Integrated analysis of genetic data with R

Zebrafish Chromosome 14 Gene Differential Expression in the fmr1 h u2787 Model of Fragile X Syndrome

Zebrafish represent a valuable model for investigating the molecular and cellular basis of Fragile X syndrome (FXS). Reduced expression of the zebrafish FMR1 orthologous gene, fmr1, causes developmental and behavioural phenotypes related to FXS. Zebrafish homozygous for the hu2787 non-sense mutation allele of fmr1 are widely used to model FXS, although FXS-relevant phenotypes seen from morpholino antisense oligonucleotide (morpholino) suppression of fmr1 transcript translation were not observed when hu2787 was first described. The subsequent discovery of transcriptional adaptation (a form of genetic compensation), whereby mutations causing non-sense-mediated decay of transcripts can drive compensatory upregulation of homologous transcripts independent of protein feedback loops, suggested an explanation for the differences reported. We examined the whole-embryo transcriptome effects of homozygosity for fmr1 h u2787 at 2 days post fertilisation. We observed statistically significant changes in expression of a number of gene transcripts, but none from genes showing sequence homology to fmr1. Enrichment testing of differentially expressed genes implied effects on lysosome function and glycosphingolipid biosynthesis. The majority of the differentially expressed genes are located, like fmr1, on Chromosome 14. Quantitative PCR tests did not support that this was artefactual due to changes in relative chromosome abundance. Enrichment testing of the "leading edge" differentially expressed genes from Chromosome 14 revealed that their co-location on this chromosome may be associated with roles in brain development and function. The differential expression of functionally related genes due to mutation of fmr1, and located on the same chromosome as fmr1, is consistent with R.A. Fisher's assertion that the selective advantage of co-segregation of particular combinations of alleles of genes will favour, during evolution, chromosomal rearrangements that place them in linkage disequilibrium on the same chromosome. However, we cannot exclude that the apparent differential expression of genes on Chromosome 14 genes was, (if only in part), caused by differences between the expression of alleles of genes unrelated to the effects of the fmr1 h u2787 mutation and made manifest due to the limited, but non-zero, allelic diversity between the genotypes compared.

Marker-assisted selection vis-à-vis bull fertility: coming full circle-a review

Bull fertility is considered an indispensable trait, as far as farm economics is concerned since it is the successful conception in a cow that provides calf crop, along with the ensuing lactation. This ensures sustainability of a dairy farm. Traditionally, bull fertility did not receive much attention by the farm managers and breeding animals were solely evaluated based on phenotypic predictors, namely, sire conception rate and seminal parameters in bull. With the advent of the molecular era in animal breeding, attempts were made to unravel the genetic complexity of bull fertility by the identification of genetic markers related to the trait. Marker-Assisted Selection (MAS) is a methodology that aims at utilizing the genetic information at markers and selecting improved populations for important traits. Traditionally, MAS was pursued using a candidate gene approach for identifying markers related to genes that are already known to have a physiological function related to the trait but this approach had certain shortcomings like stringent criteria for significance testing. Now, with the availability of genome-wide data, the number of markers identified and variance explained in relation to bull fertility has gone up. So, this presents a unique opportunity to revisit MAS by selection based on the information of a large number of genome-wide markers and thus, improving the accuracy of selection.

Dysregulation of microRNA in cholangiocarcinoma identified through a meta-analysis of microRNA profiling

BACKGROUND

In the past decades, the potential of microRNA (miRNA) in cancer diagnostics and prognostics has gained a lot of interests. In this study, a meta-analysis was conducted upon the pooled miRNA microarray data of cholangiocarcinoma (CCA).

AIM

To identify differentially expressed (DE) miRNAs and perform functional analyses in order to gain insights to understanding miRNA-target interactions involved in tumorigenesis pathways of CCA.

METHODS

Raw data from 8 CCA miRNA microarray datasets, consisting of 443 samples in total, were integrated and statistically analyzed to identify DE miRNAs via comparison of levels of miRNA expression between CCA and normal bile duct samples using t-tests (P < 0.001). The 10-fold cross validation was performed in order to increase the robustness of the t-test results.

RESULTS

Our data showed 70 up-regulated and 48 down-regulated miRNAs in CCA. Gene Ontology and pathway enrichment analyses revealed that mRNA targets of DE miRNAs were significantly involved in several biological processes. The most prominent dysregulated pathways included phosphatidylinositol-3 kinases/Akt, mitogen-activated protein kinase and Ras signaling pathways.

CONCLUSION

DE miRNAs found in our meta-analysis revealed dysregulation in major cancer pathways involved in the development of CCA. These results indicated the necessity of understanding the miRNA-target interactions and the significance of dysregulated miRNAs in terms of diagnostics and prognostics of cancers.

Reconstructing and mining the B cell repertoire with ImmunediveRsity

The B cell antigen receptor repertoire is highly diverse and constantly modified by clonal selection. High-throughput DNA sequencing (HTS) of the lymphocyte repertoire (Rep-Seq) represents a promising technology to explore such diversity ex-vivo and assist in the identification of antigen-specific antibodies based on molecular signatures of clonal selection. Therefore, integrative tools for repertoire reconstruction and analysis from antibody sequences are needed. We developed ImmunediveRity, a stand-alone pipeline primarily based in R programming for the integral analysis of B cell repertoire data generated by HTS. The pipeline integrates GNU software and in house scripts to perform quality filtering, sequencing noise correction and repertoire reconstruction based on V, D and J segment assignment, clonal origin and unique heavy chain identification. Post-analysis scripts generate a wealth of repertoire metrics that in conjunction with a rich graphical output facilitates sample comparison and repertoire mining. Its performance was tested with raw and curated human and mouse 454-Roche sequencing benchmarks providing good approximations of repertoire structure. Furthermore, ImmunediveRsity was used to mine the B cell repertoire of immunized mice with a model antigen, allowing the identification of previously validated antigen-specific antibodies, and revealing different and unexpected clonal diversity patterns in the post-immunization IgM and IgG compartments. Although ImmunediveRsity is similar to other recently developed tools, it offers significant advantages that facilitate repertoire analysis and repertoire mining. ImmunediveRsity is open source and free for academic purposes and it runs on 64 bit GNU/Linux and MacOS. Available at: https://bitbucket.org/ImmunediveRsity/immunediversity/

A genome-wide search for type 2 diabetes susceptibility genes in an extended Arab family

Twenty percent of people aged 20 to 79 have type 2 diabetes (T2D) in the United Arab Emirates (UAE). Genome-wide association studies (GWAS) to identify genes for T2D have not been reported for Arab countries. We performed a discovery GWAS in an extended UAE family (N=178; 66 diabetic; 112 healthy) genotyped on the Illumina Human 660 Quad Beadchip, with independent replication of top hits in 116 cases and 199 controls. Power to achieve genome-wide significance (commonly P=5×10(-8)) was therefore limited. Nevertheless, transmission disequilibrium testing in FBAT identified top hits at Chromosome 4p12-p13 (KCTD8: rs4407541, P=9.70×10(-6); GABRB1: rs10517178/rs1372491, P=4.19×10(-6)) and 14q13 (PRKD1: rs10144903, 3.92×10(-6)), supported by analysis using a linear mixed model approximation in GenABEL (4p12-p13 GABRG1/GABRA2: rs7662743, Padj-agesex=2.06×10(-5); KCTD8: rs4407541, Padj-agesex=1.42×10(-4); GABRB1: rs10517178/rs1372491, Padj-agesex=0.027; 14q13 PRKD1: rs10144903, Padj-agesex=6.95×10(-5)). SNPs across GABRG1/GABRA2 did not replicate, whereas more proximal SNPs rs7679715 (Padj-agesex=0.030) and rs2055942 (Padj-agesex=0.022) at COX7B2/GABRA4 did, in addition to a trend distally at KCTD8 (rs4695718: Padj-agesex=0.096). Modelling of discovery and replication data support independent signals at GABRA4 (rs2055942: Padj-agesex-combined=3×10(-4)) and at KCTD8 (rs4695718: Padj-agesex-combined=2×10(-4)). Replication was observed for PRKD1 rs1953722 (proxy for rs10144903; Padj-agesex=0.031; Padj-agesex-combined=2×10(-4)). These genes may provide important functional leads in understanding disease pathogenesis in this population.

Role of proteomics in understanding prion infection

Transmissible spongiform encephalopathies or prion diseases are fatal neurodegenerative pathologies characterized by the autocatalytic misfolding and polymerization of a cellular glycoprotein (cellular prion protein [PrP(C)]) that accumulates in the CNS and leads to neurodegeneration. The detailed mechanics of PrP(C) conversion to its pathological isoform (PrP(TSE)) are unclear but one or more exogenous factors are likely involved in the process of PrP misfolding. In the last 20 years, proteomic investigations have identified several endogenous proteins that interact with PrP(C), PrP(TSE) or both, which are possibly involved in the prion pathogenetic process. However, current approaches have not yet produced convincing conclusions on the biological value of such PrP interactors. Future advancements in the comprehension of the molecular pathogenesis of prion diseases, in experimental techniques and in data analysis procedures, together with a boost in more productive international collaborations, are therefore needed to improve the understanding on the role of PrP interactors. Finally, the advancement of 'omics' techniques in prion diseases will contribute to the development of novel diagnostic tests and effective drugs.

A combined DPA1~DPB1 amino acid epitope is the primary unit of selection on the HLA-DP heterodimer

Here, we present results for DPA1 and DPB1 four-digit allele-level typing in a large (n = 5,944) sample of unrelated European American stem cell donors previously characterized for other class I and class II loci. Examination of genetic data for both chains of the DP heterodimer in the largest cohort to date, at the amino acid epitope, allele, genotype, and haplotype level, allows new insights into the functional units of selection and association for the DP heterodimer. The data in this study suggest that for the DPA1-DPB1 heterodimer, the unit of selection is the combined amino acid epitope contributed by both the DPA1 and DPB1 genes, rather than the allele, and that patterns of LD are driven primarily by dimer stability and conformation of the P1 pocket. This may help explain the differential pattern of allele frequency distribution observed for this locus relative to the other class II loci. These findings further support the notion that allele-level associations in disease and transplantation may not be the most important unit of analysis, and that they should be considered instead in the molecular context.

Mixed Modeling with Whole Genome Data

Objective. We consider the need for a modeling framework for related individuals and various sources of variations. The relationships could either be among relatives in families or among unrelated individuals in a general population with cryptic relatedness; both could be refined or derived with whole genome data. As with variations they can include oliogogenes, polygenes, single nucleotide polymorphism (SNP), and covariates.Methods. We describe mixed models as a coherent theoretical framework to accommodate correlations for various types of outcomes in relation to many sources of variations. The framework also extends to consortium meta-analysis involving both population-based and family-based studies.Results. Through examples we show that the framework can be furnished with general statistical packages whose great advantage lies in simplicity and exibility to study both genetic and environmental effects. Areas which require further work are also indicated.Conclusion. Mixed models will play an important role in practical analysis of data on both families and unrelated individuals when whole genome information is available.

solQTL: a tool for QTL analysis, visualization and linking to genomes at SGN database

Background

A common approach to understanding the genetic basis of complex traits is through identification of associated quantitative trait loci (QTL). Fine mapping QTLs requires several generations of backcrosses and analysis of large populations, which is time-consuming and costly effort. Furthermore, as entire genomes are being sequenced and an increasing amount of genetic and expression data are being generated, a challenge remains: linking phenotypic variation to the underlying genomic variation. To identify candidate genes and understand the molecular basis underlying the phenotypic variation of traits, bioinformatic approaches are needed to exploit information such as genetic map, expression and whole genome sequence data of organisms in biological databases.

Description

The Sol Genomics Network (SGN, http://solgenomics.net) is a primary repository for phenotypic, genetic, genomic, expression and metabolic data for the Solanaceae family and other related Asterids species and houses a variety of bioinformatics tools. SGN has implemented a new approach to QTL data organization, storage, analysis, and cross-links with other relevant data in internal and external databases. The new QTL module, solQTL, http://solgenomics.net/qtl/, employs a user-friendly web interface for uploading raw phenotype and genotype data to the database, R/QTL mapping software for on-the-fly QTL analysis and algorithms for online visualization and cross-referencing of QTLs to relevant datasets and tools such as the SGN Comparative Map Viewer and Genome Browser. Here, we describe the development of the solQTL module and demonstrate its application.

Conclusions

solQTL allows Solanaceae researchers to upload raw genotype and phenotype data to SGN, perform QTL analysis and dynamically cross-link to relevant genetic, expression and genome annotations. Exploration and synthesis of the relevant data is expected to help facilitate identification of candidate genes underlying phenotypic variation and markers more closely linked to QTLs. solQTL is freely available on SGN and can be used in private or public mode.

HLA-DRB1*0401 and HLA-DRB1*0408 are strongly associated with the development of antibodies against interferon-beta therapy in multiple sclerosis

The formation of antibodies to interferon-beta (IFN-β), a protein-based disease-modifying agent for multiple sclerosis (MS), is a problem in clinical practice. These antibodies may neutralize the biological effects of the protein drug, potentially decreasing its therapeutic effects. By high-resolution HLA class I and II typing we identified two HLA class II alleles associated with the development of antibodies to IFN-β. In two independent continuous and binary-trait association studies, HLA-DRB1^∗0401 and HLA-DRB1^∗0408 (odds ratio: 5.15)—but not other HLA alleles—were strongly associated with the development of binding and neutralizing antibodies to IFN-β. The associated HLA-DRB1^∗04 alleles differ from nonassociated HLA-DRB1^∗04 alleles by a glycine-to-valine substitution in position 86 of the epitope-binding alpha-helix of the HLA class II molecule. The peptide-binding motif of HLA-DRB1^∗0401 and ^∗0408 might promote binding and presentation of an immunogenic peptide, which may eventually break T cell tolerance and facilitate antibody development to IFN-β. In summary, we identified genetic factors determining the immunogenicity of IFN-β, a protein-based disease-modifying agent for the treatment of MS.

AssociationDB: web-based exploration of genomic association

Genome-wide association studies use hundreds of thousands of markers making it challenging to present and finally interpret the results. We developed a graphical, web-based solution for an interactive exploration of the results of case-control studies, with a tight integration of related gene information and tissue-specific expression data. Association results are presented as physical position-based vertical bars with known genes included as horizontal bars at their respective physical positions. The interface allows the specification of filtering criteria for the association data and highlights potentially interesting genes with user-specified terms occurring in their reports or with relevant expression patterns. Pop-up windows and hyperlinks provide drill-down capabilities and quick access to relevant data AssociationDB can either be used as a stand-alone solution or as a front-end joining association results obtained by other software with genomic information.

Association of alpha-synuclein gene haplotypes with Parkinson's disease

In a previous study, we detected an association between a dinucleotide repeat (Rep1) in the alpha-Synuclein (SNCA) gene and sporadic Parkinson's disease (PD). To extend our previous finding in a larger sample and further determine the role of SNCA in the development of PD, we screened a sample of 194 familial PD (FPD), 327 sporadic PD (SPD), and 215 controls with the Rep1 marker and 2 single nucleotide polymorphisms (SNPs) (770 and int4) in the SNCA gene. There was significant difference in allele frequency between African American and American Indian groups for Rep1 marker (p=0.03). These two samples were excluded from further analysis because of sample size. Comparison of allele frequency differences between PD and controls for the single-locus was significant only for Rep1 and SPD (p=0.017). The global case control association was highly significant for the three loci haplotypes comparisons. Our results indicate that Rep1 locus may be in linkage disequilibrium (LD) with a mutation in the gene or itself could be a risk factor for SPD.

Computer programs for population genetics data analysis: a survival guide

The analysis of genetic diversity within species is vital for understanding evolutionary processes at the population level and at the genomic level. A large quantity of data can now be produced at an unprecedented rate, requiring the use of dedicated computer programs to extract all embedded information. Several statistical packages have been recently developed, which offer a panel of standard and more sophisticated analyses. We describe here the functionalities, special features and assumptions of more than 20 such programs, indicate how they can interoperate, and discuss new directions that could lead to improved software and analyses.

Pedigree-drawing with R and graphviz

Two functions for pedigree-drawing available in R (http://www.r-project.org): plot.pedigree in kinship and pedtodot in gap are described. The latter requires graphviz (http://www.graphviz.org). They can produce many pedigree diagrams quickly into a single file, serving as alternatives to programs that only offer interactive use.

AVAILABILITY

Packages kinship and gap are available from http://cran.r-project.org.