The Association Between the 5-Hydroxytryptamine Receptor 2A Gene Variants rs6311 and rs6313 and Obstructive Sleep Apnea in the Iranian Kurdish Population.

Introduction: Sleep is one of the most significant parts of everyone's life. Most people sleep for about one-third of their lives. Sleep disorders negatively impact the quality of life. Obstructive sleep apnea (OSA) is a severe sleep disorder that significantly impacts the patient's life and their family members. This study aimed to investigate the relationship between rs6313 and rs6311 polymorphisms in the serotonin receptor type 2A gene and OSA in the Kurdish population. Materials and Methods: The study's population comprises 100 OSA sufferers and 100 healthy people. Polysomnography diagnostic tests were done on both the patient and control groups. The polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) was used to investigate the relationship between OSA and LEPR gene polymorphisms. Results: Statistical analysis showed a significant relationship between genotype frequencies of patient and control groups of rs6311 with OSA in dominant [odds ratio (OR) = 5.203, p < 0.001) and codominant models (OR = 9.7, p < 0.001). Also, there was a significant relationship between genotype frequencies of patient and control groups of rs6313 with OSA in dominant (OR = 10.565, p < 0.001) and codominant models (OR = 5.938, p < 0.001). Conclusions: Findings from the study demonstrated that the two polymorphisms rs6311 and rs6313 could be effective at causing OSA; however, there was no correlation between the severity of the disease and either of the two polymorphisms.

BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases.

Genome-wide Association Studies (GWAS) methods have identified individual single-nucleotide polymorphisms (SNPs) significantly associated with specific phenotypes. Nonetheless, many complex diseases are polygenic and are controlled by multiple genetic variants that are usually non-linearly dependent. These genetic variants are marginally less effective and remain undetected in GWAS analysis. Kernel-based tests (KBT), which evaluate the joint effect of a group of genetic variants, are therefore critical for complex disease analysis. However, choosing different kernel functions in KBT can significantly influence the type I error control and power, and selecting the optimal kernel remains a statistically challenging task. A few existing methods suffer from inflated type 1 errors, limited scalability, inferior power or issues of ambiguous conclusions. Here, we present a new Bayesian framework, BayesKAT (https://github.com/wangjr03/BayesKAT), which overcomes these kernel specification issues by selecting the optimal composite kernel adaptively from the data while testing genetic associations simultaneously. Furthermore, BayesKAT implements a scalable computational strategy to boost its applicability, especially for high-dimensional cases where other methods become less effective. Based on a series of performance comparisons using both simulated and real large-scale genetics data, BayesKAT outperforms the available methods in detecting complex group-level associations and controlling type I errors simultaneously. Applied on a variety of groups of functionally related genetic variants based on biological pathways, co-expression gene modules and protein complexes, BayesKAT deciphers the complex genetic basis and provides mechanistic insights into human diseases.

Clinical and Genetic Spectrum in a Large Cohort of Hereditary Spastic Paraplegia.

BACKGROUND: Next-generation sequencing-based molecular assessment has benefited the diagnosis of hereditary spastic paraplegia (HSP) subtypes. However, the clinical and genetic spectrum of HSP due to large fragment deletions/duplications has yet to be fully defined. OBJECTIVE: We aim to better characterize the clinical phenotypes and genetic features of HSP and to provide new thoughts on diagnosis. METHODS: Whole-exome sequencing (WES) was performed in patients with clinically suspected HSP, followed by multiple ligation-dependent probe amplification (MLPA) sequentially carried out for those with negative findings in known causative genes. Genotype-phenotype correlation analyses were conducted under specific genotypes. RESULTS: We made a genetic diagnosis in 60% (162/270) of patients, of whom 48.9% (132/270) had 24 various subtypes due to point mutations (SPG4/SPG11/SPG35/SPG7/SPG10/SPG5/SPG3A/SPG2/SPG76/SPG30/SPG6/SPG9A/SPG12/SPG15/SPG17/SPG18/SPG26/SPG49/SPG55/SPG56/SPG57/SPG62/SPG78/SPG80). Thirty patients were found to have causative rearrangements by MLPA (11.1%), among which SPG4 was the most prevalent (73.3%), followed by SPG3A (16.7%), SPG6 (3.3%), SPG7 (3.3%), and SPG11 (3.3%). Clinical analysis showed that some symptoms were often related to specific subtypes, and rearrangement-related SPG3A patients seemingly had later onset. We observed a presumptive anticipation among SPG4 and SPG3A families due to rearrangement. CONCLUSIONS: Based on the largest known Asian HSP cohort, including the largest subgroup of rearrangement-related pedigrees, we gain a comprehensive understanding of the clinical and genetic spectrum of HSP. We propose a diagnostic flowchart to sequentially detect the causative genes in practice. Large fragment mutations account for a considerable proportion of HSP, and thus, MLPA screening acts as a beneficial supplement to routine WES. © 2024 International Parkinson and Movement Disorder Society.

Transcriptional linkage analysis with in vivo AAV-Perturb-seq.

The ever-growing compendium of genetic variants associated with human pathologies demands new methods to study genotype-phenotype relationships in complex tissues in a high-throughput manner1,2. Here we introduce adeno-associated virus (AAV)-mediated direct in vivo single-cell CRISPR screening, termed AAV-Perturb-seq, a tuneable and broadly applicable method for transcriptional linkage analysis as well as high-throughput and high-resolution phenotyping of genetic perturbations in vivo. We applied AAV-Perturb-seq using gene editing and transcriptional inhibition to systematically dissect the phenotypic landscape underlying 22q11.2 deletion syndrome3,4 genes in the adult mouse brain prefrontal cortex. We identified three 22q11.2-linked genes involved in known and previously undescribed pathways orchestrating neuronal functions in vivo that explain approximately 40% of the transcriptional changes observed in a 22q11.2-deletion mouse model. Our findings suggest that the 22q11.2-deletion syndrome transcriptional phenotype found in mature neurons may in part be due to the broad dysregulation of a class of genes associated with disease susceptibility that are important for dysfunctional RNA processing and synaptic function. Our study establishes a flexible and scalable direct in vivo method to facilitate causal understanding of biological and disease mechanisms with potential applications to identify genetic interventions and therapeutic targets for treating disease.

Network expansion of genetic associations defines a pleiotropy map of human cell biology.

Interacting proteins tend to have similar functions, influencing the same organismal traits. Interaction networks can be used to expand the list of candidate trait-associated genes from genome-wide association studies. Here, we performed network-based expansion of trait-associated genes for 1,002 human traits showing that this recovers known disease genes or drug targets. The similarity of network expansion scores identifies groups of traits likely to share an underlying genetic and biological process. We identified 73 pleiotropic gene modules linked to multiple traits, enriched in genes involved in processes such as protein ubiquitination and RNA processing. In contrast to gene deletion studies, pleiotropy as defined here captures specifically multicellular-related processes. We show examples of modules linked to human diseases enriched in genes with known pathogenic variants that can be used to map targets of approved drugs for repurposing. Finally, we illustrate the use of network expansion scores to study genes at inflammatory bowel disease genome-wide association study loci, and implicate inflammatory bowel disease-relevant genes with strong functional and genetic support.

Association of single nucleotide polymorphisms of interferon-γ with pulmonary tuberculosis in population of Himachal Pradesh, India.

Interferon-gamma (IFN-γ) plays an integral role in the host immunity against tuberculosis (TB). The gene encoding IFN-γ is polymorphic and several studies have reported the association of its genetic polymorphisms with TB in different populations of the world. The present study investigated the association of rs2069705 (C/T), rs1861494 (C/T), rs1861493 (A/G) and rs2069718 (C/T) single nucleotide polymorphisms (SNPs) of IFN-γ with pulmonary TB in a population of Himachal Pradesh, India. For present study, 210 pulmonary TB patients and 205 healthy controls (HCs) were recruited. The selected SNPs of IFN-γ were genotyped by amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) and plasma IFN-γ levels were measured by ELISA. The 'T' allele of rs1861494 SNP was found to increase susceptibility to TB in the studied population (OR = 2.18, 95%CI = 1.57-3.03; p < 0.001). After stratifying the subjects on basis of sex, males with 'T' allele of rs2069718 SNP were found to be at higher risk to TB (OR = 1.55, 95%CI = 1.07-2.25; p = 0.02). We also found moderate linkage disequilibrium among the studied SNPs. The haplotypes C-T-A-T and T-T-G-T of rs2069705-rs1861494-rs1861493-rs2069718 were overrepresented in TB patients and found to increase susceptibility to TB (p = 0.012). The plasma IFN-γ levels in TB patients were around seven times higher in comparison to HCs (p < 0.0001). The HCs with genotype 'AA' of SNP rs1861493 were found with higher plasma IFN-γ levels than 'AG/GG' genotype (p = 0.023). In conclusion, the results suggest the association of rs1861494 (C/T) and rs2069718 (C/T) SNPs of IFN-γ with TB and genotype 'AA' of rs1861493 is associated with higher plasma IFN-γ levels in the population of Himachal Pradesh, India.

Placental genomics mediates genetic associations with complex health traits and disease.

As the master regulator in utero, the placenta is core to the Developmental Origins of Health and Disease (DOHaD) hypothesis but is historically understudied. To identify placental gene-trait associations (GTAs) across the life course, we perform distal mediator-enriched transcriptome-wide association studies (TWAS) for 40 traits, integrating placental multi-omics from the Extremely Low Gestational Age Newborn Study. At [Formula: see text], we detect 248 GTAs, mostly for neonatal and metabolic traits, across 176 genes, enriched for cell growth and immunological pathways. In aggregate, genetic effects mediated by placental expression significantly explain 4 early-life traits but no later-in-life traits. 89 GTAs show significant mediation through distal genetic variants, identifying hypotheses for distal regulation of GTAs. Investigation of one hypothesis in human placenta-derived choriocarcinoma cells reveal that knockdown of mediator gene EPS15 upregulates predicted targets SPATA13 and FAM214A, both associated with waist-hip ratio in TWAS, and multiple genes involved in metabolic pathways. These results suggest profound health impacts of placental genomic regulation in developmental programming across the life course.

Variation in caprine KRTAP1-3 and its association with cashmere fibre diameter.

Keratin-associated proteins (KAPs) are components of cashmere fibres. The gene encoding the KAP1-3 protein (KRTAP1-3) has been described in goats, but little is known about sequence variation in this gene and if it affects cashmere fibre traits. In this study, we used a polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) technique to screen for nucleotide sequence variation in caprine KRTAP1-3 in 327 Longdong cashmere goats, then analysed association between the genetic variation that was revealed and some cashmere fibre traits. Six PCR-SSCP patterns representing six different variant sequences of KRTAP1-3 (named A to F) were revealed. Among these variant sequences, seven single nucleotide polymorphisms (SNPs) were detected, with two of them being non-synonymous. Goats with genotype AC had higher mean fibre diameter (MFD) than those with genotype AB (P < 0.001), while goats with genotype AB had higher MFD than those with AA (P < 0.001). The presence of C (P < 0.001) and B (P = 0.006) in a genotype was associated with increased MFD, and together this suggests that variation in caprine KRTAP1-3 affects the key fibre trait of MFD.

Portability of 245 polygenic scores when derived from the UK Biobank and applied to 9 ancestry groups from the same cohort.

The low portability of polygenic scores (PGSs) across global populations is a major concern that must be addressed before PGSs can be used for everyone in the clinic. Indeed, prediction accuracy has been shown to decay as a function of the genetic distance between the training and test cohorts. However, such cohorts differ not only in their genetic distance but also in their geographical distance and their data collection and assaying, conflating multiple factors. In this study, we examine the extent to which PGSs are transferable between ancestries by deriving polygenic scores for 245 curated traits from the UK Biobank data and applying them in nine ancestry groups from the same cohort. By restricting both training and testing to the UK Biobank data, we reduce the risk of environmental and genotyping confounding from using different cohorts. We define the nine ancestry groups at a sub-continental level, based on a simple, robust, and effective method that we introduce here. We then apply two different predictive methods to derive polygenic scores for all 245 phenotypes and show a systematic and dramatic reduction in portability of PGSs trained using Northwestern European individuals and applied to nine ancestry groups. These analyses demonstrate that prediction already drops off within European ancestries and reduces globally in proportion to genetic distance. Altogether, our study provides unique and robust insights into the PGS portability problem.

Photoreceptor degeneration in ABCA4-associated retinopathy and its genetic correlates.

BACKGROUNDOutcome measures sensitive to disease progression are needed for ATP-binding cassette, sub-family A, member 4-associated (ABCA4-associated) retinopathy. We aimed to quantify ellipsoid zone (EZ) loss and photoreceptor degeneration beyond EZ-loss in ABCA4-associated retinopathy and investigate associations between photoreceptor degeneration, genotype, and age.METHODSWe analyzed 132 eyes from 66 patients (of 67 enrolled) with molecularly confirmed ABCA4-associated retinopathy from a prospective natural history study with a median [IQR] follow-up of 4.2 years [3.1, 5.1]. Longitudinal spectral-domain optical coherence tomography volume scans (37 B-scans, 30° × 15°) were segmented using a deep learning (DL) approach. For genotype-phenotype analysis, a model of ABCA4 variants was applied with the age of criterion EZ-loss (6.25 mm2) as the dependent variable.RESULTSPatients exhibited an average (square-root-transformed) EZ-loss progression rate of [95% CI] 0.09 mm/y [0.06, 0.11]. Outer nuclear layer (ONL) thinning extended beyond the area of EZ-loss. The average distance from the EZ-loss boundary to normalization of ONL thickness (to ±2 z score units) was 3.20° [2.53, 3.87]. Inner segment (IS) and outer segment (OS) thinning was less pronounced, with an average distance from the EZ-loss boundary to layer thickness normalization of 1.20° [0.91, 1.48] for the IS and 0.60° [0.49, 0.72] for the OS. An additive model of allele severity explained 52.7% of variability in the age of criterion EZ-loss.CONCLUSIONPatients with ABCA4-associated retinopathy exhibited significant alterations of photoreceptors outside of EZ-loss. DL-based analysis of photoreceptor laminae may help monitor disease progression and estimate the severity of ABCA4 variants.TRIAL REGISTRATIONClinicalTrials.gov identifier: NCT01736293.FUNDINGNational Eye Institute Intramural Research Program and German Research Foundation grant PF950/1-1.

Seipin Deficiency as a Model of Severe Adipocyte Dysfunction: Lessons from Rodent Models and Teaching for Human Disease.

Obesity prevalence is increasing worldwide, leading to cardiometabolic morbidities. Adipocyte dysfunction, impairing white adipose tissue (WAT) expandability and metabolic flexibility, is central in the development of obesity-related metabolic complications. Rare syndromes of lipodystrophy characterized by an extreme paucity of functional adipose tissue should be considered as primary adipocyte dysfunction diseases. Berardinelli-Seip congenital lipodystrophy (BSCL) is the most severe form with a near absence of WAT associated with cardiometabolic complications such as insulin resistance, liver steatosis, dyslipidemia, and cardiomyopathy. Twenty years ago, mutations in the BSCL2 gene have been identified as the cause of BSCL in human. BSCL2 encodes seipin, an endoplasmic reticulum (ER) anchored protein whose function was unknown back then. Studies of seipin knockout mice or rats demonstrated how seipin deficiency leads to severe lipodystrophy and to cardiometabolic complications. At the cellular levels, seipin is organized in multimers that are particularly enriched at ER/lipid droplet and ER/mitochondria contact sites. Seipin deficiency impairs both adipocyte differentiation and mature adipocyte maintenance. Experiments using adipose tissue transplantation in seipin knockout mice and tissue-specific deletion of seipin have provided a large body of evidence that liver steatosis, cardiomyopathy, and renal injury, classical diabetic complications, are all consequences of lipodystrophy. Rare adipocyte dysfunctions such as in BSCL are the key paradigm to unravel the pathways that control adipocyte homeostasis. The knowledge gathered through the study of these pathologies may bring new strategies to maintain and improve adipose tissue expandability.

SNP characteristics and validation success in genome wide association studies.

Genome wide association studies (GWASs) have identified tens of thousands of single nucleotide polymorphisms (SNPs) associated with human diseases and characteristics. A significant fraction of GWAS findings can be false positives. The gold standard for true positives is an independent validation. The goal of this study was to identify SNP features associated with validation success. Summary statistics from the Catalog of Published GWASs were used in the analysis. Since our goal was an analysis of reproducibility, we focused on the diseases/phenotypes targeted by at least 10 GWASs. GWASs were arranged in discovery-validation pairs based on the time of publication, with the discovery GWAS published before validation. We used four definitions of the validation success that differ by stringency. Associations of SNP features with validation success were consistent across the definitions. The strongest predictor of SNP validation was the level of statistical significance in the discovery GWAS. The magnitude of the effect size was associated with validation success in a non-linear manner. SNPs with risk allele frequencies in the range 30-70% showed a higher validation success rate compared to rarer or more common SNPs. Missense, 5'UTR, stop gained, and SNPs located in transcription factor binding sites had a higher validation success rate compared to intergenic, intronic and synonymous SNPs. There was a positive association between validation success and the level of evolutionary conservation of the sites. In addition, validation success was higher when discovery and validation GWASs targeted the same ethnicity. All predictors of validation success remained significant in a multivariate logistic regression model indicating their independent contribution. To conclude, we identified SNP features predicting validation success of GWAS hits. These features can be used to select SNPs for validation and downstream functional studies.

Leveraging Allele-Specific Expression for Therapeutic Response Gene Discovery in Glioblastoma.

Glioblastoma is the most prevalent primary malignant brain tumor in adults and is characterized by poor prognosis and universal tumor recurrence. Effective glioblastoma treatments are lacking, in part due to somatic mutations and epigenetic reprogramming that alter gene expression and confer drug resistance. To investigate recurrently dysregulated genes in glioblastoma, we interrogated allele-specific expression (ASE), the difference in expression between two alleles of a gene, in glioblastoma stem cells (GSC) derived from 43 patients. A total of 118 genes were found with recurrent ASE preferentially in GSCs compared with normal tissues. These genes were enriched for apoptotic regulators, including schlafen family member 11 (SLFN11). Loss of SLFN11 gene expression was associated with aberrant promoter methylation and conferred resistance to chemotherapy and PARP inhibition. Conversely, low SLFN11 expression rendered GSCs susceptible to the oncolytic flavivirus Zika. This discovery effort based upon ASE revealed novel points of vulnerability in GSCs, suggesting a potential alternative treatment strategy for chemotherapy-resistant glioblastoma. SIGNIFICANCE: Assessing allele-specific expression reveals genes with recurrent cis-regulatory changes that are enriched in glioblastoma stem cells, including SLFN11, which modulates chemotherapy resistance and susceptibility to the oncolytic Zika virus.

First case series of Polish patients with cerebrotendinous xanthomatosis and systematic review of cases from the 21st century.

Cerebrotendinous xanthomatosis (CTX) is an inborn error of metabolism caused by recessive variants in the cytochrome P450 CYP27A1 gene. CTX is said to manifest with childhood-onset chronic diarrhea and the classic triad of juvenile-onset cataracts, Achilles tendons xanthomas, and progressive ataxia. It is currently one of the few inherited neurometabolic disorders amenable to a specific treatment. The diagnosis may be significantly delayed resulting in permanent neurological impairment. A retrospective review of the clinical characteristics and diagnostic findings in case series of six Polish patients with CTX. Additional retrospective review of symptoms and pathogenic variants of 568 CTX available cases and case series from the past 20 years. To the best of our knowledge, this is the widest review of CTX cases reported in years 2000-2021. We report the largest cohort of Polish patients ever published, with the identification of two hot-spot mutations. During the review of available 568 cases, we found significant differences in the clinical phenotypes and the localization of variants within the gene between Asian and non-Asian populations. These findings may facilitate molecular testing in the Polish and Asian populations. Invariably better screening for CTX and wider awareness is needed.

Identification of diagnostic signatures in ulcerative colitis patients via bioinformatic analysis integrated with machine learning.

Ulcerative colitis (UC) is an immune-related disorder with enhanced prevalence globally. Early diagnosis is critical for the effective treatment of UC. However, it still lacks specific diagnostic signatures. The aim of our study was to explore efficient signatures and construct the diagnostic model for UC. Microarray data of GSE87473 and GSE48634, which were obtained from tissue biopsy samples, were downloaded from the Gene Expression Omnibus (GEO), and differently expressed genes (DEGs), GO, and KEGG analyses were performed. We constructed the PPI network via STRING database. The immune infiltration of the samples was evaluated using CIBERSORT methods combined with the LM22 feature matrix. The logistic regression model was constructed, with the expression of selected genes as the predictor variable, and the UC occurrence as the responsive variable. As a result, a total of 126 DEGs between the UC patients and normal counterparts were identified. The GO and KEGG analysis revealed that multiple biological processes, such as antimicrobial humoral immune response mediated by antimicrobial peptide and IL-17 signaling pathway, were enriched. The infiltration of eight immune cell types (B cells naive, Dendritic.cells.activated, Macrophages.M0, Macrophages.M2, Mast.cells.resting, Neutrophils, Plasma.cells, and T.cells.follicular.helper) was significantly different between patients with UC and normal counterparts. The top 50 most significant DEGs were selected for the construction of the PPI network. The average AUC of the logistic regression model in the fivefold cross-validation was 0.8497 in the training set, GSE87473. The AUC of another independent verification set of GSE48634 from the GEO database was 0.7208. In conclusion, we identified potential hub genes, including REG3A, REG1A, DEFA6, REG1B, and DEFA5, which might be significantly associated with UC progression. The logistic regression model based on the five genes could reliably diagnose UC patients.

Functional Gly297Ser Variant of the Physiological Dysglycemic Peptide Pancreastatin Is a Novel Risk Factor for Cardiometabolic Disorders.

Pancreastatin (PST), a chromogranin A-derived potent physiological dysglycemic peptide, regulates glucose/insulin homeostasis. We have identified a nonsynonymous functional PST variant (p.Gly297Ser; rs9658664) that occurs in a large section of human populations. Association analysis of this single nucleotide polymorphism with cardiovascular/metabolic disease states in Indian populations (n = 4,300 subjects) displays elevated plasma glucose, glycosylated hemoglobin, diastolic blood pressure, and catecholamines in Gly/Ser subjects as compared with wild-type individuals (Gly/Gly). Consistently, the 297Ser allele confers an increased risk (∼1.3-1.6-fold) for type 2 diabetes/hypertension/coronary artery disease/metabolic syndrome. In corroboration, the variant peptide (PST-297S) displays gain-of-potency in several cellular events relevant for cardiometabolic disorders (e.g., increased expression of gluconeogenic genes, increased catecholamine secretion, and greater inhibition of insulin-stimulated glucose uptake) than the wild-type peptide. Computational docking analysis and molecular dynamics simulations show higher affinity binding of PST-297S peptide with glucose-regulated protein 78 (GRP78) and insulin receptor than the wild-type peptide, providing a mechanistic basis for the enhanced activity of the variant peptide. In vitro binding assays validate these in silico predictions of PST peptides binding to GRP78 and insulin receptor. In conclusion, the PST 297Ser allele influences cardiovascular/metabolic phenotypes and emerges as a novel risk factor for type 2 diabetes/hypertension/coronary artery disease in human populations.

Evaluating the role of ARSA in Chinese patients with Parkinson's disease.

Recent studies have suggested ARSA, a gene responsible for metachromatic leukodystrophy, could be a genetic modifier of Parkinson's disease (PD) pathogenesis, acting as a molecular chaperone for α-synuclein. To elucidate the role of ARSA variants in PD, we did a comprehensive analysis of ARSA variants by performing next-generation sequencing on 477 PD families, 1440 sporadic early-onset PD patients and 1962 sporadic late-onset PD patients and 2636 controls from Chinese mainland, as well as the association between ARSA variants and cognitive function of PD patients. We identified 2 familial PD following autosomal dominant inherence carrying rare variants of ARSA, but they had limited clinical significance. We detected a total of 81 coding variants of ARSA in our subjects but none of the identified variants were associated with either susceptibility or cognitive performance of PD, while loss-of-function variants showed slightly increased burden in late-onset PD (0.25% vs. 0%, p = 0.08). Our results suggested ARSA may not play important roles in PD of Chinese population.

A new era in functional genomics screens.

The past 25 years of genomics research first revealed which genes are encoded by the human genome and then a detailed catalogue of human genome variation associated with many diseases. Despite this, the function of many genes and gene regulatory elements remains poorly characterized, which limits our ability to apply these insights to human disease. The advent of new CRISPR functional genomics tools allows for scalable and multiplexable characterization of genes and gene regulatory elements encoded by the human genome. These approaches promise to reveal mechanisms of gene function and regulation, and to enable exploration of how genes work together to modulate complex phenotypes.