Whole-genome sequencing reveals activation-induced cytidine deaminase signatures during indolent chronic lymphocytic leukaemia evolution.

Patients with chromosome 13q deletion or normal cytogenetics represent the majority of chronic lymphocytic leukaemia (CLL) cases, yet have relatively few driver mutations. To better understand their genomic landscape, here we perform whole-genome sequencing on a cohort of patients enriched with these cytogenetic characteristics. Mutations in known CLL drivers are seen in only 33% of this cohort, and associated with normal cytogenetics and unmutated IGHV. The most commonly mutated gene in our cohort, IGLL5, shows a mutational pattern suggestive of activation-induced cytidine deaminase (AID) activity. Unsupervised analysis of mutational signatures demonstrates the activities of canonical AID (c-AID), leading to clustered mutations near active transcriptional start sites; non-canonical AID (nc-AID), leading to genome-wide non-clustered mutations, and an ageing signature responsible for most mutations. Using mutation clonality to infer time of onset, we find that while ageing and c-AID activities are ongoing, nc-AID-associated mutations likely occur earlier in tumour evolution.

SNP genotyping defines complex gene-flow boundaries among African malaria vector mosquitoes.

Mosquitoes in the Anopheles gambiae complex show rapid ecological and behavioral diversification, traits that promote malaria transmission and complicate vector control efforts. A high-density, genome-wide mosquito SNP-genotyping array allowed mapping of genomic differentiation between populations and species that exhibit varying levels of reproductive isolation. Regions near centromeres or within polymorphic inversions exhibited the greatest genetic divergence, but divergence was also observed elsewhere in the genomes. Signals of natural selection within populations were overrepresented among genomic regions that are differentiated between populations, implying that differentiation is often driven by population-specific selective events. Complex genomic differentiation among speciating vector mosquito populations implies that tools for genome-wide monitoring of population structure will prove useful for the advancement of malaria eradication.

cDNA sequences for transcription factors and signaling proteins of the hemichordate Saccoglossus kowalevskii: efficacy of the expressed sequence tag (EST) approach for evolutionary and developmental studies of a new organism.

We describe a collection of expressed sequence tags (ESTs) for Saccoglossus kowalevskii, a direct-developing hemichordate valuable for evolutionary comparisons with chordates. The 202,175 ESTs represent 163,633 arrayed clones carrying cDNAs prepared from embryonic libraries, and they assemble into 13,677 continuous sequences (contigs), leaving 10,896 singletons (excluding mitochondrial sequences). Of the contigs, 53% had significant matches when BLAST was used to query the NCBI databases (< or = 10(-10)), as did 51% of the singletons. Contigs most frequently matched sequences from amphioxus (29%), chordates (67%), and deuterostomes (87%). From the clone array, we isolated 400 full-length sequences for transcription factors and signaling proteins of use for evolutionary and developmental studies. The set includes sequences for fox, pax, tbx, hox, and other homeobox-containing factors, and for ligands and receptors of the TGFbeta, Wnt, Hh, Delta/Notch, and RTK pathways. At least 80% of key sequences have been obtained, when judged against gene lists of model organisms. The median length of these cDNAs is 2.3 kb, including 1.05 kb of 3' untranslated region (UTR). Only 30% are entirely matched by single contigs assembled from ESTs. We conclude that an EST collection based on 150,000 clones is a rich source of sequences for molecular developmental work, and that the EST approach is an efficient way to initiate comparative studies of a new organism.

Distinct physiological states of Plasmodium falciparum in malaria-infected patients.

Infection with the malaria parasite Plasmodium falciparum leads to widely different clinical conditions in children, ranging from mild flu-like symptoms to coma and death. Despite the immense medical implications, the genetic and molecular basis of this diversity remains largely unknown. Studies of in vitro gene expression have found few transcriptional differences between different parasite strains. Here we present a large study of in vivo expression profiles of parasites derived directly from blood samples from infected patients. The in vivo expression profiles define three distinct transcriptional states. The biological basis of these states can be interpreted by comparison with an extensive compendium of expression data in the yeast Saccharomyces cerevisiae. The three states in vivo closely resemble, first, active growth based on glycolytic metabolism, second, a starvation response accompanied by metabolism of alternative carbon sources, and third, an environmental stress response. The glycolytic state is highly similar to the known profile of the ring stage in vitro, but the other states have not been observed in vitro. The results reveal a previously unknown physiological diversity in the in vivo biology of the malaria parasite, in particular evidence for a functional mitochondrion in the asexual-stage parasite, and indicate in vivo and in vitro studies to determine how this variation may affect disease manifestations and treatment.

Positive natural selection in the human lineage.

Positive natural selection is the force that drives the increase in prevalence of advantageous traits, and it has played a central role in our development as a species. Until recently, the study of natural selection in humans has largely been restricted to comparing individual candidate genes to theoretical expectations. The advent of genome-wide sequence and polymorphism data brings fundamental new tools to the study of natural selection. It is now possible to identify new candidates for selection and to reevaluate previous claims by comparison with empirical distributions of DNA sequence variation across the human genome and among populations. The flood of data and analytical methods, however, raises many new challenges. Here, we review approaches to detect positive natural selection, describe results from recent analyses of genome-wide data, and discuss the prospects and challenges ahead as we expand our understanding of the role of natural selection in shaping the human genome.

Family-based association study of 76 candidate genes in bipolar disorder: BDNF is a potential risk locus. Brain-derived neutrophic factor.

Identification of the genetic bases for bipolar disorder remains a challenge for the understanding of this disease. Association between 76 candidate genes and bipolar disorder was tested by genotyping 90 single-nucleotide polymorphisms (SNPs) in these genes in 136 parent-proband trios. In this preliminary analysis, SNPs in two genes, brain-derived neurotrophic factor (BDNF) and the alpha subunit of the voltage-dependent calcium channel were associated with bipolar disorder at the P<0.05 level. In view of the large number of hypotheses tested, the two nominally positive associations were then tested in independent populations of bipolar patients and only BDNF remains a potential risk gene. In the replication samples, excess transmission of the valine allele of amino acid 66 of BDNF was observed in the direction of the original result in an additional sample of 334 parent-proband trios (T/U=108/87, P=0.066). Resequencing of 29 kb surrounding the BDNF gene identified 44 additional SNPs. Genotyping eight common SNPs identified three additional markers transmitted to bipolar probands at the P < 0.05 level. Strong LD was observed across this region and all adjacent pairwise haplotypes showed excess transmission to the bipolar proband. Analysis of these haplotypes using TRANSMIT revealed a global P value of 0.03. A single haplotype was identified that is shared by both the original dataset and the replication sample that is uniquely marked by both the rare A allele of the original SNP and a novel allele 11.5 kb 3'. Therefore, this study of 76 candidate genes has identified BDNF as a potential risk allele that will require additional study to confirm.

Genomewide search for type 2 diabetes mellitus susceptibility loci in Finnish families: the Botnia study.

Type 2 diabetes mellitus is a heterogeneous inherited disorder characterized by chronic hyperglycemia resulting from pancreatic beta-cell dysfunction and insulin resistance. Although the pathogenic mechanisms are not fully understood, manifestation of the disease most likely requires interaction between both environmental and genetic factors. In the search for such susceptibility genes, we have performed a genomewide scan in 58 multiplex families (comprising 440 individuals, 229 of whom were affected) from the Botnia region in Finland. Initially, linkage between chromosome 12q24 and impaired insulin secretion had been reported, by Mahtani et al., in a subsample of 26 families. In the present study, we extend the initial genomewide scan to include 32 additional families, update the affectation status, and fine map regions of interest, and we try to replicate the initial stratification analysis. In our analysis of all 58 families, we identified suggestive linkage to one region, chromosome 9p13-q21 (nonparametric linkage [NPL] score 3.9; P<.0002). Regions with nominal P values <.05 include chromosomes 2p11 (NPL score 2.0 [P<.03]), 3p24-p22 (NPL score 2.2 [P<.02]), 4q32-q33 (NPL score 2.5 [P<.01]), 12q24 (NPL score 2.1 [P<.03]), 16p12-11 (NPL score 1.7 [P<.05]), and 17p12-p11 (NPL score 1.9 [P<.03]). When chromosome 12q24 was analyzed in only the 32 additional families, a nominal P value <.04 was observed. Together with data from other published genomewide scans, these findings lend support to the hypothesis that regions on chromosome 9p13-q21 and 12q24 may harbor susceptibility genes for type 2 diabetes.

Multiclass cancer diagnosis using tumor gene expression signatures.

The optimal treatment of patients with cancer depends on establishing accurate diagnoses by using a complex combination of clinical and histopathological data. In some instances, this task is difficult or impossible because of atypical clinical presentation or histopathology. To determine whether the diagnosis of multiple common adult malignancies could be achieved purely by molecular classification, we subjected 218 tumor samples, spanning 14 common tumor types, and 90 normal tissue samples to oligonucleotide microarray gene expression analysis. The expression levels of 16,063 genes and expressed sequence tags were used to evaluate the accuracy of a multiclass classifier based on a support vector machine algorithm. Overall classification accuracy was 78%, far exceeding the accuracy of random classification (9%). Poorly differentiated cancers resulted in low-confidence predictions and could not be accurately classified according to their tissue of origin, indicating that they are molecularly distinct entities with dramatically different gene expression patterns compared with their well differentiated counterparts. Taken together, these results demonstrate the feasibility of accurate, multiclass molecular cancer classification and suggest a strategy for future clinical implementation of molecular cancer diagnostics.

Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses.

We have generated a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, we analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct subclasses of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients.

The plasticity of dendritic cell responses to pathogens and their components.

Dendritic cells are involved in the initiation of both innate and adaptive immunity. To systematically explore how dendritic cells modulate the immune system in response to different pathogens, we used oligonucleotide microarrays to measure gene expression profiles of dendritic cells in response to Escherichia coli, Candida albicans, and influenza virus as well as to their molecular components. Both a shared core response and pathogen-specific programs of gene expression were observed upon exposure to each of these pathogens. These results reveal that dendritic cells sense diverse pathogens and elicit tailored pathogen-specific immune responses.

A radiation hybrid map of mouse genes.

A comprehensive gene-based map of a genome is a powerful tool for genetic studies and is especially useful for the positional cloning and positional candidate approaches. The availability of gene maps for multiple organisms provides the foundation for detailed conserved-orthology maps showing the correspondence between conserved genomic segments. These maps make it possible to use cross-species information in gene hunts and shed light on the evolutionary forces that shape the genome. Here we report a radiation hybrid map of mouse genes, a combined project of the Whitehead Institute/Massachusetts Institute of Technology Center for Genome Research, the Medical Research Council UK Mouse Genome Centre, and the National Center for Biotechnology Information. The map contains 11,109 genes, screened against the T31 RH panel and positioned relative to a reference map containing 2,280 mouse genetic markers. It includes 3,658 genes homologous to the human genome sequence and provides a framework for overlaying the human genome sequence to the mouse and for sequencing the mouse genome.

Genetic variation in the 5q31 cytokine gene cluster confers susceptibility to Crohn disease.

Linkage disequilibrium (LD) mapping provides a powerful method for fine-structure localization of rare disease genes, but has not yet been widely applied to common disease. We sought to design a systematic approach for LD mapping and apply it to the localization of a gene (IBD5) conferring susceptibility to Crohn disease. The key issues are: (i) to detect a significant LD signal (ii) to rigorously bound the critical region and (iii) to identify the causal genetic variant within this region. We previously mapped the IBD5 locus to a large region spanning 18 cM of chromosome 5q31 (P<10(-4)). Using dense genetic maps of microsatellite markers and single-nucleotide polymorphisms (SNPs) across the entire region, we found strong evidence of LD. We bound the region to a common haplotype spanning 250 kb that shows strong association with the disease (P< 2 x 10(-7)) and contains the cytokine gene cluster. This finding provides overwhelming evidence that a specific common haplotype of the cytokine region in 5q31 confers susceptibility to Crohn disease. However, genetic evidence alone is not sufficient to identify the causal mutation within this region, as strong LD across the region results in multiple SNPs having equivalent genetic evidence-each consistent with the expected properties of the IBD5 locus. These results have important implications for Crohn disease in particular and LD mapping in general.

High-resolution haplotype structure in the human genome.

Linkage disequilibrium (LD) analysis is traditionally based on individual genetic markers and often yields an erratic, non-monotonic picture, because the power to detect allelic associations depends on specific properties of each marker, such as frequency and population history. Ideally, LD analysis should be based directly on the underlying haplotype structure of the human genome, but this structure has remained poorly understood. Here we report a high-resolution analysis of the haplotype structure across 500 kilobases on chromosome 5q31 using 103 single-nucleotide polymorphisms (SNPs) in a European-derived population. The results show a picture of discrete haplotype blocks (of tens to hundreds of kilobases), each with limited diversity punctuated by apparent sites of recombination. In addition, we develop an analytical model for LD mapping based on such haplotype blocks. If our observed structure is general (and published data suggest that it may be), it offers a coherent framework for creating a haplotype map of the human genome.

Chemosensitivity prediction by transcriptional profiling.

In an effort to develop a genomics-based approach to the prediction of drug response, we have developed an algorithm for classification of cell line chemosensitivity based on gene expression profiles alone. Using oligonucleotide microarrays, the expression levels of 6,817 genes were measured in a panel of 60 human cancer cell lines (the NCI-60) for which the chemosensitivity profiles of thousands of chemical compounds have been determined. We sought to determine whether the gene expression signatures of untreated cells were sufficient for the prediction of chemosensitivity. Gene expression-based classifiers of sensitivity or resistance for 232 compounds were generated and then evaluated on independent sets of data. The classifiers were designed to be independent of the cells' tissue of origin. The accuracy of chemosensitivity prediction was considerably better than would be expected by chance. Eighty-eight of 232 expression-based classifiers performed accurately (with P < 0.05) on an independent test set, whereas only 12 of the 232 would be expected to do so by chance. These results suggest that at least for a subset of compounds genomic approaches to chemosensitivity prediction are feasible.

Ducky mouse phenotype of epilepsy and ataxia is associated with mutations in the Cacna2d2 gene and decreased calcium channel current in cerebellar Purkinje cells.

The mouse mutant ducky, a model for absence epilepsy, is characterized by spike-wave seizures and ataxia. The ducky gene was mapped previously to distal mouse chromosome 9. High-resolution genetic and physical mapping has resulted in the identification of the Cacna2d2 gene encoding the alpha2delta2 voltage-dependent calcium channel subunit. Mutations in Cacna2d2 were found to underlie the ducky phenotype in the original ducky (du) strain and in a newly identified strain (du(2J)). Both mutations are predicted to result in loss of the full-length alpha2delta2 protein. Functional analysis shows that the alpha2delta2 subunit increases the maximum conductance of the alpha1A/beta4 channel combination when coexpressed in vitro in Xenopus oocytes. The Ca(2+) channel current in acutely dissociated du/du cerebellar Purkinje cells was reduced, with no change in single-channel conductance. In contrast, no effect on Ca(2+) channel current was seen in cerebellar granule cells, results consistent with the high level of expression of the Cacna2d2 gene in Purkinje, but not granule, neurons. Our observations document the first mammalian alpha2delta mutation and complete the association of each of the major classes of voltage-dependent Ca(2+) channel subunits with a phenotype of ataxia and epilepsy in the mouse.

On the allelic spectrum of human disease.

Human disease genes show enormous variation in their allelic spectra; that is, in the number and population frequency of the disease-predisposing alleles at the loci. For some genes, there are a few predominant disease alleles. For others, there is a wide range of disease alleles, each relatively rare. The allelic spectrum is important: disease genes with only a few deleterious alleles can be more readily identified and are more amenable to clinical testing. Here, we weave together strands from the human mutation and population genetics literature to provide a framework for understanding and predicting the allelic spectra of disease genes. The theory does a reasonable job for diseases where the genetic etiology is well understood. It also has bearing on the Common Disease/Common Variants (CD/CV) hypothesis, predicting that at loci where the total frequency of disease alleles is not too small, disease loci will have relatively simple spectra.

Lower-than-expected linkage disequilibrium between tightly linked markers in humans suggests a role for gene conversion.

Understanding the pattern of linkage disequilibrium (LD) in the human genome is important both for successful implementation of disease-gene mapping approaches and for inferences about human demographic histories. Previous studies have examined LD between loci within single genes or confined genomic regions, which may not be representative of the genome; between loci separated by large distances, where little LD is seen; or in population groups that differ from one study to the next. We measured LD in a large set of locus pairs distributed throughout the genome, with loci within each pair separated by short distances (average 124 bp). Given current models of the history of the human population, nearly all pairs of loci at such short distances would be expected to show complete LD as a consequence of lack of recombination in the short interval. Contrary to this expectation, a significant fraction of pairs showed incomplete LD. A standard model of recombination applied to these data leads to an estimate of effective human population size of 110,000. This estimate is an order of magnitude higher than most estimates based on nucleotide diversity. The most likely explanation of this discrepancy is that gene conversion increases the apparent rate of recombination between nearby loci.

Association analysis of NOTCH4 loci in schizophrenia using family and population-based controls.

A genetic association between NOTCH4 and schizophrenia has previously been proposed. Unsing all markers previously shown to be associated, we found no evidence for such in three independent family-based samples (n=519 parent-offspring trios), and a case-control sample derived from the same ethnic background as the original observation. These data strongly suggest that NOTCH4 is not a significant susceptibility allele for schizophrenia.

Genomewide linkage analysis of stature in multiple populations reveals several regions with evidence of linkage to adult height.

Genomewide linkage analysis has been extremely successful at identification of the genetic variation underlying single-gene disorders. However, linkage analysis has been less successful for common human diseases and other complex traits in which multiple genetic and environmental factors interact to influence disease risk. We hypothesized that a highly heritable complex trait, in which the contribution of environmental factors was relatively limited, might be more amenable to linkage analysis. We therefore chose to study stature (adult height), for which heritability is approximately 75%-90% (Phillips and Matheny 1990; Carmichael and McGue 1995; Preece 1996; Silventoinen et al. 2000). We reanalyzed genomewide scans from four populations for which genotype and height data were available, using a variance-components method implemented in GENEHUNTER 2.0 (Pratt et al. 2000). The populations consisted of 408 individuals in 58 families from the Botnia region of Finland, 753 individuals in 183 families from other parts of Finland, 746 individuals in 179 families from Southern Sweden, and 420 individuals in 63 families from the Saguenay-Lac-St.-Jean region of Quebec. Four regions showed evidence of linkage to stature: 6q24-25, multipoint LOD score 3.85 at marker D6S1007 in Botnia (genomewide P<.06), 7q31.3-36 (LOD 3.40 at marker D7S2195 in Sweden, P<.02), 12p11.2-q14 (LOD 3.35 at markers D12S10990-D12S398 in Finland, P<.05) and 13q32-33 (LOD 3.56 at markers D13S779-D13S797 in Finland, P<.05). In a companion article (Perola et al. 2001 [in this issue]), strong supporting evidence is obtained for linkage to the region on chromosome 7. These studies suggest that highly heritable complex traits such as stature may be genetically tractable and provide insight into the genetic architecture of complex traits.