Anna Di Rienzo

Tracing European Founder Lineages in the Near Eastern mtDNA Pool

Founder analysis is a method for analysis of nonrecombining DNA sequence data, with the aim of identification and dating of migrations into new territory. The method picks out founder sequence types in potential source populations and dates lineage clusters deriving from them in the settlement zone of interest. Here, using mtDNA, we apply the approach to the colonization of Europe, to estimate the proportion of modern lineages whose ancestors arrived during each major phase of settlement. To estimate the Palaeolithic and Neolithic contributions to European mtDNA diversity more accurately than was previously achievable, we have now extended the Near Eastern, European, and northern-Caucasus databases to 1,234, 2, 804, and 208 samples, respectively. Both back-migration into the source population and recurrent mutation in the source and derived populations represent major obstacles to this approach. We have developed phylogenetic criteria to take account of both these factors, and we suggest a way to account for multiple dispersals of common sequence types. We conclude that (i) there has been substantial back-migration into the Near East, (ii) the majority of extant mtDNA lineages entered Europe in several waves during the Upper Palaeolithic, (iii) there was a founder effect or bottleneck associated with the Last Glacial Maximum, 20,000 years ago, from which derives the largest fraction of surviving lineages, and (iv) the immigrant Neolithic component is likely to comprise less than one-quarter of the mtDNA pool of modern Europeans.

Using Environmental Correlations to Identify Loci Underlying Local Adaptation

Loci involved in local adaptation can potentially be identified by an unusual correlation between allele frequencies and important ecological variables or by extreme allele frequency differences between geographic regions. However, such comparisons are complicated by differences in sample sizes and the neutral correlation of allele frequencies across populations due to shared history and gene flow. To overcome these difficulties, we have developed a Bayesian method that estimates the empirical pattern of covariance in allele frequencies between populations from a set of markers and then uses this as a null model for a test at individual SNPs. In our model the sample frequencies of an allele across populations are drawn from a set of underlying population frequencies; a transform of these population frequencies is assumed to follow a multivariate normal distribution. We first estimate the covariance matrix of this multivariate normal across loci using a Monte Carlo Markov chain. At each SNP, we then provide a measure of the support, a Bayes factor, for a model where an environmental variable has a linear effect on the transformed allele frequencies compared to a model given by the covariance matrix alone. This test is shown through power simulations to outperform existing correlation tests. We also demonstrate that our method can be used to identify SNPs with unusually large allele frequency differentiation and offers a powerful alternative to tests based on pairwise or global FST. Software is available at http://www.eve.ucdavis.edu/gmcoop/.

Reconstructing Native American population history.

The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved. One contentious issue is whether the settlement occurred by means of a single migration or multiple streams of migration from Siberia. The pattern of dispersals within the Americas is also poorly understood. To address these questions at a higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. Here we show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call ‘First American’. However, speakers of Eskimo–Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan speakers on both sides of the Panama isthmus, who have ancestry from both North and South America.

Phenotype‐genotype correlation of in vitro SN‐38 (active metabolite of irinotecan) and bilirubin glucuronidation in human liver tissue with UGT1A1 promoter polymorphism

Hepatic uridine diphosphate glucuronosyltransferase (UGT) isoform 1A1 (UGT1A1) is primarily responsible for the glucuronidation of SN‐38 (7‐ethyl‐10‐hydroxycamptothecin), the active metabolite of the anticancer agent irinotecan. UGT1A1, also catalyzing the glucuronidation of bilirubin, has been shown to have reduced activity in Gilberts syndrome. The presence of an additional TA repeat [(TA)7 TAA] in the TATA sequence of UGT1A1 has been associated with Gilberts syndrome.

Detection of the Signature of Natural Selection in Humans: Evidence from the Duffy Blood Group Locus

The Duffy blood group locus, which encodes a chemokine receptor, is characterized by three alleles-FY*A, FY*B, and FY*O. The frequency of the FY*O allele, which corresponds to the absence of Fy antigen on red blood cells, is at or near fixation in most sub-Saharan African populations but is very rare outside Africa. The FST value for the FY*O allele is the highest observed for any allele in humans, providing strong evidence for the action of natural selection at this locus. Homozygosity for the FY*O allele confers complete resistance to vivax malaria, suggesting that this allele has been the target of selection by Plasmodium vivax or some other infectious agent. To characterize the signature of directional selection at this locus, we surveyed DNA sequence variation, both in a 1.9-kb region centered on the FY*O mutation site and in a 1-kb region 5-6 kb away from it, in 17 Italians and in a total of 24 individuals from five sub-Saharan African populations. The level of variation across both regions is two- to threefold lower in the Africans than in the Italians. As a result, the pooled African sample shows a significant departure from the neutral expectation for the number of segregating sites, whereas the Italian sample does not. The FY*O allele occurs on two major haplotypes in three of the five African populations. This finding could be due to recombination, recurrent mutation, population structure, and/or mutation accumulation and drift. Although we are unable to distinguish among these alternative hypotheses, it is likely that the two major haplotypes originated prior to selection on the FY*O mutation.

Adjusting the focus on human variation

Studies of nuclear sequence variation are accumulating, such that we can expect a good description of the structure of human variation across populations and genomic regions in the near future. This description will help to elucidate the evolutionary forces that shape patterns of variability. Such an understanding will be of general biological interest, but could also facilitate the design and interpretation of disease-mapping studies. Here, we integrate the results from surveys of nuclear sequence variation. When nuclear sequences are considered together with mtDNA and microsatellites, it becomes clear that neither the standard neutral model, nor a simple long-term exponential growth model, can account for all the available human variation data. A possible explanation is that a subset of loci are not evolving neutrally; even so, more-complex models of effective population size and structure might be necessary to explain the data.

Complex signatures of natural selection at the Duffy blood group locus.

The Duffy blood group locus (FY) has long been considered a likely target of natural selection, because of the extreme pattern of geographic differentiation of its three major alleles (FY*B, FY*A, and FY*O). In the present study, we resequenced the FY region in samples of Hausa from Cameroon (fixed for FY*O), Han Chinese (fixed for FY*A), Italians, and Pakistanis. Our goals were to characterize the signature of directional selection on FY*O in sub-Saharan Africa and to understand the extent to which natural selection has also played a role in the extreme geographic differentiation of the other derived allele at this locus, FY*A. The data from the FY region are compared with the patterns of variation observed at 10 unlinked, putatively neutral loci from the same populations, as well as with theoretical expectations from the neutral-equilibrium model. The FY region in the Hausa shows evidence of directional selection in two independent properties of the data (i.e., level of sequence variation and frequency spectrum), observations that are consistent with the FY*O mutation being the target. The Italian and Chinese FY data show patterns of variation that are very unusual, particularly with regard to frequency spectrum and linkage disequilibrium, but do not fit the predictions of any simple model of selection. These patterns may represent a more complex and previously unrecognized signature of positive selection.

Adaptation – not by sweeps alone

There has been recent progress in identifying selective sweeps underlying a range of adaptations. Jonathan Pritchard and Anna Di Rienzo argue that many adaptive events in natural populations may occur by polygenic adaptation, which would largely go undetected by conventional methods for detecting selection.

Adaptations to climate in candidate genes for common metabolic disorders.

Evolutionary pressures due to variation in climate play an important role in shaping phenotypic variation among and within species and have been shown to influence variation in phenotypes such as body shape and size among humans. Genes involved in energy metabolism are likely to be central to heat and cold tolerance. To test the hypothesis that climate shaped variation in metabolism genes in humans, we used a bioinformatics approach based on network theory to select 82 candidate genes for common metabolic disorders. We genotyped 873 tag SNPs in these genes in 54 worldwide populations (including the 52 in the Human Genome Diversity Project panel) and found correlations with climate variables using rank correlation analysis and a newly developed method termed Bayesian geographic analysis. In addition, we genotyped 210 carefully matched control SNPs to provide an empirical null distribution for spatial patterns of allele frequency due to population history alone. For nearly all climate variables, we found an excess of genic SNPs in the tail of the distributions of the test statistics compared to the control SNPs, implying that metabolic genes as a group show signals of spatially varying selection. Among our strongest signals were several SNPs (e.g., LEPR R109K, FABP2 A54T) that had previously been associated with phenotypes directly related to cold tolerance. Since variation in climate may be correlated with other aspects of environmental variation, it is possible that some of the signals that we detected reflect selective pressures other than climate. Nevertheless, our results are consistent with the idea that climate has been an important selective pressure acting on candidate genes for common metabolic disorders.

The Simons Genome Diversity Project: 300 genomes from 142 diverse populations

Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.