Genetics

8 typically slower than ϳ1 km s −1 ) might differ significantly from what is assumed by current modelling efforts 27 . The expected equation-of-state differences among small bodies (ice versus rock, for instance) presents another dimension of study; having recently adapted our code for massively parallel architectures (K. M. Olson and E.A, manuscript in preparation), we are now ready to perform a more comprehensive analysis.

GENEPOP (version 1.2) is a population genetic software package for haploid or diploid data that is able to perform two major tasks. First, it computes exact tests or their unbiased estimation for Hardy-Weinberg equilibrium, population differentiation, and two-locus genotypic disequilibrium. Second, it converts the input GENE-POP file to formats used by other popular programs, like BIOSYS (Swofford and Selander 1981), DIPLOIDL (Weir 1990b), LINKDOS (Garnier-Gere and Dillmann 1992), and Slatkin's (1993) isolation-by-distance program, thereby allowing communication between them (ecumenicism).

Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.

We present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-distances among all pairs of haplotypes. This analysis of molecular variance (AMOVA) produces estimates of variance components and F-statistic analogs, designated here as @-statistics, reflecting the correlation of haplotypic diversity at different levels of hierarchical subdivision. The method is flexible enough to accommodate several alternative input matrices, corresponding to different types of molecular data, as well as different types of evolutionary assumptions, without modifying the basic structure of the analysis. The significance of the variance components and @-statistics is tested using a permutational approach, eliminating the normality assumption that is conventional for analysis of variance but inappropriate for molecular data. Application of AMOVA to human mitochondrial DNA haplotype data shows that population subdivisions are better resolved when some measure of molecular differences among haplotypes is introduced into the analysis. At the intraspecific level, however, the additional information provided by knowing the exact phylogenetic relations among haplotypes or by a nonlinear translation of restriction-site change into nucleotide diversity does not significantly modify the inferred population genetic structure. Monte Carlo studies show that site sampling does not fundamentally affect the significance of the molecular variance components. The AMOVA treatment is easily extended in several different directions and it constitutes a coherent and flexible framework for the statistical analysis of molecular data.

PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication . A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/. [Bootstrap analysis; branch testing; LRT and aLRT; maximum likelihood; NNI; phylogenetic software; SPR; tree search algorithms.]

The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure, and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall the project provides new insights into the organization and regulation of our genes and genome, and an expansive resource of functional annotations for biomedical research.

The magnitudes of the systematic biases involved in sample heterozygosity and sample genetic distances are evaluated, and formulae for obtaining unbiased estimates of average heterozygosity and genetic distance are developed. It is also shown that the number of individuals to be used for estimating average heterozygosity can be very small if a large number of loci are studied and the average heterozygosity is low. The number of individuals to be used for estimating genetic distance can also be very small if the genetic distance is large and the average heterozygosity of the two species compared is low.

Graphene sheets-one-atom-thick two-dimensional layers of sp 2 -bonded carbon-are predicted to have a range of unusual properties. Their thermal conductivity and mechanical stiffness may rival the remarkable in-plane values for graphite (,3,000 Wm 21 K 21 and 1,060 GPa, respectively); their fracture strength should be comparable to that of carbon nanotubes for similar types of defects 1-3 ; and recent studies have shown that individual graphene sheets have extraordinary electronic transport properties 4-8 . One possible route to harnessing these properties for applications would be to incorporate graphene sheets in a composite material. The manufacturing of such composites requires not only that graphene sheets be produced on a sufficient scale but that they also be incorporated, and homogeneously distributed, into various matrices. Graphite, inexpensive and available in large quantity, unfortunately does not readily exfoliate to yield individual graphene sheets. Here we present a general approach for the preparation of graphene-polymer composites via complete exfoliation of graphite 9 and molecular-level dispersion of individual, chemically modified graphene sheets within polymer hosts. A polystyrene-graphene composite formed by this route exhibits a percolation threshold 10 of ,0.1 volume per cent for room-temperature electrical conductivity, the lowest reported value for any carbon-based composite except for those involving carbon nanotubes 11 ; at only 1 volume per cent, this composite has a conductivity of ,0.1 S m 21 , sufficient for many electrical applications 12 . Our bottom-up chemical approach of tuning the graphene sheet properties provides a path to a broad new class of graphenebased materials and their use in a variety of applications.

In this paper we report exploratory analyses of high-density oligonucleotide array data from the Affymetrix GeneChip R system with the objective of improving upon currently used measures of gene expression. Our analyses make use of three data sets: a small experimental study consisting of five MGU74A mouse GeneChip R arrays, part of the data from an extensive spike-in study conducted by Gene Logic and Wyeth's Genetics Institute involving 95 HG-U95A human GeneChip R arrays; and part of a dilution study conducted by Gene Logic involving 75 HG-U95A GeneChip R arrays. We display some familiar features of the perfect match and mismatch probe (P M and M M) values of these data, and examine the variance-mean relationship with probe-level data from probes believed to be defective, and so delivering noise only. We explain why we need to normalize the arrays to one another using probe level intensities. We then examine the behavior of the P M and M M using spike-in data and assess three commonly used summary measures: Affymetrix's (i) average difference (AvDiff) and (ii) MAS 5.0 signal, and (iii) the Li and Wong multiplicative model-based expression index (MBEI). The exploratory data analyses of the probe level data motivate a new summary measure that is a robust multiarray average (RMA) of background-adjusted, normalized, and log-transformed P M values. We evaluate the four expression summary measures using the dilution study data, assessing their behavior in terms of bias, variance and (for MBEI and RMA) model fit. Finally, we evaluate the algorithms in terms of their ability to detect known levels of differential expression using the spike-in data. We conclude that there is no obvious downside to using RMA and attaching a standard error (SE) to this quantity using a linear model which removes probe-specific affinities.

Human lymphocytes were either exposed to X-irradiation (25 to 200 rads) or treated with HzOz (9.1 to 291 u&f) at 4°C and the extent of DNA migration was measured using a singlecell microgel electrophoresis technique under alkaline conditions. Both agents induced a significant increase in DNA migration, beginning at the lowest dose evaluated. Migration patterns were relatively homogeneous among cells exposed to X-rays but heterogeneous among cells treated with HzOz. An analysis of repair kinetics following exposure to 200 rads X-rays was conducted with lymphocytes obtained from three individuals. The bulk of the DNA repair occurred within the first IS min, while all of the repair was essentially complete by 120 min after exposure. However, some cells demonstrated no repair during this incubation period while other cells demonstrated DNA migration patterns indicative of more damage than that induced by the initial irradiation with X-rays. This technique appears to be sensitive and useful for detecting damage and repair in single cells. @ IYXX Academic Press. Inc.

A simple mathematical method is developed to estimate the number of nucleotide substitutions per site between two DNA sequences, by extending Kimura's (1980) two-parameter method to the case where a G+C-content bias exists. This method will be useful when there are strong transition-transversion and G+C-content biases, as in the case of Drosophila mitochondrial DNA.

Causal attribution of recent biological trends to climate change is complicated because non-climatic influences dominate local, short-term biological changes. Any underlying signal from climate change is likely to be revealed by analyses that seek systematic trends across diverse species and geographic regions; however, debates within the Intergovernmental Panel on Climate Change (IPCC) reveal several definitions of a 'systematic trend'. Here, we explore these differences, apply diverse analyses to more than 1,700 species, and show that recent biological trends match climate change predictions. Global meta-analyses documented significant range shifts averaging 6.1 km per decade towards the poles (or metres per decade upward), and significant mean advancement of spring events by 2.3 days per decade. We define a diagnostic fingerprint of temporal and spatial 'sign-switching' responses uniquely predicted by twentieth century climate trends. Among appropriate long-term/large-scale/multi-species data sets, this diagnostic fingerprint was found for 279 species. This suite of analyses generates 'very high confidence' (as laid down by the IPCC) that climate change is already affecting living systems.

Here, we show that exosomes from a mouse and a human mast cell line (MC/9 and HMC-1, respectively), as well as primary bone marrow-derived mouse mast cells, contain RNA. Microarray assessments revealed the presence of mRNA from approximately 1300 genes, many of which are not present in the cytoplasm of the donor cell. In vitro translation proved that the exosome mRNAs were functional. Quality control RNA analysis of total RNA derived from exosomes also revealed presence of small RNAs, including microRNAs. The RNA from mast cell exosomes is transferable to other mouse and human mast cells. After transfer of mouse exosomal RNA to human mast cells, new mouse proteins were found in the recipient cells, indicating that transferred exosomal mRNA can be translated after entering another cell. In summary, we show that exosomes contain both mRNA and microRNA, which can be delivered to another cell, and can be functional in this new location. We propose that this RNA is called "exosomal shuttle RNA" (esRNA).

Key Words programmed cell death, abiotic stress, pathogen defense s Abstract Several reactive oxygen species (ROS) are continuously produced in plants as byproducts of aerobic metabolism. Depending on the nature of the ROS species, some are highly toxic and rapidly detoxified by various cellular enzymatic and nonenzymatic mechanisms. Whereas plants are surfeited with mechanisms to combat increased ROS levels during abiotic stress conditions, in other circumstances plants appear to purposefully generate ROS as signaling molecules to control various processes including pathogen defense, programmed cell death, and stomatal behavior. This review describes the mechanisms of ROS generation and removal in plants during development and under biotic and abiotic stress conditions. New insights into the complexity and roles that ROS play in plants have come from genetic analyses of ROS detoxifying and signaling mutants. Considering recent ROS-induced genomewide expression analyses, the possible functions and mechanisms for ROS sensing and signaling in plants are compared with those in animals and yeast.

A novel and robust automated docking method that predicts the bound conformations of flexible ligands to macromolecular targets has been developed and tested, in combination with a new scoring function that estimates the free energy change upon binding. Interestingly, this method applies a Lamarckian model of genetics, in which environmental adaptations of an individual's phenotype are reverse transcribed into its genotype and become Ž . heritable traits sic . We consider three search methods, Monte Carlo simulated annealing, a traditional genetic algorithm, and the Lamarckian genetic algorithm, and compare their performance in dockings of seven protein᎐ligand test systems having known three-dimensional structure. We show that both the traditional and Lamarckian genetic algorithms can handle ligands with more degrees of freedom than the simulated annealing method used in earlier versions of AUTODOCK, and that the Lamarckian genetic algorithm is the most efficient, reliable, and successful of the three. The empirical free energy function was calibrated using a set of 30 structurally known protein᎐ligand complexes with experimentally determined binding constants. Linear regression analysis of the observed binding constants in terms of a wide variety of structure-derived molecular properties was performed. The final model had a residual standard y1 Ž y1 . error of 9.11 kJ mol 2.177 kcal mol and was chosen as the new energy Abstract: The authors describe the development and testing of a semiempirical free energy force field for use in AutoDock4 and similar grid-based docking methods. The force field is based on a comprehensive thermodynamic model that allows incorporation of intramolecular energies into the predicted free energy of binding. It also incorporates a charge-based method for evaluation of desolvation designed to use a typical set of atom types. The method has been calibrated on a set of 188 diverse protein-ligand complexes of known structure and binding energy, and tested on a set of 100 complexes of ligands with retroviral proteases. The force field shows improvement in redocking simulations over the previous AutoDock3 force field.

DNA sequence data are generally interpreted as favouring Kimura's neutral theory but not without dissent and often with a great deal of controversy with respect to molecular clocks, DNA polymorphism, adaptive evolution, and gene genealogy. Although the theory serves as a guiding principle, many issues concerning mutation, recombination, and selection remain unsettled. Of particular importance is the need for more knowledge about the function and structure of molecules.

Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%. I...

We describe a new basis for the construction of a genetic linkage map of the human genome. The basic principle of the mapping scheme is to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms, when hybridized to restriction digests of an individual's DNA. Each of these probes will define a locus. Loci can be expanded or contracted to include more or less polymorphism by further application of recombinant DNA technology. Suitably polymorphic loci can be tested for linkage relationships in human pedigrees by established methods; and loci can be arranged into linkage groups to form a true genetic map of "DNA marker loci." Pedigrees in which inherited traits are known to be segregating can then be analyzed, making possible the mapping of the gene(s) responsible for the trait with respect to the DNA marker loci, without requiring direct access to a specified gene's DNA. For inherited diseases mapped in this way, linked DNA marker loci can be used predictively for genetic counseling.

The long-standing challenge of designing and constructing new crystalline solid-state materials from molecular building blocks is just beginning to be addressed with success. A conceptual approach that requires the use of secondary building units to direct the assembly of ordered frameworks epitomizes this process: we call this approach reticular synthesis. This chemistry has yielded materials designed to have predetermined structures, compositions and properties. In particular, highly porous frameworks held together by strong metal-oxygen-carbon bonds and with exceptionally large surface area and capacity for gas storage have been prepared and their pore metrics systematically varied and functionalized. The deconstruction of diamond and lonsdaleite. a, diamond; b, lonsdaleite ('hexagonal diamond'). The units outlined in red are the natural tiles for these structures.

DNA micro-arrays now permit scientists to screen thousands of genes simultaneously and determine whether those genes are active, hyperactive or silent in normal or cancerous tissue. Because these new micro-array devices generate bewildering amounts of raw data, new analytical methods must be developed to sort out whether cancer tissues have distinctive signatures of gene expression over normal tissues or other types of cancer tissues.

On activation, T cells undergo distinct developmental pathways, attaining specialized properties and effector functions. T-helper (T H ) cells are traditionally thought to differentiate into T H 1 and T H 2 cell subsets. T H 1 cells are necessary to clear intracellular pathogens and T H 2 cells are important for clearing extracellular organisms 1,2 . Recently, a subset of interleukin (IL)-17-producing T (T H 17) cells distinct from T H 1 or T H 2 cells has been described and shown to have a crucial role in the induction of autoimmune tissue injury 3-5 . In contrast, CD4 1 CD25 1 Foxp3 1 regulatory T (T reg ) cells inhibit autoimmunity and protect against tissue injury 6 . Transforming growth factor-b (TGF-b) is a critical differentiation factor for the generation of T reg cells 7 . Here we show, using mice with a reporter introduced into the endogenous Foxp3 locus, that IL-6, an acute phase protein induced during inflammation 8,9 , completely inhibits the generation of Foxp3 1 T reg cells induced by TGF-b. We also demonstrate that IL-23 is not the differentiation factor for the generation of T H 17 cells. Instead, IL-6 and TGF-b together induce the differentiation of pathogenic T H 17 cells from naive T cells. Our data demonstrate a dichotomy in the generation of pathogenic (T H 17) T cells that induce autoimmunity and regulatory (Foxp3 1 ) T cells that inhibit autoimmune tissue injury.

insight review articles NATURE | VOL 414 | 15 NOVEMBER 2001 | www.nature.com 353 E nergy can be stored in different forms: as mechanical energy (for example, potential energy or rotation energy of a flywheel); in an electric or magnetic field (capacitors and coils, respectively); as chemical energy of reactants and fuels (batteries, petrol or hydrogen); or as nuclear fuel (uranium or deuterium). Chemical and electric energy can be transmitted easily because they both involve electronic Coulomb interaction. Chemical energy is based on the energy of unpaired outer electrons (valence electrons) eager to be stabilized by electrons from other atoms. The hydrogen atom is most attractive because its electron (for charge neutrality) is accompanied by only one proton. Hydrogen thus has the best ratio of valence electrons to protons (and neutrons) of all the periodic table, and the energy gain per electron is very high.

Despite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets-either with respect to the number of taxa or base pairs-can easily require a month of run time. Therefore, we have developed, implemented, and thoroughly tested rapid bootstrap heuristics in RAxML (Randomized Axelerated Maximum Likelihood) that are more than an order of magnitude faster than current algorithms. These new heuristics can contribute to resolving the computational bottleneck and improve current methodology in phylogenetic analyses. Computational experiments to assess the performance and relative accuracy of these heuristics were conducted on 22 diverse DNA and AA (amino acid), single gene as well as multigene, real-world alignments containing 125 up to 7764 sequences. The standard BS (SBS) and rapid BS (RBS) values drawn on the best-scoring ML tree are highly correlated and show almost identical average support values. The weighted RF (Robinson-Foulds) distance between SBSand RBS-based consensus trees was smaller than 6% in all cases (average 4%). More importantly, RBS inferences are between 8 and 20 times faster (average 14.73) than SBS analyses with RAxML and between 18 and 495 times faster than BS analyses with competing programs, such as PHYML or GARLI. Moreover, this performance improvement increases with alignment size. Finally, we have set up two freely accessible Web servers for this significantly improved version of RAxML that provide access to the 200-CPU cluster of the Vital-IT unit at the Swiss Institute of Bioinformatics and the 128-CPU cluster of the CIPRES project at the San Diego Supercomputer Center. These Web servers offer the possibility to conduct large-scale phylogenetic inferences to a large part of the community that does not have access to, or the expertise to use, high-performance computing resources. [Maximum likelihood; phylogenetic inference; rapid bootstrap; RAxML; support values.]

We describe an isothermal, single-reaction method for assembling multiple overlapping DNA molecules by the concerted action of a 5¢ exonuclease, a DNA polymerase and a DNA ligase. First we recessed DNA fragments, yielding single-stranded DNA overhangs that specifically annealed, and then covalently joined them. This assembly method can be used to seamlessly construct synthetic and natural genes, genetic pathways and entire genomes, and could be a useful molecular engineering tool.

To provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information, the Swiss-Prot, TrEMBL and PIR protein database activities have united to form the Universal Protein Knowledgebase (UniProt) consortium. Our mission is to provide a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and query interfaces. The central database will have two sections, corresponding to the familiar Swiss-Prot (fully manually curated entries) and TrEMBL (enriched with automated classification, annotation and extensive cross-references). For convenient sequence searches, UniProt also provides several non-redundant sequence databases. The UniProt NREF (UniRef) databases provide representative subsets of the knowledgebase suitable for efficient searching. The comprehensive UniProt Archive (UniParc) is updated daily from many public source databases. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). The scientific community is encouraged to submit data for inclusion in UniProt.

Normal somatic cells invariably enter a state of irreversibly arrested growth and altered function after a finite number of divisions. This process, termed replicative senescence, is thought to be a tumor-suppressive mechanism and an underlying cause of aging. There is ample evidence that escape from senescence, or immortality, is important for malignant transformation. By contrast, the role of replicative senescence in organismic aging is controversial. Studies on cells cultured from donors of different ages, genetic backgrounds, or species suggest that senescence occurs in vivo and that organismic lifespan and cell replicative lifespan are under common genetic control. However, senescent cells cannot be distinguished from quiescent or terminally differentiated cells in tissues. Thus, evidence that senescent cells exist and accumulate with age in vivo is lacking. We show that several human cells express a f3-galactosidase, histochemically de-

Because a natural entity "species" cannot be recognized as a group of strains that is genetically well separated from its phylogenetic neighbors, a pragmatic approach was taken to define a species by a polyphasic approach which a DNA reassociation value of about 70% plays a dominant role. With the establishment of rapid sequence analysis of 16s rRNA and the recognition of its potential to determine the phylogenetic position of any prokaryotic organism, the role of 16s rRNA similarities in the present species definition in bacteriology needs to be clarified. Comparative studies clearly reveal the limitations of the sequence analysis of this conserved gene and gene product in the determination of relationships at the strain level for which DNA-DNA reassociation experiments still constitute the superior method. Since today the primary structure of 16s rRNA is easier to determine than hybridization between DNA strands, the strength of the sequence analysis is to recognize the level at which DNA pairing studies need to be performed, which certainly applies to similarities of 97% and higher.

Hyperhomocysteinaemia has been identified as a risk factor for cerebrovascular, peripheral vascular, and coronary heart disease. 1-4 Elevated levels of plasma homocysteine can result from genetic or nutrient-related disturbances in the trans-sulphuration or re-methylation pathways for homocysteine metabolism. 1,5-7 5,10-Methylenetetrahydrofolate reductase (MTHFR) catalyzes the reduction of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, the predominant circulatory form of folate and carbon donor for the re-methylation of homocysteine to methionine. Reduced MTHFR activity with a thermolabile enzyme has been reported in patients with coronary and peripheral artery diseases. We have identified a common mutation in MTHFR which alters a highly-conserved amino acid; the substitution occurs at a frequency of approximately 38% of unselected chromosomes. The mutation in the heterozygous or homozygous state correlates with reduced enzyme activity and increased thermolability in lymphocyte extracts; in vitro expression of a mutagenized cDNA containing the mutation confirms its effect on thermolability of MTHFR. Finally, individuals homozygous for the mutation have significantly elevated plasma homocysteine levels. This mutation in MTHFR may represent an important genetic risk factor in vascular disease.

Haplotype-based methods offer a powerful approach to disease gene mapping, based on association between causal mutations and the ancestral haplotypes on which they arose. We characterized haplotype patterns across 51 autosomal regions (spanning 13Mb of the human genome) in samples from Africa, Europe and Asia. We show that the human genome can be parsed objectively into haplotype blocks: sizeable regions over which there is little evidence for historical recombination, and within which only a few common haplotypes are observed. The boundaries of blocks and specific haplotypes they contain are highly correlated across populations. We demonstrate that such haplotype frameworks provide substantial statistical power in association studies of common genetic variation across each region. Our results provide a foundation for the construction of a haplotype map of the human genome, facilitating comprehensive genetic association studies of human disease.