Y-chromosome based evidence for pre-neolithic origin of the genetically homogeneous but diverse Sardinian population: inference for association scans

The island of Sardinia shows a unique high incidence of several autoimmune diseases with multifactorial inheritance, particularly type 1 diabetes and multiple sclerosis. The prior knowledge of the genetic structure of this population is fundamental to establish the optimal design for association studies in these diseases. Previous work suggested that the Sardinians are a relatively homogenous population, but some reports were contradictory and data were largely based on variants subject to selection. For an unbiased assessment of genetic structure, we studied a combination of neutral Y-chromosome variants, 21 biallelic and 8 short tandem repeats (STRs) in 930 Sardinian males. We found a high degree of interindividual variation but a homogenous distribution of the detected variability in samples from three separate regions of the island. One haplogroup, I-M26, is rare or absent outside Sardinia and is very common (0.37 frequency) throughout the island, consistent with a founder effect. A Bayesian full likelihood analysis (BATWING) indicated that the time from the most recent common ancestor (TMRCA) of I-M26, was 21.0 (16.0-25.5) thousand years ago (KYA) and that the population began to expand 14.0 (7.8-22.0) KYA. These results suggest a largely pre-Neolithic settlement of the island with little subsequent gene flow from outside populations. Consequently, Sardinia is an especially attractive venue for case-control genome wide association scans in common multifactorial diseases. Concomitantly, the high degree of interindividual variation in the current population facilitates fine mapping efforts to pinpoint the aetiologic polymorphisms.     

Effective number of breeders and maintenance of genetic diversity in the captive bearded vulture population

We combined pedigree data with data derived from 14 microsatellite loci to investigate genetic diversity and its maintenance in the captive source population for the reintroduction of the bearded vulture into the Alps. We found the captive population to be genetically more variable than the largest natural population in Europe, both in terms of mean number of alleles per locus and mean observed and expected heterozygosity. Allelic diversity of the captive population was higher than, and mean heterozygosity measurements were comparable with the ones found in two large, extinct populations from Sardinia and the Alps represented by museum specimens. The amount of genetic variability recruited with the founders was still present in the captive population of the year 2000, mainly because the carriers of rare alleles were still alive. However, the decline in expected heterozygosity and the loss of alleles over generations in captivity was significant. Point estimates of effective population size, N(e), based on pedigree data and estimates of effective number of breeders, N(b), based on allele frequency changes, ranged from 20 to 30 and were significantly smaller than the census size. The results demonstrate that the amount of genetic variability in the captive bearded vulture population is comparable or even larger than the amount present in natural populations. However, the population is in danger to lose genetic variability over time because of genetic drift. Management strategies should therefore aim at preserving genetic variability by minimising kinship, and at increasing N(e) by recruiting additional founders and enhancing gene flow between the released, the captive and natural populations.     

Low-pass genome-wide sequencing and variant inference using identity-by-descent in an isolated human population

Whole-genome sequencing in an isolated population with few founders directly ascertains variants from the population bottleneck that may be rare elsewhere. In such populations, shared haplotypes allow imputation of variants in unsequenced samples without resorting to complex statistical methods as in studies of outbred cohorts. We focus on an isolated population cohort from the Pacific Island of Kosrae, Micronesia, where we previously collected SNP array and rich phenotype data for the majority of the population. We report identification of long regions with haplotypes co-inherited between pairs of individuals and methodology to leverage such shared genetic content for imputation. Our estimates show that sequencing as few as 40 personal genomes allows for inference in up to 60% of the 3000-person cohort at the average locus. We ascertained a pilot data set of whole-genome sequences from seven Kosraean individuals, with average 5× coverage. This assay identified 5,735,306 unique sites of which 1,212,831 were previously unknown. Additionally, these variants are unusually enriched for alleles that are rare in other populations when compared to geographic neighbors (published Korean genome SJK). We used the presence of shared haplotypes between the seven Kosraen individuals to estimate expected imputation accuracy of known and novel homozygous variants at 99.6% and 97.3%, respectively. This study presents whole-genome analysis of a homogenous isolate population with emphasis on optimal rare variant inference.     

Predicting signatures of "synthetic associations" and "natural associations" from empirical patterns of human genetic variation

Genome-wide association studies (GWAS) have in recent years discovered thousands of associated markers for hundreds of phenotypes. However, associated loci often only explain a relatively small fraction of heritability and the link between association and causality has yet to be uncovered for most loci. Rare causal variants have been suggested as one scenario that may partially explain these shortcomings. Specifically, Dickson et al. recently reported simulations of rare causal variants that lead to association signals of common, tag single nucleotide polymorphisms, dubbed "synthetic associations". However, an open question is what practical implications synthetic associations have for GWAS. Here, we explore the signatures exhibited by such "synthetic associations" and their implications based on patterns of genetic variation observed in human populations, thus accounting for human evolutionary history -a force disregarded in previous simulation studies. This is made possible by human population genetic data from HapMap 3 consisting of both resequencing and array-based genotyping data for the same set of individuals from multiple populations. We report that synthetic associations tend to be further away from the underlying risk alleles compared to "natural associations" (i.e. associations due to underlying common causal variants), but to a much lesser extent than previously predicted, with both the age and the effect size of the risk allele playing a part in this phenomenon. We find that while a synthetic association has a lower probability of capturing causal variants within its linkage disequilibrium block, sequencing around the associated variant need not extend substantially to have a high probability of capturing at least one causal variant. We also show that the minor allele frequency of synthetic associations is lower than of natural associations for most, but not all, loci that we explored. Finally, we find the variance in associated allele frequency to be a potential indicator of synthetic associations.     

Allele and genotype frequencies of metabolic genes in Native Americans from Argentina and Paraguay

Interethnic differences in the allele frequencies of CYP2D6, NAT2, GSTM1 and GSTT1 deletions have been documented for Caucasians, Asians, and Africans population. On the other hand, data on Amerindians are scanty and limited to a few populations from southern areas of South America. In this report we analyze the frequencies of 11 allele variants of CYP2D6 and 4 allele variants of NAT2 genes, and the frequency of GSTM1 and GSTT1 homozygous deleted genotypes in a sample of 90 donors representing 8 Native American populations from Argentina and Paraguay, identified as Amerindians on the basis of their geographic location, genealogical data, mitochondrial- and Y-chromosome DNA markers. For CYP2D6, 88.6% of the total allele frequency corresponded to *1, *2, *4 and *10 variants. Average frequencies for NAT2 *4, *5, *6 and *7 alleles were 51.2%, 25%, 6.1%, and 20.1%, respectively. GSTM1 deletion ranged from 20% to 66%, while GSTT1 deletion was present in four populations in less than 50%. We assume that CYP2D6 *2, *4, *10, *14; NAT2 *5, *7 alleles and GSTM1 and GSTT1 *0/*0 genotypes are founder variants brought to America by the first Asian settlers.     

Satyrinae butterflies from Sardinia and Corsica show a kaleidoscopic intraspecific biogeography (Lepidoptera,Nymphlidae)

The Mediterranean islands of Sardinia and Corsica are known for their multitude of endemics. Butterflies in particular have received much attention. However, no comprehensive studies aiming to compare populations of butterflies from Sardinia and Corsica with those from the neighbouring mainland and Sicily have been carried out. In the present study, the eleven Satyrinae species inhabiting Sardinia and Corsica islands were examined and compared with continental and Sicilian populations by means of geometric morphometrics of male genitalia. Relative warp computation, discriminant analyses, hierarchical clustering, and cross‐validation tests were used to identify coherent distributional patterns including both islands and mainland populations. The eleven species showed multifaceted distributional patterns, although three main conclusions can be drawn: (1) populations from North Africa and Spain are generally different from those belonging to the Italian Peninsula; (2) populations from Sardinia and Sicily often resemble the North Africa/Spain ones; Corsica shows transitional populations similar to those from France; and (3) sea barriers represent filters to dispersal, although their efficacy appears to be unrelated to their extension. Indeed, the short sea straits between Sardinia and Corsica and between Sicily and the Italian Peninsula revealed a strong effectiveness with respect to preventing faunal exchanges; populations giving onto sea channels between Corsica and Northern Italy and between Sicily and Tunisia showed a higher similarity. A comparison of island and mainland distributions of the eleven taxa have helped to unravel the complex co‐occurrence of historical factors, refugial dynamics, and recent (post‐glacial) dispersal with respect to shaping the populations of Mediterranean island butterflies. © 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 100 , 195–212.     

Population Analysis of Large Copy Number Variants and Hotspots of Human Genetic Disease

Copy number variants (CNVs) contribute to human genetic and phenotypic diversity. However, the distribution of larger CNVs in the general population remains largely unexplored. We identify large variants in ~2500 individuals by using Illumina SNP data, with an emphasis on “hotspots” prone to recurrent mutations. We find variants larger than 500 kb in 5%–10% of individuals and variants greater than 1 Mb in 1%–2%. In contrast to previous studies, we find limited evidence for stratification of CNVs in geographically distinct human populations. Importantly, our sample size permits a robust distinction between truly rare and polymorphic but low-frequency copy number variation. We find that a significant fraction of individual CNVs larger than 100 kb are rare and that both gene density and size are strongly anticorrelated with allele frequency. Thus, although large CNVs commonly exist in normal individuals, which suggests that size alone can not be used as a predictor of pathogenicity, such variation is generally deleterious. Considering these observations, we combine our data with published CNVs from more than 12,000 individuals contrasting control and neurological disease collections. This analysis identifies known disease loci and highlights additional CNVs (e.g., 3q29, 16p12, and 15q25.2) for further investigation. This study provides one of the first analyses of large, rare (0.1%–1%) CNVs in the general population, with insights relevant to future analyses of genetic disease.     

Detecting rare variant associations by identity-by-descent mapping in case-control studies

Identity-by-descent (IBD) mapping tests whether cases share more segments of IBD around a putative causal variant than do controls. These segments of IBD can be accurately detected from genome-wide SNP data. We investigate the power of IBD mapping relative to that of SNP association testing for genome-wide case-control SNP data. Our focus is particularly on rare variants, as these tend to be more recent and hence more likely to have recent shared ancestry. We simulate data from both large and small populations and find that the relative performance of IBD mapping and SNP association testing depends on population demographic history and the strength of selection against causal variants. We also present an IBD mapping analysis of a type 1 diabetes data set. In those data we find that we can detect association only with the HLA region using IBD mapping. Overall, our results suggest that IBD mapping may have higher power than association analysis of SNP data when multiple rare causal variants are clustered within a gene. However, for outbred populations, very large sample sizes may be required for genome-wide significance unless the causal variants have strong effects.     

Microsatellite genetic distances between oceanic populations of the humpback whale (Megaptera novaeangliae)

Mitochondrial DNA haplotypes of humpback whales show strong segregation between oceanic populations and between feeding grounds within oceans, but this highly structured pattern does not exclude the possibility of extensive nuclear gene flow. Here we present allele frequency data for four microsatellite loci typed across samples from four major oceanic regions: the North Atlantic (two mitochondrially distinct populations), the North Pacific, and two widely separated Antarctic regions, East Australia and the Antarctic Peninsula. Allelic diversity is a little greater in the two Antarctic samples, probably indicating historically greater population sizes. Population subdivision was examined using a wide range of measures, including Fst, various alternative forms of Slatkin's Rst, Goldstein and colleagues' delta mu, and a Monte Carlo approximation to Fisher's exact test. The exact test revealed significant heterogeneity in all but one of the pairwise comparisons between geographically adjacent populations, including the comparison between the two North Atlantic populations, suggesting that gene flow between oceans is minimal and that dispersal patterns may sometimes be restricted even in the absence of obvious barriers, such as land masses, warm water belts, and antitropical migration behavior. The only comparison where heterogeneity was not detected was the one between the two Antarctic population samples. It is unclear whether failure to find a difference here reflects gene flow between the regions or merely lack of statistical power arising from the small size of the Antarctic Peninsula sample. Our comparison between measures of population subdivision revealed major discrepancies between methods, with little agreement about which populations were most and least separated. We suggest that unbiased Rst (URst, see Goodman 1995) is currently the most reliable statistic, probably because, unlike the other methods, it allows for unequal sample sizes. However, in view of the fact that these alternative measures often contradict one another, we urge caution in the use of microsatellite data to quantify genetic distance.      

Rare and Low Frequency Variant Stratification in the UK Population: Description and Impact on Association Tests

Although variations in allele frequencies at common SNPs have been extensively studied in different populations, little is known about the stratification of rare variants and its impact on association tests. In this paper, we used Affymetrix 500K genotype data from the WTCCC to investigate if variants in three different frequency categories (below 1%, between 1 and 5%, above 5%) show different stratification patterns in the UK population. We found that these patterns are indeed different. The top principal component extracted from the rare variant category shows poor correlations with any principal component or combination of principal components from the low frequency or common variant categories. These results could suggest that a suitable solution to avoid false positive association due to population stratification would involve adjusting for the respective PCs when testing for variants in different allele frequency categories. However, we found this was not the case both on type 2 diabetes data and on simulated data. Indeed, adjusting rare variant association tests on PCs derived from rare variants does no better to correct for population stratification than adjusting on PCs derived from more common variants. Mixed models perform slightly better for low frequency variants than PC based adjustments but less well for the rarest variants. These results call for the need of new methodological developments specifically devoted to address rare variant stratification issues in association tests.     

Using Lifetime Risk Estimates in Personal Genomic Profiles: Estimation of Uncertainty

Personal genome tests are now offered direct-to-consumer (DTC) via genetic variants identified by genome-wide association studies (GWAS) for common diseases. Tests report risk estimates (age-specific and lifetime) for various diseases based on genotypes at multiple loci. However, uncertainty surrounding such risk estimates has not been systematically investigated. With breast cancer as an example, we examined the combined effect of uncertainties in population incidence rates, genotype frequency, effect sizes, and models of joint effects among genetic variants on lifetime risk estimates. We performed simulations to estimate lifetime breast cancer risk for carriers and noncarriers of genetic variants. We derived population-based cancer incidence rates from Surveillance, Epidemiology, and End Results (SEER) Program and comparative international data. We used data for non-Hispanic white women from 2003 to 2005. We derived genotype frequencies and effect sizes from published GWAS and meta-analyses. For a single genetic variant in FGFR2 gene (rs2981582), combination of uncertainty in these parameters produced risk estimates where upper and lower 95% simulation intervals differed by more than 3-fold. Difference in population incidence rates was the largest contributor to variation in risk estimates. For a panel of five genetic variants, estimated lifetime risk of developing breast cancer before age 80 for a woman that carried all risk variants ranged from 6.1% to 21%, depending on assumptions of additive or multiplicative joint effects and breast cancer incidence rates. Epidemiologic parameters involved in computation of disease risk have substantial uncertainty, and cumulative uncertainty should be properly recognized. Reliance on point estimates alone could be seriously misleading.     

Molecular variation in endothelial nitric oxide synthase gene (eNOS) in western Mediterranean populations

Endothelial nitric oxide synthase (eNOS or NOS3) is the main responsible for nitric oxide (NO) production in vascular system and different polymorphisms have been identified in epidemiological studies. Trying to test the eNOS genetic variation in general populations we studied the 27-bp VNTR in intron 4 and G894T substitution in exon 7 markers in 6 Western Mediterranean populations (3 from Iberian Peninsula, 1 from North Africa, and 2 from Sardinia) and a sample from Ivory Coast. The VNTR frequencies in Western Mediterranean and Ivory Coast fit well into the ranges previously described for Europeans and Sub-Saharans respectively, and a typical African allele has been detected in polymorphic frequencies in the Berber sample. The G894T substitution presents the highest frequencies described for the T allele in the North Mediterranean populations. Linkage disequilibrium is present between both markers in all populations except in the Ivory Coast sample. The variation found for these polymorphisms indicates that they may be a useful tool for population studies even at microgeographical level.     

Genetic variation and population structure of the Japanese sika deer (Cervus nippon) in the Tohoku District based on mitochondrial D-loop sequences

The sika deer (Cervus nippon) once inhabited the entire Tohoku District, the northeastern part of the main island of Japan. Currently, they are isolated as three discontinuous populations on Mt. Goyo, the Oshika Peninsula, and Kinkazan Island. To assess the genetic diversity and relationships among the sika deer populations in the Tohoku District, we analyzed the mitochondrial DNA D-loop sequences from 177 individuals. We detected a total of five haplotypes. Three haplotypes were present in the population from Mt. Goyo at a haplotype diversity of 0.235 ± 0.061, two haplotypes in the population from the Oshika Peninsula at 0.171 ± 0.064, and only one haplotype was detected in the population from the Kinkazan Island. A significant genetic differentiation was observed among all population pairs. Collectively, our data supports the observed population bottlenecks in the past. Four of the five haplotypes were specific to one of the three populations, whereas only one haplotype was shared between the Mt. Goyo and the Oshika Peninsula populations. This common haplotype may indicate a common ancestral population in the Tohoku District. Conversely, the D-loop haplotypes were completely different among the Kinkazan Island and Oshika Peninsula populations. The lack of a shared haplotype indicates that female gene flow between the two populations is very limited and that the 0.6 km strait acts as a strong barrier.     

Interacting selection diversifies warning signals in a polytypic frog: an examination with the strawberry poison frog

Aposematic signals represent one of the most accessible traits to evaluate the interaction of natural and sexual selection on signal evolution. Here we investigate the contributions of these two selective forces on the aposematic signal evolution of the highly polytypic strawberry poison frog, Oophaga pumilio, of Bocas del Toro, Panama. Previous research has shown that the brightness of O. pumilio warning coloration can inform predators of the toxicity levels associated with different populations of the archipelago. Other studies suggest that sexual selection may be influencing warning signal brightness within populations via female mate choice (Isla Solarte, Isla Bastimentos, and Aquacate Peninsula populations) and male–male competition (Isla Solarte). Here we present two non-exclusive scenarios for how natural and sexual selection interact to drive phenotypic variation across this archipelago: (1) predators impose a selective regime whereby populations above a toxicity-brightness threshold are at liberty to diversify via sexual selection and below which populations are constrained to maintain a stricter resemblance to a more cryptic population mean, and (2) synergistic/additive effects of inter- and intrasexual selection drive the evolution of brighter males within populations above this toxicity threshold. We investigate whether aposematic patterns of divergence across the archipelago relative to the common mainland phenotype meet these predictions using existing data on O. pumilio morph toxicity measures and overall conspicuousness estimates to an avian predator. Using standardized z-scores to evaluate the range of trait values, we find that indeed the population representative of the common mainland phenotype (Almirante) represents an intermediate level of both toxicity and conspicuousness, and that derived Bocas del Toro populations vary in each of those components in directions predicted by the proposed scenarios. Furthermore, we find greater divergence towards conspicuousness than crypsis, a pattern suggestive of sexual and natural selection acting synergistically in morphs with high toxicity.     

A Comparison of Y-Chromosome Variation in Sardinia and Anatolia Is More Consistent with Cultural Rather than Demic Diffusion of Agriculture

Two alternative models have been proposed to explain the spread of agriculture in Europe during the Neolithic period. The demic diffusion model postulates the spreading of farmers from the Middle East along a Southeast to Northeast axis. Conversely, the cultural diffusion model assumes transmission of agricultural techniques without substantial movements of people. Support for the demic model derives largely from the observation of frequency gradients among some genetic variants, in particular haplogroups defined by single nucleotide polymorphisms (SNPs) in the Y-chromosome. A recent network analysis of the R-M269 Y chromosome lineage has purportedly corroborated Neolithic expansion from Anatolia, the site of diffusion of agriculture. However, the data are still controversial and the analyses so far performed are prone to a number of biases. In the present study we show that the addition of a single marker, DYSA7.2, dramatically changes the shape of the R-M269 network into a topology showing a clear Western-Eastern dichotomy not consistent with a radial diffusion of people from the Middle East. We have also assessed other Y-chromosome haplogroups proposed to be markers of the Neolithic diffusion of farmers and compared their intra-lineage variation—defined by short tandem repeats (STRs)—in Anatolia and in Sardinia, the only Western population where these lineages are present at appreciable frequencies and where there is substantial archaeological and genetic evidence of pre-Neolithic human occupation. The data indicate that Sardinia does not contain a subset of the variability present in Anatolia and that the shared variability between these populations is best explained by an earlier, pre-Neolithic dispersal of haplogroups from a common ancestral gene pool. Overall, these results are consistent with the cultural diffusion and do not support the demic model of agriculture diffusion.     

Effective population size and evolutionary dynamics in outbred laboratory populations of Drosophila

Census population size, sex-ratio and female reproductive success were monitored in 10 laboratory populations of Drosophila melanogaster selected for different ages of reproduction. With this demographic information, we estimated eigenvalue, variance and probability of allele loss effective population sizes. We conclude that estimates of effective size based on gene-frequency change at a few loci are biased downwards. We analysed the relative roles of selection and genetic drift in maintaining genetic variation in laboratory populations of Drosophila. We suggest that rare, favourable genetic variants in our laboratory populations have a high chance of being lost if their fitness effect is weak, e.g. 1% or less. However, if the fitness effect of this variation is 10% or greater, these rare variants are likely to increase to high frequency. The demographic information developed in this study suggests that some of our laboratory populations harbour more genetic variation than expected. One explanation for this finding is that part of the genetic variation in these outbred laboratory Drosophila populations may be maintained by some form of balancing selection. We suggest that, unlike bacteria, medium-term adaptation of laboratory populations of fruit flies is not primarily driven by new mutations, but rather by changes in the frequency of preexisting alleles.     

Genetic data on Alghero population (Sardinia): Contrast between biological and cultural evidence

Data on 20 genetic polymorphisms (61 alleles) in the Algehero population on the northwestern coast of Sardinia are presented and discussed in relation to its linguistic peculiarity inside the island. Since the Aragonese (Spain) conquest of Sardinia in the 13th century, the Catalan language, the same as that spoken in Northeastern Spain and certain districts of Southern France, has been used in Alghero even until today. Analysis for heterogeneity of gene frequency distributions indicates that the genetic information obtained on Alghero is adequate to discriminate Sardinians from other neighbouring populations. Genetic variation between populations measured through genetic distances and principal-component analysis shows that the present-day population of Alghero is much closer genetically to Sardinians than to Catalonians. Our genetic results do not support any interpretation of the linguistic affinities between Alghero and Catalonia at present as indicative of biological kinship. © 1994 Wiley-Liss, Inc.     

Contrasting phylogeographical patterns for springtails reflect different evolutionary histories between the Antarctic Peninsula and continental Antarctica

Aim  We examined the genetic structure among populations and regions for the springtails Cryptopygus antarcticus antarcticus and Gomphiocephalus hodgsoni (Collembola) to identify potential historical refugia and subsequent colonization routes, and to examine population growth/expansion and relative ages of population divergence.
Location  Antarctic Peninsula for C. a. antarcticus ; Antarctic continent (southern Victoria Land) for G. hodgsoni .
Methods  Samples were collected from 24 and 28 locations across the Antarctic Peninsula and southern Victoria Land regions for C. a. antarcticus and G. hodgsoni , respectively. We used population genetic, demographic and nested clade analyses based on mitochondrial DNA (cytochrome c oxidase subunit I and subunit II).
Results  Both species were found to have population structures compatible with the presence of historical glacial refugia on Pleistocene (2 Ma–present) time-scales, followed by post-glacial expansion generating contemporary geographically isolated populations. However, G. hodgsoni populations were characterized by a fragmented pattern with several 'phylogroups' (likely ancestral haplotypes present in high frequency) retaining strong ancestral linkages among present-day populations. Conversely, C. a. antarcticus had an excess of rare haplotypes with a much reduced volume of ancestral lineages, possibly indicating historical founder/bottleneck events and widespread expansion.
Main conclusions  We infer that these differences reflect distinct evolutionary histories in each locality despite the resident species having similar life-history characteristics. We suggest that this has predominantly been influenced by variation in the success of colonization events as a result of intrinsic historical glaciological differences between the Antarctic Peninsula and continental Antarctic environments.     

Genetic estimates of contemporary effective population size: what can they tell us about the importance of genetic stochasticity for wild population persistence?

Genetic stochasticity due to small population size contributes to population extinction, especially when population fragmentation disrupts gene flow. Estimates of effective population size ( N _e) can therefore be informative about population persistence, but there is a need for an assessment of their consistency and informative relevance. Here we review the body of empirical estimates of N _e for wild populations obtained with the temporal genetic method and published since Frankham's (1995 ) review. Theoretical considerations have identified important sources of bias for this analytical approach, and we use empirical data to investigate the extent of these biases. We find that particularly model selection and sampling require more attention in future studies.
We report a median unbiased N _e estimate of 260 (among 83 studies) and find that this median estimate tends to be smaller for populations of conservation concern, which may therefore be more sensitive to genetic stochasticity. Furthermore, we report a median N _e/ N ratio of 0.14, and find that this ratio may actually be higher for small populations, suggesting changes in biological interactions at low population abundances. We confirm the role of gene flow in countering genetic stochasticity by finding that N _e correlates strongest with neutral genetic metrics when populations can be considered isolated. This underlines the importance of gene flow for the estimation of N _e, and of population connectivity for conservation in general. Reductions in contemporary gene flow due to ongoing habitat fragmentation will likely increase the prevalence of genetic stochasticity, which should therefore remain a focal point in the conservation of biodiversity.     

HAPLOFREQ--estimating haplotype frequencies efficiently.

A commonly used tool in disease association studies is the search for discrepancies between the haplotype distribution in the case and control populations. In order to find this discrepancy, the haplotypes frequency in each of the populations is estimated from the genotypes. We present a new method HAPLOFREQ to estimate haplotype frequencies over a short genomic region given the genotypes or haplotypes with missing data or sequencing errors. Our approach incorporates a maximum likelihood model based on a simple random generative model which assumes that the genotypes are independently sampled from the population. We first show that if the phased haplotypes are given, possibly with missing data, we can estimate the frequency of the haplotypes in the population by finding the global optimum of the likelihood function in polynomial time. If the haplotypes are not phased, finding the maximum value of the likelihood function is NP-hard. In this case, we define an alternative likelihood function which can be thought of as a relaxed likelihood function. We show that the maximum relaxed likelihood can be found in polynomial time and that the optimal solution of the relaxed likelihood approaches asymptotically to the haplotype frequencies in the population. In contrast to previous approaches, our algorithms are guaranteed to converge in polynomial time to a global maximum of the different likelihood functions. We compared the performance of our algorithm to the widely used program PHASE, and we found that our estimates are at least 10% more accurate than PHASE and about ten times faster than PHASE. Our techniques involve new algorithms in convex optimization. These algorithms may be of independent interest. Particularly, they may be helpful in other maximum likelihood problems arising from survey sampling.