Jason G. Mezey

Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa

Asian rice, Oryza sativa is a cultivated, inbreeding species that feeds over half of the worlds population. Understanding the genetic basis of diverse physiological, developmental, and morphological traits provides the basis for improving yield, quality and sustainability of rice. Here we show the results of a genome-wide association study based on genotyping 44,100 SNP variants across 413 diverse accessions of O. sativa collected from 82 countries that were systematically phenotyped for 34 traits. Using cross-population-based mapping strategies, we identified dozens of common variants influencing numerous complex traits. Significant heterogeneity was observed in the genetic architecture associated with subpopulation structure and response to environment. This work establishes an open-source translational research platform for genome-wide association studies in rice that directly links molecular variation in genes and metabolic pathways with the germplasm resources needed to accelerate varietal development and crop improvement.

THE DIMENSIONALITY OF GENETIC VARIATION FOR WING SHAPE IN DROSOPHILA MELANOGASTER

Abstract Absolute constraints are limitations on genetic variation that preclude evolutionary change in some aspect of the phenotype. Absolute constraints may reflect complete absence of variation, lack of genetic variation that extends the range of phenotypes beyond some limit, or lack of additive genetic variation. This last type of absolute constraint is bidirectional, because the mean cannot evolve to be larger or smaller. Most traits do possess genetic variation, so bidirectional absolute constraints are most likely to be detected in a multivariate context, where they would reflect combinations of traits, or dimensions in phenotype space that cannot evolve. A bidirectional absolute constraint will cause the additive genetic covariance matrix (G) to have a rank less than the number of traits studied. In this study, we estimate the rank of the G‐matrix for 20 aspects of wing shape in Drosophila melanogaster. Our best estimates of matrix rank are 20 in both sexes. Lower 95% confidence intervals of rank are 17 for females and 18 for males. We therefore find little evidence of bidirectional absolute constraints. We discuss the importance of this result for resolving the relative roles of selection and drift processes versus constraints in the evolution of wing shape in Drosophila.

Automated measurement of Drosophila wings

BackgroundMany studies in evolutionary biology and genetics are limited by the rate at which phenotypic information can be acquired. The wings of Drosophila species are a favorable target for automated analysis because of the many interesting questions in evolution and development that can be addressed with them, and because of their simple structure.ResultsWe have developed an automated image analysis system (WINGMACHINE) that measures the positions of all the veins and the edges of the wing blade of Drosophilid flies. A video image is obtained with the aid of a simple suction device that immobilizes the wing of a live fly. Low-level processing is used to find the major intersections of the veins. High-level processing then optimizes the fit of an a priori B-spline model of wing shape. WINGMACHINE allows the measurement of 1 wing per minute, including handling, imaging, analysis, and data editing. The repeatabilities of 12 vein intersections averaged 86% in a sample of flies of the same species and sex.Comparison of 2400 wings of 25 Drosophilid species shows that wing shape is quite conservative within the group, but that almost all taxa are diagnosably different from one another. Wing shape retains some phylogenetic structure, although some species have shapes very different from closely related species. The WINGMACHINE system facilitates artificial selection experiments on complex aspects of wing shape. We selected on an index which is a function of 14 separate measurements of each wing. After 14 generations, we achieved a 15 S.D. difference between up and down-selected treatments.ConclusionWINGMACHINE enables rapid, highly repeatable measurements of wings in the family Drosophilidae. Our approach to image analysis may be applicable to a variety of biological objects that can be represented as a framework of connected lines.

Circulating endothelial microparticles as a measure of early lung destruction in cigarette smokers.

RATIONALE There is increasing evidence that emphysema is associated with primary loss of pulmonary capillary endothelium. Plasma levels of endothelial microparticles (EMPs), small vesicles released from activated or apoptotic endothelial cells, are elevated in vascular-related disorders. OBJECTIVES To evaluate whether plasma EMP levels are elevated in smokers with early lung destruction as assessed by normal spirometry but reduced diffusing capacity of the lung for carbon monoxide (Dl(co)). METHODS Lung health was assessed by pulmonary function tests (PFTs: spirometry, total lung capacity, Dl(co)) and chest X-ray; smoking status was assessed by urine nicotine and cotinine. EMP levels (CD42b(-)CD31(+) microparticles) were quantified as activated or apoptotic. The initial cohort (n = 92) included healthy nonsmokers (normal PFTs), healthy smokers (normal PFTs), and smokers with early evidence of lung destruction (normal spirometry, low Dl(co)). Two prospective cohorts were then tested: a group similar to the initial cohort and an HIV1(+) cohort. MEASUREMENTS AND MAIN RESULTS Healthy smokers had mildly increased levels of EMPs. Strikingly, 95% of smokers with normal spirometry, low Dl(co) had increased EMPs, with reduced CD62(+)/CD31(+) ratios (P < 10(-4)) and elevated CD42b(-)CD31(+) annexin V(+) EMPs (P < 10(-4)), suggesting derivation from endothelial apoptosis. Most elevated EMPs were angiotensin-converting enzyme positive, suggesting derivation from pulmonary capillaries. Both prospective cohorts confirmed the initial cohort data. CONCLUSIONS Plasma EMPs with apoptotic characteristics are elevated in smokers with normal spirometry but reduced Dl(co), consistent with the concept that emphysema is associated, in part, with capillary endothelium apoptosis, suggesting that the early development of emphysema might be monitored with plasma EMP levels.

BRAIN-DERIVED NEUROTROPHIC FACTOR AS A MODEL SYSTEM FOR EXAMINING GENE BY ENVIRONMENT INTERACTIONS ACROSS DEVELOPMENT

There has been a dramatic rise in gene x environment studies of human behavior over the past decade that have moved the field beyond simple nature versus nurture debates. These studies offer promise in accounting for more variability in behavioral and biological phenotypes than studies that focus on genetic or experiential factors alone. They also provide clues into mechanisms of modifying genetic risk or resilience in neurodevelopmental disorders. Yet, it is rare that these studies consider how these interactions change over the course of development. In this paper, we describe research that focuses on the impact of a polymorphism in a brain-derived neurotrophic factor (BDNF) gene, known to be involved in learning and development. Specifically we present findings that assess the effects of genotypic and environmental loadings on neuroanatomic and behavioral phenotypes across development. The findings illustrate the use of a genetic mouse model that mimics the human polymorphism, to constrain the interpretation of gene-environment interactions across development in humans.

Interpretation of the results of common principal components analyses.

Abstract Common principal components (CPC) analysis is a new tool for the comparison of phenotypic and genetic variance‐covariance matrices. CPC was developed as a method of data summarization, but frequently biologists would like to use the method to detect analogous patterns of trait correlation in multiple populations or species. To investigate the properties of CPC, we simulated data that reflect a set of causal factors. The CPC method performs as expected from a statistical point of view, but often gives results that are contrary to biological intuition. In general, CPC tends to underestimate the degree of structure that matrices share. Differences of trait variances and covariances due to a difference in a single causal factor in two otherwise identically structured datasets often cause CPC to declare the two datasets unrelated. Conversely, CPC could identify datasets as having the same structure when causal factors are different. Reordering of vectors before analysis can aid in the detection of patterns. We urge caution in the biological interpretation of CPC analysis results.

Four loci explain 83% of size variation in the horse.

Horse body size varies greatly due to intense selection within each breed. American Miniatures are less than one meter tall at the withers while Shires and Percherons can exceed two meters. The genetic basis for this variation is not known. We hypothesize that the breed population structure of the horse should simplify efforts to identify genes controlling size. In support of this, here we show with genome-wide association scans (GWAS) that genetic variation at just four loci can explain the great majority of horse size variation. Unlike humans, which are naturally reproducing and possess many genetic variants with weak effects on size, we show that horses, like other domestic mammals, carry just a small number of size loci with alleles of large effect. Furthermore, three of our horse size loci contain the LCORL, HMGA2 and ZFAT genes that have previously been found to control human height. The LCORL/NCAPG locus is also implicated in cattle growth and HMGA2 is associated with dog size. Extreme size diversification is a hallmark of domestication. Our results in the horse, complemented by the prior work in cattle and dog, serve to pinpoint those very few genes that have played major roles in the rapid evolution of size during domestication.

Whole-genome SNP association in the horse: identification of a deletion in myosin Va responsible for Lavender Foal Syndrome.

Lavender Foal Syndrome (LFS) is a lethal inherited disease of horses with a suspected autosomal recessive mode of inheritance. LFS has been primarily diagnosed in a subgroup of the Arabian breed, the Egyptian Arabian horse. The condition is characterized by multiple neurological abnormalities and a dilute coat color. Candidate genes based on comparative phenotypes in mice and humans include the ras-associated protein RAB27a (RAB27A) and myosin Va (MYO5A). Here we report mapping of the locus responsible for LFS using a small set of 36 horses segregating for LFS. These horses were genotyped using a newly available single nucleotide polymorphism (SNP) chip containing 56,402 discriminatory elements. The whole genome scan identified an associated region containing these two functional candidate genes. Exon sequencing of the MYO5A gene from an affected foal revealed a single base deletion in exon 30 that changes the reading frame and introduces a premature stop codon. A PCR–based Restriction Fragment Length Polymorphism (PCR–RFLP) assay was designed and used to investigate the frequency of the mutant gene. All affected horses tested were homozygous for this mutation. Heterozygous carriers were detected in high frequency in families segregating for this trait, and the frequency of carriers in unrelated Egyptian Arabians was 10.3%. The mapping and discovery of the LFS mutation represents the first successful use of whole-genome SNP scanning in the horse for any trait. The RFLP assay can be used to assist breeders in avoiding carrier-to-carrier matings and thus in preventing the birth of affected foals.

Patterns of ancestry, signatures of natural selection, and genetic association with stature in Western African pygmies.

African Pygmy groups show a distinctive pattern of phenotypic variation, including short stature, which is thought to reflect past adaptation to a tropical environment. Here, we analyze Illumina 1M SNP array data in three Western Pygmy populations from Cameroon and three neighboring Bantu-speaking agricultural populations with whom they have admixed. We infer genome-wide ancestry, scan for signals of positive selection, and perform targeted genetic association with measured height variation. We identify multiple regions throughout the genome that may have played a role in adaptive evolution, many of which contain loci with roles in growth hormone, insulin, and insulin-like growth factor signaling pathways, as well as immunity and neuroendocrine signaling involved in reproduction and metabolism. The most striking results are found on chromosome 3, which harbors a cluster of selection and association signals between approximately 45 and 60 Mb. This region also includes the positional candidate genes DOCK3, which is known to be associated with height variation in Europeans, and CISH, a negative regulator of cytokine signaling known to inhibit growth hormone-stimulated STAT5 signaling. Finally, pathway analysis for genes near the strongest signals of association with height indicates enrichment for loci involved in insulin and insulin-like growth factor signaling.

PCAdmix: Principal Components-Based Assignment of Ancestry along Each Chromosome in Individuals with Admixed Ancestry from Two or More Populations

Abstract Identifying ancestry along each chromosome in admixed individuals provides a wealth of information for understanding the population genetic history of admixture events and is valuable for admixture mapping and identifying recent targets of selection. We present PCAdmix (available at https://sites.google.com/site/pcadmix/home), a Principal Components-based algorithm for determining ancestry along each chromosome from a high-density, genome-wide set of phased single-nucleotide polymorphism (SNP) genotypes of admixed individuals. We compare our method to HAPMIX on simulated data from two ancestral populations, and we find high concordance between the methods. Our method also has better accuracy than LAMP when applied to three-population admixture, a situation as yet unaddressed by HAPMIX. Finally, we apply our method to a data set of four Latino populations with European, African, and Native American ancestry. We find evidence of assortative mating in each of the four populations, and we identify regions of shared ancestry that may be recent targets of selection and could serve as candidate regions for admixture-based association mapping.