A new multipoint method for genome-wide association studies by imputation of genotypes

Genome-wide association studies are set to become the method of choice for uncovering the genetic basis of human diseases. A central challenge in this area is the development of powerful multipoint methods that can detect causal variants that have not been directly genotyped. We propose a coherent analysis framework that treats the problem as one involving missing or uncertain genotypes. Central to our approach is a model-based imputation method for inferring genotypes at observed or unobserved SNPs, leading to improved power over existing methods for multipoint association mapping. Using real genome-wide association study data, we show that our approach (i) is accurate and well calibrated, (ii) provides detailed views of associated regions that facilitate follow-up studies and (iii) can be used to validate and correct data at genotyped markers. A notable future use of our method will be to boost power by combining data from genome-wide scans that use different SNP sets.     

Bayesian method to predict individual SNP genotypes from gene expression data

RNA profiling can be used to capture the expression patterns of many genes that are associated with expression quantitative trait loci (eQTLs). Employing published putative cis eQTLs, we developed a Bayesian approach to predict SNP genotypes that is based only on RNA expression data. We show that predicted genotypes can accurately and uniquely identify individuals in large populations. When inferring genotypes from an expression data set using eQTLs of the same tissue type (but from an independent cohort), we were able to resolve 99% of the identities of individuals in the cohort at P(adjusted) ≤ 1 × 10(-5). When eQTLs derived from one tissue were used to predict genotypes using expression data from a different tissue, the identities of 90% of the study subjects could be resolved at P(adjusted) ≤ 1 × 10(-5). We discuss the implications of deriving genotypic information from RNA data deposited in the public domain.     

In vivo RNA interference demonstrates a role for Nramp1 in modifying susceptibility to type 1 diabetes

Type 1 diabetes is an autoimmune disease influenced by multiple genetic loci. Although more than 20 insulin-dependent diabetes (Idd) loci have been implicated in the nonobese diabetic (NOD) mouse model, few causal gene variants have been identified. Here we show that RNA interference (RNAi) can be used to probe candidate genes in this disease model. Slc11a1 encodes a phagosomal ion transporter, Nramp1, that affects resistance to intracellular pathogens and influences antigen presentation. This gene is the strongest candidate among the 42 genes in the Idd5.2 region; a naturally occurring mutation in the protective Idd5.2 haplotype results in loss of function of the Nramp1 protein. Using lentiviral transgenesis, we generated NOD mice in which Slc11a1 is silenced by RNAi. Silencing reduced the frequency of type 1 diabetes, mimicking the protective Idd5.2 region. Our results demonstrate a role for Slc11a1 in modifying susceptibility to type 1 diabetes and illustrate that RNAi can be used to study causal genes in a mammalian model organism.     

In situ analyses of genome instability in breast cancer

Transition through telomere crisis is thought to be a crucial event in the development of most breast carcinomas. Our goal in this study was to determine where this occurs in the context of histologically defined breast cancer progression. To this end, we assessed genome instability (using fluorescence in situ hybridization) and other features associated with telomere crisis in normal ductal epithelium, usual ductal hyperplasia, ductal carcinoma in situ and invasive cancer. We modeled this process in vitro by measuring these same features in human mammary epithelial cell cultures during ZNF217-mediated transition through telomere crisis and immortalization. Taken together, the data suggest that transition through telomere crisis and immortalization in breast cancer occurs during progression from usual ductal hyperplasia to ductal carcinoma in situ.     

A unified mixed-model method for association mapping that accounts for multiple levels of relatedness

As population structure can result in spurious associations, it has constrained the use of association studies in human and plant genetics. Association mapping, however, holds great promise if true signals of functional association can be separated from the vast number of false signals generated by population structure. We have developed a unified mixed-model approach to account for multiple levels of relatedness simultaneously as detected by random genetic markers. We applied this new approach to two samples: a family-based sample of 14 human families, for quantitative gene expression dissection, and a sample of 277 diverse maize inbred lines with complex familial relationships and population structure, for quantitative trait dissection. Our method demonstrates improved control of both type I and type II error rates over other methods. As this new method crosses the boundary between family-based and structured association samples, it provides a powerful complement to currently available methods for association mapping.     

MAGIC, an in vivo genetic method for the rapid construction of recombinant DNA molecules

We describe a highly engineered in vivo cloning method, mating-assisted genetically integrated cloning (MAGIC), that facilitates the rapid construction of recombinant DNA molecules. MAGIC uses bacterial mating, in vivo site-specific endonuclease cleavage and homologous recombination to catalyze the transfer of a DNA fragment between a donor vector in one bacterial strain and a recipient plasmid in a separate bacterial strain. Recombination events are genetically selected and result in placement of the gene of interest under the control of new regulatory elements with high efficiency. MAGIC eliminates the need for restriction enzymes, DNA ligases, preparation of DNA and all in vitro manipulations required for subcloning and allows the rapid construction of multiple constructs with minimal effort. We show that MAGIC can generate constructs for expression in multiple organisms. As this new method requires only the simple mixing of bacterial strains, it represents a substantial advance in high-throughput recombinant DNA production that will save time, effort and expense in functional genomics studies.     

A robust statistical method for case-control association testing with copy number variation

Copy number variation (CNV) is pervasive in the human genome and can play a causal role in genetic diseases. The functional impact of CNV cannot be fully captured through linkage disequilibrium with SNPs. These observations motivate the development of statistical methods for performing direct CNV association studies. We show through simulation that current tests for CNV association are prone to false-positive associations in the presence of differential errors between cases and controls, especially if quantitative CNV measurements are noisy. We present a statistical framework for performing case-control CNV association studies that applies likelihood ratio testing of quantitative CNV measurements in cases and controls. We show that our methods are robust to differential errors and noisy data and can achieve maximal theoretical power. We illustrate the power of these methods for testing for association with binary and quantitative traits, and have made this software available as the R package CNVtools.     

Cyclin-dependent kinase 2 is essential for meiosis but not for mitotic cell division in mice

We targeted the locus encoding the cyclin-dependent kinase 2 (CDK2) by homologous recombination in mouse embryonic stem (ES) cells. Embryonic fibroblasts lacking CDK2 proliferate normally and become immortal after continuous passage in culture. Elimination of a conditional Cdk2 allele in immortal cells does not have a significant effect on proliferation. Cdk2-/- mice are viable and survive for up to two years, indicating that CDK2 is also dispensable for proliferation and survival of most cell types. But CDK2 is essential for completion of prophase I during meiotic cell division in male and female germ cells, an unforeseen role for this cell cycle kinase.     

'Racial' differences in genetic effects for complex diseases

'Racial' differences are frequently debated in clinical, epidemiological and molecular research and beyond. In particular, there is considerable controversy regarding the existence and importance of 'racial' differences in genetic effects for complex diseases influenced by a large number of genes. An important question is whether ancestry influences the impact of each gene variant on the disease risk. Here, we addressed this question by examining the genetic effects for 43 validated gene-disease associations across 697 study populations of various descents. The frequencies of the genetic marker of interest in the control populations often (58%) showed large heterogeneity (statistical variability) between 'races'. Conversely, we saw large heterogeneity in the genetic effects (odds ratios) between 'races' in only 14% of cases. Genetic markers for proposed gene-disease associations vary in frequency across populations, but their biological impact on the risk for common diseases may usually be consistent across traditional 'racial' boundaries.     

Cryptorchidism in mice mutant for Insl3.

Impaired testicular descent (cryptorchidism) is one of the most frequent congenital abnormalities in humans, involving 2% of male births. Cryptorchidism can result in infertility and increases risk for development of germ-cell tumours. Testicular descent from abdomen to scrotum occurs in two distinct phases: the trans-abdominal phase and the inguino-scrotal phase. Currently, little is known about the factors that regulate the trans-abdominal phase of testicular descent. Leydig insulin-like hormone (Insl3) is a member of the insulin hormone superfamily expressed in the developing testis. We show here that mice mutant for Insl3 are viable, but exhibit bilateral cryptorchidism due to developmental abnormalities of the gubernaculum, resulting in abnormal spermatogenesis and infertility. Female homozygotes have impaired fertility associated with deregulation of the oestrus cycle. These findings reveal roles for Insl3 in the development of the urogenital tract and in female fertility. Insl3 may act as a hormone to regulate the growth and differentiation of the gubernaculum, thereby mediating intra-abdominal testicular descent.     

Genome-wide in situ exon capture for selective resequencing

Increasingly powerful sequencing technologies are ushering in an era of personal genome sequences and raising the possibility of using such information to guide medical decisions. Genome resequencing also promises to accelerate the identification of disease-associated mutations. Roughly 98% of the human genome is composed of repeats and intergenic or non-protein-coding sequences. Thus, it is crucial to focus resequencing on high-value genomic regions. Protein-coding exons represent one such type of high-value target. We have developed a method of using flexible, high-density microarrays to capture any desired fraction of the human genome, in this case corresponding to more than 200,000 protein-coding exons. Depending on the precise protocol, up to 55-85% of the captured fragments are associated with targeted regions and up to 98% of intended exons can be recovered. This methodology provides an adaptable route toward rapid and efficient resequencing of any sizeable, non-repeat portion of the human genome.     

Population choice in mapping genes for complex diseases

The difficulty of identifying susceptibility genes for common diseases has polarized geneticists' views on what disease models are appropriate and how best to proceed once high-density genome maps become available. Different disease models have different implications for using linkage or linkage-disequilibrium-based approaches for mapping complex disease genes. We argue that the choice of study population is a critical factor when designing a study, and that genetically simplified isolates are more useful than diverse continental populations under most assumptions.     

Strategies for dissecting epigenetic mechanisms in the mouse

Epigenetics generally refers to heritable changes in gene expression that are independent of nucleotide sequence. With complete genome sequences in hand, understanding the epigenetic control of genomes is the next step towards comprehending how the same DNA sequence gives rise to different cells, lineages and organs. Epigenetics also contributes to individual variation in normal biology and in disease states. The mouse provides a unique opportunity to understand how epigenetic differences contribute to both development and disease in a tractable mammalian system. Here we discuss current approaches and protocols used to study epigenetics in the mouse, including loss-of-function studies, mutagenesis screens, somatic cell nuclear transfer, genomics and proteomics.     

Systematic screen for human disease genes in yeast

High similarity between yeast and human mitochondria allows functional genomic study of Saccharomyces cerevisiae to be used to identify human genes involved in disease. So far, 102 heritable disorders have been attributed to defects in a quarter of the known nuclear-encoded mitochondrial proteins in humans. Many mitochondrial diseases remain unexplained, however, in part because only 40-60% of the presumed 700-1,000 proteins involved in mitochondrial function and biogenesis have been identified. Here we apply a systematic functional screen using the pre-existing whole-genome pool of yeast deletion mutants to identify mitochondrial proteins. Three million measurements of strain fitness identified 466 genes whose deletions impaired mitochondrial respiration, of which 265 were new. Our approach gave higher selection than other systematic approaches, including fivefold greater selection than gene expression analysis. To apply these advantages to human disorders involving mitochondria, human orthologs were identified and linked to heritable diseases using genomic map positions.     

Parameters for reliable results in genetic association studies in common disease.

It is increasingly apparent that the identification of true genetic associations in common multifactorial disease will require studies comprising thousands rather than the hundreds of individuals employed to date. Using 2,873 families, we were unable to confirm a recently published association of the interleukin 12B gene in 422 type I diabetic families. These results emphasize the need for large datasets, small P values and independent replication if results are to be reliable.