An evaluation of the draft human genome sequence

The completed draft version of the human genome, comprised of multiple short contigs encompassing 85% or more of euchromatin, was announced in June of 2000 (ref. 1). The detailed findings of the sequencing consortium were reported several months later. The draft sequence has provided insight into global characteristics, such as the total number of genes and a more accurate definition of gene families. Also of importance are genome positional details such as local genome architecture, regional gene density and the location of transcribed units that are critical for disease gene identification. We carried out a series of mapping and computational experiments using a nonredundant collection of 925 expressed sequence tags (ESTs) and sections of the public draft genome sequence that were available at different timepoints between April 2000 and April 2001. We found discrepancies in both the reported coverage of the human genome and the accuracy of mapping of genomic clones, suggesting some limitations of the draft genome sequence in providing accurate positional information and detailed characterization of chromosomal subregions.     

An SSLP marker-anchored BAC framework map of the mouse genome

We have constructed a BAC framework map of the mouse genome consisting of 2,808 PCR-confirmed BAC clusters, using a previously described method. Fingerprints of BACs from selected clusters confirm the accuracy of the map. Combined with BAC fingerprint data, the framework map covers 37% of the mouse genome.     

An integrated approach to characterize genetic interaction networks in yeast metabolism

Although experimental and theoretical efforts have been applied to globally map genetic interactions, we still do not understand how gene-gene interactions arise from the operation of biomolecular networks. To bridge the gap between empirical and computational studies, we i, quantitatively measured genetic interactions between ～185,000 metabolic gene pairs in Saccharomyces cerevisiae, ii, superposed the data on a detailed systems biology model of metabolism and iii, introduced a machine-learning method to reconcile empirical interaction data with model predictions. We systematically investigated the relative impacts of functional modularity and metabolic flux coupling on the distribution of negative and positive genetic interactions. We also provide a mechanistic explanation for the link between the degree of genetic interaction, pleiotropy and gene dispensability. Last, we show the feasibility of automated metabolic model refinement by correcting misannotations in NAD biosynthesis and confirming them by in vivo experiments.     

An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis

Using advanced gene targeting methods, generating mouse models of cancer that accurately reproduce the genetic alterations present in human tumors is now relatively straightforward. The challenge is to determine to what extent such models faithfully mimic human disease with respect to the underlying molecular mechanisms that accompany tumor progression. Here we describe a method for comparing mouse models of cancer with human tumors using gene-expression profiling. We applied this method to the analysis of a model of Kras2-mediated lung cancer and found a good relationship to human lung adenocarcinoma, thereby validating the model. Furthermore, we found that whereas a gene-expression signature of KRAS2 activation was not identifiable when analyzing human tumors with known KRAS2 mutation status alone, integrating mouse and human data uncovered a gene-expression signature of KRAS2 mutation in human lung cancer. We confirmed the importance of this signature by gene-expression analysis of short hairpin RNA-mediated inhibition of oncogenic Kras2. These experiments identified both a pattern of gene expression indicative of KRAS2 mutation and potential effectors of oncogenic KRAS2 activity in human cancer. This approach provides a strategy for using genomic analysis of animal models to probe human disease.     

An adaptive radiation model for the origin of new gene functions

Current models for the evolution of new gene functions after gene duplication presume that the duplication events themselves have no effect on fitness. But those duplications that result in new gene functions are likely to be positively selected from their inception. The evolution of new function may start with the amplification of an existing gene with some level of preadaptation for that function, followed by a period of competitive evolution among the gene copies, resulting in the preservation of the most effective variant and the 'pseudogenization' and eventual loss of the rest.     

An initiation site for meiotic crossing-over and gene conversion in the mouse

During meiosis, the reductional segregation of homologous chromosomes at the first meiotic division requires reciprocal exchange (crossing over) between homologs. The number of crossovers is tightly regulated (one to two per homolog in mice), and their distribution in the genome is not random-recombination 'hot' and 'cold' regions can be identified. We developed a molecular assay to study these events directly in mouse germ cells. This analysis was developed with reference to the proteosome subunit beta type 9 (Psmb9, previously called Lmp2) hot-spot region identified through genetic analysis. Here we show that this hot spot is an initiation site of meiotic recombination on the basis of two observations: (i) crossover density is maximal in an interval of 210 bp and decreases on both sides of this region; (ii) a high frequency of gene conversion is found in the region of highest crossover density. We then used this strategy to carry out the first temporal analysis of meiotic recombination in mouse spermatogenesis and demonstrate that crossover events occur during the pachytene stage of meiotic prophase.     

An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations

Population structure causes genome-wide linkage disequilibrium between unlinked loci, leading to statistical confounding in genome-wide association studies. Mixed models have been shown to handle the confounding effects of a diffuse background of large numbers of loci of small effect well, but they do not always account for loci of larger effect. Here we propose a multi-locus mixed model as a general method for mapping complex traits in structured populations. Simulations suggest that our method outperforms existing methods in terms of power as well as false discovery rate. We apply our method to human and Arabidopsis thaliana data, identifying new associations and evidence for allelic heterogeneity. We also show how a priori knowledge from an A. thaliana linkage mapping study can be integrated into our method using a Bayesian approach. Our implementation is computationally efficient, making the analysis of large data sets (n > 10,000) practicable.     

An Hfe-dependent pathway mediates hyposideremia in response to lipopolysaccharide-induced inflammation in mice

Inflammation influences iron balance in the whole organism. A common clinical manifestation of these changes is anemia of chronic disease (ACD; also called anemia of inflammation). Inflammation reduces duodenal iron absorption and increases macrophage iron retention, resulting in low serum iron concentrations (hyposideremia). Despite the protection hyposideremia provides against proliferating microorganisms, this 'iron withholding' reduces the iron available to maturing red blood cells and eventually contributes to the development of anemia. Hepcidin antimicrobial peptide (Hamp) is a hepatic defensin-like peptide hormone that inhibits duodenal iron absorption and macrophage iron release. Hamp is part of the type II acute phase response and is thought to have a crucial regulatory role in sequestering iron in the context of ACD. Mice with deficiencies in the hemochromatosis gene product, Hfe, mounted a general inflammatory response after injection of lipopolysaccharide but lacked appropriate Hamp expression and did not develop hyposideremia. These data suggest a previously unidentified role for Hfe in innate immunity and ACD.     

An Icelandic example of the impact of population structure on association studies

The impact of population structure on association studies undertaken to identify genetic variants underlying common human diseases is an issue of growing interest. Spurious associations of alleles with disease phenotypes may be obtained or true associations overlooked when allele frequencies differ notably among subpopulations that are not represented equally among cases and controls. Population structure influences even carefully designed studies and can affect the validity of association results. Most study designs address this problem by sampling cases and controls from groups that share the same nationality or self-reported ethnic background, with the implicit assumption that no substructure exists within such groups. We examined population structure in the Icelandic gene pool using extensive genealogical and genetic data. Our results indicate that sampling strategies need to take account of substructure even in a relatively homogenous genetic isolate. This will probably be even more important in larger populations.