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Disparities in data underlying clinical genomic interpretation is an acknowledged problem, but there is a paucity of data demonstrating it. The All of Us Research Program is collecting data including whole-genome sequences, health records, and surveys for at least a million participants with diverse ancestry and access to healthcare, representing one of the largest biomedical research repositories of its kind. Here, we examine pathogenic and likely pathogenic variants that were identified in the All of Us cohort. The European ancestry subgroup showed the highest overall rate of pathogenic variation, with 2.26% of participants having a pathogenic variant. Other ancestry groups had lower rates of pathogenic variation, including 1.62% for the African ancestry group and 1.32% in the Latino/Admixed American ancestry group. Pathogenic variants were most frequently observed in genes related to Breast/Ovarian Cancer or Hypercholesterolemia. Variant frequencies in many genes were consistent with the data from the public gnomAD database, with some notable exceptions resolved using gnomAD subsets. Differences in pathogenic variant frequency observed between ancestral groups generally indicate biases of ascertainment of knowledge about those variants, but some deviations may be indicative of differences in disease prevalence. This work will allow targeted precision medicine efforts at revealed disparities. A comparison of the frequency of pathogenic mutations in 73 genes in the All of Us cohort highlights the differences in pathogenic variation attributed to ancestry. [ABSTRACT FROM AUTHOR]

Disparities in data underlying clinical genomic interpretation is an acknowledged problem, but there is a paucity of data demonstrating it. The All of Us Research Program is collecting data including whole-genome sequences, health records, and surveys for at least a million participants with diverse ancestry and access to healthcare, representing one of the largest biomedical research repositories of its kind. Here, we examine pathogenic and likely pathogenic variants that were identified in the All of Us cohort. The European ancestry subgroup showed the highest overall rate of pathogenic variation, with 2.26% of participants having a pathogenic variant. Other ancestry groups had lower rates of pathogenic variation, including 1.62% for the African ancestry group and 1.32% in the Latino/Admixed American ancestry group. Pathogenic variants were most frequently observed in genes related to Breast/Ovarian Cancer or Hypercholesterolemia. Variant frequencies in many genes were consistent with the data from the public gnomAD database, with some notable exceptions resolved using gnomAD subsets. Differences in pathogenic variant frequency observed between ancestral groups generally indicate biases of ascertainment of knowledge about those variants, but some deviations may be indicative of differences in disease prevalence. This work will allow targeted precision medicine efforts at revealed disparities. A comparison of the frequency of pathogenic mutations in 73 genes in the All of Us cohort highlights the differences in pathogenic variation attributed to ancestry. [ABSTRACT FROM AUTHOR]

Exome sequencing of genes associated with heritable thoracic aortic disease (HTAD) failed to identify a pathogenic variant in a large family with Marfan syndrome (MFS). A genome‐wide linkage analysis for thoracic aortic disease identified a peak at 15q21.1, and genome sequencing identified a novel deep intronic FBN1 variant that segregated with thoracic aortic disease in the family (LOD score 2.7) and was predicted to alter splicing. RT‐PCR and bulk RNA sequencing of RNA harvested from fibroblasts explanted from the affected proband revealed an insertion of a pseudoexon between exons 13 and 14 of the FBN1 transcript, predicted to lead to nonsense mediated decay (NMD). Treating the fibroblasts with an NMD inhibitor, cycloheximide, greatly improved the detection of the pseudoexon‐containing transcript. Family members with the FBN1 variant had later onset aortic events and fewer MFS systemic features than typical for individuals with haploinsufficiency of FBN1. Variable penetrance of the phenotype and negative genetic testing in MFS families should raise the possibility of deep intronic FBN1 variants and the need for additional molecular studies. [ABSTRACT FROM AUTHOR]

Background: Genetic variants in the SLC14A1, ACKR1, and KEL genes, which encode Kidd, Duffy, and Kell red blood cell antigens, respectively, may result in weakened expression of antigens or a null phenotype. These variants are of particular interest to individuals with sickle cell disease (SCD), who frequently undergo chronic transfusion therapy with antigen‐matched units. The goal was to describe the diversity and the frequency of variants in SLC14A1, ACKR1, and KEL genes among individuals with SCD using whole genome sequencing (WGS) data. Study Design and Methods: Two large SCD cohorts were studied: the Recipient Epidemiology and Donor Evaluation Study III (REDS‐III) (n = 2634) and the Outcome Modifying Gene in SCD (OMG) (n = 640). Most of the studied individuals were of mixed origin. WGS was performed as part of the National Heart, Lung, and Blood Institute's Trans‐Omics for Precision Medicine (TOPMed) program. Results: In SLC14A1, variants included four encoding a weak Jka phenotype and five null alleles (JKnull). JKA*01N.09 was the most common JKnull. One possible JKnull mutation was novel: c.812G>T. In ACKR1, identified variants included two that predicted Fyx (FY*X) and one corresponding to the c.‐67T>C GATA mutation. The c.‐67T>C mutation was associated with FY*A (FY*01N.01) in four participants. FY*X was identified in 49 individuals. In KEL, identified variants included three null alleles (KEL*02N.17, KEL*02N.26, and KEL*02N.04) and one allele predicting Kmod phenotype, all in heterozygosity. Conclusions: We described the diversity and distribution of SLC14A1, ACKR1, and KEL variants in two large SCD cohorts, comprising mostly individuals of mixed ancestry. This information may be useful for planning the transfusion support of patients with SCD. [ABSTRACT FROM AUTHOR]

Variation in the enzymatic activity of pharmacogenes is defined by star alleles (haplotypes) comprised of single‐nucleotide variants, small insertion‐deletions, and large structural variants. We recently developed Stargazer, a next‐generation sequencing‐based tool to call star alleles for the clinically important CYP2D6 gene. Here, we present the utility of extending Stargazer to call star alleles for 28 pharmacogenes using whole genome sequencing (WGS) data. We applied Stargazer to WGS data from 70 ethnically diverse samples from the Genetic Testing Reference Materials Coordination Program (GeT‐RM). These reference samples were extensively characterized by GeT‐RM using multiple pharmacogenetic testing assays. In all 28 genes, Stargazer recalled 100% of star alleles (N = 92) present in GeT‐RM's consensus genotypes (N = 1,559). Stargazer also detected star alleles not previously reported by GeT‐RM, including complex structural variants. Our results demonstrate that combining WGS data and Stargazer enables automated, accurate, and comprehensive genotyping of pharmacogenes in the human genome. [ABSTRACT FROM AUTHOR]

Insulin growth factor 1 (IGF1) is amajor anabolic signal that is essential during skeletal development, cellular adhesion and migration. Recent transcriptomic studies have shown that there is an upregulation in IGF1 expression in calvarial osteoblasts derived from patients with singlesuture craniosynostosis (SSC). Upregulation of the IGF1 signaling pathway is knownto induce increased expression of a set of osteogenic markers that previously have been shown to be correlated with contractility and migration. Although the IGF1 signaling pathway has been implicated in SSC, a correlation between IGF1, contractility and migration has not yet been investigated. Here, we examined the effect of IGF1 activation in inducing cellular contractility and migration in SSCosteoblasts usingmicropost arrays and time-lapsemicroscopy. We observed that the contractile forces and migration speeds of SSC osteoblasts correlated with IGF1 expression. Moreover, both contractility and migration of SSC osteoblasts were directly affected by the interaction of IGF1 with IGF1 receptor (IGF1R). Our results suggest that IGF1 activity can provide valuable insight for phenotype-genotype correlation in SSC osteoblasts and might provide a target for therapeutic intervention. [ABSTRACT FROM AUTHOR]

Nervous and neuroendocrine systems mediate environmental conditions to control a variety of life history traits. Our goal was to provide mechanistic insights as to how neurosecretory signals mediate division of labor in the honey bee (Apis mellifera). Worker division of labor is based on a process of behavioral maturation by individual bees, which involves performing in-hive tasks early in adulthood, then transitioning to foraging for food outside the hive. Social and nutritional cues converge on endocrine factors to regulate behavioral maturation, but whether neurosecretory systems are central to this process is not known. To explore this, we performed transcriptomic profiling of a neurosecretory region of the brain, the pars intercerebralis (PI). We first compared PI transcriptional profiles for bees performing in-hive tasks and bees engaged in foraging. Using these results as a baseline, we then performed manipulative experiments to test whether the PI is responsive to dietary changes and/or changes in juvenile hormone (JH) levels. Results reveal a robust molecular signature of behavioral maturation in the PI, with a subset of gene expression changes consistent with changes elicited by JH treatment. In contrast, dietary changes did not induce transcriptomic changes in the PI consistent with behavioral maturation or JH treatment. Based on these results, we propose a new verbal model of the regulation of division of labor in honey bees in which the relationship between diet and nutritional physiology is attenuated, and in its place is a relationship between social signals and nutritional physiology that is mediated by JH. [ABSTRACT FROM AUTHOR]

Worker honey bees undergo a socially regulated, highly stable lipid loss as part of their behavioral maturation. We used large-scale transcriptomic and proteomic experiments, physiological experiments and RNA interference to explore the mechanistic basis for this lipid loss. Lipid loss was associated with thousands of gene expression changes in abdominal fat bodies. Many of these genes were also regulated in young bees by nutrition during an initial period of lipid gain. Surprisingly, in older bees, which is when maximum lipid loss occurs, diet played less of a role in regulating fat body gene expression for components of evolutionarily conserved nutrition-related endocrine systems involving insulin and juvenile hormone signaling. By contrast, fat body gene expression in older bees was regulated more strongly by evolutionarily novel regulatory factors, queen mandibular pheromone (a honey bee-specific social signal) and vitellogenin (a conserved yolk protein that has evolved novel, maturation-related functions in the bee), independent of nutrition. These results demonstrate that conserved molecular pathways can be manipulated to achieve stable lipid loss through evolutionarily novel regulatory processes. [ABSTRACT FROM AUTHOR]

The article offers information on a report which presents a meta-analysis tool that analyzes sequence and expression data, and reveals a flexible cis-regulatory code underlying a complex honey bee behavioral maturation. It reflects that the tool will help the scientists for conducting integrative analyses of the multitude of generated datasets. It provides information that complex phenotypes are produced by a multitude of heritable and environmental determinants.