Selective footprints and genes relevant to cold adaptation and other phenotypic traits are unscrambled in the genomes of divergently selected chicken breeds

BACKGROUND

The genomes of worldwide poultry breeds divergently selected for performance and other phenotypic traits may also be affected by, and formed due to, past and current admixture events. Adaptation to diverse environments, including acclimation to harsh climatic conditions, has also left selection footprints in breed genomes.

RESULTS

Using the Chicken 50K_CobbCons SNP chip, we genotyped four divergently selected breeds: two aboriginal, cold tolerant Ushanka and Orloff Mille Fleur, one egg-type Russian White subjected to artificial selection for cold tolerance, and one meat-type White Cornish. Signals of selective sweeps were determined in the studied breeds using three methods: (1) assessment of runs of homozygosity islands, (2) F_ST based population differential analysis, and (3) haplotype differentiation analysis. Genomic regions of true selection signatures were identified by two or more methods or in two or more breeds. In these regions, we detected 540 prioritized candidate genes supplemented them with those that occurred in one breed using one statistic and were suggested in other studies. Amongst them, SOX5, ME3, ZNF536, WWP1, RIPK2, OSGIN2, DECR1, TPO, PPARGC1A, BDNF, MSTN, and beta-keratin genes can be especially mentioned as candidates for cold adaptation. Epigenetic factors may be involved in regulating some of these important genes (e.g., TPO and BDNF).

CONCLUSION

Based on a genome-wide scan, our findings can help dissect the genetic architecture underlying various phenotypic traits in chicken breeds. These include genes representing the sine qua non for adaptation to harsh environments. Cold tolerance in acclimated chicken breeds may be developed following one of few specific gene expression mechanisms or more than one overlapping response known in cold-exposed individuals, and this warrants further investigation.

Modeling the Dependence Structure in Genome Wide Association Studies of Binary Phenotypes in Family Data

Genome-wide association studies (GWASs) are a popular tool for detecting association between genetic variants or single nucleotide polymorphisms (SNPs) and complex traits. Family data introduce complexity due to the non-independence of the family members. Methods for non-independent data are well established, but when the GWAS contains distinct family types, explicit modeling of between-family-type differences in the dependence structure comes at the cost of significantly increased computational burden. The situation is exacerbated with binary traits. In this paper, we perform several simulation studies to compare multiple candidate methods to perform single SNP association analysis with binary traits. We consider generalized estimating equations (GEE), generalized linear mixed models (GLMMs), or generalized least square (GLS) approaches. We study the influence of different working correlation structures for GEE on the GWAS findings and also the performance of different analysis method(s) to conduct a GWAS with binary trait data in families. We discuss the merits of each approach with attention to their applicability in a GWAS. We also compare the performances of the methods on the alcoholism data from the Minnesota Center for Twin and Family Research (MCTFR) study.

Parametric Linkage Analysis Identifies Five Novel Genome-Wide Significant Loci for Familial Lung Cancer

OBJECTIVE

One of four American cancer patients dies of lung cancer. Environmental factors such as tobacco smoking are known to affect lung cancer risk. However, there is a genetic factor to lung cancer risk as well. Here, we perform parametric linkage analysis on family-based genotype data in an effort to find genetic loci linked to the disease.

METHODS

197 individuals from families with a high-risk history of lung cancer were recruited and genotyped using an Illumina array. Parametric linkage analyses were performed using an affected-only phenotype model with an autosomal dominant inheritance using a disease allele frequency of 0.01. Three types of analyses were performed: single variant two-point, collapsed haplotype pattern variant two-point, and multipoint analysis.

RESULTS

Five novel genome-wide significant loci were identified at 18p11.23, 2p22.2, 14q13.1, 16p13, and 20q13.11. The families most informative for linkage were also determined.

CONCLUSIONS

The 5 novel signals are good candidate regions, containing genes that have been implicated as having somatic changes in lung cancer or other cancers (though not in germ line cells). Targeted sequencing on the significant loci is planned to determine the causal variants at these loci.

Copy Number Variations in Tilapia Genomes

Discovering the nature and pattern of genome variation is fundamental in understanding phenotypic diversity among populations. Although several millions of single nucleotide polymorphisms (SNPs) have been discovered in tilapia, the genome-wide characterization of larger structural variants, such as copy number variation (CNV) regions has not been carried out yet. We conducted a genome-wide scan for CNVs in 47 individuals from three tilapia populations. Based on 254 Gb of high-quality paired-end sequencing reads, we identified 4642 distinct high-confidence CNVs. These CNVs account for 1.9% (12.411 Mb) of the used Nile tilapia reference genome. A total of 1100 predicted CNVs were found overlapping with exon regions of protein genes. Further association analysis based on linear model regression found 85 CNVs ranging between 300 and 27,000 base pairs significantly associated to population types (R ² > 0.9 and P > 0.001). Our study sheds first insights on genome-wide CNVs in tilapia. These CNVs among and within tilapia populations may have functional effects on phenotypes and specific adaptation to particular environments.

Accounting for selection and correlation in the analysis of two-stage genome-wide association studies

The problem of selection bias has long been recognized in the analysis of two-stage trials, where promising candidates are selected in stage 1 for confirmatory analysis in stage 2. To efficiently correct for bias, uniformly minimum variance conditionally unbiased estimators (UMVCUEs) have been proposed for a wide variety of trial settings, but where the population parameter estimates are assumed to be independent. We relax this assumption and derive the UMVCUE in the multivariate normal setting with an arbitrary known covariance structure. One area of application is the estimation of odds ratios (ORs) when combining a genome-wide scan with a replication study. Our framework explicitly accounts for correlated single nucleotide polymorphisms, as might occur due to linkage disequilibrium. We illustrate our approach on the measurement of the association between 11 genetic variants and the risk of Crohn's disease, as reported in Parkes and others (2007. Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility. Nat. Gen. 39: (7), 830-832.), and show that the estimated ORs can vary substantially if both selection and correlation are taken into account.

A novel MSX1 intronic mutation associated with autosomal dominant non-syndromic oligodontia in a large Chinese family pedigree

BACKGROUND

Tooth agenesis is a common developmental dental anomaly. The aim of the study was to identify the causal genetic mutation in a four-generation Chinese family affected with non-syndromic autosomal dominant tooth agenesis.

METHODS

Genome-wide scanning was performed using the Illumina Linkage-12 array. Genotyping of short tandem repeat markers was used to finely map the causative locus. Haplotype analysis and Sanger sequencing was performed to precisely locate the position and nature of the gene defect.

RESULTS

Clinical examination of the available 23 family members showed variable tooth agenesis in 10 subjects, ranging from oligodontia to mild hypodontia. Genome-wide scanning and haplotype analyses identified the 4p16.1-p16.3 region with a maximum multi-point LOD score of 3.50, which overlapped with the MSX1 gene. A single heterozygous point mutation IVS1-5 G>A in the MSX1 gene was exclusively detected in the 10 family members affected with tooth agenesis. Sequencing of MSX1 cDNA revealed that the intronic mutation did not affect the normal splicing pattern of the pre-mRNA. However, real-time qPCR analysis of lymphocyte RNA showed that the level of MSX1 mRNA was significantly decreased in individuals heterozygous for the mutation.

CONCLUSIONS

We identified and characterized a novel intronic mutation in the MSX1 gene in a large Chinese pedigree, adding to the small repertoire of MSX1 mutations associated with autosomal dominant tooth agenesis. We hypothesize that the variable degree of tooth agenesis observed in each affected individual may be due to sub-optimal levels of MSX1 expression during critical stages tooth development.

Finding novel genes by testing G × E interactions in a genome-wide association study

In a genome-wide association study (GWAS), investigators typically focus their primary analysis on the direct (marginal) associations of each single nucleotide polymorphism (SNP) with the trait. Some SNPs that are truly associated with the trait may not be identified in this scan if they have a weak marginal effect and thus low power to be detected. However, these SNPs may be quite important in subgroups of the population defined by an environmental or personal factor, and may be detectable if such a factor is carefully considered in a gene-environment (G × E) interaction analysis. We address the question "Using a genome wide interaction scan (GWIS), can we find new genes that were not found in the primary GWAS scan?" We review commonly used approaches for conducting a GWIS in case-control studies, and propose a new two-step screening and testing method (EDG×E) that is optimized to find genes with a weak marginal effect. We simulate several scenarios in which our two-step method provides 70-80% power to detect a disease locus while a marginal scan provides less than 5% power. We also provide simulations demonstrating that the EDG×E method outperforms other GWIS approaches (including case only and previously proposed two-step methods) for finding genes with a weak marginal effect. Application of this method to a G × Sex scan for childhood asthma reveals two potentially interesting SNPs that were not identified in the marginal-association scan. We distribute a new software program (G×Escan, available at http://biostats.usc.edu/software) that implements this new method as well as several other GWIS approaches.

Increased CNV-region deletions in mild cognitive impairment (MCI) and Alzheimer's disease (AD) subjects in the ADNI sample

We investigated the genome-wide distribution of CNVs in the Alzheimer's disease (AD) Neuroimaging Initiative (ADNI) sample (146 with AD, 313 with Mild Cognitive Impairment (MCI), and 181 controls). Comparison of single CNVs between cases (MCI and AD) and controls shows overrepresentation of large heterozygous deletions in cases (p-value<0.0001). The analysis of CNV-Regions identifies 44 copy number variable loci of heterozygous deletions, with more CNV-Regions among affected than controls (p=0.005). Seven of the 44 CNV-Regions are nominally significant for association with cognitive impairment. We validated and confirmed our main findings with genome re-sequencing of selected patients and controls. The functional pathway analysis of the genes putatively affected by deletions of CNV-Regions reveals enrichment of genes implicated in axonal guidance, cell-cell adhesion, neuronal morphogenesis and differentiation. Our findings support the role of CNVs in AD, and suggest an association between large deletions and the development of cognitive impairment.

Role of genetics in the diagnosis and prognosis of Crohn's disease

Considering the epidemiological, genetic and immunological data, we can conclude that the inflammatory bowel diseases are heterogeneous disorders of multifactorial etiology in which hereditability and environment interact to produce the disease. It is probable that patients have a genetic predisposition for the development of the disease coupled with disturbances in immunoregulation. Several genes have so far been related to the diagnosis of Crohn's disease. These genes are related to innate pattern recognition receptors, to epithelial barrier homeostasis and maintenance of epithelial barrier integrity, to autophagy and to lymphocyte differentiation. So far, the strongest and most replicated associations with Crohn's disease have been demonstrated with NOD2, IL23R and ATG16L1 genes. Many genes have so far been implicated in the prognosis of Crohn's disease and many attempts have been made for classification of genetic profiles in Crohn's disease. CARD15 seems to be not only a susceptibility gene, but also a disease-modifier gene for Crohn's disease. Enriching our understanding of Crohn's disease genetics is of value, but when combining genetic data with functional data the outcome could be of major importance to clinicians.