A genetic analysis of cortical thickness in 372 twins

Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure.

Genome-wide association study of intraocular pressure identifies the GLCCI1/ICA1 region as a glaucoma susceptibility locus

To discover quantitative trait loci for intraocular pressure, amajor risk factor for glaucoma and the only modifiable one,weperformed agenome-wide association studyonadiscoverycohort of2175individualsfromSydney, Australia. We found a novel association between intraocular pressure and a common variant at 7p21 near to GLCCI1 and ICA1. The findings in this region were confirmed through two UK replication cohorts totalling 4866 individuals (rs59072263, Pcombined = 1.10 × 10-8). A copy of the G allele at this SNP is associated with an increase in mean IOP of 0.45 mmHg (95%CI = 0.30-0.61 mmHg). These results lend support to the implication of vesicle trafficking and glucocorticoid inducibility pathways in the determination of intraocular pressure and in the pathogenesis of primary open-angle glaucoma.

Genetic insights into common pathways and complex relationships among iImmune-mediated diseases

Shared aetiopathogenic factors among immune-mediated diseases have long been suggested by their co-familiality and co-occurrence, and molecular support has been provided by analysis of human leukocyte antigen (HLA) haplotypes and genome-wide association studies. The interrelationships can now be better appreciated following the genotyping of large immune disease sample sets on a shared SNP array: the 'Immunochip'. Here, we systematically analyse loci shared among major immune-mediated diseases. This reveals that several diseases share multiple susceptibility loci, but there are many nuances. The most associated variant at a given locus frequently differs and, even when shared, the same allele often has opposite associations. Interestingly, risk alleles conferring the largest effect sizes are usually disease-specific. These factors help to explain why early evidence of extensive 'sharing' is not always reflected in epidemiological overlap. © 2013 Macmillan Publishers Limited. All rights reserved.

Functional evaluation of genetic variants associated with endometriosis near GREB1

STUDY QUESTION: Do DNA variants in the growth regulation by estrogen in breast cancer 1 (GREB1) region regulate endometrial GREB1 expression and increase the risk of developing endometriosis in women? SUMMARY ANSWER: We identified new single nucleotide polymorphisms (SNPs) with strong association with endometriosis at the GREB1 locus although we did not detect altered GREB1 expression in endometriosis patients with defined genotypes. WHAT IS ALREADY KNOWN: Genome-wide association studies have identified the GREB1 region on chromosome 2p25.1 for increasing endometriosis risk. The differential expression of GREB1 has also been reported by others in association with endometriosis disease phenotype. STUDY DESIGN, SIZE, DURATION: Fine mapping studies comprehensively evaluated SNPs within the GREB1 region in a large-scale data set (>2500 cases and >4000 controls). Publicly available bioinformatics tools were employed to functionally annotate SNPs showing the strongest association signal with endometriosis risk. Endometrial GREB1 mRNA and protein expression was studied with respect to phases of the menstrual cycle (n = 2-45 per cycle stage) and expression quantitative trait loci (eQTL) analysis for significant SNPs were undertaken for GREB1 [mRNA (n = 94) and protein (n = 44) in endometrium]. PARTICIPANTS/MATERIALS, SETTING, METHODS: Participants in this study are females who provided blood and/or endometrial tissue samples in a hospital setting. The key SNPs were genotyped using Sequenom MassARRAY. The functional roles and regulatory annotations for identified SNPs are predicted by various publicly available bioinformatics tools. Endometrial GREB1 expression work employed qRT-PCR, western blotting and immunohistochemistry studies. MAIN RESULTS AND THE ROLE OF CHANCE: Fine mapping results identified a number of SNPs showing stronger association (0.004 < P < 0.032) with endometriosis risk than the original GWAS SNP (rs13394619) (P = 0.034). Some of these SNPs were predicted to have functional roles, for example, interaction with transcription factor motifs. The haplotype (a combination of alleles) formed by the risk alleles from two common SNPs showed significant association (P = 0.026) with endometriosis and epistasis analysis showed no evidence for interaction between the two SNPs, suggesting an additive effect of SNPs on endometriosis risk. In normal human endometrium, GREB1 protein expression was altered depending on the cycle stage (significantly different in late proliferative versus late secretory, P < 0.05) and cell type (glandular epithelium, not stromal cells). However, GREB1 expression in endometriosis cases versus controls and eQTL analyses did not reveal any significant changes. LIMITATIONS, REASONS FOR CAUTION: In silico prediction tools are generally based on cell lines different to our tissue and disease of interest. Functional annotations drawn from these analyses should be considered with this limitation in mind. We identified cell-specific and hormone-specific changes in GREB1 protein expression. The lack of a significant difference observed following our GREB1 expression studies may be the result of moderate power on mixed cell populations in the endometrial tissue samples. WIDER IMPLICATIONS OF THE FINDINGS: This study further implicates the GREB1 region on chromosome 2p25.1 and the GREB1 gene with involvement in endometriosis risk. More detailed functional studies are required to determine the role of the novel GREB1 transcripts in endometriosis pathophysiology. STUDY FUNDING/COMPETING INTERESTS: Funding for this work was provided by NHMRC Project Grants APP1012245, APP1026033, APP1049472 and APP1046880. There are no competing interests.

Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs

Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 x 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 x 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average.

Genomic inflation factors under polygenic inheritance

Population structure, including population stratification and cryptic relatedness, can cause spurious associations in genome-wide association studies (GWAS). Usually, the scaled median or mean test statistic for association calculated from multiple single-nucleotide-polymorphisms across the genome is used to assess such effects, and 'genomic control' can be applied subsequently to adjust test statistics at individual loci by a genomic inflation factor. Published GWAS have clearly shown that there are many loci underlying genetic variation for a wide range of complex diseases and traits, implying that a substantial proportion of the genome should show inflation of the test statistic. Here, we show by theory, simulation and analysis of data that in the absence of population structure and other technical artefacts, but in the presence of polygenic inheritance, substantial genomic inflation is expected. Its magnitude depends on sample size, heritability, linkage disequilibrium structure and the number of causal variants. Our predictions are consistent with empirical observations on height in independent samples of ~4000 and ~133,000 individuals.

Genome-wide association study of migraine implicates a common susceptibility variant on 8q22.1

Migraine is a common episodic neurological disorder, typically presenting with recurrent attacks of severe headache and autonomic dysfunction. Apart from rare monogenic subtypes, no genetic or molecular markers for migraine have been convincingly established. We identified the minor allele of rs1835740 on chromosome 8q22.1 to be associated with migraine (P = 5.38 x 10(-)(9), odds ratio = 1.23, 95% CI 1.150-1.324) in a genome-wide association study of 2,731 migraine cases ascertained from three European headache clinics and 10,747 population-matched controls. The association was replicated in 3,202 cases and 40,062 controls for an overall meta-analysis P value of 1.69 x 10(-)(1)(1) (odds ratio = 1.18, 95% CI 1.127-1.244). rs1835740 is located between MTDH (astrocyte elevated gene 1, also known as AEG-1) and PGCP (encoding plasma glutamate carboxypeptidase). In an expression quantitative trait study in lymphoblastoid cell lines, transcript levels of the MTDH were found to have a significant correlation to rs1835740 (P = 3.96 x 10(-)(5), permuted threshold for genome-wide significance 7.7 x 10(-)(5). To our knowledge, our data establish rs1835740 as the first genetic risk factor for migraine.

Within-family outliers: Segregating alleles or environmental effects? A linkage analysis of height from 5815 sibling pairs

Most information in linkage analysis for quantitative traits comes from pairs of relatives that are phenotypically most discordant or concordant. Confounding this, within-family outliers from non-genetic causes may create false positives and negatives. We investigated the influence of within-family outliers empirically, using one of the largest genome-wide linkage scans for height. The subjects were drawn from Australian twin cohorts consisting of 8447 individuals in 2861 families, providing a total of 5815 possible pairs of siblings in sibships. A variance component linkage analysis was performed, either including or excluding the within-family outliers. Using the entire dataset, the largest LOD scores were on chromosome 15q (LOD 2.3) and 11q (1.5). Excluding within-family outliers increased the LOD score for most regions, but the LOD score on chromosome 15 decreased from 2.3 to 1.2, suggesting that the outliers may create false negatives and false positives, although rare alleles of large effect may also be an explanation. Several regions suggestive of linkage to height were found after removing the outliers, including 1q23.1 (2.0), 3q22.1 (1.9) and 5q32 (2.3). We conclude that the investigation of the effect of within-family outliers, which is usually neglected, should be a standard quality control measure in linkage analysis for complex traits and may reduce the noise for the search of common variants of modest effect size as well as help identify rare variants of large effect and clinical significance. We suggest that the effect of within-family outliers deserves further investigation via theoretical and simulation studies.

Drought adaptation of stay-green sorghum is associated with canopy development, leaf anatomy, root growth, and water uptake

Stay-green sorghum plants exhibit greener leaves and stems during the grain-filling period under water-limited conditions compared with their senescent counterparts, resulting in increased grain yield, grain mass, and lodging resistance. Stay-green has been mapped to a number of key chromosomal regions, including Stg1, Stg2, Stg3, and Stg4, but the functions of these individual quantitative trait loci (QTLs) remain unclear. The objective of this study was to show how positive effects of Stg QTLs on grain yield under drought can be explained as emergent consequences of their effects on temporal and spatial water-use patterns that result from changes in leaf-area dynamics. A set of four Stg near-isogenic lines (NILs) and their recurrent parent were grown in a range of field and semicontrolled experiments in southeast Queensland, Australia. These studies showed that the four Stg QTLs regulate canopy size by: (1) reducing tillering via increased size of lower leaves, (2) constraining the size of the upper leaves; and (3) in some cases, decreasing the number of leaves per culm. In addition, they variously affect leaf anatomy and root growth. The multiple pathways by which Stg QTLs modulate canopy development can result in considerable developmental plasticity. The reduction in canopy size associated with Stg QTLs reduced pre-flowering water demand, thereby increasing water availability during grain filling and, ultimately, grain yield. The generic physiological mechanisms underlying the stay-green trait suggest that similar Stg QTLs could enhance post-anthesis drought adaptation in other major cereals such as maize, wheat, and rice.

Bayesian Inference for Retrospective Population Genetics Models Using Markov Chain Monte Carlo Methods

Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

Directional dominance on stature and cognition in diverse human populations

Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3, 4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5, 6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.

A preliminary genetic map of Zhikong scallop (Chlamys farreri Jones et Preston 1904)

Zhikong scallop (Chlamys farreri Jones et Preston 1904) is one of the most important aquaculture species in China. The development of a genetic linkage map would provide a powerful tool for the genetic improvement of this species. Amplified fragment length polymorphism (AFLP) is a PCR-based technique that has proven to be powerful in genome fingerprinting and mapping, and population analysis. Genetic maps of C. farreri were constructed using AFLP markers and a full-sib family with 60 progeny. A total of 503 segregating AFLP markers were obtained, with 472 following the Mendelian segregation ratio of 1:1 and 31 markers showing significant (P< 0.05) segregation distortion. The male map contained 166 informative AFLP markers in 23 linkage groups covering 2468 cM. The average distance between markers was 14.9 cM. The female genetic map consisted of 198 markers in 25 linkage groups spanning 3130 cM with an average inter-marker spacing of 15.8 cM. DNA polymorphisms that segregated in a 3:1 ratio as well as the AFLP markers that were heterozygous in both parents were included to construct combined linkage genetic map. Five shared linkage groups, ranging from 61.1 to 162.5 cM, were identified between the male and female maps, covering 431 cM. Amplified fragment length polymorphism markers appeared to be evenly distributed within the linkage groups. Although preliminary, these maps provide a starting point for the mapping of the functional genes and quantitative trait loci in C. farreri.

A genetic linkage map of Pacific white shrimp (Litopenaeus vannamei): sex-linked microsatellite markers and high recombination rates

Pacific white shrimp (Litopenaeus vannamei) is the leading species farmed in the Western Hemisphere and an economically important aquaculture species in China. In this project, a genetic linkage map was constructed using amplified fragment length polymorphism (AFLP) and microsatellite markers. One hundred and eight select AFLP primer combinations and 30 polymorphic microsatellite markers produced 2071 markers that were polymorphic in either of the parents and segregated in the progeny. Of these segregating markers, 319 were mapped to 45 linkage groups of the female framework map, covering a total of 4134.4 cM; and 267 markers were assigned to 45 linkage groups of the male map, covering a total of 3220.9 cM. High recombination rates were found in both parental maps. A sex-linked microsatellite marker was mapped on the female map with 6.6 cM to sex and a LOD of 17.8, two other microsatellite markers were also linked with both 8.6 cM to sex and LOD score of 14.3 and 16.4. The genetic maps presented here will serve as a basis for the construction of a high-resolution genetic map, quantitative trait loci (QTLs) detection, marker-assisted selection (MAS) and comparative genome mapping.

Genetic and genomic analyses of musculoskeletal differences between BEH and BEL strains

Berlin high (BEH) and Berlin low (BEL) strains selected for divergent growth differ 3-fold in body weight. We aimed at examining muscle mass, which is a major contributor to body weight, by exploring anatomical characteristics of the soleus muscle, its fiber numbers and their cross sectional area (CSA), by analysing transcriptome of the gastrocnemius and by initiating quantitative trait locus (QTL) mapping. BEH muscles were 4-to-8 times larger compared to BEL strain. In sub-strain BEH+/+, mutant myostatin was replaced with a wild type allele, however, BEH+/+muscles still were 2-to-4 times larger compared to the BEL strain. BEH soleus contained 2-times more (P<0.0001) and 2-times larger in CSA (P<0.0001) fibers compared to BEL strain. In addition, soleus femoral attachment anomaly (SFAA) was observed in all BEL mice. One significant (chromosome 1) and four suggestive (chromosomes 3, 4, 6 and 9) muscle weight QTLs were mapped in 21-day old F2 intercross (n=296) between BEH and BEL strains. The frequency of SFAA incidence in the F2 and in the backcross to BEL strain (BCL) suggested the presence of more than one causative gene. Two suggestive SFAA QTLs were mapped in BCL, however, their peak markers were not associated with the phenotype in F2. RNA-Seq analysis revealed 2,148 differentially expressed (P<0.1) genes and 45,673 SNPs and >2,000 indels between BEH+/+ and BEL males. In conclusion, contrasting muscle traits, genomic and gene expression differences between BEH and BEL strains provide a promising model for the search of genes involved in muscle growth and musculoskeletal morphogenesis.

Natural variation of rice strigolactone biosynthesis is associated with the deletion of two MAX1 orthologs

Rice (Oryza sativa) cultivar Azucena--belonging to the Japonica subspecies--exudes high strigolactone (SL) levels and induces high germination of the root parasitic plant Striga hermonthica. Consistent with the fact that SLs also inhibit shoot branching, Azucena is a low-tillering variety. In contrast, Bala, an Indica cultivar, is a low-SL producer, stimulates less Striga germination, and is highly tillered. Using a Bala × Azucena F6 population, a major quantitative trait loci--qSLB1.1--for the exudation of SL, tillering, and induction of Striga germination was detected on chromosome 1. Sequence analysis of the corresponding locus revealed a rearrangement of a 51- to 59-kbp stretch between 28.9 and 29 Mbp in the Bala genome, resulting in the deletion of two cytochrome P450 genes--SLB1 and SLB2--with high homology to the Arabidopsis SL biosynthesis gene, MAX1. Both rice genes rescue the Arabidopsis max1-1 highly branched mutant phenotype and increase the production of the SL, ent-2'-epi-5-deoxystrigol, when overexpressed in Bala. Furthermore, analysis of this region in 367 cultivars of the publicly available Rice Diversity Panel population shows that the rearrangement at this locus is a recurrent natural trait associated with the Indica/Japonica divide in rice.