A Cracking Combination GENE EXPRESSION

HIGHLIGHTS

FUNCTIONAL GENOMICS IN BRIEF

A cracking combination GENE EXPRESSION

As genome sequencing and high- Random monoallelic expression of three genes throughput functional genomics clustered within 60 kb of mouse t complex approaches generate more and genomic DNA. more data, researchers need Sano, Y. et al. Genome Res. 15, 1833–1841 (2001) new ways to tease out biologi- cally relevant information. There are three mechanisms of gene-dosage control in Two important advances in mammals: random X inactivation, parent-of-origin autosomal bioinformatics techniques — gene imprinting and random autosomal inactivation. This last both of which rely on the com- is very rare, but Sano et al. now report a cluster of three genes bination of data sets — are now — Nubp2, Igfals and Jsap1 — on mouse chromosome 17 that reported that allow better predic- undergo this process. In single cells, these genes show X-like, tions of gene and protein function. acid sequences random monoallelic expression, but can switch between active Ge et al. have shown how gene- have diverged. Dietmann and Holm and inactive states during cell division — monoallelic expression and protein–protein inter- combine sequence, structural and expression correlates with the 50% methylation status of the action data can be integrated to refine functional information to create a genomic region. The authors discuss possible mechanisms for predictions of genetic interactions. tree of protein structures, in which such gene expression patterns and their involvement in the And Dietmann and Holm have the most structurally similar proteins biology of the t complex. devised an improved computational lie on the same branch of the tree. method for detecting remote homol- This approach overcomes some of HUMAN GENETICS ogy on the basis of structural similar- the shortcomings of other bioinfor- ities between proteins. matics tools. Their analysis can also An apolipoprotein influencing triglycerides in Ge et al. began their study by infer homology relationships humans and mice revealed by comparative investigating whether genes that are between proteins and group them sequencing. co-expressed at the transcriptional into ‘superfamilies’.The results com- Pennacchio, L. A. et al. Science 294, 169–173 (2001) level are more likely to encode pro- pare very favourably with a protein Apolipoproteins are known to affect plasma lipid levels in teins that interact with each other. classification system that is manually humans  an important factor in susceptibility to heart They tested this in yeast, using tran- curated by experts (SCOP). Finally, disease. Pennacchio et al. explored the already known scriptional microarray data and a the authors show that their automat- apolipoprotein gene cluster on chromosome 11 for new combination of genome-wide two- ed system could be used to predict the susceptibility loci. By comparing mouse and human sequence, hybrid data, as well as individual pro- superfamily membership, and there- they identified a new locus, which when knocked out in mice tein data from literature searches. In fore a putative function, of a new pro- leads to a substantial increase in plasma lipid levels, but when general, clusters of co-expressed tein structure that might be deter- overexpressed causes these levels to drop below wild-type genes do indeed have a higher chance mined as part of a structural levels. This marked effect prompted the authors to look for of giving a positive score in the two- genomics project. SNPs in the human locus  all three rare alleles that they hybrid assays and in experimental Such computational approaches studied were associated with high lipid levels. data derived from the literature. This are essential if we are to predict and lends weight to the idea that co- understand complex genetic net- DEVELOPMENTAL BIOLOGY expression and protein interaction works from data generated by high- are both useful predictors of func- throughput genomic studies. And as Reciprocal mouse and human limb phenotypes tional interaction. More importantly, the experimental technologies caused by gain- and loss-of-function mutations the combination of these two types of improve and generate more compre- affecting Lmbr1. data can also provide new insights hensive and complementary data 159 into functionally related groups of sets, the prospects for further combi- Clark, R. M. et al. Genetics , 715–726 (2001) genes. The authors provide an exam- natorial approaches to data analysis Most of the dominantly inherited preaxial polydactly and ple in which a group of genes that is will be bright. syndactyly phenotypes, which affect limb-digit number, map involved in a network of stress- Magdalena Skipper to human chromosome 7q36 and to a homologous region in response protein–protein interactions References and links mice. By using deletion chromosomes, these authors show is divided into two co-expression ORIGINAL RESEARCH PAPERS Ge, H. et al. that limb defects that map to this region in mice result from clusters. This refines the view of how Correlation between transcriptome and gain-of-function mutations, rather than by haploinsufficiency. interactome mapping data from Saccharomyces the genes interact and leads to cerevisiae. Nature Genet. 10.1038/ng776 (2001) | Mice with loss-of-function mutations in limb region 1 the development of new, testable Dietmann, S. & Holm, L. Identification of homology (Lmbr1), which might be allelic to the known limb hypotheses. in protein structure classification. Nature Struct. Biol. 8, 953–957 (2001) morphology mutants Hemimelic extra toes and Hammertoe, Important clues about function FURTHER READING Lichtarge, O. Getting past have fewer limb digits than normal. Because this phenotype can come from protein structure, appearances: the many-fold consequences of is reciprocal to polydactly, the authors propose that levels remote homology. Nature Struct. Biol. 8, 918–920 especially if the proteins in question (2001) | Brenner, S. E. A tour of structural of Lmbr1 activity control the morphology of the vertebrate are distantly related and their amino- genomics. Nature Rev. Genet. 2, 801–809 (2001) limb skeleton.