No abstract

Variation in DNA sequence contributes to individual differences in quantitative traits, but in humans the specific sequence variants are known for very few traits. We characterized variation in gene expression in cells from individuals belonging to three major population groups. This quantitative phenotype differs significantly between European-derived and Asian-derived populations for 1,097 of 4,197 genes tested. For the phenotypes with the strongest evidence of cis determinants, most of the variation is due to allele frequency differences at cis-linked regulators. The results show that specific genetic variation among populations contributes appreciably to differences in gene expression phenotypes. Populations differ in prevalence of many complex genetic diseases, such as diabetes and cardiovascular disease. As some of these are probably influenced by the level of gene expression, our results suggest that allele frequency differences at regulatory polymorphisms also account for some population differences in prevalence of complex diseases.The expression levels of genes determine the distinctive characteristics of cells. Recent studies have shown that gene expression levels in humans differ not only among cell types within an individual but also among individuals 1,2 . This observation led to analysis of gene expression as a phenotype and to the identification of polymorphic genetic variants that influence individual differences in expression level [3][4][5][6][7][8] . However, these studies of the genetics of human gene expression have been restricted to individuals from one Europeanderived sample, the families collected by the Centre d'Etude du Polymorphisme Humain Correspondence should be addressed to V.G.C. (vcheung@mail.med.upenn.edu) or R.S.S. (spielman@pobox.upenn.edu). Accession codes. Gene Expression Omnibus (GEO): GSE5859.URLs. Human Variation Panel: http://ccr.coriell.org/nigms/cells/humdiv.html. MultiExperiment Viewer: http://www.tm4.org. Information on HapMap SNP markers can be found at http://www.hapmap.org.Note: Supplementary information is available on the Nature Genetics website. COMPETING INTERESTS STATEMENTThe authors declare that they have no competing financial interests. Much of the recognized genetic variation among populations is in DNA polymorphisms with no known functional significance. On the other hand, some allele frequency differences between populations have highly significant phenotypic consequences. Among the bestestablished are the differences in allele frequencies for mendelian genetic diseases. The marked population differences in prevalence of these qualitative phenotypes (such as cystic fibrosis 9 and Tay-Sachs disease 10 ) are entirely due to differences in frequencies of the mutant alleles. However, genetic differences among populations in quantitative phenotypes are potentially just as important functionally.Here we extend the comparative genetic analysis of population differences from qualitative phenotypes to a particular quantitative phenotype, the expression ...

R-loops are three-stranded nucleic acid structures found abundantly and yet often viewed as by-products of transcription. Studying cells from patients with a motor neuron disease (amyotrophic lateral sclerosis 4 [ALS4]) caused by a mutation in senataxin, we uncovered how R-loops promote transcription. In ALS4 patients, the senataxin mutation depletes R-loops with a consequent effect on gene expression. With fewer R-loops in ALS4 cells, the expression of BAMBI, a negative regulator of transforming growth factor β (TGF-β), is reduced; that then leads to the activation of the TGF-β pathway. We uncovered that genome-wide R-loops influence promoter methylation of over 1,200 human genes. DNA methyl-transferase 1 favors binding to double-stranded DNA over R-loops. Thus, in forming R-loops, nascent RNA blocks DNA methylation and promotes further transcription. Hence, our results show that nucleic acid structures, in addition to sequences, influence the binding and activity of regulatory proteins.

RNA/DNA hybrids form when RNA hybridizes with its template DNA generating a three-stranded structure known as the R-loop. Knowledge of how they form and resolve, as well as their functional roles, is limited. Here, by pull-down assays followed by mass spectrometry, we identified 803 proteins that bind to RNA/DNA hybrids. Because these proteins were identified using in vitro assays, we confirmed that they bind to R-loops in vivo. They include proteins that are involved in a variety of functions, including most steps of RNA processing. The proteins are enriched for K homology (KH) and helicase domains. Among them, more than 300 proteins preferred binding to hybrids than double-stranded DNA. These proteins serve as starting points for mechanistic studies to elucidate what RNA/DNA hybrids regulate and how they are regulated.

Our genotype inference method combines sparse marker data from a linkage scan and highresolution SNP genotypes for several individuals to infer genotypes for related individuals. We illustrate the method's utility by inferring over 53 million SNP genotypes for 78 children in the Centre d'Etude du Polymorphisme Humain families. The method can be used to obtain highdensity genotypes in different family structures, including nuclear families commonly used in complex disease gene mapping studies.Even though groups such as The SNP Consortium 1 and the International HapMap Consortium 2,3 have identified millions of polymorphic markers and stimulated the development of high-throughput genotyping techniques [4][5][6] , genotyping of polymorphic markers remains a labor-intensive and costly step in genetic mapping studies. To decrease the cost of family-based genetic studies, we developed a computational approach that uses high-density genotype data for a subset of individuals in a pedigree to infer genotypes for the remaining relatives (see http://genomics.med.upenn.edu/genotypeinference and http://www.sph.umich.edu/csg/abecasis/Merlin/ for the software). This approach greatly reduces the amount of conventional 'wet-lab' experimentation required to carry out association analysis in pedigrees.Many gene mapping projects use a tiered approach: first, genome-wide linkage analysis is carried out using widely spaced markers across the genome; then, genotypes are determined for many more markers near observed linkage peaks and are tested by association analysis. Our approach reduces work in the second stage because experimental genotyping is required for only a subset of individuals. Genotypes for the remaining individuals are obtained in two steps. First, low-resolution genotypes from linkage analysis are used to identify regions of shared identity-by-descent (IBD) between relatives. Then, with information on IBD sharing between individuals and high-density genotype data on some members of the family, we infer most of the unobserved high-density genotypes for the remaining individuals. COMPETING INTERESTS STATEMENTThe authors declare that they have no competing financial interests. To illustrate this procedure, we used it to infer genotypes for the children in ten Centre d'Etude du Polymorphisme Humain (CEPH)-HapMap pedigrees. All the grandparents and parents of these pedigrees have been genotyped at about 1 million SNP markers in Phase I of the International HapMap Project 3 . First, we used genotypes of 6,564 genetic markers obtained previously on all individuals to determine the grandparental origin for every chromosomal segment in each child. Specifically, for each child and at every marker, we considered the allele from the mother and determined whether that allele was inherited from a transmitted chromosome that originated in the maternal grandfather or grandmother; we did the same for the paternal side. Results from adjacent markers allow us to confirm the grandparental origins of each genomic region (Fig. 1a)....

The invariant lineage of Caenorhabditis elegans has powerful potential for quantifying developmental variability in normal and stressed embryos. Previous studies of division timing by automated lineage tracing suggested that variability in cell cycle timing is low in younger embryos, but manual lineage tracing of specific lineages suggested that variability may increase for later divisions. We developed improved automated lineage tracing methods that allow routine lineage tracing through the last round of embryonic cell divisions and we applied these methods to trace the lineage of 18 wild-type embryos. Cell cycle lengths, division axes and cell positions are remarkably consistent among these embryos at all stages, with only slight increases in variability later in development. The resulting quantitative 4-dimensional model of embryogenesis provides a powerful reference dataset to identify defects in mutants or in embryos that have experienced environmental perturbations. We also traced the lineages of embryos imaged at higher temperatures to quantify the decay in developmental robustness under temperature stress. Developmental variability increases modestly at 25°C compared with 22°C and dramatically at 26°C, and we identify homeotic transformations in a subset of embryos grown at 26°C. The deep lineage tracing methods provide a powerful tool for analysis of normal development, gene expression and mutants and we provide a graphical user interface to allow other researchers to explore the average behavior of arbitrary cells in a reference embryo.

In this study, our phenotype of interest is meiotic recombination. Using genotypes of approximately 6,000 SNP markers in members of the Centre d'Etude du Polymorphisme Humain Utah pedigrees, we found extensive individual variation in the number of female and male recombination events. The locations and frequencies of these recombination events vary along the genome. In both female and male meiosis, the regions with the most recombination events are found at the ends of the chromosomes. Our analysis also shows that there are polymorphic differences among individuals in the activity of the recombination "jungles"; these preferred sites of meiotic recombination differ greatly among individuals. These findings have important implications for understanding genetic disorders that result from improper chromosome segregation.

RNA abasic sites and the mechanisms involved in their regulation are mostly unknown; in contrast, DNA abasic sites are well-studied. We found surprisingly that, in yeast and human cells, RNA abasic sites are prevalent. When a base is lost from RNA, the remaining ribose is found as a closed-ring or an open-ring sugar with a reactive C1′ aldehyde group. Using primary amine-based reagents that react with the aldehyde group, we uncovered evidence for abasic sites in nascent RNA, messenger RNA, and ribosomal RNA from yeast and human cells. Mass spectroscopic analysis confirmed the presence of RNA abasic sites. The RNA abasic sites were found to be coupled to R-loops. We show that human methylpurine DNA glycosylase cleaves N-glycosidic bonds on RNA and that human apurinic/apyrimidinic endonuclease 1 incises RNA abasic sites in RNA–DNA hybrids. Our results reveal that, in yeast and human cells, there are RNA abasic sites, and we identify a glycosylase that generates these sites and an AP endonuclease that processes them.