A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels.

ABSTRACT: Coagulation factor VIII (FVIII) and its carrier protein von Willebrand factor (VWF) are critical to coagulation and platelet aggregation. We leveraged whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program along with TOPMed-based imputation of genotypes in additional samples to identify genetic associations with circulating FVIII and VWF levels in a single-variant meta-analysis, including up to 45 289 participants. Gene-based aggregate tests were implemented in TOPMed. We identified 3 candidate causal genes and tested their functional effect on FVIII release from human liver endothelial cells (HLECs) and VWF release from human umbilical vein endothelial cells. Mendelian randomization was also performed to provide evidence for causal associations of FVIII and VWF with thrombotic outcomes. We identified associations (P < 5 × 10-9) at 7 new loci for FVIII (ST3GAL4, CLEC4M, B3GNT2, ASGR1, F12, KNG1, and TREM1/NCR2) and 1 for VWF (B3GNT2). VWF, ABO, and STAB2 were associated with FVIII and VWF in gene-based analyses. Multiphenotype analysis of FVIII and VWF identified another 3 new loci, including PDIA3. Silencing of B3GNT2 and the previously reported CD36 gene decreased release of FVIII by HLECs, whereas silencing of B3GNT2, CD36, and PDIA3 decreased release of VWF by HVECs. Mendelian randomization supports causal association of higher FVIII and VWF with increased risk of thrombotic outcomes. Seven new loci were identified for FVIII and 1 for VWF, with evidence supporting causal associations of FVIII and VWF with thrombotic outcomes. B3GNT2, CD36, and PDIA3 modulate the release of FVIII and/or VWF in vitro.

The frequency of pathogenic variation in the All of Us cohort reveals ancestry-driven disparities.

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.

An FBN1 deep intronic variant is associated with pseudoexon formation and a variable Marfan phenotype in a five generation family.

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.

Whole genome sequencing identifies structural variants contributing to hematologic traits in the NHLBI TOPMed program.

Genome-wide association studies have identified thousands of single nucleotide variants and small indels that contribute to variation in hematologic traits. While structural variants are known to cause rare blood or hematopoietic disorders, the genome-wide contribution of structural variants to quantitative blood cell trait variation is unknown. Here we utilized whole genome sequencing data in ancestrally diverse participants of the NHLBI Trans Omics for Precision Medicine program (N = 50,675) to detect structural variants associated with hematologic traits. Using single variant tests, we assessed the association of common and rare structural variants with red cell-, white cell-, and platelet-related quantitative traits and observed 21 independent signals (12 common and 9 rare) reaching genome-wide significance. The majority of these associations (N = 18) replicated in independent datasets. In genome-editing experiments, we provide evidence that a deletion associated with lower monocyte counts leads to disruption of an S1PR3 monocyte enhancer and decreased S1PR3 expression.

Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed.

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value <5×10-9) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes.

TOP-LD: A tool to explore linkage disequilibrium with TOPMed whole-genome sequence data.

Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project. Here, we present TOP-LD, an online tool to explore LD inferred with high-coverage (∼30×) WGS data from 15,578 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. TOP-LD provides a significant upgrade compared to current LD tools, as the TOPMed WGS data provide a more comprehensive representation of genetic variation than the 1000 Genomes data, particularly for rare variants and in the specific populations that we analyzed. For example, TOP-LD encompasses LD information for 150.3, 62.2, and 36.7 million variants for European, African, and East Asian ancestral samples, respectively, offering 2.6- to 9.1-fold increase in variant coverage compared to HaploReg 4.0 or LDlink. In addition, TOP-LD includes tens of thousands of structural variants (SVs). We demonstrate the value of TOP-LD in fine-mapping at the GGT1 locus associated with gamma glutamyltransferase in the African ancestry participants in UK Biobank. Beyond fine-mapping, TOP-LD can facilitate a wide range of applications that are based on summary statistics and estimates of LD. TOP-LD is freely available online.

Germline SAMD9L truncation variants trigger global translational repression.

SAMD9L is an interferon-induced tumor suppressor implicated in a spectrum of multisystem disorders, including risk for myeloid malignancies and immune deficiency. We identified a heterozygous de novo frameshift variant in SAMD9L in an infant with B cell aplasia and clinical autoinflammatory features who died from respiratory failure with chronic rhinovirus infection. Autopsy demonstrated absent bone marrow and peripheral B cells as well as selective loss of Langerhans and Purkinje cells. The frameshift variant led to expression of a truncated protein with interferon treatment. This protein exhibited a gain-of-function phenotype, resulting in interference in global protein synthesis via inhibition of translational elongation. Using a mutational scan, we identified a region within SAMD9L where stop-gain variants trigger a similar translational arrest. SAMD9L variants that globally suppress translation had no effect or increased mRNA transcription. The complex-reported phenotype likely reflects lineage-dominant sensitivities to this translation block. Taken together, our findings indicate that interferon-triggered SAMD9L gain-of-function variants globally suppress translation.

Diversity of variant alleles encoding Kidd, Duffy, and Kell antigens in individuals with sickle cell disease using whole genome sequencing data from the NHLBI TOPMed Program.

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.

Coagulation factor VIII: Relationship to cardiovascular disease risk and whole genome sequence and epigenome-wide analysis in African Americans.

BACKGROUND: Prospective studies have suggested higher factor VIII (FVIII) levels are an independent risk factor for coronary heart disease (CHD) and stroke. However, limited information, including on genetic and epigenetic contributors to FVIII variation, is available specifically among African Americans (AAs), who have higher FVIII levels than Europeans. OBJECTIVES: We measured FVIII levels in ~3400 AAs from the community-based Jackson Heart Study and assessed genetic, epigenetic, and epidemiological correlates of FVIII, as well as incident cardiovascular disease (CVD) associations. METHODS: We assessed cross-sectional associations of FVIII with CVD risk factors as well as incident CHD, stroke, heart failure, and mortality associations. We additionally assessed associations with TOPMed whole genome sequencing data and an epigenome-wide methylation array. RESULTS: Our results confirmed associations between FVIII and risk of incident CHD events and total mortality in AAs; mortality associations were largely independent of traditional risk factors. We also demonstrate an association of FVIII with incident heart failure, independent of B-type natriuretic peptide. Two genomic regions were strongly associated with FVIII (ABO and VWF). The index variant at VWF is specific to individuals of African descent and is distinct from the previously reported European VWF association signal. Epigenome-wide association analysis showed significant FVIII associations with several CpG sites in the ABO region. However, after adjusting for ABO genetic variants, ABO CpG sites were not significant. CONCLUSIONS: Larger sample sizes of AAs will be required to discover additional genetic and epigenetic contributors to FVIII phenotypic variation, which may have consequences for CVD health disparities.

Calling Star Alleles With Stargazer in 28 Pharmacogenes With Whole Genome Sequences.

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.

Genomic characterization of the RH locus detects complex and novel structural variation in multi-ethnic cohorts.

PURPOSE: Rh antigens can provoke severe alloimmune reactions, particularly in high-risk transfusion contexts, such as sickle cell disease. Rh antigens are encoded by the paralogs, RHD and RHCE, located in one of the most complex genetic loci. Our goal was to characterize RH genetic variation in multi-ethnic cohorts, with the focus on detecting RH structural variation (SV). METHODS: We customized analytical methods to estimate paralog-specific copy number from next-generation sequencing (NGS) data. We applied these methods to clinically characterized samples, including four World Health Organization (WHO) genotyping references and 1135 Asian and Native American blood donors. Subsequently, we surveyed 1715 African American samples from the Jackson Heart Study. RESULTS: Most samples in each dataset exhibited SV. SV detection enabled prediction of the immunogenic RhD and RhC antigens in concordance (>99%) with serological phenotyping. RhC antigen expression was associated with exon 2 hybrid alleles (RHCE*CE-D(2)-CE). Clinically relevant exon 4-7 hybrid alleles (RHD*D-CE(4-7)-D) and exon 9 hybrid alleles (RHCE*CE-D(9)-CE) were prevalent in African Americans. CONCLUSION: This study shows custom NGS methods can accurately detect RH SV, and that SV is important to inform prediction of relevant RH alleles. Additionally, this study provides the first large NGS survey of RH alleles in African Americans.

Stargazer: a software tool for calling star alleles from next-generation sequencing data using CYP2D6 as a model.

PURPOSE: Genotyping CYP2D6 is important for precision drug therapy because the enzyme it encodes metabolizes approximately 25% of drugs, and its activity varies considerably among individuals. Genotype analysis of CYP2D6 is challenging due to its highly polymorphic nature. Over 100 haplotypes (star alleles) have been defined for CYP2D6, some involving a gene conversion with its nearby nonfunctional but highly homologous paralog CYP2D7. We present Stargazer, a new bioinformatics tool that uses next-generation sequencing (NGS) data to call star alleles for CYP2D6 ( https://stargazer.gs.washington.edu/stargazerweb/ ). Stargazer is currently being extended for other pharmacogenes. METHODS: Stargazer identifies star alleles from NGS data by detecting single nucleotide variants, insertion-deletion variants, and structural variants. Stargazer detects structural variation, including gene deletions, duplications, and conversions, by calculating paralog-specific copy numbers from read depths. RESULTS: We applied Stargazer to the NGS data of 32 ethnically diverse HapMap trios that were genotyped by TaqMan assays, long-range polymerase chain reaction, quantitative multiplex polymerase chain reaction, high-resolution melting analysis, and/or Sanger sequencing. CYP2D6 genotyping by Stargazer was 99.0% concordant with the data obtained by these methods, and showed that 28.1% of the samples had structural variation including CYP2D6/CYP2D7 hybrids. CONCLUSION: Accurate genotyping of pharmacogenes with NGS and subsequent allele calling with Stargazer will aid the implementation of precision drug therapy.

Whole genome sequence association with E-selectin levels reveals loss-of-function variant in African Americans.

E-selectin mediates the rolling of circulating leukocytes during inflammatory processes. Previous genome-wide association studies in European and Asian individuals have identified the ABO locus associated with E-selectin levels. Using Trans-Omics for Precision Medicine whole genome sequencing data in 2249 African Americans (AAs) from the Jackson Heart Study, we examined genome-wide associations with soluble E-selectin levels. In addition to replicating known signals at ABO, we identified a novel association of a common loss-of-function, missense variant in Fucosyltransferase 6 (FUT6; rs17855739,p.Glu274Lys, P = 9.02 × 10-24) with higher soluble E-selectin levels. This variant is considerably more common in populations of African ancestry compared to non-African ancestry populations. We replicated the association of FUT6 p.Glu274Lys with higher soluble E-selectin in an independent population of 748 AAs from the Women's Health Initiative and identified an additional pleiotropic association with vitamin B12 levels. Despite the broad role of both selectins and fucosyltransferases in various inflammatory, immune and cancer-related processes, we were unable to identify any additional disease associations of the FUT6 p.Glu274Lys variant in an electronic medical record-based phenome-wide association scan of over 9000 AAs.

MACF1 Mutations Encoding Highly Conserved Zinc-Binding Residues of the GAR Domain Cause Defects in Neuronal Migration and Axon Guidance.

To date, mutations in 15 actin- or microtubule-associated genes have been associated with the cortical malformation lissencephaly and variable brainstem hypoplasia. During a multicenter review, we recognized a rare lissencephaly variant with a complex brainstem malformation in three unrelated children. We searched our large brain-malformation databases and found another five children with this malformation (as well as one with a less severe variant), analyzed available whole-exome or -genome sequencing data, and tested ciliogenesis in two affected individuals. The brain malformation comprised posterior predominant lissencephaly and midline crossing defects consisting of absent anterior commissure and a striking W-shaped brainstem malformation caused by small or absent pontine crossing fibers. We discovered heterozygous de novo missense variants or an in-frame deletion involving highly conserved zinc-binding residues within the GAR domain of MACF1 in the first eight subjects. We studied cilium formation and found a higher proportion of mutant cells with short cilia than of control cells with short cilia. A ninth child had similar lissencephaly but only subtle brainstem dysplasia associated with a heterozygous de novo missense variant in the spectrin repeat domain of MACF1. Thus, we report variants of the microtubule-binding GAR domain of MACF1 as the cause of a distinctive and most likely pathognomonic brain malformation. A gain-of-function or dominant-negative mechanism appears likely given that many heterozygous mutations leading to protein truncation are included in the ExAC Browser. However, three de novo variants in MACF1 have been observed in large schizophrenia cohorts.

The role of genomics in transfusion medicine.

PURPOSE OF REVIEW: To summarize recent advances in red blood cell (RBC) blood group genotyping, with an emphasis on advances in the use of NGS next generation sequencing (NGS) to detect clinically relevant blood group gene variation. RECENT FINDINGS: Genetic information is useful in predicting RBC blood group antigen expression in several clinical contexts, particularly, for patients at high-risk for allosensitization, such as multiple transfused patients. Blood group antigen expression is directed by DNA variants affecting multiply genes. With over 300 known antigens, NGS offers the attractive prospect of comprehensive blood group genotyping. Recent studies from several groups show that NGS reliably detects blood group gene single nucleotide variants (SNVs) with good correlation with other genetic methods and serology. Additionally, new custom NGS methods accurately detect complex DNA variants, including hybrid RH alleles. Thus, recent work shows that NGS detects known and novel blood group gene variants in patients, solves challenging clinical cases, and detects relevant blood group variation in donors. SUMMARY: New work shows that NGS is particularly robust in identifying SNVs in blood group genes, whereas custom genomic tools can be used to identify known and novel complex structural variants, including in the RH system.

Activation of the IGF1 pathway mediates changes in cellular contractility and motility in single-suture craniosynostosis.

Insulin growth factor 1 (IGF1) is a major 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 single-suture craniosynostosis (SSC). Upregulation of the IGF1 signaling pathway is known to 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 SSC osteoblasts using micropost arrays and time-lapse microscopy. 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.

Diet and endocrine effects on behavioral maturation-related gene expression in the pars intercerebralis of the honey bee brain.

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.

Diet-dependent gene expression in honey bees: honey vs. sucrose or high fructose corn syrup.

Severe declines in honey bee populations have made it imperative to understand key factors impacting honey bee health. Of major concern is nutrition, as malnutrition in honey bees is associated with immune system impairment and increased pesticide susceptibility. Beekeepers often feed high fructose corn syrup (HFCS) or sucrose after harvesting honey or during periods of nectar dearth. We report that, relative to honey, chronic feeding of either of these two alternative carbohydrate sources elicited hundreds of differences in gene expression in the fat body, a peripheral nutrient-sensing tissue analogous to vertebrate liver and adipose tissues. These expression differences included genes involved in protein metabolism and oxidation-reduction, including some involved in tyrosine and phenylalanine metabolism. Differences between HFCS and sucrose diets were much more subtle and included a few genes involved in carbohydrate and lipid metabolism. Our results suggest that bees receive nutritional components from honey that are not provided by alternative food sources widely used in apiculture.

New meta-analysis tools reveal common transcriptional regulatory basis for multiple determinants of behavior.

A fundamental problem in meta-analysis is how to systematically combine information from multiple statistical tests to rigorously evaluate a single overarching hypothesis. This problem occurs in systems biology when attempting to map genomic attributes to complex phenotypes such as behavior. Behavior and other complex phenotypes are influenced by intrinsic and environmental determinants that act on the transcriptome, but little is known about how these determinants interact at the molecular level. We developed an informatic technique that identifies statistically significant meta-associations between gene expression patterns and transcription factor combinations. Deploying this technique for brain transcriptome profiles from ca. 400 individual bees, we show that diverse determinants of behavior rely on shared combinations of transcription factors. These relationships were revealed only when we considered complex and variable regulatory rules, suggesting that these shared transcription factors are used in distinct ways by different determinants. This regulatory code would have been missed by traditional gene coexpression or cis-regulatory analytic methods. We expect that our meta-analysis tools will be useful for a broad array of problems in systems biology and other fields.

Mechanisms of stable lipid loss in a social insect.

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.