Recent advances in human quantitative-trait-locus mapping: comparison of methods for selected sibling pairs

During the past few years, there has been a great deal of new work on methods for mapping quantitative-trait loci by use of sibling pairs and sibships. There are several new methods based on linear regression, as well as several more that are based on score statistics. In theory, most of the new methods should be relatively robust to violations of distributional assumptions and to selected sampling, but, in practice, there has been little evaluation of how the methods perform on selected samples. We survey most of the new regression-based statistics and score statistics and propose a few minor variations on the score statistics. We use simulation to evaluate the type I error and the power of all of the statistics, considering (a) population samples of sibling pairs and (b) sibling pairs ascertained on the basis of at least one sibling with a trait value in the top 10% of the distribution. Most of the statistics have correct type I error for selected samples. The statistics proposed by Xu et al. and by Sham and Purcell are generally the most powerful, along with one of our score statistic variants. Even among the methods that are most powerful for "nice" data, some are more robust than others to non-Gaussian trait models and/or misspecified trait parameters.     

Composite statistics for QTL mapping with moderately discordant sibling pairs

Extreme discordant sibling-pair (EDSP) designs have been shown in theory to be very powerful for mapping quantitative-trait loci (QTLs) in humans. However, their practical applicability has been somewhat limited by the need to phenotype very large populations to find enough pairs that are extremely discordant. In this paper, we demonstrate that there is also substantial power in pairs that are only moderately discordant, and that designs using moderately discordant pairs can yield a more practical balance between phenotyping and genotyping efforts. The power we demonstrate for moderately discordant pairs stems from a new statistical result. Statistical analysis in discordant-pair studies is generally done by testing for reduced identity by descent (IBD) sharing in the pairs. By contrast, the most commonly-used statistical methods for more standard QTL mapping are Haseman-Elston regression and variance-components analysis. Both of these use statistics that are functions of the trait values given IBD information for the pedigree. We show that IBD sharing statistics and "trait value given IBD" statistics contribute complementary rather than redundant information, and thus that statistics of the two types can be combined to form more powerful tests of linkage. We propose a simple composite statistic, and test it with simulation studies. The simulation results show that our composite statistic increases power only minimally for extremely discordant pairs. However, it boosts the power of moderately discordant pairs substantially and makes them a very practical alternative. Our composite statistic is straightforward to calculate with existing software; we give a practical example of its use by applying it to a Genetic Analysis Workshop (GAW) data set.     

A powerful and robust new linkage statistic for discordant sibling pairs

Previously, Szatkiewicz and colleagues evaluated the performance of a wide variety of statistics for quantitative-trait-locus linkage, using discordant sibling pairs. They found that the most powerful statistics, in general, were a score statistic and a "composite statistic." However, whereas these two statistics have equal power under ideal conditions, each has limitations that reduce its power in certain circumstances. The score statistic depends on estimates of trait parameters and can lose a lot of power if those estimates are incorrect. The composite statistic is not sensitive to trait-parameter estimates but does depend on arbitrary weights that must be chosen on the basis of the ascertainment scheme. In this report, we elucidate the algebraic relationship between the score and composite statistics and then use that relationship to suggest a new statistic that combines the best properties of both. We call our new statistic the "robust discordant pair" (RDP) statistic. We report simulation studies to show that the RDP statistic does, indeed, have all of the strengths and none of the weaknesses of the score and composite statistics.     

DNA methylation profiles in sibling pairs discordant for intrauterine exposure to maternal gestational diabetes

Intrauterine exposure to hyperglycemia is reported to confer increased metabolic risk in later life, supporting the ‘developmental origins of health and disease’ hypothesis. Epigenetic alterations are suggested as one of the possible underlying mechanisms. In this study, we compared pairwise DNA methylation differences between siblings whose intrauterine exposure to maternal gestational diabetes (GDM) were discordant. Methylation of peripheral blood DNA of 18 sibling pairs was measured using Infinium HumanMethylation450 BeadChip assays. Of the 465,447 CpG sites analyzed, 12 showed differential methylation (false discovery rate <0.15), including markers within genes associated with monogenic diabetes (HNF4A) or obesity (RREB1). The overall methylation at HNF4A showed inverse correlations with mRNA expression levels, though non significant. In a gene set enrichment analysis, metabolism and signal transduction pathways were enriched. In conclusion, we found DNA methylation markers associated with intrauterine exposure to maternal GDM, including those within genes previously implicated in diabetes or obesity.     

Linkage analysis of extremely discordant and concordant sibling pairs identifies quantitative trait loci influencing variation in human menopausal age

Age at natural menopause may be used as parameter for evaluating the rate of ovarian aging. Environmental factors determine only a small part of the large variation in menopausal age. Studies have shown that genetic factors are likely to be involved in variation in menopausal age. To identify quantitative-trait loci for this trait, we performed a genomewide linkage study with age at natural menopause as a continuous quantitative phenotype in Dutch sister pairs, through use of a selective sampling scheme. A total of 165 families were ascertained using extreme selected sampling and were genotyped for 417 markers. Data were analyzed by Haseman-Elston regression and by an adjusted variance-components analysis. Subgroup analyses for early and late menopausal age were conducted by Haseman-Elston regression. In the adjusted variance-components analysis, 12 chromosomes had a LOD score of > or =1.0. Two chromosomal regions showed suggestive linkage: 9q21.3 (LOD score 2.6) and Xp21.3 (LOD score 3.1). Haseman-Elston regression showed rather similar locations of the peaks but yielded lower LOD scores. A permutation test to obtain empirical P values resulted in a significant peak on the X chromosome. To our knowledge, this is the first study to attempt to identify loci responsible for variability in menopausal age and in which several chromosomal regions were identified with suggestive and significant linkage. Although the finding of the region on the X chromosome comes as no surprise, because of its widespread involvement in premature ovarian failure, the definition of which particular gene is involved is of great interest. The region on chromosome 9 deserves further consideration. Both findings require independent confirmation.     

Using discordant sib pairs to map loci for qualitative traits with high sibling recurrence risk.

A common approach for detecting genetic linkage using siblings is to collect affected sib pairs (ASPs) and to identify markers where allele sharing exceeds expectation. Alternatively, markers can be analyzed in discordant sib pairs (DSPs) for allele sharing below expectation. Relative to the ASP approach, according to Risch, the power of the DSP approach increases with sibling recurrence risk, the two approaches being equally effective at 50% recurrence risk. However, with many diseases associated with more moderate sibling recurrence risk, less emphasis has been placed on the use of DSPs and the development of the underlying theory. In this paper, we expand the work of Risch to provide a more general foundation for DSP studies, since power can be quite high under the appropriate conditions. For example, in some highly affected populations, such as the diabetes-prone Pima Indians, sibling recurrence risk can be very large and, thus, DSPs ideal. Similarly, as we show through simulation, DSPs are preferable for diabetic nephropathy due to a 70% recurrence rate among siblings with insulin-dependent diabetes mellitus. Following the diabetic nephropathy example, we consider more systematically the situations in which DSPs can provide an efficient alternative to ASPs.     

Efficiency robust tests for mapping quantitative trait loci using extremely discordant sib pairs

In 1972, Haseman and Elston proposed a pioneering regression method for mapping quantitative trait loci using randomly selected sib pairs. Recently, the statistical power of their method was shown to be increased when extremely discordant sib pairs are ascertained. While the precise genetic model may not be known, prior information that constrains IBD probabilities is often available. We investigate properties of tests that are robust against model uncertainty and show that the power gain from further constraining IBD probabilities is marginal. The additional linkage information contained in the trait values can be incorporated by combining the Haseman-Elston regression method and a robust allele sharing test.     

Genetic association mapping based on discordant sib pairs: the discordant-alleles test.

Family-based tests of association provide the opportunity to test for an association between a disease and a genetic marker. Such tests avoid false-positive results produced by population stratification, so that evidence for association may be interpreted as evidence for linkage or causation. Several methods that use family-based controls have been proposed, including the haplotype relative risk, the transmission-disequilibrium test, and affected family-based controls. However, because these methods require genotypes on affected individuals and their parents, they are not ideally suited to the study of late-onset diseases. In this paper, we develop several family-based tests of association that use discordant sib pairs (DSPs) in which one sib is affected with a disease and the other sib is not. These tests are based on statistics that compare counts of alleles or genotypes or that test for symmetry in tables of alleles or genotypes. We describe the use of a permutation framework to assess the significance of these statistics. These DSP-based tests provide the same general advantages as parent-offspring trio-based tests, while being applicable to essentially any disease; they may also be tailored to particular hypotheses regarding the genetic model. We compare the statistical properties of our DSP-based tests by computer simulation and illustrate their use with an application to Alzheimer disease and the apolipoprotein E polymorphism. Our results suggest that the discordant-alleles test, which compares the numbers of nonmatching alleles in DSPs, is the most powerful of the tests we considered, for a wide class of disease models and marker types. Finally, we discuss advantages and disadvantages of the DSP design for genetic association mapping.     

Linkage analysis of extremely discordant and concordant sibling pairs identifies quantitative-trait loci that influence variation in the human personality trait neuroticism

Several theoretical studies have suggested that large samples of randomly ascertained siblings can be used to ascertain phenotypically extreme individuals and thereby increase power to detect genetic linkage in complex traits. Here, we report a genetic linkage scan using extremely discordant and concordant sibling pairs, selected from 34,580 sibling pairs in the southwest of England who completed a personality questionnaire. We performed a genomewide scan for quantitative-trait loci (QTLs) that influence variation in the personality trait of neuroticism, or emotional stability, and we established genomewide empirical significance thresholds by simulation. The maximum pointwise P values, expressed as the negative logarithm (base 10), were found on 1q (3.95), 4q (3.84), 7p (3.90), 12q (4.74), and 13q (3.81). These five loci met or exceeded the 5% genomewide significance threshold of 3.8 (negative logarithm of the P value). QTLs on chromosomes 1, 12, and 13 are likely to be female specific. One locus, on chromosome 1, is syntenic with that reported from QTL mapping of rodent emotionality, an animal model of neuroticism, suggesting that some animal and human QTLs influencing emotional stability may be homologous.     

Recent advances in clustering methods for protein interaction networks

The increasing availability of large-scale protein-protein interaction data has made it possible to understand the basic components and organization of cell machinery from the network level. The arising challenge is how to analyze such complex interacting data to reveal the principles of cellular organization, processes and functions. Many studies have shown that clustering protein interaction network is an effective approach for identifying protein complexes or functional modules, which has become a major research topic in systems biology. In this review, recent advances in clustering methods for protein interaction networks will be presented in detail. The predictions of protein functions and interactions based on modules will be covered. Finally, the performance of different clustering methods will be compared and the directions for future research will be discussed.     

Recent advances in implicit solvent-based methods for biomolecular simulations

Implicit solvent-based methods play an increasingly important role in molecular modeling of biomolecular structure and dynamics. Recent methodological developments have mainly focused on the extension of the generalized Born (GB) formalism for variable dielectric environments and accurate treatment of nonpolar solvation. Extensive efforts in parameterization of GB models and implicit solvent force fields have enabled ab initio simulation of protein folding to native or near-native structures. Another exciting area that has benefited from the advances in implicit solvent models is the development of constant pH molecular dynamics methods, which have recently been applied to the calculations of protein pK(a) values and the studies of pH-dependent peptide and protein folding.     

A comparison of genetic variation in two sibling species pairs of haplodiploid insects

Sibling species pairs of sweat bees (Halictus confusus andH. tumulorum) and pine sawflies (Neodiprion pratti andN. maurus) were surveyed for genetic variability using enzyme electrophoresis. Levels of heterozygosity were found to be within the ranges earlier recorded for Hymenoptera. Expected heterozygosities were not significantly higher in the sawflies than in the sweat bees. Estimates of genetic identity between the sibling species were not lower than those generally found for diplodiploid insect species: no evidence was found for an increased rate of evolution in these haplodiploids. Genetic identity data among populations ofH. confusus and betweenHalictus species were within the range expected for conspecific populations and sibling species, respectively. InNeodiprion all genetic distances were low but the two populations ofN. pratti had similar genetic distances as each did toN. maurus, indicating the necessity for further systematic studies of the genus. The research reported here was supported by NSERC operating grants to the junior author. Collections of samples were made through NSERC funding previously available to Drs. R. E. Owen and G. Knerer, L. R. was supported by an Internationaliserringsstipendium from the University of Copenhagen, and L. P. by an NSERC University Research Fellowship.     

Recent advances in B-cell epitope prediction methods

Identification of epitopes that invoke strong responses from B-cells is one of the key steps in designing effective vaccines against pathogens. Because experimental determination of epitopes is expensive in terms of cost, time, and effort involved, there is an urgent need for computational methods for reliable identification of B-cell epitopes. Although several computational tools for predicting B-cell epitopes have become available in recent years, the predictive performance of existing tools remains far from ideal. We review recent advances in computational methods for B-cell epitope prediction, identify some gaps in the current state of the art, and outline some promising directions for improving the reliability of such methods.     

Recent advances in methods of direct optical resolution

Very great advances have been made in the field of direct optical resolution of organic compounds by chromatographic techniques. Chiral capillary gas chromatography now permits a determination of the enantiomeric composition of a few nanograms of a compound present in a mixture of many others. Coupled with high resolution mass spectrometry the technique will additionally permit structural elucidation; of great interest in pheromone research and related areas. Analytical separations of enantiomers are now also carried out by high-performance liquid chromatography (HPLC) methods based on a variety of principles. Basically, two main types are used, differing as to whether the mobile phase has to be a chiral medium or not. Two-dimensional HPLC, whereby compounds separated on a non-chiral column are progressively and automatically transferred to a chiral column for optical resolution, has been used successsfully for chiral amino acid separations. Many different chiral sorbents for preparative LC and HPLC resolutions have been prepared; some of these are now used in columns capable of producing pure enantiomers from a given racemate at a rate of the order of one gram/hour in continuous, automatic HPLC procedures. Apart from all important applications of these results of optical resolution technology, an increased knowledge of the underlying chiral recognition phenomena responsible for enantioselection has also been achieved.     

Human pedigree-based quantitative-trait-locus mapping: localization of two genes influencing HDL-cholesterol metabolism.

Common disorders with genetic susceptibilities involve the action of multiple genes interacting with each other and with environmental factors, making it difficult to localize the specific genetic loci responsible. An important route to the disentangling of this complex inheritance is through the study of normal physiological variation in quantitative risk factors that may underlie liability to disease. We present an analysis of HDL-cholesterol (HDL-C), which is inversely correlated with risk of heart disease. A variety of HDL subphenotypes were analyzed, including HDL particle-size classes and the concentrations and proportions of esterified and unesterified HDL-C. Results of a complete genomic screen in large, randomly ascertained pedigrees implicated two loci, one on chromosome 8 and the other on chromosome 15, that influence a component of HDL-C-namely, unesterified HDL2a-C. Multivariate analyses of multiple HDL phenotypes and simultaneous multilocus analysis of the quantitative-trait loci identified permit further characterization of the genetic effects on HDL-C. These analyses suggest that the action of the chromosome 8 locus is specific to unesterified cholesterol levels, whereas the chromosome 15 locus appears to influence both HDL-C concentration and distribution of cholesterol among HDL particle sizes.     

Recent advances for the production and recovery methods of lysozyme

Lysozyme is an antimicrobial peptide with a high enzymatic activity and positive charges. Therefore, it has applications in food and pharmaceutical industries as an antimicrobial agent. Lysozyme is ubiquitous in both animal and plant kingdoms. Currently, egg-white lysozyme is the most commercially available form of lysozyme. The main concerns of egg-white lysozyme are high recovery cost, low activity and most importantly the immunological problems to some people. Therefore, human lysozyme production has gained importance in recent years. Scientists have developed transgenic plants, animals and microorganisms that can produce human lysozyme. Out of these, microbial production has advantages for commercial productions, because high production levels are achievable in a relatively short time. It has been reported that fermentation parameters, such as pH, temperature, aeration, are key factors to increase the effectiveness of the human lysozyme production. Moreover, purification of the lysozyme from the fermentation broth needs to be optimized for the economical production. In conclusion, this review paper covers the mechanism of lysozyme, its sources, production methods and recovery of lysozyme.