Identity-by-Descent Mapping to Detect Rare Variants Conferring Susceptibility to Multiple Sclerosis

Genome-wide association studies (GWAS) have identified around 60 common variants associated with multiple sclerosis (MS), but these loci only explain a fraction of the heritability of MS. Some missing heritability may be caused by rare variants that have been suggested to play an important role in the aetiology of complex diseases such as MS. However current genetic and statistical methods for detecting rare variants are expensive and time consuming. 'Population-based linkage analysis' (PBLA) or so called identity-by-descent (IBD) mapping is a novel way to detect rare variants in extant GWAS datasets. We employed BEAGLE fastIBD to search for rare MS variants utilising IBD mapping in a large GWAS dataset of 3,543 cases and 5,898 controls. We identified a genome-wide significant linkage signal on chromosome 19 (LOD = 4.65; p = 1.9×10-6). Network analysis of cases and controls sharing haplotypes on chromosome 19 further strengthened the association as there are more large networks of cases sharing haplotypes than controls. This linkage region includes a cluster of zinc finger genes of unknown function. Analysis of genome wide transcriptome data suggests that genes in this zinc finger cluster may be involved in very early developmental regulation of the CNS. Our study also indicates that BEAGLE fastIBD allowed identification of rare variants in large unrelated population with moderate computational intensity. Even with the development of whole-genome sequencing, IBD mapping still may be a promising way to narrow down the region of interest for sequencing priority. © 2013 Lin et al.

Identity by descent and candidate gene mapping of Richieri-Costa and Pereira syndrome

The Richieri-Costa-Pereira syndrome is a rare autosomal recessive disorder characterized by short stature, Robin sequence, cleft mandible, pre/postaxial anomalies and clubfoot. of 15 families reported with this disorder 14 are from Brazil suggesting a founder effect. We studied 15 families using identity-by-descent as a hypothesis to attempt gene localization We have examined through linkage analysis 497 polymorphicmarkers and also performed direct sequencing of exons for 10 candidate genes selected on the basis of their expression in the developing mandible and limb. No evidence for allele sharing at any locus tested or mutations in candidate genes was found. Additional higher resolution mapping, new families and other candidate genes might improve future chances of gene identification. (C) 2003 Wiley-Liss, Inc.

Prediction of multilocus identity-by-descent

Previous studies have enabled exact prediction of probabilities of identity-by-descent (IBD) in randommating populations for a few loci (up to four or so), with extension to more using approximate regression methods. Here we present a precise predictor of multiple-locus IBD using simple formulas based on exact results for two loci. In particular, the probability of non-IBD X ABC at each of ordered loci A, B, and C can be well approximated by XABC = XABXBC/XB and generalizes to X123. . .k = X12X23. . .Xk-1,k/ Xk-2, where X is the probability of non-IBD at each locus. Predictions from this chain rule are very precise with population bottlenecks and migration, but are rather poorer in the presence of mutation. From these coefficients, the probabilities of multilocus IBD and non-IBD can also be computed for genomic regions as functions of population size, time, and map distances. An approximate but simple recurrence formula is also developed, which generally is less accurate than the chain rule but is more robust with mutation. Used together with the chain rule it leads to explicit equations for non-IBD in a region. The results can be applied to detection of quantitative trait loci (QTL) by computing the probability of IBD at candidate loci in terms of identity-by-state at neighboring markers.

Comparison of identity by descent and identity by state for detecting genetic regions under selection in a sorghum pedigree breeding program

Seventy sorghum inbred lines which formed part of the Queensland Department of Primary Industries (QDPI) sorghum breeding program were screened with 104 previously mapped RFLP markers. The lines were related by pedigree and consisted of ancestral source lines, intermediate lines and recent releases from the program. We compared the effect of defining marker alleles using either identity by state (IBS) or identity by descent (IBD) on our capacity to trace markers through the pedigree and detect evidence of selection for particular alleles. Allelic identities defined using IBD were much more sensitive for detecting non-Mendelian segregation in this pedigree. Only one marker allele showed significant evidence of selection when IBS was used compared with ten regions with particular allelic identities when IBD was used. Regions under selection were compared with the location of QTLs for agronomic traits known to be under selection in the breeding program. Only two of the ten regions were associated with known QTLs that matched with knowledge of the agronomic characteristics of the ancestral lines. Some of the other regions were hypothesised to be associated with genes for particular traits based on the properties of the ancestral source lines.

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.

Using identity-by-de scent information in affected sib pairs to increase the efficiency of genetic association studies

T he aim of this study was to determine whether identity-by-descent (IBD) information for affected sib pairs (ASPs) can be used to select a sample of cases for a genetic case-control study which will provide more power for detecting association with loci in a known linkage region. By modeling the expected frequency of the disease allele in ASPs showing IBD sharing of 0, 1, or 2 alleles, and considering additive, recessive, and dominant disease models, we show that cases selected from IBD 2 families are best for this purpose, followed by those selected from IBD 1 families; least useful are cases selected from IBD 0 families.

Prediction of IBD based on population history for fine gene mapping

A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDL probabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBD L are used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM.

Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

Acheiropodia is caused by a genomic deletion in C7orf2, the human orthologue of the Lmbr1 gene

Acheiropodia is an autosomal recessive developmental disorder presenting with bilateral congenital amputations of the upper and lower extremities and aplasia of the hands and feet. This severely handicapping condition appears to affect only the extremities, with no other systemic manifestations reported. Recently, a locus for acheiropodia was mapped on chromosome 7q36. Herein we report the narrowing of the critical region for the acheiropodia gene and the subsequent identification of a common mutation in C7orf2-the human orthologue of the mouse Lmbr1 gene-that is responsible for the disease. Analysis of five families with acheiropodia, by means of 15 polymorphic markers, narrowed the critical region to 1.3 cM, on the basis of identity by descent, and to <0.5 Mb, on the basis of physical mapping. Analysis of C7orf2, the human orthologue of the mouse Lmbr1 gene, identified a deletion in all five families, thus identifying a common acheiropodia mutation. The deletion was identified at both the genomic-DNA and mRNA level. It leads to the production of a C7orf2 transcript lacking exon 4 and introduces a premature stop codon downstream of exon 3. Given the nature of the acheiropodia phenotype, it appears likely that the Lmbr1 gene plays an important role in limb development.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.

A new semi-dwarfing gene identified by molecular mapping of quantitative trait loci in barley.

Semi-dwarfing genes have been widely used in spring barley (Hordeum vulgare L.) breeding programs in many parts of the world, but the success in developing barley cultivars with semi-dwarfing genes has been limited in North America. Exploiting new semi-dwarfing genes may help in solving this dilemma. A recombinant inbred line population was developed by crossing ZAU 7, a semi-dwarf cultivar from China, to ND16092, a tall breeding line from North Dakota. To identify quantitative trait loci (QTL) controlling plant height, a linkage map comprised of 111 molecular markers was constructed. Simple interval mapping was performed for each of the eight environments. A consistent QTL for plant height was found on chromosome 7HL. This QTL is not associated with maturity and rachis internode length. We suggest the provisional name Qph-7H for this QTL. Qph-7H from ZAU 7 reduced plant height to about 3/4 of normal; thus, Qph-7H is considered a semi-dwarfing gene. Other QTLs for plant height were found, but their expression was variable across the eight environments tested.

Marker selection by Akaike information criterion and Bayesian information criterion

We carried out a discriminant analysis with identity by descent (IBD) at each marker as inputs, and the sib pair type (affected-affected versus affected-unaffected) as the output. Using simple logistic regression for this discriminant analysis, we illustrate the importance of comparing models with different number of parameters. Such model comparisons are best carried out using either the Akaike information criterion (AIC) or the Bayesian information criterion (BIC). When AIC (or BIC) stepwise variable selection was applied to the German Asthma data set, a group of markers were selected which provide the best fit to the data (assuming an additive effect). Interestingly, these 25-26 markers were not identical to those with the highest (in magnitude) single-locus lod scores.

A Pd-24 Pregnant Molecular Nanoball: Self-Templated Stellation by Precise Mapping of Coordination Sites

We found that Pd(II) ion (M) and the smallest 120 bidentate donor pyrimidine (L-a) self-assemble into a mononuclear M(L-a)(4) complex (1a) instead of the expected smallest M-12(L-a)(24) molecular ball (1), presumably due to the weak coordination nature of the pyrimidine. To construct such a pyrimidine bridged nanoball, we employed a new donor tris(4-(pyrimidin-5-yl)phenyl)amine (L); which upon selective complexation with Pd(II) ions resulted in the formation of a pregnant M24L24 molecular nanoball (2) consisting of a pyrimidine-bridged Pd-12 baby-ball supported by a Pd-12 larger mother-ball. The formation of the baby-ball was not successful without the support of the mother-ball. Thus, we created an example of a self-assembly where the inner baby-ball resembling to the predicted M-12(L-a)(24) ball (1) was incarcerated by the giant outer mother-ball by means of geometrical constraints. Facile conversion of the pregnant ball 2 to a smaller M-12(L-b)(24) ball 3 with dipyridyl donor was achieved in a single step.

Defining the orientation of the tandem fusions that occurred during the evolution of Indian muntjac chromosomes by BAC mapping

The Indian muntjac (Muntiacus muntjak vaginalis) has a karyotype of 2n=6 in the female and 7 in the male, the karyotypic evolution of which through extensive tandem fusions and several centric fusions has been well-documented by recent molecular cytogenetic studies. In an attempt to define the fusion orientations of conserved chromosomal segments and the molecular mechanisms underlying the tandem fusions, we have constructed a highly redundant (more than six times of whole genome coverage) bacterial artificial chromosome (BAC) library of Indian muntjac. The BAC library contains 124,800 clones with no chromosome bias and has an average insert DNA size of 120 kb. A total of 223 clones have been mapped by fluorescent in situ hybridization onto the chromosomes of both Indian muntjac and Chinese muntjac and a high-resolution comparative map has been established. Our mapping results demonstrate that all tandem fusions that occurred during the evolution of Indian muntjac karyotype from the acrocentric 2n=70 hypothetical ancestral karyotype are centromere-telomere (head-tail) fusions.