Genome wide association study reveals plant loci controlling heritability of the rhizosphere microbiome

Host genetics has recently been shown to be a driver of plant microbiome composition. However, identifying the underlying genetic loci controlling microbial selection remains challenging. Genome-wide association studies (GWAS) represent a potentially powerful, unbiased method to identify microbes sensitive to the host genotype and to connect them with the genetic loci that influence their colonization. Here, we conducted a population-level microbiome analysis of the rhizospheres of 200 sorghum genotypes. Using 16S rRNA amplicon sequencing, we identify rhizosphere-associated bacteria exhibiting heritable associations with plant genotype, and identify significant overlap between these lineages and heritable taxa recently identified in maize. Furthermore, we demonstrate that GWAS can identify host loci that correlate with the abundance of specific subsets of the rhizosphere microbiome. Finally, we demonstrate that these results can be used to predict rhizosphere microbiome structure for an independent panel of sorghum genotypes based solely on knowledge of host genotypic information.Subject terms: Agricultural genetics, Plant ecology, Soil microbiology     

Genome wide CNV analysis reveals additional variants associated with milk production traits in Holsteins

Background

Milk production is an economically important sector of global agriculture. Much attention has been paid to the identification of quantitative trait loci (QTL) associated with milk, fat, and protein yield and the genetic and molecular mechanisms underlying them. Copy number variation (CNV) is an emerging class of variants which may be associated with complex traits.

Results

In this study, we performed a genome-wide association between CNVs and milk production traits in 26,362 Holstein bulls and cows. A total of 99 candidate CNVs were identified using Illumina BovineSNP50 array data, and association tests for each production trait were performed using a linear regression analysis with PCA correlation. A total of 34 CNVs on 22 chromosomes were significantly associated with at least one milk production trait after false discovery rate (FDR) correction. Some of those CNVs were located within or near known QTL for milk production traits. We further investigated the relationship between associated CNVs with neighboring SNPs. For all 82 combinations of traits and CNVs (less than 400 kb in length), we found 17 cases where CNVs directly overlapped with tag SNPs and 40 cases where CNVs were adjacent to tag SNPs. In 5 cases, CNVs located were in strong linkage disequilibrium with tag SNPs, either within or adjacent to the same haplotype block. There were an additional 20 cases where CNVs did not have a significant association with SNPs, suggesting that the effects of those CNVs were probably not captured by tag SNPs.

Conclusion

We conclude that combining CNV with SNP analyses reveals more genetic variations underlying milk production traits than those revealed by SNPs alone.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-683) contains supplementary material, which is available to authorized users.     

Genome wide association studies and prion disease

Over the last decade remarkable advances in genotyping and sequencing technology have resulted in hundreds of novel gene associations with disease. These have typically involved high frequency alleles in common diseases and with the advent of next generation sequencing, disease causing recessive mutations in rare inherited syndromes. Here we discuss the impact of these advances and other gene discovery methods in the prion diseases. Several quantitative trait loci in mouse have been mapped and their human counterparts analyzed (HECTD2, CPNE8); other candidate genes regions have been chosen for functional reasons (SPRN, CTSD). Human genome wide association has been done in variant Creutzfeldt-Jakob disease (CJD) and are ongoing in larger collections of sporadic CJD with findings around, but not clearly beyond, the levels of statistical significance required in these studies (THRB-RARB, STMN2). Future work will include closer integration of animal and human genetic studies, larger and combined genome wide association, analysis of structural genetic variation and next generation sequencing studies involving the entire exome or genome.Key words: prion, genetic, CJD, GWAS     

Genome wide association studies and prion disease

Over the last decade remarkable advances in genotyping and sequencing technology have resulted in hundreds of novel gene associations with disease. These have typically involved high frequency alleles in common diseases and with the advent of next generation sequencing, disease causing recessive mutations in rare inherited syndromes. Here we discuss the impact of these advances and other gene discovery methods in the prion diseases. Several quantitative trait loci in mouse have been mapped and their human counterparts analysed (HECTD2, CPNE8); other candidate genes regions have been chosen for functional reasons (SPRN, CTSD). Human genome wide association has been done in variant Creutzfeldt-Jakob disease (CJD) and are ongoing in larger collections of sporadic CJD with findings around, but not clearly beyond, the levels of statistical significance required in these studies (THRB-RARB, STMN2). Future work will include closer integration of animal and human genetic studies, larger and combined genome wide association, analysis of structural genetic variantion and next generation sequencing studies involving the entire coding exome or genome.     

Genome wide association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants

Background

Obesity is a major health problem. Although heritability is substantial, genetic mechanisms predisposing to obesity are not very well understood. We have performed a genome wide association study (GWA) for early onset (extreme) obesity.

Methodology/Principal Findings

a) GWA (Genome-Wide Human SNP Array 5.0 comprising 440,794 single nucleotide polymorphisms) for early onset extreme obesity based on 487 extremely obese young German individuals and 442 healthy lean German controls; b) confirmatory analyses on 644 independent families with at least one obese offspring and both parents. We aimed to identify and subsequently confirm the 15 SNPs (minor allele frequency ≥10%) with the lowest p-values of the GWA by four genetic models: additive, recessive, dominant and allelic. Six single nucleotide polymorphisms (SNPs) in FTO (fat mass and obesity associated gene) within one linkage disequilibrium (LD) block including the GWA SNP rendering the lowest p-value (rs1121980; log-additive model: nominal p = 1.13×10⁻⁷, corrected p = 0.0494; odds ratio (OR)_CT 1.67, 95% confidence interval (CI) 1.22–2.27; OR_TT 2.76, 95% CI 1.88–4.03) belonged to the 15 SNPs showing the strongest evidence for association with obesity. For confirmation we genotyped 11 of these in the 644 independent families (of the six FTO SNPs we chose only two representing the LD bock). For both FTO SNPs the initial association was confirmed (both Bonferroni corrected p<0.01). However, none of the nine non-FTO SNPs revealed significant transmission disequilibrium.

Conclusions/Significance

Our GWA for extreme early onset obesity substantiates that variation in FTO strongly contributes to early onset obesity. This is a further proof of concept for GWA to detect genes relevant for highly complex phenotypes. We concurrently show that nine additional SNPs with initially low p-values in the GWA were not confirmed in our family study, thus suggesting that of the best 15 SNPs in the GWA only the FTO SNPs represent true positive findings.     

Major gender difference in association of FTO gene variant among severely obese children with obesity and obesity related phenotypes

Recent studies have shown that SNPs in the FTO gene predispose to childhood and adult obesity. In this study, we examined the association between variants in FTO and KIAA1005, a gene that maps closely to FTO, and obesity, as well as obesity related traits among 450 well characterised severely obese children and 512 normal weight controls. FTO showed significant association with several obesity related traits while SNPs in KIAA1005 did not. When stratified by gender, the FTO variant rs9939609 showed association with obesity and BMI among girls (P = 0.006 and 0.004, respectively) but not among boys. Gender differences were also found in the associations of the FTO rs9939609 with obesity related traits such as insulin sensitivity and plasma glucose. This study suggests that FTO may have an important role for gender specific development of severe obesity and insulin resistance in children.     

Association analysis of the FTO gene with obesity in children of Caucasian and African ancestry reveals a common tagging SNP

Recently an association was demonstrated between the single nucleotide polymorphism (SNP), rs9939609, within the FTO locus and obesity as a consequence of a genome wide association (GWA) study of type 2 diabetes in adults. We examined the effects of two perfect surrogates for this SNP plus 11 other SNPs at this locus with respect to our childhood obesity cohort, consisting of both Caucasians and African Americans (AA). Utilizing data from our ongoing GWA study in our cohort of 418 Caucasian obese children (BMI>or=95th percentile), 2,270 Caucasian controls (BMI<95th percentile), 578 AA obese children and 1,424 AA controls, we investigated the association of the previously reported variation at the FTO locus with the childhood form of this disease in both ethnicities. The minor allele frequencies (MAF) of rs8050136 and rs3751812 (perfect surrogates for rs9939609 i.e. both r(2) = 1) in the Caucasian cases were 0.448 and 0.443 respectively while they were 0.391 and 0.386 in Caucasian controls respectively, yielding for both an odds ratio (OR) of 1.27 (95% CI 1.08-1.47; P = 0.0022). Furthermore, the MAFs of rs8050136 and rs3751812 in the AA cases were 0.449 and 0.115 respectively while they were 0.436 and 0.090 in AA controls respectively, yielding an OR of 1.05 (95% CI 0.91-1.21; P = 0.49) and of 1.31 (95% CI 1.050-1.643; P = 0.017) respectively. Investigating all 13 SNPs present on the Illumina HumanHap550 BeadChip in this region of linkage disequilibrium, rs3751812 was the only SNP conferring significant risk in AA. We have therefore replicated and refined the association in an AA cohort and distilled a tag-SNP, rs3751812, which captures the ancestral origin of the actual mutation. As such, variants in the FTO gene confer a similar magnitude of risk of obesity to children as to their adult counterparts and appear to have a global impact.     

Genome wide association mapping and candidate gene analysis for pod shatter resistance in Brassica juncea and its progenitor species

Molecular Biology Reports - We investigated phenotypic variations for pod shattering, pod length and number of seeds per pod in large germplasm collections of Brassica juncea (2n?=?36;...     

Genome wide association identifies PPFIA1 as a candidate gene for acute lung injury risk following major trauma

Acute Lung Injury (ALI) is a syndrome with high associated mortality characterized by severe hypoxemia and pulmonary infiltrates in patients with critical illness. We conducted the first investigation to use the genome wide association (GWA) approach to identify putative risk variants for ALI. Genome wide genotyping was performed using the Illumina Human Quad 610 BeadChip. We performed a two-stage GWA study followed by a third stage of functional characterization. In the discovery phase (Phase 1), we compared 600 European American trauma-associated ALI cases with 2266 European American population-based controls. We carried forward the top 1% of single nucleotide polymorphisms (SNPs) at p<0.01 to a replication phase (Phase 2) comprised of a nested case-control design sample of 212 trauma-associated ALI cases and 283 at-risk trauma non-ALI controls from ongoing cohort studies. SNPs that replicated at the 0.05 level in Phase 2 were subject to functional validation (Phase 3) using expression quantitative trait loci (eQTL) analyses in stimulated B-lymphoblastoid cell lines (B-LCL) in family trios. 159 SNPs from the discovery phase replicated in Phase 2, including loci with prior evidence for a role in ALI pathogenesis. Functional evaluation of these replicated SNPs revealed rs471931 on 11q13.3 to exert a cis-regulatory effect on mRNA expression in the PPFIA1 gene (p = 0.0021). PPFIA1 encodes liprin alpha, a protein involved in cell adhesion, integrin expression, and cell-matrix interactions. This study supports the feasibility of future multi-center GWA investigations of ALI risk, and identifies PPFIA1 as a potential functional candidate ALI risk gene for future research.     

Genome wide association studies in presence of misclassified binary responses

Background

Misclassification has been shown to have a high prevalence in binary responses in both livestock and human populations. Leaving these errors uncorrected before analyses will have a negative impact on the overall goal of genome-wide association studies (GWAS) including reducing predictive power. A liability threshold model that contemplates misclassification was developed to assess the effects of mis-diagnostic errors on GWAS. Four simulated scenarios of case–control datasets were generated. Each dataset consisted of 2000 individuals and was analyzed with varying odds ratios of the influential SNPs and misclassification rates of 5% and 10%.

Results

Analyses of binary responses subject to misclassification resulted in underestimation of influential SNPs and failed to estimate the true magnitude and direction of the effects. Once the misclassification algorithm was applied there was a 12% to 29% increase in accuracy, and a substantial reduction in bias. The proposed method was able to capture the majority of the most significant SNPs that were not identified in the analysis of the misclassified data. In fact, in one of the simulation scenarios, 33% of the influential SNPs were not identified using the misclassified data, compared with the analysis using the data without misclassification. However, using the proposed method, only 13% were not identified. Furthermore, the proposed method was able to identify with high probability a large portion of the truly misclassified observations.

Conclusions

The proposed model provides a statistical tool to correct or at least attenuate the negative effects of misclassified binary responses in GWAS. Across different levels of misclassification probability as well as odds ratios of significant SNPs, the model proved to be robust. In fact, SNP effects, and misclassification probability were accurately estimated and the truly misclassified observations were identified with high probabilities compared to non-misclassified responses. This study was limited to situations where the misclassification probability was assumed to be the same in cases and controls which is not always the case based on real human disease data. Thus, it is of interest to evaluate the performance of the proposed model in that situation which is the current focus of our research.

     

Genome wide DNA methylation profiling for epigenetic alteration in coronary artery disease patients

Background

The alteration in the epigenome forms an interface between the genotype and the environment. Epigenetic alteration is expected to make a significant contribution to the development of cardiovascular disease where environmental interactions play a key role in disease progression. We had previously shown that global DNA hypermethylation per se is associated with coronary artery disease (CAD) and is further accentuated by high levels of homocysteine, a thiol amino acid which is an independent risk factor for cardiovascular disease and is also a key modulator of macromolecular methylation.

Results

We have identified 72 differentially methylated regions (DMRs) that were hypermethylated in CAD patients in the background of varying homocysteine levels. Following deep bisulfite sequencing of a few of the selected DMRs, we found significantly higher methylation in CAD cases. We get six CpG sites in three DMRs that included the intronic region of C1QL4 gene and upstream region of CCDC47 and TGFBR3 genes.

Conclusion

To the best of our knowledge, this is the first study to identify hypermethylated regions across the genome in patients with coronary artery disease. Further validation in different populations is necessary for this information to be used for disease risk assessment and management.     

Genome wide analysis of Cyclophilin gene family from rice and Arabidopsis and its comparison with yeast

Cyclophilin proteins are the members of immunophillin group of proteins, known for their property of binding to the immune-suppressant drug cyclosporin A, hence named as cyclophilins. These proteins are characterized by the presence of peptidyl prolyl isomerase (PPIase) domain which catalyzes the cis-trans isomerisation process of proline residues. In the present study, an in-silico based approach was followed to identify and characterize the cyclophilin family from rice, Arabidopsis and yeast. We were able to identify 28 rice, 35 Arabidopsis and 8 yeast cyclophilin genes from their respective genomes on the basis of their annotation as well as the presence of highly conserved PPIase domain. The evolutionary relationship of the cyclophilin genes from the three genomes was analyzed using the phylogenetic tree. We have also classified the rice cyclophilin genes on the basis of localization of the protein in cell. The structural similarity of the cyclophilins was also analyzed on the basis of their homology model. The expression analysis performed using Genevestigator revealed a very strong stress responsive behavior of the gene family which was more prominent in later stages of stress. The study indicates the importance of the gene family in stress response as well as several developmental stages thus opening up many avenues for future study on the cyclophilin proteins.     

Genome wide gene expression studies in mood disorders

Microarrays offer the possibility of screening in parallel virtually all genes expressed in a given tissue or to study the molecular signature associated with available treatments. As such, this technology has been increasingly used to investigate multifactorial and polygenic complex traits such as psychiatric disorders, in particular, schizophrenia and mood disorders. This review focuses on microarray studies investigating mood disorders. Study designs, methodologic approaches and limitations, subsequent follow-up strategies, and confirmation of results are discussed. Despite the apparent disparate and not always concordant results, it appears evident that this technology is a powerful and inevitable approach for the study of mood disorders, especially when phenotype-specific confounders are properly accounted for. Thus, alterations of mitochondrial, oligodendrocyte, and myelin related genes in bipolar disorder, of signaling and olidendroglial related genes in depression, and of GABA-glutamate related genes in depression and suicide have been observed and have confirmed new avenues for the study and the treatment of these complex disorders.     

Genome analysis with gene expression microarrays

Advances in biochemistry, chemistry and engineering have enabled the development of a new gene expression assay. This ‘chip-based’ approach utilizes microscopic arrays of cDNAs printed on glass as high-density hybridization targets. Fluorescent probe mixtures derived from total cellular messenger RNA (mRNA) hybridize to cognate elements on the array, allowing accurate measurement of the expression of the corresponding genes. Array densities of >1,000 cDNAs per cm² enable quantitative expression monitoring of a large number of genes in a single hybridization. A two-color fluorescence detection scheme allows rapid and simultaneous differential expression analysis of independent biological samples. Mass-produced microarrays provide a new tool for genome expression analysis that may revolutionize genetic dissection, drug discovery and human disease diagnostics.     

Genome wide computational analysis of Brugia malayi helicases: a comparison with human host

The availability of Brugia malayi genome sequence has paved ways for the search of homologues for a variety of genes. Helicases are ubiquitous enzymes involved in all the nucleic acid metabolic pathways and are essential for the development and growth. The genome wide analysis of B. malayi for different helicases showed the presence of a number of DEAD box helicases, 7 DEAH box helicases, RecQ helicases, repair helicases, super killer helicases, MCM2-7 complex, Rad54 and two subunits of Ku helicase. The comparison of protein sequence of each helicase with its human counterpart indicated characteristic differences in filarial helicases. There are noticeable differences in some of the filarial helicases such as DHX35, RecQL1 and Ku. Further characterization of these helicases will help in understanding physiological significance of these helicases in filarial parasites, which in future can be utilized for chemotherapy of parasitic infection.     

Genome wide survey,and expression analysis of Ornithine decarboxylase gene associated with alkaloid biosynthesis in plants

Plant ODC (ornithine decarboxylase) plays a vital role in normalizing cell division in actively growing tissues. The ODC is a key precursor enzyme for nicotine and nornicotine biosynthesis in plants. ODCs are widely present in many plant families but have not been functionally validated and characterized at the molecular level. In the present study, 58 plant ODCs were identified and were found to contain two putative regulatory motifs, specifically PLP (Pyridoxal 5′-phosphate) and Orn/DAP/Arg decarboxylase family 2 pyridoxal-phosphate, that are highly conserved among diverse plant species. Further, the cis-regulatory elements and interacting partners of the gene revealed the importance of ODC in various metabolic pathways. The qRT-PCR revealed highest relative expression of ODC in floral meristem and roots. Our results suggest that ODC can be effectively used as an ideal candidate for engineering polyamine biosynthesis and would be crucial for developing ultra-low nicotine content tobacco lines via genome editing.