulatory sequences to their target genes. TAD and TAD-boundary disruption have been implicated in rare-disease pathogenesis; however, we have a limited framework for integrating TADs and their variation across cell types into the interpretation of common-trait-associated variants. Here, we investigate an attribute of 3D genome architecture-the stability of TAD boundaries across cell types-and demonstrate its relevance to understanding how genetic variation in TADs contributes to complex disease. By synthesizing TAD maps across 37 diverse cell types with 41 genome-wide association studies (GWASs), we investigate the differences in disease association and evolutionary pressure on variation in TADs versus TAD boundaries. We demonstrate that genetic variation in TAD boundaries contributes more to complex-trait heritability, especially for immunologic, hematologic, and metabolic traits. We also show that TAD boundaries are more evolutionarily constrained than TADs. Next, stratifying boundaries by their stability across cell types, we find substantial variation. Compared to boundaries unique to a specific cell type, boundaries stable across cell types are further enriched for complex-trait heritability, evolutionary constraint, CTCF binding, and housekeeping genes. Thus, considering TAD boundary stability across cell types provides valuable context for understanding the genome's functional landscape and enabling variant interpretation that takes 3D structure into account.

Neanderthal introgression reintroduced functional ancestral alleles lost in Eurasian populations.

Neanderthal ancestry remains across modern Eurasian genomes and introgressed sequences influence diverse phenotypes. Here, we demonstrate that introgressed sequences reintroduced thousands of ancestral alleles that were lost in Eurasian populations before introgression. Our simulations and variant effect predictions argue that these reintroduced alleles (RAs) are more likely to be tolerated by modern humans than are introgressed Neanderthal-derived alleles (NDAs) due to their distinct evolutionary histories. Consistent with this, we show enrichment for RAs and depletion for NDAs on introgressed haplotypes with expression quantitative trait loci (eQTL) and phenotype associations. Analysis of available cross-population eQTLs and massively parallel reporter assay data show that RAs commonly influence gene expression independent of linked NDAs. We further validate these independent effects for one RA in vitro. Finally, we demonstrate that NDAs are depleted for regulatory activity compared to RAs, while RAs have activity levels similar to non-introgressed variants. In summary, our study reveals that Neanderthal introgression reintroduced thousands of lost ancestral variants with gene regulatory activity and that these RAs were more tolerated than NDAs. Thus, RAs and their distinct evolutionary histories must be considered when evaluating the effects of introgression.

Minimal residual disease negativity and lenalidomide maintenance therapy are associated with superior survival outcomes in multiple myeloma.

Modern combinations of therapies for multiple myeloma have led to improvement in survival outcomes with near 100% overall response rate and 25% complete response rates, particularly with autologous hematopoietic cell transplant (AHCT). Minimal residual disease (MRD) assessment with multiparameter flow cytometry is a valid prognostic biomarker for progression-free survival (PFS) and overall survival (OS). However, few data exist regarding whether MRD positivity or negativity will meaningfully influence treatment decisions. We evaluated 433 patients who received induction therapy, followed by AHCT. Participants had MRD assessment by multiparameter flow cytometry before and at days +100 and +365 following AHCT. They also received either lenalidomide, bortezomib, or no maintenance therapy following AHCT. Maintenance treatment with lenalidomide improved MRD negativity at day +365 compared to bortezomib (92.9% vs 41.6%, p = 0.01), or no maintenance therapy (92.9% vs 24.4%, p = 0.012). The median PFS for patients who were MRD negative at day + 365 was 42 vs 17.5 months (p < 0.001) and median OS was 80.6 vs 59 months (p = 0.02). Maintenance therapy following AHCT for multiple myeloma improves the depth of response as assessed by MRD.

Allele-specific SHAPE-MaP assessment of the effects of somatic variation and protein binding on mRNA structure.

The impact of inherited and somatic mutations on messenger RNA (mRNA) structure remains poorly understood. Recent technological advances that leverage next-generation sequencing to obtain experimental structure data, such as SHAPE-MaP, can reveal structural effects of mutations, especially when these data are incorporated into structure modeling. Here, we analyze the ability of SHAPE-MaP to detect the relatively subtle structural changes caused by single-nucleotide mutations. We find that allele-specific sorting greatly improved our detection ability. Thus, we used SHAPE-MaP with a novel combination of clone-free robotic mutagenesis and allele-specific sorting to perform a rapid, comprehensive survey of noncoding somatic and inherited riboSNitches in two cancer-associated mRNAs, TPT1 and LCP1 Using rigorous thermodynamic modeling of the Boltzmann suboptimal ensemble, we identified a subset of mutations that change TPT1 and LCP1 RNA structure, with approximately 14% of all variants identified as riboSNitches. To confirm that these in vitro structures were biologically relevant, we tested how dependent TPT1 and LCP1 mRNA structures were on their environments. We performed SHAPE-MaP on TPT1 and LCP1 mRNAs in the presence or absence of cellular proteins and found that both mRNAs have similar overall folds in all conditions. RiboSNitches identified within these mRNAs in vitro likely exist under biological conditions. Overall, these data reveal a robust mRNA structural landscape where differences in environmental conditions and most sequence variants do not significantly alter RNA structural ensembles. Finally, predicting riboSNitches in mRNAs from sequence alone remains particularly challenging; these data will provide the community with benchmarks for further algorithmic development.

Socio-cultural and Knowledge-Based Barriers to Tuberculosis Diagnosis for Women in Bhopal, India.

BACKGROUND: In India, only one woman is diagnosed with tuberculosis (TB) for every 2.4 men. Previous studies have indicated gender disparities in care-seeking behavior and TB diagnosis; however, little is known about the specific barriers women face. OBJECTIVES: This study aimed to characterize socio-cultural and knowledge-based barriers that affected TB diagnosis for women in Bhopal, India. MATERIALS AND METHODS: In-depth interviews were conducted with 13 affected women and 6 health-care workers. The Bhopal Diagnostic Microscopy Laboratory Register (n = 121) and the Bhopal district report (n = 261) were examined for diagnostic and care-seeking trends. RESULTS: Women, especially younger women, faced socio-cultural barriers and stigma, causing many to hide their symptoms. Older women had little awareness about TB. Women often sought treatment from private practitioners, resulting in delayed diagnosis. CONCLUSIONS: Understanding these diagnostic and help-seeking behaviors barriers for women is critical for development of a gender-sensitive TB control program.

Increased Transcript Complexity in Genes Associated with Chronic Obstructive Pulmonary Disease.

Genome-wide association studies aim to correlate genotype with phenotype. Many common diseases including Type II diabetes, Alzheimer's, Parkinson's and Chronic Obstructive Pulmonary Disease (COPD) are complex genetic traits with hundreds of different loci that are associated with varied disease risk. Identifying common features in the genes associated with each disease remains a challenge. Furthermore, the role of post-transcriptional regulation, and in particular alternative splicing, is still poorly understood in most multigenic diseases. We therefore compiled comprehensive lists of genes associated with Type II diabetes, Alzheimer's, Parkinson's and COPD in an attempt to identify common features of their corresponding mRNA transcripts within each gene set. The SERPINA1 gene is a well-recognized genetic risk factor of COPD and it produces 11 transcript variants, which is exceptional for a human gene. This led us to hypothesize that other genes associated with COPD, and complex disorders in general, are highly transcriptionally diverse. We found that COPD-associated genes have a statistically significant enrichment in transcript complexity stemming from a disproportionately high level of alternative splicing, however, Type II Diabetes, Alzheimer's and Parkinson's disease genes were not significantly enriched. We also identified a subset of transcriptionally complex COPD-associated genes (~40%) that are differentially expressed between mild, moderate and severe COPD. Although the genes associated with other lung diseases are not extensively documented, we found preliminary data that idiopathic pulmonary disease genes, but not cystic fibrosis modulators, are also more transcriptionally complex. Interestingly, complex COPD transcripts are more often the product of alternative acceptor site usage. To verify the biological importance of these alternative transcripts, we used RNA-sequencing analyses to determine that COPD-associated genes are frequently expressed in lung and liver tissues and are regulated in a tissue-specific manner. Additionally, many complex COPD-associated genes are spliced differently between COPD and non-COPD patients. Our analysis therefore suggests that post-transcriptional regulation, particularly alternative splicing, is an important feature specific to COPD disease etiology that warrants further investigation.