gpart: human genome partitioning and visualization of high-density SNP data by identifying haplotype blocks.

SUMMARY: For the analysis of high-throughput genomic data produced by next-generation sequencing (NGS) technologies, researchers need to identify linkage disequilibrium (LD) structure in the genome. In this work, we developed an R package gpart which provides clustering algorithms to define LD blocks or analysis units consisting of SNPs. The visualization tool in gpart can display the LD structure and gene positions for up to 20 000 SNPs in one image. The gpart functions facilitate construction of LD blocks and SNP partitions for vast amounts of genome sequencing data within reasonable time and memory limits in personal computing environments. AVAILABILITY AND IMPLEMENTATION: The R package is available at https://bioconductor.org/packages/gpart. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A new haplotype block detection method for dense genome sequencing data based on interval graph modeling of clusters of highly correlated SNPs.

Motivation: Linkage disequilibrium (LD) block construction is required for research in population genetics and genetic epidemiology, including specification of sets of single nucleotide polymorphisms (SNPs) for analysis of multi-SNP based association and identification of haplotype blocks in high density sequencing data. Existing methods based on a narrow sense definition do not allow intermediate regions of low LD between strongly associated SNP pairs and tend to split high density SNP data into small blocks having high between-block correlation. Results: We present Big-LD, a block partition method based on interval graph modeling of LD bins which are clusters of strong pairwise LD SNPs, not necessarily physically consecutive. Big-LD uses an agglomerative approach that starts by identifying small communities of SNPs, i.e. the SNPs in each LD bin region, and proceeds by merging these communities. We determine the number of blocks using a method to find maximum-weight independent set. Big-LD produces larger LD blocks compared to existing methods such as MATILDE, Haploview, MIG ++, or S-MIG ++ and the LD blocks better agree with recombination hotspot locations determined by sperm-typing experiments. The observed average runtime of Big-LD for 13 288 240 non-monomorphic SNPs from 1000 Genomes Project autosome data (286 East Asians) is about 5.83 h, which is a significant improvement over the existing methods. Availability and implementation: Source code and documentation are available for download at http://github.com/sunnyeesl/BigLD. Contact: yyoo@snu.ac.kr. Supplementary information: Supplementary data are available at Bioinformatics online.

Prolines in Transit Peptides Are Crucial for Efficient Preprotein Translocation into Chloroplasts.

Chloroplasts import many preproteins that can be classified based on their physicochemical properties. The cleavable N-terminal transit peptide (TP) of chloroplast preproteins contains all the information required for import into chloroplasts through Toc/Tic translocons. The question of whether and how the physicochemical properties of preproteins affect TP-mediated import into chloroplasts has not been elucidated. Here, we present evidence that Pro residues in TP mediate efficient translocation through the chloroplast envelope membranes for proteins containing transmembrane domains (TMDs) or proteins prone to aggregation. By contrast, the translocation of soluble proteins through the chloroplast envelope membranes is less dependent on TP prolines. Proless TPs failed to mediate protein translocation into chloroplasts; instead, these mutant TPs led to protein mistargeting to the chloroplast envelope membranes or nonspecific protein aggregation during import into chloroplasts. The mistargeting of TMD-containing proteins caused by Pro-less TPs in wild-type protoplasts was mimicked by wild-type TPs in hsp93-V protoplasts, in which preprotein translocation is compromised. We propose that the physicochemical properties of chloroplast proteins affect protein translocation through the chloroplast envelope, and prolines in TP have a crucial role in the efficient translocation of TMD-containing proteins.

Multiple linear combination (MLC) regression tests for common variants adapted to linkage disequilibrium structure.

By jointly analyzing multiple variants within a gene, instead of one at a time, gene-based multiple regression can improve power, robustness, and interpretation in genetic association analysis. We investigate multiple linear combination (MLC) test statistics for analysis of common variants under realistic trait models with linkage disequilibrium (LD) based on HapMap Asian haplotypes. MLC is a directional test that exploits LD structure in a gene to construct clusters of closely correlated variants recoded such that the majority of pairwise correlations are positive. It combines variant effects within the same cluster linearly, and aggregates cluster-specific effects in a quadratic sum of squares and cross-products, producing a test statistic with reduced degrees of freedom (df) equal to the number of clusters. By simulation studies of 1000 genes from across the genome, we demonstrate that MLC is a well-powered and robust choice among existing methods across a broad range of gene structures. Compared to minimum P-value, variance-component, and principal-component methods, the mean power of MLC is never much lower than that of other methods, and can be higher, particularly with multiple causal variants. Moreover, the variation in gene-specific MLC test size and power across 1000 genes is less than that of other methods, suggesting it is a complementary approach for discovery in genome-wide analysis. The cluster construction of the MLC test statistics helps reveal within-gene LD structure, allowing interpretation of clustered variants as haplotypic effects, while multiple regression helps to distinguish direct and indirect associations.

The Prenylated Rab GTPase Receptor PRA1.F4 Contributes to Protein Exit from the Golgi Apparatus.

Prenylated Rab acceptor1 (PRA1) functions in the recruitment of prenylated Rab proteins to their cognate organelles. Arabidopsis (Arabidopsis thaliana) contains a large number of proteins belonging to the AtPRA1 family. However, their physiological roles remain largely unknown. Here, we investigated the physiological role of AtPRA1.F4, a member of the AtPRA1 family. A T-DNA insertion knockdown mutant of AtPRA1.F4, atpra1.f4, was smaller in stature than parent plants and possessed shorter roots, whereas transgenic plants overexpressing HA:AtPRA1.F4 showed enhanced development of secondary roots and root hairs. However, both overexpression and knockdown plants exhibited increased sensitivity to high-salt stress, lower vacuolar Na+/K+-ATPase and plasma membrane ATPase activities, lower and higher pH in the vacuole and apoplast, respectively, and highly vesiculated Golgi apparatus. HA:AtPRA1.F4 localized to the Golgi apparatus and assembled into high-molecular-weight complexes. atpra1.f4 plants displayed a defect in vacuolar trafficking, which was complemented by low but not high levels of HA:AtPRA1.F4 Overexpression of HA:AtPRA1.F4 also inhibited protein trafficking at the Golgi apparatus, albeit differentially depending on the final destination or type of protein: trafficking of vacuolar proteins, plasma membrane proteins, and trans-Golgi network (TGN)-localized SYP61 was strongly inhibited; trafficking of TGN-localized SYP51 was slightly inhibited; and trafficking of secretory proteins and TGN-localized SYP41 was negligibly or not significantly inhibited. Based on these results, we propose that Golgi-localized AtPRA1.F4 is involved in the exit of many but not all types of post-Golgi proteins from the Golgi apparatus. Additionally, an appropriate level of AtPRA1.F4 is crucial for its function at the Golgi apparatus.

Mitochondrial targeting of the Arabidopsis F1-ATPase γ-subunit via multiple compensatory and synergistic presequence motifs.

The majority of mitochondrial proteins are encoded in the nuclear genome and imported into mitochondria posttranslationally from the cytosol. An N-terminal presequence functions as the signal for the import of mitochondrial proteins. However, the functional information in the presequence remains elusive. This study reports the identification of critical sequence motifs from the presequence of Arabidopsis thaliana F1-ATPase γ-subunit (pFAγ). pFAγ was divided into six 10-amino acid segments, designated P1 to P6 from the N to the C terminus, each of which was further divided into two 5-amino acid subdivisions. These P segments and their subdivisions were substituted with Ala residues and fused to green fluorescent protein (GFP). Protoplast targeting experiments using these GFP constructs revealed that pFAγ contains several functional sequence motifs that are dispersed throughout the presequence. The sequence motifs DQEEG (P4a) and VVRNR (P5b) were involved in translocation across the mitochondrial membranes. The sequence motifs IAARP (P2b) and IAAIR (P3a) participated in binding to mitochondria. The sequence motifs RLLPS (P2a) and SISTQ (P5a) assisted in pulling proteins into the matrix, and the sequence motif IAARP (P2b) functioned in Tom20-dependent import. In addition, these sequence motifs exhibit complex relationships, including synergistic functions. Thus, multiple sequence motifs dispersed throughout the presequence are proposed to function cooperatively during protein import into mitochondria.

Supervised diagnostic classification of cognitive attributes using data augmentation.

Over recent decades, machine learning, an integral subfield of artificial intelligence, has revolutionized diverse sectors, enabling data-driven decisions with minimal human intervention. In particular, the field of educational assessment emerges as a promising area for machine learning applications, where students can be classified and diagnosed using their performance data. The objectives of Diagnostic Classification Models (DCMs), which provide a suite of methods for diagnosing students' cognitive states in relation to the mastery of necessary cognitive attributes for solving problems in a test, can be effectively addressed through machine learning techniques. However, the challenge lies in the latent nature of cognitive status, which makes it difficult to obtain labels for the training dataset. Consequently, the application of machine learning methods to DCMs often assumes smaller training sets with labels derived either from theoretical considerations or human experts. In this study, the authors propose a supervised diagnostic classification model with data augmentation (SDCM-DA). This method is designed to utilize the augmented data using a data generation model constructed by leveraging the probability of correct responses for each attribute mastery pattern derived from the expert-labeled dataset. To explore the benefits of data augmentation, a simulation study is carried out, contrasting it with classification methods that rely solely on the expert-labeled dataset for training. The findings reveal that utilizing data augmentation with the estimated probabilities of correct responses substantially enhances classification accuracy. This holds true even when the augmentation originates from a small labeled sample with occasional labeling errors, and when the tests contain lower-quality items that may inaccurately measure students' true cognitive status. Moreover, the study demonstrates that leveraging augmented data for learning can enable the successful classification of students, thereby eliminating the necessity for specifying an underlying response model.

A family-based association study after genome-wide linkage analysis identified two genetic loci for renal function in a Mongolian population.

The estimated glomerular filtration rate is a well-known measure of renal function and is widely used to follow the course of disease. Although there have been several investigations establishing the genetic background contributing to renal function, Asian populations have rarely been used in these genome-wide studies. Here, we aimed to find candidate genetic determinants of renal function in 1007 individuals from 73 extended families of Mongolian origin. Linkage analysis found two suggestive regions near 9q21 (logarithm of odds (LOD) 2.82) and 15q15 (LOD 2.70). The subsequent family-based association study found 2 and 10 significant single-nucleotide polymorphisms (SNPs) in each region, respectively. The strongest SNPs on chromosome 9 and 15 were rs17400257 and rs1153831 with P-values of 7.21 × 10(-9) and 2.47 × 10(-11), respectively. Genes located near these SNPs are considered candidates for determining renal function and include FRMD3, GATM, and SPATA5L1. Thus, we identified possible loci that determine renal function in an isolated Asian population. Consistent with previous reports, our study found genes linked and associated with renal function in other populations.

Comprehensive genomic analyses associate UGT8 variants with musical ability in a Mongolian population.

BACKGROUND: Musical abilities such as recognising music and singing performance serve as means for communication and are instruments in sexual selection. Specific regions of the brain have been found to be activated by musical stimuli, but these have rarely been extended to the discovery of genes and molecules associated with musical ability. METHODS: A total of 1008 individuals from 73 families were enrolled and a pitch-production accuracy test was applied to determine musical ability. To identify genetic loci and variants that contribute to musical ability, we conducted family-based linkage and association analyses, and incorporated the results with data from exome sequencing and array comparative genomic hybridisation analyses. RESULTS: We found significant evidence of linkage at 4q23 with the nearest marker D4S2986 (LOD=3.1), whose supporting interval overlaps a previous study in Finnish families, and identified an intergenic single nucleotide polymorphism (SNP) (rs1251078, p = 8.4 × 10(-17)) near UGT8, a gene highly expressed in the central nervous system and known to act in brain organisation. In addition, a non-synonymous SNP in UGT8 was revealed to be highly associated with musical ability (rs4148254, p = 8.0 × 10(-17)), and a 6.2 kb copy number loss near UGT8 showed a plausible association with musical ability (p = 2.9 × 10(-6)). CONCLUSIONS: This study provides new insight into the genetics of musical ability, exemplifying a methodology to assign functional significance to synonymous and non-coding alleles by integrating multiple experimental methods.

Enhancement of the Anticancer Ability of Natural Killer Cells through Allogeneic Mitochondrial Transfer.

An in vitro culture period of at least 2 weeks is required to produce sufficient natural killer (NK) cells for immunotherapy, which are the key effectors in hematological malignancy treatment. Mitochondrial damage and fragmentation reduce the NK cell immune surveillance capacity. Thus, we hypothesized that the transfer of healthy mitochondria to NK cells could enhance their anticancer effects. Allogeneic healthy mitochondria isolated from WRL-68 cells were transferred to NK cells. We evaluated NK cells' proliferative capacity, cell cycle, and cytotoxic capacity against various cancer cell types by analyzing specific lysis and the cytotoxic granules released. The relationship between the transferred allogenic mitochondrial residues and NK cell function was determined. After mitochondrial transfer, the NK cell proliferation rate was 1.2-fold higher than that of control cells. The mitochondria-treated NK cells secreted a 2.7-, 4.1-, and 5-fold higher amount of granzyme B, perforin, and IFN-γ, respectively, when co-cultured with K562 cells. The specific lysis of various solid cancer cells increased 1.3-1.6-fold. However, once allogeneic mitochondria were eliminated, the NK cell activity returned to the pre-mitochondrial transfer level. Mitochondria-enriched NK cells have the potential to be used as a novel solid cancer treatment agent, without the need for in vitro cytokine-induced culture.

Small heat shock protein Hsp17.8 functions as an AKR2A cofactor in the targeting of chloroplast outer membrane proteins in Arabidopsis.

Plastid proteins that are encoded by the nuclear genome and synthesized in the cytosol undergo posttranslational targeting to plastids. Ankyrin repeat protein 2A (AKR2A) and AKR2B were recently shown to be involved in the targeting of proteins to the plastid outer envelope. However, it remains unknown whether other factors are involved in this process. In this study, we investigated a factor involved in AKR2A-mediated protein targeting to chloroplasts in Arabidopsis (Arabidopsis thaliana). Hsp17.8, a member of the class I (CI) cytosolic small heat shock proteins (sHsps), was identified in interactions with AKR2A. The interaction between Hsp17.8 and AKR2A was further confirmed by coimmunoprecipitation experiments. The carboxyl-terminal ankyrin repeat domain of AKR2A was responsible for AKR2A binding to Hsp17.8. Other CI cytosolic sHsps also interact with AKR2A to varying degrees. Additionally, Hsp17.8 binds to chloroplasts in vitro and enhances AKR2A binding to chloroplasts. HSP17.8 was expressed under normal growth conditions, and its expression increased after heat shock. Hsp17.8 exists as a dimer under normal physiological conditions, and it is converted to high oligomeric complexes, ranging from 240 kD to greater than 480 kD, after heat shock. High levels of Hsp17.8 together with AKR2A resulted in increased plastid targeting of Outer Envelope Protein7 (OEP7), a plastid outer envelope protein expressed as a green fluorescent protein fusion protein. In contrast, artificial microRNA suppression of HSP17.8 and closely related CI cytosolic sHSPs in protoplasts resulted in a reduction of OEP7:green fluorescent protein targeting to plastids. Based on these data, we propose that Hsp17.8 functions as an AKR2A cofactor in targeting membrane proteins to plastid outer membranes under normal physiological conditions.

Human leukocyte antigen class I genotypes in relation to heterosexual HIV type 1 transmission within discordant couples.

Differences in immune control of HIV-1 infection are often attributable to the highly variable HLA class I molecules that present viral epitopes to CTL. In our immunogenetic analyses of 429 HIV-1 discordant Zambian couples (infected index partners paired with cohabiting seronegative partners), several HLA class I variants in index partners were associated with contrasting rates and incidence of HIV-1 transmission within a 12-year study period. In particular, A*3601 on the A*36-Cw*04-B*53 haplotype was the most unfavorable marker of HIV-1 transmission by index partners, while Cw*1801 (primarily on the A*30-Cw*18-B*57 haplotype) was the most favorable, irrespective of the direction of transmission (male to female or female to male) and other commonly recognized cofactors of infection, including age and GUI. The same HLA markers were further associated with contrasting viral load levels in index partners, but they had no clear impact on HIV-1 acquisition by the seronegative partners. Thus, HLA class I gene products not only mediate HIV-1 pathogenesis and evolution but also influence heterosexual HIV-1 transmission.

Haplotype inference for present-absent genotype data using previously identified haplotypes and haplotype patterns.

MOTIVATION: Killer immunoglobulin-like receptor (KIR) genes vary considerably in their presence or absence on a specific regional haplotype. Because presence or absence of these genes is largely detected using locus-specific genotyping technology, the distinction between homozygosity and hemizygosity is often ambiguous. The performance of methods for haplotype inference (e.g. PL-EM, PHASE) for KIR genes may be compromised due to the large portion of ambiguous data. At the same time, many haplotypes or partial haplotype patterns have been previously identified and can be incorporated to facilitate haplotype inference for unphased genotype data. To accommodate the increased ambiguity of present-absent genotyping of KIR genes, we developed a hybrid approach combining a greedy algorithm with the Expectation-Maximization (EM) method for haplotype inference based on previously identified haplotypes and haplotype patterns. RESULTS: We implemented this algorithm in a software package named HAPLO-IHP (Haplotype inference using identified haplotype patterns) and compared its performance with that of HAPLORE and PHASE on simulated KIR genotypes. We compared five measures in order to evaluate the reliability of haplotype assignments and the accuracy in estimating haplotype frequency. Our method outperformed the two existing techniques by all five measures when either 60% or 25% of previously identified haplotypes were incorporated into the analyses. AVAILABILITY: The HAPLO-IHP is available at http://www.soph.uab.edu/Statgenetics/People/KZhang/HAPLO-IHP/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Fusion of a highly N-glycosylated polypeptide increases the expression of ER-localized proteins in plants.

Plants represent promising systems for producing various recombinant proteins. One key area of focus for improving this technology is developing methods for producing recombinant proteins at high levels. Many methods have been developed to increase the transcript levels of recombinant genes. However, methods for increasing protein production involving steps downstream of transcription, including translation, have not been fully explored. Here, we investigated the effects of N-glycosylation on protein production and provide evidence that N-glycosylation greatly increases the expression levels of ER-targeted recombinant proteins. Fusion of the extracellular domain (M domain) of protein tyrosine phosphatase receptor type C (CD45), which contains four putative N-glycosylation sites to a model protein, leptin at the C-terminus, increased recombinant protein levels by 6.1 fold. This increase was specific to ER-targeted proteins and was dependent on N-glycosylation. Moreover, expression levels of leptin, leukemia inhibitory factor and GFP were also greatly increased by fusion of M domain at either the N or C-terminus. Furthermore, the increase in protein levels resulted from enhanced translation, but not transcription. Based on these results, we propose that fusing a small domain containing N-glycosylation sites to target proteins is a powerful technique for increasing the expression levels of recombinant proteins in plants.

Evolution of rubisco complex small subunit transit peptides from algae to plants.

Chloroplasts evolved from a free-living cyanobacterium acquired by the ancestor of all photosynthetic eukaryotes, including algae and plants, through a single endosymbiotic event. During endosymbiotic conversion, the majority of genes in the endosymbiont were transferred to the host nucleus and many of the proteins encoded by these genes must therefore be transported into the chloroplast after translation in the cytosol. Chloroplast-targeted proteins contain a targeting signal, named the transit peptide (TP), at the N-terminus. However, the evolution of TPs is not well understood. In this study, TPs from RbcS (rubisco small subunit) were compared between lower and higher eukaryotes. Chlamydomonas reinhardtii RbcS (CrRbcS) TP was non-functional in Arabidopsis. However, inclusion of a critical sequence motif, FP-RK, from Arabidopsis thaliana RbcS (AtRbcS) TP allowed CrRbcS TP to deliver proteins into plant chloroplasts. The position of the FP-RK motif in CrRbcS TP was critical for function. The QMMVW sequence motif in CrRbcS TP was crucial for its transport activity in plants. CrRbcS TPs containing additional plant motifs remained functional in C. reinhardtii. These results suggest that TPs evolved by acquiring additional sequence motifs to support protein targeting to chloroplasts during evolution of land plants from algae.

Effects of Single Nucleotide Polymorphism Marker Density on Haplotype Block Partition.

Many researchers have found that one of the most important characteristics of the structure of linkage disequilibrium is that the human genome can be divided into non-overlapping block partitions in which only a small number of haplotypes are observed. The location and distribution of haplotype blocks can be seen as a population property influenced by population genetic events such as selection, mutation, recombination and population structure. In this study, we investigate the effects of the density of markers relative to the full set of all polymorphisms in the region on the results of haplotype partitioning for five popular haplotype block partition methods: three methods in Haploview (confidence interval, four gamete test, and solid spine), MIG++ implemented in PLINK 1.9 and S-MIG++. We used several experimental datasets obtained by sampling subsets of single nucleotide polymorphism (SNP) markers of chromosome 22 region in the 1000 Genomes Project data and also the HapMap phase 3 data to compare the results of haplotype block partitions by five methods. With decreasing sampling ratio down to 20% of the original SNP markers, the total number of haplotype blocks decreases and the length of haplotype blocks increases for all algorithms. When we examined the marker-independence of the haplotype block locations constructed from the datasets of different density, the results using below 50% of the entire SNP markers were very different from the results using the entire SNP markers. We conclude that the haplotype block construction results should be used and interpreted carefully depending on the selection of markers and the purpose of the study.

Interactions between Transmembrane Helices within Monomers of the Aquaporin AtPIP2;1 Play a Crucial Role in Tetramer Formation.

Aquaporin (AQP) is a water channel protein found in various subcellular membranes of both prokaryotic and eukaryotic cells. The physiological functions of AQPs have been elucidated in many organisms. However, understanding their biogenesis remains elusive, particularly regarding how they assemble into tetramers. Here, we investigated the amino acid residues involved in the tetramer formation of the Arabidopsis plasma membrane AQP AtPIP2;1 using extensive amino acid substitution mutagenesis. The mutant proteins V41A/E44A, F51A/L52A, F87A/I91A, F92A/I93A, V95A/Y96A, and H216A/L217A, harboring alanine substitutions in the transmembrane (TM) helices of AtPIP2;1 polymerized into multiple oligomeric complexes with a variable number of subunits greater than four. Moreover, these mutant proteins failed to traffic to the plasma membrane, instead of accumulating in the endoplasmic reticulum (ER). Structure-based modeling revealed that these residues are largely involved in interactions between TM helices within monomers. These results suggest that inter-TM interactions occurring both within and between monomers play crucial roles in tetramer formation in the AtPIP2;1 complex. Moreover, the assembly of AtPIP2;1 tetramers is critical for their trafficking from the ER to the plasma membrane, as well as water permeability.

Nine-year refractive changes in the Barbados Eye Studies.

PURPOSE: To describe 9-year changes in refractive errors and estimate incidence of myopia and hyperopia in adults of African-descent, along with associated risk factors. METHODS: The 9-year follow-up of the Barbados Eye Studies (1997-2003) reexamined 2793 surviving cohort members (81% participation). Refractive errors were determined by automated refraction. Myopia/hyperopia were defined as spherical equivalent < -0.5 diopters (D)/> +0.5 D, and the cutoff for moderate-high myopia/hyperopia was 3.0 D. Incidence rates of myopia/hyperopia were estimated by the product-limit approach, based on eyes without such conditions at baseline. Risk factors were evaluated by logistic regression in discrete time hazard models. RESULTS: Nine-year refraction changes varied by age. Persons aged 40 to 49 years experienced hyperopic shifts (median, +0.38 D), whereas persons > or =60 years had myopic shifts (median, -0.75D). Overall 9-year incidence was 12.0% for myopia and 29.5% for hyperopia; rates were 3.6% and 2.0% for moderate-high myopia and hyperopia, respectively. Myopia risk increased with age, baseline nuclear lens opacities (risk ratio [RR] = 1.7; 95% confidence interval [CI]: 1.01-2.9), glaucoma (RR = 6.0, 95% CI: 3.9-9.3), and ocular hypertension (RR = 2.0, 95% CI: 1.3-3.0), while cortical lens opacities decreased risk (RR = 0.6, 95% CI: 0.4-0.9). Incidence of moderate-high myopia was also related to baseline age, nuclear opacities, glaucoma, male gender (RR = 1.7, 95% CI: 1.0-2.8), and diabetes history (RR = 1.9, 95% CI: 1.01-3.5). Hyperopia risk decreased with older age, male gender, and glaucoma diagnosis. CONCLUSIONS: Refractive errors continue to develop frequently in older adults. Nuclear lens opacities, glaucoma, and diabetes increase the risk of older-onset myopia, a result of public health relevance to this and similar African-origin populations.

Clique-Based Clustering of Correlated SNPs in a Gene Can Improve Performance of Gene-Based Multi-Bin Linear Combination Test.

Gene-based analysis of multiple single nucleotide polymorphisms (SNPs) in a gene region is an alternative to single SNP analysis. The multi-bin linear combination test (MLC) proposed in previous studies utilizes the correlation among SNPs within a gene to construct a gene-based global test. SNPs are partitioned into clusters of highly correlated SNPs, and the MLC test statistic quadratically combines linear combination statistics constructed for each cluster. The test has degrees of freedom equal to the number of clusters and can be more powerful than a fully quadratic or fully linear test statistic. In this study, we develop a new SNP clustering algorithm designed to find cliques, which are complete subnetworks of SNPs with all pairwise correlations above a threshold. We evaluate the performance of the MLC test using the clique-based CLQ algorithm versus using the tag-SNP-based LDSelect algorithm. In our numerical power calculations we observed that the two clustering algorithms produce identical clusters about 40~60% of the time, yielding similar power on average. However, because the CLQ algorithm tends to produce smaller clusters with stronger positive correlation, the MLC test is less likely to be affected by the occurrence of opposing signs in the individual SNP effect coefficients.

Power of maximum HLOD tests to detect linkage to obesity genes.

BACKGROUND: We investigate the power of heterogeneity LOD test to detect linkage when a trait is determined by several major genes using Genetic Analysis Workshop 13 simulated data. We consider three traits, two of which are disease-causing traits: 1) the rate of change in body mass index (BMI); and 2) the maximum BMI; and 3) the disease itself (hypertension). Of interest is the power of "HLOD2", the maximum heterogeneity LOD obtained upon maximizing over the two genetic models. RESULTS: Using a trait phenotype Obesity Slope, we observe that the power to detect the two markers closest to the two genes (S1, S2) at the 0.05 level using HLOD2 is 13% and 10%. The power of HLOD2 for Max BMI phenotype is 12% and 9%. The corresponding values for the Hypertension phenotype are 8% and 6%. CONCLUSION: The power to detect linkage to the slope genes is quite low. But the power using disease-related traits as a phenotype is greater than the power using the disease (hypertension) phenotype.