Multilocus analysis of genetic divergence between outcrossing Arabidopsis species: evidence of genome-wide admixture

P>Outcrossing Arabidopsis species that diverged from their inbreeding relative Arabidopsis thaliana 5 million yr ago and display a biogeographical pattern of interspecific sympatry vs intraspecific allopatry provides an ideal model for studying impacts of gene introgression and polyploidization on species diversification. Flow cytometry analyses detected ploidy polymorphisms of 2x and 4x in Arabidopsis lyrata ssp. kamchatica of Taiwan. Genomic divergence between species/subspecies was estimated based on 98 randomly chosen nuclear genes. Multilocus analyses revealed a mosaic genome in diploid A. l. kamchatica composed of Arabidopsis halleri-like and A. lyrata-like alleles. Coalescent analyses suggest that the segregation of ancestral polymorphisms alone cannot explain the high inconsistency between gene trees across loci, and that gene introgression via diploid A. l. kamchatica likely distorts the molecular phylogenies of Arabidopsis species. However, not all genes migrated across species freely. Gene ontology analyses suggested that some nonmigrating genes were constrained by natural selection. High levels of estimated ancestral polymorphisms between A. halleri and A. lyrata suggest that gene flow between these species has not completely ceased since their initial isolation. Polymorphism data of extant populations also imply recent gene flow between the species. Our study reveals that interspecific gene flow affects the genome evolution in Arabidopsis.

Genome-wide investigation reveals high evolutionary rates in annual model plants

Background: ;Rates of molecular evolution vary widely among species. While significant deviations from molecular clock have been found in many taxa, effects of life histories on molecular evolution are not fully understood. In plants, annual/perennial life history traits have long been suspected to influence the evolutionary rates at the molecular level. To date, however, the number of genes investigated on this subject is limited and the conclusions are mixed. To evaluate the possible heterogeneity in evolutionary rates between annual and perennial plants at the genomic level, we investigated 85 nuclear housekeeping genes, 10 non-housekeeping families, and 34 chloroplast;genes using the genomic data from model plants including Arabidopsis thaliana and Medicago truncatula for annuals and grape (Vitis vinifera) and popular (Populus trichocarpa) for perennials.;Results: ;According to the cross-comparisons among the four species, 74-82% of the nuclear genes and 71-97% of the chloroplast genes suggested higher rates of molecular evolution in the two annuals than those in the two perennials. The significant heterogeneity in evolutionary rate between annuals and perennials was consistently found both in nonsynonymous sites and synonymous sites. While a linear correlation of evolutionary rates in orthologous genes between species was observed in nonsynonymous sites, the correlation was weak or invisible in synonymous sites. This tendency was clearer in nuclear genes than in chloroplast genes, in which the overall;evolutionary rate was small. The slope of the regression line was consistently lower than unity, further confirming the higher evolutionary rate in annuals at the genomic level.;Conclusions: ;The higher evolutionary rate in annuals than in perennials appears to be a universal phenomenon both in nuclear and chloroplast genomes in the four dicot model plants we investigated. Therefore, such heterogeneity in evolutionary rate should result from factors that have genome-wide influence, most likely those associated with annual/perennial life history. Although we acknowledge current limitations of this kind of study, mainly due to a small sample size available and a distant taxonomic relationship of the model organisms, our results indicate that the genome-wide survey is a promising approach toward further understanding of the;mechanism determining the molecular evolutionary rate at the genomic level.

Genome-wide identification of quantitative trait loci in a cross between Hampshire and Landrace I: carcass traits

We report the identification of quantitative trait loci (QTL) affecting carcass composition, carcass length, fat deposition and lean meat content using a genome scan across 462 animals from a combined intercross and backcross between Hampshire and Landrace pigs. Data were analysed using multiple linear regression fitting additive and dominance effects. This model was compared with a model including a parent-of-origin effect to spot evidence of imprinting. Several precisely defined muscle phenotypes were measured in order to dissect body composition in more detail. Three significant QTL were detected in the study at the 1% genome-wide level, and twelve significant QTL were detected at the 5% genome-wide level. These QTL comprise loci affecting fat deposition and lean meat content on SSC1, 4, 9, 10, 13 and 16, a locus on SSC2 affecting the ratio between weight of meat and bone in back and weight of meat and bone in ham and two loci affecting carcass length on SSC12 and 17. The well-defined phenotypes in this study enabled us to detect QTL for sizes of individual muscles and to obtain information of relevance for the description of the complexity underlying other carcass traits.

Copy number variation of the Beta-defensin genes in europeans: no supporting evidence for association with lung function, chronic obstructive pulmonary disease or asthma

Lung function measures are heritable, predict mortality and are relevant in diagnosis of chronic obstructive pulmonary disease (COPD). COPD and asthma are diseases of the airways with major public health impacts and each have a heritable component. Genome-wide association studies of SNPs have revealed novel genetic associations with both diseases but only account for a small proportion of the heritability. Complex copy number variation may account for some of the missing heritability. A well-characterised genomic region of complex copy number variation contains beta-defensin genes (DEFB103, DEFB104 and DEFB4), which have a role in the innate immune response. Previous studies have implicated these and related genes as being associated with asthma or COPD. We hypothesised that copy number variation of these genes may play a role in lung function in the general population and in COPD and asthma risk. We undertook copy number typing of this locus in 1149 adult and 689 children using a paralogue ratio test and investigated association with COPD, asthma and lung function. Replication of findings was assessed in a larger independent sample of COPD cases and smoking controls. We found evidence for an association of beta-defensin copy number with COPD in the adult cohort (OR = 1.4, 95%CI:1.02-1.92, P = 0.039) but this finding, and findings from a previous study, were not replicated in a larger follow-up sample(OR = 0.89, 95%CI:0.72-1.07, P = 0.217). No robust evidence of association with asthma in children was observed. We found no evidence for association between beta-defensin copy number and lung function in the general populations. Our findings suggest that previous reports of association of beta-defensin copy number with COPD should be viewed with caution. Suboptimal measurement of copy number can lead to spurious associations. Further beta-defensin copy number measurement in larger sample sizes of COPD cases and children with asthma are needed.

Fine-scale population structure analysis of seven local Swiss sheep breeds using genome-wide SNP data

As part of the global sheep Hapmap project, 24 individuals from each of seven indigenous Swiss sheep breeds (Bundner Oberländer sheep (BOS), Engadine Red sheep (ERS), Swiss Black-Brown Mountain sheep (SBS), Swiss Mirror sheep (SMS), Swiss White Alpine (SWA) sheep, Valais Blacknose sheep (VBS) and Valais Red sheep (VRS)), were genotyped using Illumina’s Ovine SNP50 BeadChip. In total, 167 animals were subjected to a detailed analysis for genetic diversity using 45 193 informative single nucleotide polymorphisms. The results of the phylogenetic analyses supported the known proximity between populations such as VBS and VRS or SMS and SWA. Average genomic relatedness within a breed was found to be 12 percent (BOS), 5 percent (ERS), 9 percent (SBS), 10 percent (SMS), 9 percent (SWA), 12 percent (VBS) and 20 percent (VRS). Furthermore, genomic relationships between breeds were found for single individuals from SWA and SMS, VRS and VBS as well as VRS and BOS. In addition, seven out of 40 indicated parent–offspring pairs could not be confirmed. These results were further supported by results from the genome-wide population cluster analysis. This study provides a better understanding of fine-scale population structures within and between Swiss sheep breeds. This relevant information will help to increase the conservation activities of the local Swiss sheep breeds.

Genome-wide identification of pathogenicity factors of the free-living amoeba Naegleria fowleri.

BACKGROUND The free-living amoeba Naegleria fowleri is the causative agent of the rapidly progressing and typically fatal primary amoebic meningoencephalitis (PAM) in humans. Despite the devastating nature of this disease, which results in > 97% mortality, knowledge of the pathogenic mechanisms of the amoeba is incomplete. This work presents a comparative proteomic approach based on an experimental model in which the pathogenic potential of N. fowleri trophozoites is influenced by the compositions of different media. RESULTS As a scaffold for proteomic analysis, we sequenced the genome and transcriptome of N. fowleri. Since the sequence similarity of the recently published genome of Naegleria gruberi was far lower than the close taxonomic relationship of these species would suggest, a de novo sequencing approach was chosen. After excluding cell regulatory mechanisms originating from different media compositions, we identified 22 proteins with a potential role in the pathogenesis of PAM. Functional annotation of these proteins revealed, that the membrane is the major location where the amoeba exerts its pathogenic potential, possibly involving actin-dependent processes such as intracellular trafficking via vesicles. CONCLUSION This study describes for the first time the 30 Mb-genome and the transcriptome sequence of N. fowleri and provides the basis for the further definition of effective intervention strategies against the rare but highly fatal form of amoebic meningoencephalitis.

CYP17A1 Enzyme Activity Is Linked to Ambulatory Blood Pressure in a Family-Based Population Study

BACKGROUND Genome-wide association studies have linked CYP17A1 coding for the steroid hormone synthesizing enzyme 17α-hydroxylase (CYP17A1) to blood pressure (BP). We hypothesized that the genetic signal may translate into a correlation of ambulatory BP (ABP) with apparent CYP17A1 activity in a family-based population study and estimated the heritability of CYP17A1 activity. METHODS In the Swiss Kidney Project on Genes in Hypertension, day and night urinary excretions of steroid hormone metabolites were measured in 518 participants (220 men, 298 women), randomly selected from the general population. CYP17A1 activity was assessed by 2 ratios of urinary steroid metabolites: one estimating the combined 17α-hydroxylase/17,20-lyase activity (ratio 1) and the other predominantly 17α-hydroxylase activity (ratio 2). A mixed linear model was used to investigate the association of ABP with log-transformed CYP17A1 activities exploring effect modification by urinary sodium excretion. RESULTS Daytime ABP was positively associated with ratio 1 under conditions of high, but not low urinary sodium excretion (P interaction <0.05). Ratio 2 was not associated with ABP. Heritability estimates (SE) for day and night CYP17A1 activities were 0.39 (0.10) and 0.40 (0.09) for ratio 1, and 0.71 (0.09) and 0.55 (0.09) for ratio 2 (P values <0.001). CYP17A1 activities, assessed with ratio 1, were lower in older participants. CONCLUSIONS Low apparent CYP17A1 activity (assessed with ratio 1) is associated with elevated daytime ABP when salt intake is high. CYP17A1 activity is heritable and diminished in the elderly. These observations highlight the modifying effect of salt intake on the association of CYP17A1 with BP.

Diabetes genes and risk of prostate cancer in the Atherosclerosis Risk in Communities study

Prostate cancer (PrCa) is a leading cause of morbidity and mortality, yet the etiology remains uncertain. Meta-analyses show that PrCa risk is reduced by 16% in men with type 2 diabetes (T2D), but the mechanism is unknown. Recent genome-wide association studies and meta-analyses have found single nucleotide polymorphisms (SNPs) that consistently predict T2D risk. We evaluated associations of incident PrCa with 14 T2D SNPs in the Atherosclerosis Risk in Communities (ARIC) study. From 1987-2000, there were 397 incident PrCa cases ascertained from state or local cancer registries among 6,642 men (1,560 blacks and 5,082 whites) aged 45-64 years at baseline. Genotypes were determined by TaqMan assay. Cox proportional hazards models were used to assess the association between PrCa and increasing number of T2D risk-raising alleles for individual SNPs and for genetic risk scores (GRS) comprised of the number of T2D risk-raising alleles across SNPs. Two-way gene-gene interactions were evaluated with likelihood ratio tests. Using additive genetic models, the T2D risk-raising allele was associated with significantly reduced risk of PrCa for IGF2BP2 rs4402960 (hazard ratio [HR]=0.79; P=0.07 among blacks only), SLC2A2 rs5400 (race-adjusted HR=0.85; P=0.05) and UCP2 rs660339 (race-adjusted HR=0.84; P=0.02), but significantly increased risk of PrCa for CAPN10 rs3792267 (race-adjusted HR=1.20; P=0.05). No other SNPs were associated with PrCa using an additive genetic model. However, at least one copy of the T2D risk-raising allele for TCF7L2 rs7903146 was associated with reduced PrCa risk using a dominant genetic model (race-adjusted HR=0.79; P=0.03). These results imply that the T2D-PrCa association may be partly due to shared genetic variation, but these results should be verified since multiple tests were performed. When the combined, additive effects of these SNPs were tested using a GRS, there was nearly a 10% reduction in risk of PrCa per T2D risk-raising allele (race-adjusted HR=0.92; P=0.02). SNPs in IGF2BP2, KCNJ11 and SLC2A2 were also involved in multiple synergistic gene-gene interactions on a multiplicative scale. In conclusion, it appears that the T2D-PrCa association may be due, in part, to common genetic variation. Further knowledge of T2D gene-PrCa mechanisms may improve understanding of PrCa etiology and may inform PrCa prevention and treatment.^

Genome-wide gene-gene interaction analysis for cardiovascular disease

Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^

Genome-wide algorithm for detecting CNV associations with diseases

SNP genotyping arrays have been developed to characterize single-nucleotide polymorphisms (SNPs) and DNA copy number variations (CNVs). The quality of the inferences about copy number can be affected by many factors including batch effects, DNA sample preparation, signal processing, and analytical approach. Nonparametric and model-based statistical algorithms have been developed to detect CNVs from SNP genotyping data. However, these algorithms lack specificity to detect small CNVs due to the high false positive rate when calling CNVs based on the intensity values. Association tests based on detected CNVs therefore lack power even if the CNVs affecting disease risk are common. In this research, by combining an existing Hidden Markov Model (HMM) and the logistic regression model, a new genome-wide logistic regression algorithm was developed to detect CNV associations with diseases. We showed that the new algorithm is more sensitive and can be more powerful in detecting CNV associations with diseases than an existing popular algorithm, especially when the CNV association signal is weak and a limited number of SNPs are located in the CNV.^

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^

Genome -wide and locus -specific instability

The discovery of expanded simple repeated sequences causing or associated with human disease has lead to a new area of research involved in the elucidation of how the expanded repeat causes disease and how the repeat becomes unstable. ^ To study the genetic basis of the (CTG)n repeat instability in the DMPK gene in myotonic dystrophy (DM1) patients, somatic cell hybrids were constructed between the lymphocytes of DM1 patients and a variety of Chinese hamster ovary (CHO) cell DNA repair gene deficient mutants. By using small pool PCR (SP-PCR), the instability of the (CTG)n can be quantitated for both the frequency and sizes of length change mutations. ^ Additional SP-PCR analysis on 2/11 subclones generated from this original hybrid showed a marked increase in large repeat deletions, ∼50%. A bimodal distribution of repeats was seen around the progenitor allele and at a large deleted product (within the normal range) with no intermediate products present. ^ To determine if the repair capacity of the CHO cell led to a mutator phenotype in the hamster and hybrid clones, SP-PCR was also done on 3 hamster microsatellites in a variety of hamster cell backgrounds. No variant alleles were seen in over 2500 genome equivalents screened. ^ Human-hamster hybrids have long been shown to be chromosomally unstable, yet information about the stability of repeated sequences was not known. To test if repeat instability was associated with either intact or non-intact human chromosomes, more than 300 microsatellite repeats on 13 human chromosomes (intact and non-intact) were analyzed in eight hybrid cells. No variants were seen between the hybrid and patient alleles in the hybrids. ^ To identify whether DM1 patients have a previously undetected level of genome wide instability or if the instability is truly locus specific, SP-PCR was done on 6 human microsatellites within the patient used to make the hybrid cells. No variants were seen in over 1000 genomes screened. ^ These studies show that the somatic cell hybrid approach is a genetically stable system that allows for the determination of factors that could lead to changes in microsatellite instability. It also shows that there is something inherent about the DM1 expanded (CTG)n repeat that it is solely targeted by, as of yet, and unknown mechanism that causes the repeat to be unstable. (Abstract shortened by UMI.)^

Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings

The study of continuously varying, quantitative traits is important in evolutionary biology, agriculture, and medicine. Variation in such traits is attributable to many, possibly interacting, genes whose expression may be sensitive to the environment, which makes their dissection into underlying causative factors difficult. An important population parameter for quantitative traits is heritability, the proportion of total variance that is due to genetic factors. Response to artificial and natural selection and the degree of resemblance between relatives are all a function of this parameter. Following the classic paper by R. A. Fisher in 1918, the estimation of additive and dominance genetic variance and heritability in populations is based upon the expected proportion of genes shared between different types of relatives, and explicit, often controversial and untestable models of genetic and non-genetic causes of family resemblance. With genome-wide coverage of genetic markers it is now possible to estimate such parameters solely within families using the actual degree of identity-by-descent sharing between relatives. Using genome scans on 4,401 quasi-independent sib pairs of which 3,375 pairs had phenotypes, we estimated the heritability of height from empirical genome-wide identity-by-descent sharing, which varied from 0.374 to 0.617 (mean 0.498, standard deviation 0.036). The variance in identity-by-descent sharing per chromosome and per genome was consistent with theory. The maximum likelihood estimate of the heritability for height was 0.80 with no evidence for non-genetic causes of sib resemblance, consistent with results from independent twin and family studies but using an entirely separate source of information. Our application shows that it is feasible to estimate genetic variance solely from within- family segregation and provides an independent validation of previously untestable assumptions. Given sufficient data, our new paradigm will allow the estimation of genetic variation for disease susceptibility and quantitative traits that is free from confounding with non-genetic factors and will allow partitioning of genetic variation into additive and non-additive components.

Genome-wide linkage scan for loci influencing plasma triglycerides

Background: Plasma triglyceride concentration is known to be a significant risk factor for cardiovascular disease (CVD). Previous studies have found that the level of triglycerides is strongly influenced by genetic factors. Methods: To identify quantitative trait loci influencing triglycerides, we conducted a genome-wide linkage scan on data from 485 Australian adult dizygotic twin pairs. Prior to linkage analysis, triglyceride values were adjusted for the effects of covariates including age, sex, time since last meal, time of blood collection (CT) and time to plasma separation. Results: The heritability estimate for ln(triglyceride) adjusted for all above fixed effects was 0.49. The highest multipoint LOD score observed was 2.94 (genome-wide p=0.049) on chromosome 7 (at 65cM). This 7p region contains several candidate genes. Two other regions with suggestive multipoint LOD scores were also identified on chromosome 4 (LOD score=2.26 at 62cM) and chromosome X (LOD score=2.01 at 81cM). Conclusions: The linkage peaks found represent newly identified regions for more detailed study, in particular the significant linkage observed on chromosome 7p13. \ (c) 2006 Elsevier B.V. All rights reserved.