Transcriptomic Profiling of Acute Cold Stress-Induced Disease Resistance (SIDR) Genes and Pathways in the Grapevine Powdery Mildew Pathosystem.

Temperatures from 2 to 8°C transiently induce quantitative resistance to powdery mildew in several host species (cold stress-induced disease resistance [SIDR]). Although cold SIDR events occur in vineyards worldwide an average of 14 to 21 times after budbreak of grapevine and can significantly delay grapevine powdery mildew (Erysiphe necator) epidemics, its molecular basis was poorly understood. We characterized the biology underlying the Vitis vinifera cold SIDR phenotype-which peaks at 24 h post-cold (hpc) treatment and results in a 22 to 28% reduction in spore penetration success-through highly replicated (n = 8 to 10) RNA sequencing experiments. This phenotype was accompanied by a sweeping transcriptional downregulation of photosynthesis-associated pathways whereas starch and sugar metabolism pathways remained largely unaffected, suggesting a transient imbalance in host metabolism and a suboptimal target for pathogen establishment. Twenty-six cold-responsive genes peaked in their differential expression at the 24-hpc time point. Finally, a subset of genes associated with nutrient and amino acid transport accounted for four of the eight most downregulated transcripts, including two nodulin 1A gene precursors, a nodulin MtN21 precursor, and a Dynein light chain 1 motor protein precursor. Reduced transport could exacerbate localized nutrient sinks that would again be transiently suboptimal for pathogen growth. This study links the transient cold SIDR phenotype to underlying transcriptional changes and provides an experimental framework and library of candidate genes to further explore cold SIDR in several systems, with an ultimate goal of identifying novel breeding or management targets for reduced disease.

Global Proteomic Profiling of Salmonella Infection by a Giant Phage.

The 240-kb Salmonella phage SPN3US genome encodes 264 gene products, many of which are functionally uncharacterized. We have previously used mass spectrometry to define the proteomes of wild-type and mutant forms of the SPN3US virion. In this study, we sought to determine whether this technique was suitable for the characterization of the SPN3US proteome during liquid infection. Mass spectrometry of SPN3US-infected cells identified 232 SPN3US and 1,994 Salmonella proteins. SPN3US proteins with related functions, such as proteins with roles in DNA replication, transcription, and virion formation, were coordinately expressed in a temporal manner. Mass spectral counts showed the four most abundant SPN3US proteins to be the major capsid protein, two head ejection proteins, and the functionally unassigned protein gp22. This high abundance of gp22 in infected bacteria contrasted with its absence from mature virions, suggesting that it might be the scaffold protein, an essential head morphogenesis protein yet to be identified in giant phages. We identified homologs to SPN3US gp22 in 45 related giant phages, including ϕKZ, whose counterpart is also abundant in infected bacteria but absent in the virion. We determined the ϕKZ counterpart to be cleaved in vitro by its prohead protease, an event that has been observed to promote head maturation of some other phages. Our findings are consistent with a scaffold protein assignment for SPN3US gp22, although direct evidence is required for its confirmation. These studies demonstrate the power of mass spectral analyses for facilitating the acquisition of new knowledge into the molecular events of viral infection.IMPORTANCE "Giant" phages with genomes >200 kb are being isolated in increasing numbers from a range of environments. With hosts such as Salmonella enterica, Pseudomonas aeruginosa, and Erwinia amylovora, these phages are of interest for phage therapy of multidrug-resistant pathogens. However, our understanding of how these complex phages interact with their hosts is impeded by the proportion (∼80%) of their gene products that are functionally uncharacterized. To develop the repertoire of techniques for analysis of phages, we analyzed a liquid infection of Salmonella phage SPN3US (240-kb genome) using third-generation mass spectrometry. We observed the temporal production of phage proteins whose genes collectively represent 96% of the SPN3US genome. These findings demonstrate the sensitivity of mass spectrometry for global proteomic profiling of virus-infected cells, and the identification of a candidate for a major head morphogenesis protein will facilitate further studies into giant phage head assembly.

Identification of Essential Genes in the Salmonella Phage SPN3US Reveals Novel Insights into Giant Phage Head Structure and Assembly.

Giant tailed bacterial viruses, or phages, such as Pseudomonas aeruginosa phage ϕKZ, have long genomes packaged into large, atypical virions. Many aspects of ϕKZ and related phage biology are poorly understood, mostly due to the fact that the functions of the majority of their proteins are unknown. We hypothesized that the Salmonella enterica phage SPN3US could be a useful model phage to address this gap in knowledge. The 240-kb SPN3US genome shares a core set of 91 genes with ϕKZ and related phages, ∼61 of which are virion genes, consistent with the expectation that virion complexity is an ancient, conserved feature. Nucleotide sequencing of 18 mutants enabled assignment of 13 genes as essential, information which could not have been determined by sequence-based searches for 11 genes. Proteome analyses of two SPN3US virion protein mutants with knockouts in 64 and 241 provided new insight into the composition and assembly of giant phage heads. The 64 mutant analyses revealed all the genetic determinants required for assembly of the SPN3US head and a likely head-tail joining role for gp64, and its homologs in related phages, due to the tailless-particle phenotype produced. Analyses of the mutation in 241, which encodes an RNA polymerase ß subunit, revealed that without this subunit, no other subunits are assembled into the head, and enabled identification of a "missing" ß' subunit domain. These findings support SPN3US as an excellent model for giant phage research, laying the groundwork for future analyses of their highly unusual virions, host interactions, and evolution. IMPORTANCE: In recent years, there has been a paradigm shift in virology with the realization that extremely large viruses infecting prokaryotes (giant phages) can be found in many environments. A group of phages related to the prototype giant phage ϕKZ are of great interest due to their virions being among the most complex of prokaryotic viruses and their potential for biocontrol and phage therapy applications. Our understanding of the biology of these phages is limited, as a large proportion of their proteins have not been characterized and/or have been deemed putative without any experimental verification. In this study, we analyzed Salmonella phage SPN3US using a combination of genomics, genetics, and proteomics and in doing so revealed new information regarding giant phage head structure and assembly and virion RNA polymerase composition. Our findings demonstrate the suitability of SPN3US as a model phage for the growing group of phages related to ϕKZ.

Whole-Genome Sequence, Assembly and Annotation of an Invasive Plant, Lonicera maackii (Amur Honeysuckle).

The invasive species Lonicera maackii (Amur Honeysuckle) is an increasing problem sweeping from the eastern United States toward the west, impacting normal forest development and animal survival across multiple taxa. Little is known about the genomics of this species, although a related invasive, Lonicera japonica, has been sequenced. Understanding the genomic foundation of the Lonicera maackii species could help us understand the biochemistry and life history that are the underpinnings of invasive success, as well as potential vulnerabilities and strengths which could guide research and development to control its spread. Here we present a draft, but high-quality, short-read whole-genome sequence, assembly, and annotation of Lonicera maackii, demonstrating that inexpensive and rapid short-read technologies can be successfully used in invasive species research. Despite being a short-read assembly, the genome length (7.93 × 108) and completeness (estimated as 90.2-92.1% by BUSCO and Merqury) are close to the previously published chromosome-level sequencing of L. japonica. No bias, by means of a Gene Ontology analysis, was identified among missing BUSCOs. A duplication of the 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase gene in both Lonicera species is identified, and the potential impact on controlling these invasive species is discussed. Future prospects for a diversity analysis of invasive species is also discussed.

Comparison of Short-Read Sequence Aligners Indicates Strengths and Weaknesses for Biologists to Consider.

Aligning short-read sequences is the foundational step to most genomic and transcriptomic analyses, but not all tools perform equally, and choosing among the growing body of available tools can be daunting. Here, in order to increase awareness in the research community, we discuss the merits of common algorithms and programs in a way that should be approachable to biologists with limited experience in bioinformatics. We will only in passing consider the effects of data cleanup, a precursor analysis to most alignment tools, and no consideration will be given to downstream processing of the aligned fragments. To compare aligners [Bowtie2, Burrows Wheeler Aligner (BWA), HISAT2, MUMmer4, STAR, and TopHat2], an RNA-seq dataset was used containing data from 48 geographically distinct samples of the grapevine powdery mildew fungus Erysiphe necator. Based on alignment rate and gene coverage, all aligners performed well with the exception of TopHat2, which HISAT2 superseded. BWA perhaps had the best performance in these metrics, except for longer transcripts (>500 bp) for which HISAT2 and STAR performed well. HISAT2 was ~3-fold faster than the next fastest aligner in runtime, which we consider a secondary factor in most alignments. At the end, this direct comparison of commonly used aligners illustrates key considerations when choosing which tool to use for the specific sequencing data and objectives. No single tool meets all needs for every user, and there are many quality aligners available.

The epiphytic microbiota of sour rot-affected grapes differs minimally from that of healthy grapes, indicating causal organisms are already present on healthy berries.

Sour rot is a disease complex produced by an interaction between grape berries and various species of yeast and acetic acid bacteria in the presence of Drosophila fruit flies. While yeast and bacteria are consistently found on healthy grape berries worldwide, we explored whether the composition of these epiphytic communities differed depending on the presence or absence of sour rot symptoms. Using high-throughput sequencing, we characterized the microbiome of sour rot-affected grapes from two geographical areas across two years. In 2015 and 2016, both healthy and sour rot-affected berries were collected from commercial and research vineyards in Geneva, NY and commercial vineyards in Tasmania, AUS. In this experiment, all associated organisms grouped together primarily by location, and not by presence/absence of symptoms or cultivar. The predominant difference between asymptomatic and symptomatic samples, regardless of location, was the abundance of Acetobacter species, which were significantly more plentiful in the symptomatic samples. Yeast genera such as Candida, Hanseniaspora, Pichia and Saccharomyces were abundant in both sets of samples, but varied by region. The consistent presence of yeast species and the increased abundance of acetic acid-generating bacteria is consistent with our understanding of their etiological role in sour rot development. In 2016, diseased grapes also were collected from vineyards in Fredonia, NY, and Modesto, CA. Consistent with our comparison study, all associated organisms again grouped together primarily by location. Yeast genera such as Candida, Hanseniaspora, Pichia and Saccharomyces were abundant in both sets of samples, but varied by region. The consistent presence of yeast species and the abundance of acetic acid-generating bacteria in both experiments is consistent with our understanding of their etiological role in sour rot development.

To Be or Not To Be T4: Evidence of a Complex Evolutionary Pathway of Head Structure and Assembly in Giant Salmonella Virus SPN3US.

Giant Salmonella phage SPN3US has a 240-kb dsDNA genome and a large complex virion composed of many proteins for which the functions of most are undefined. We recently determined that SPN3US shares a core set of genes with related giant phages and sequenced and characterized 18 amber mutants to facilitate its use as a genetic model system. Notably, SPN3US and related giant phages contain a bolus of ejection proteins within their heads, including a multi-subunit virion RNA polymerase (vRNAP), that enter the host cell with the DNA during infection. In this study, we characterized the SPN3US virion using mass spectrometry to gain insight into its head composition and the features that its head shares with those of related giant phages and with T4 phage. SPN3US has only homologs to the T4 proteins critical for prohead shell formation, the portal and major capsid proteins, as well as to the major enzymes essential for head maturation, the prohead protease and large terminase subunit. Eight of ~50 SPN3US head proteins were found to undergo proteolytic processing at a cleavage motif by the prohead protease gp245. Gp245 undergoes auto-cleavage of its C-terminus, suggesting this is a conserved activation and/or maturation feature of related phage proteases. Analyses of essential head gene mutants showed that the five subunits of the vRNAP must be assembled for any subunit to be incorporated into the prohead, although the assembled vRNAP must then undergo subsequent major conformational rearrangements in the DNA packed capsid to allow ejection through the ~30 Å diameter tail tube for transcription from the injected DNA. In addition, ejection protein candidate gp243 was found to play a critical role in head assembly. Our analyses of the vRNAP and gp243 mutants highlighted an unexpected dichotomy in giant phage head maturation: while all analyzed giant phages have a homologous protease that processes major capsid and portal proteins, processing of ejection proteins is not always a stable/defining feature. Our identification in SPN3US, and related phages, of a diverged paralog to the prohead protease further hints toward a complicated evolutionary pathway for giant phage head structure and assembly.

A high productivity/low maintenance approach to high-performance computation for biomedicine: four case studies.

The rapid advances in high-throughput biotechnologies such as DNA microarrays and mass spectrometry have generated vast amounts of data ranging from gene expression to proteomics data. The large size and complexity involved in analyzing such data demand a significant amount of computing power. High-performance computation (HPC) is an attractive and increasingly affordable approach to help meet this challenge. There is a spectrum of techniques that can be used to achieve computational speedup with varying degrees of impact in terms of how drastic a change is required to allow the software to run on an HPC platform. This paper describes a high- productivity/low-maintenance (HP/LM) approach to HPC that is based on establishing a collaborative relationship between the bioinformaticist and HPC expert that respects the former's codes and minimizes the latter's efforts. The goal of this approach is to make it easy for bioinformatics researchers to continue to make iterative refinements to their programs, while still being able to take advantage of HPC. The paper describes our experience applying these HP/LM techniques in four bioinformatics case studies: (1) genome-wide sequence comparison using Blast, (2) identification of biomarkers based on statistical analysis of large mass spectrometry data sets, (3) complex genetic analysis involving ordinal phenotypes, (4) large-scale assessment of the effect of possible errors in analyzing microarray data. The case studies illustrate how the HP/LM approach can be applied to a range of representative bioinformatics applications and how the approach can lead to significant speedup of computationally intensive bioinformatics applications, while making only modest modifications to the programs themselves.

Handling multiple testing while interpreting microarrays with the Gene Ontology Database.

BACKGROUND: The development of software tools that analyze microarray data in the context of genetic knowledgebases is being pursued by multiple research groups using different methods. A common problem for many of these tools is how to correct for multiple statistical testing since simple corrections are overly conservative and more sophisticated corrections are currently impractical. A careful study of the nature of the distribution one would expect by chance, such as by a simulation study, may be able to guide the development of an appropriate correction that is not overly time consuming computationally. RESULTS: We present the results from a preliminary study of the distribution one would expect for analyzing sets of genes extracted from Drosophila, S. cerevisiae, Wormbase, and Gramene databases using the Gene Ontology Database. CONCLUSIONS: We found that the estimated distribution is not regular and is not predictable outside of a particular set of genes. Permutation-based simulations may be necessary to determine the confidence in results of such analyses.

Kidney tumor biomarkers revealed by simultaneous multiple matrix metabolomics analysis.

Metabolomics is increasingly being used in cancer biology for biomarker discovery and identification of potential novel therapeutic targets. However, a systematic metabolomics study of multiple biofluids to determine their interrelationships and to describe their use as tumor proxies is lacking. Using a mouse xenograft model of kidney cancer, characterized by subcapsular implantation of Caki-1 clear cell human kidney cancer cells, we examined tissue, serum, and urine all obtained simultaneously at baseline (urine) and at, or close to, animal sacrifice (urine, tissue, and plasma). Uniform metabolomics analysis of all three "matrices" was accomplished using gas chromatography- and liquid chromatography-mass spectrometry. Of all the metabolites identified (267 in tissue, 246 in serum, and 267 in urine), 89 were detected in all 3 matrices, and the majority was altered in the same direction. Heat maps of individual metabolites showed that alterations in serum were more closely related to tissue than was urine. Two metabolites, cinnamoylglycine and nicotinamide, were concordantly and significantly (when corrected for multiple testing) altered in tissue and serum, and cysteine-glutathione disulfide showed the highest change (232.4-fold in tissue) of any metabolite. On the basis of these and other considerations, three pathways were chosen for biologic validation of the metabolomic data, resulting in potential therapeutic target identification. These data show that serum metabolomics analysis is a more accurate proxy for tissue changes than urine and that tryptophan degradation (yielding anti-inflammatory metabolites) is highly represented in renal cell carcinoma, and support the concept that PPAR-α antagonism may be a potential therapeutic approach for this disease.

Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer.

Kidney cancer is the seventh most common cancer in the Western world, its incidence is increasing, and it is frequently metastatic at presentation, at which stage patient survival statistics are grim. In addition, there are no useful biofluid markers for this disease, such that diagnosis is dependent on imaging techniques that are not generally used for screening. In the present study, we use metabolomics techniques to identify metabolites in kidney cancer patients' urine, which appear at different levels (when normalized to account for urine volume and concentration) from the same metabolites in nonkidney cancer patients. We found that quinolinate, 4-hydroxybenzoate, and gentisate are differentially expressed at a false discovery rate of 0.26, and these metabolites are involved in common pathways of specific amino acid and energetic metabolism, consistent with high tumor protein breakdown and utilization, and the Warburg effect. When added to four different (three kidney cancer-derived and one "normal") cell lines, several of the significantly altered metabolites, quinolinate, α-ketoglutarate, and gentisate, showed increased or unchanged cell proliferation that was cell line-dependent. Further evaluation of the global metabolomics analysis, as well as confirmation of the specific potential biomarkers using a larger sample size, will lead to new avenues of kidney cancer diagnosis and therapy.

Genes and biochemical pathways in human skeletal muscle affecting resting energy expenditure and fuel partitioning.

Genes influencing resting energy expenditure (REE) and respiratory quotient (RQ) represent candidate genes for obesity and the metabolic syndrome because of the involvement of these traits in energy balance and substrate oxidation. We aim to explore the molecular basis for individual variation in REE and fuel partitioning as reflected by RQ. We performed microarray studies in human vastus lateralis muscle biopsies from 40 healthy subjects with measured REE and RQ values. We identified 2,392 and 1,115 genes significantly correlated with REE and RQ, respectively. Genes correlated with REE and RQ encompass a broad array of functions, including carbohydrate and lipid metabolism, gene expression, mitochondrial processes, and membrane transport. Microarray pathway analysis revealed that REE was positively correlated with upregulation of G protein-coupled receptor signaling (meet criteria/total genes: 65 of 283) involved in autonomic nervous system functions, including those receptors mediating adrenergic, dopamine, γ-aminobutyric acid (GABA), neuropeptide Y (NPY), and serotonin action (meet criteria/total genes: 46 of 176). Reduced REE was associated with an increase in genes participating in ubiquitin-proteasome-dependent proteolytic pathways (58 of 232). Serine-type peptidase activity (9 of 76) was positively correlated with RQ, while genes involved in the protein phosphatase type 2A complex (4 of 9), mitochondrial function and cellular respiration (38 of 315), and unfolded protein binding (19 of 97) were associated with reduced RQ values and a preference for lipid fuel metabolism. Individual variations in whole body REE and RQ are regulated by differential expressions of specific genes and pathways intrinsic to skeletal muscle.

Evidence of positive selection on a class I ADH locus.

The alcohol dehydrogenase (ADH) family of enzymes catalyzes the reversible oxidation of alcohol to acetaldehyde. Seven ADH genes exist in a segment of ~370 kb on 4q21. Products of the three class I ADH genes that share 95% sequence identity are believed to play the major role in the first step of ethanol metabolism. Because the common belief that selection has operated at the ADH1B*47His allele in East Asian populations lacks direct biological or statistical evidence, we used genomic data to test the hypothesis. Data consisted of 54 single-nucleotide polymorphisms (SNPs) across the ADH clusters in a global sampling of 42 populations. Both the F(st) statistic and the long-range haplotype (LRH) test provided positive evidence of selection in several East Asian populations. The ADH1B Arg47His functional polymorphism has the highest F(st) of the 54 SNPs in the ADH cluster, and it is significantly above the mean F(st) of 382 presumably neutral sites tested on the same 42 population samples. The LRH test that uses cores including that site and extending on both sides also gives significant evidence of positive selection in some East Asian populations for a specific haplotype carrying the ADH1B*47His allele. Interestingly, this haplotype is present at a high frequency in only some East Asian populations, whereas the specific allele also exists in other East Asian populations and in the Near East and Europe but does not show evidence of selection with use of the LRH test. Although the ADH1B*47His allele conveys a well-confirmed protection against alcoholism, that modern phenotypic manifestation does not easily translate into a positive selective force, and the nature of that selective force, in the past and/or currently, remains speculative.

The effect of insulin on expression of genes and biochemical pathways in human skeletal muscle.

To study the insulin effects on gene expression in skeletal muscle, muscle biopsies were obtained from 20 insulin sensitive individuals before and after euglycemic hyperinsulinemic clamps. Using microarray analysis, we identified 779 insulin-responsive genes. Particularly noteworthy were effects on 70 transcription factors, and an extensive influence on genes involved in both protein synthesis and degradation. The genetic program in skeletal muscle also included effects on signal transduction, vesicular traffic and cytoskeletal function, and fuel metabolic pathways. Unexpected observations were the pervasive effects of insulin on genes involved in interacting pathways for polyamine and S-adenoslymethionine metabolism and genes involved in muscle development. We further confirmed that four insulin-responsive genes, RRAD, IGFBP5, INSIG1, and NGFI-B (NR4A1), were significantly up-regulated by insulin in cultured L6 skeletal muscle cells. Interestingly, insulin caused an accumulation of NGFI-B (NR4A1) protein in the nucleus where it functions as a transcription factor, without translocation to the cytoplasm to promote apoptosis. The role of NGFI-B (NR4A1) as a new potential mediator of insulin action highlights the need for greater understanding of nuclear transcription factors in insulin action.

Considerable haplotype diversity within the 23kb encompassing the ADH7 gene.

BACKGROUND: Of the seven known human alcohol dehydrogenase (ADH) genes, the non-liver expressed ADH7 gene codes for the enzyme with the highest maximal activity for ethanol. Previous study from our laboratory has suggested that ADH7 has an epistatic role for protection against alcoholism based on a single ADH7 SNP. METHODS: We have now studied seven SNPs, additional populations for the SNP previously examined, and six more new SNPs, across 23 kb of ADH7 in 38 population samples originating from different geographical regions of the world. RESULTS: The overall linkage disequilibrium is moderate to strong across this region even though considerable 7-SNP haplotype diversity is observed. This uncommonly high haplotype diversity is explained by high LD within each "half," the three upstream SNPs and the four downstream SNPs, but near randomization between the "halves." This division significantly simplified the haplotype pattern: only four major haplotypes account for almost all chromosomes in all populations in each "half." CONCLUSIONS: The low linkage disequilibrium between these two "halves" suggests multiple recombination(s) have occurred in this region, specifically, within intron 7. The absence of strong LD between the functional variation in ADH1B that is strongly associated with alcoholism and any of the variation in ADH7 supports the genetic independence of ADH7 in association studies. Thus, the previously observed epistatic effect of ADH7 cannot be explained by its linkage disequilibrium with a causative factor in ADH1B.

A proline-threonine substitution in codon 351 of ADH1C is common in Native Americans.

BACKGROUND: The alcohol dehydrogenase (ADH) genes have been repeatedly associated with protection against alcoholism. Until now, only four protein coding variants have been identified (ADH1C Arg271Gln, Ile349Val, ADH1B Arg47His, and Arg369Cys), and only two of these (ADH1CIle349Val and ADH1B Arg47His) have been routinely tested in association studies with alcoholism. METHODS: The new ADH1C*351Thr allele was identified by direct sequencing of DNA samples that gave different typing results for the ADH1C Ile349Val polymorphism with different typing protocols. RESULTS: A new coding variant has been identified at codon 351 of ADH1C. This allele is found in most Native American populations that we have studied with allele frequencies of the new ADH1C*351Thr allele as high as 26%. Only two instances of this allele have been seen in a large survey of African and Eurasian populations. CONCLUSIONS: The changes in charge, size, and rotational mobility caused by this amino acid substitution should be significant. Because this new variant codes for a new enzyme form in Native Americans, the kinetics of this enzyme should be studied and considered in studies of the role of in the protection against alcoholism in Native Americans.

ALFRED: An allele frequency database for anthropology.

The deluge of data from the human genome project (HGP) presents new opportunities for molecular anthropologists to study human variation through the promise of vast numbers of new polymorphisms (e.g., single nucleotide polymorphisms or SNPs). Collecting the resulting data into a single, easily accessible resource will be important to facilitate this research. We created a prototype Web-accessible database named ALFRED (ALelle FREquency Database, http://alfred.med.yale.edu/alfred/) to store and make publicly available allele frequency data on diverse polymorphic sites for many populations. In constructing this database, we considered many different concerns relating to the types of information needed for anthropology, population genetics, molecular genetics, and statistics, as well as issues of data integrity and ease of access to data. We also developed links to other Web-based databases as well as procedures for others to make links to the data in ALFRED. Here we present an overview of the issues considered and provisional solutions, as well as an example of data already available. It is our hope that this database will be useful for research and teaching in a wide range of fields, and that colleagues from various fields will contribute to making ALFRED an important resource for many studies as yet unforeseen.

Allelic variation at alcohol metabolism genes ( ADH1B, ADH1C, ALDH2) and alcohol dependence in an American Indian population.

Enzymes encoded by two gene families, alcohol dehydrogenase ( ADH) and aldehyde dehydrogenase ( ALDH), mediate alcohol metabolism in humans. Allelic variants have been identified that alter metabolic rates and influence risk for alcoholism. Specifically, ADH1B*47His (previously ADH2-2) and ALDH2-2 have been shown to confer protection against alcoholism, presumably through accumulation of acetaldehyde in the blood and a resultant 'flushing response' to alcohol consumption. In the current study, variants at ADH1B (previously ADH2), ADH1C (previously ADH3), and ALDH2 were assayed in DNA extracts from participants belonging to a Southwest American Indian tribe ( n=490) with a high prevalence of alcoholism. Each subject underwent a clinical interview for diagnosis of alcohol dependence, as well as evaluation of intermediate phenotypes such as binge drinking and flushing response to alcohol consumption. Detailed haplotypes were constructed and tested against alcohol dependence and related intermediate phenotypes using both association and linkage analysis. ADH and ALDH variants were also assayed in three Asian and one African population (no clinical data) in order to provide an evolutionary context for the haplotype data. Both linkage and association analysis identified several ADH1C alleles and a neighboring microsatellite marker that affected risk of alcohol dependence and were also related to binge drinking. These data strengthen the support for ADH as a candidate locus for alcohol dependence and suggest further productive study.