Thousands Of Alleles Research Articles

A gene with a thousand alleles: The hyper-variable effectors of plant-parasitic nematodes

Pathogens are engaged in a fierce evolutionary arms race with their host. The genes at the forefront of the engagement between kingdoms are often part of diverse and highly mutable gene families. Even in this context, we discovered unprecedented variation in the hyper-variable (HYP) effectors of plant-parasitic nematodes. HYP effectors are single-gene loci that potentially harbor thousands of alleles. Alleles vary in the organization, as well as the number, of motifs within a central hyper-variable domain (HVD). We dramatically expand the HYP repertoire of two plant-parasitic nematodes and define distinct species-specific "rules" underlying the apparently flawless genetic rearrangements. Finally, by analyzing the HYPs in 68 individual nematodes, we unexpectedly found that despite the huge number of alleles, most individuals are germline homozygous. These data support a mechanism of programmed genetic variation, termed HVD editing, where alterations are locus specific, strictly governed by rules, and theoretically produce thousands of variants without errors.

Structural architecture and brain network efficiency link polygenic scores to intelligence.

Intelligence is highly heritable. Genome-wide association studies (GWAS) have shown that thousands of alleles contribute to variation in intelligence with small effect sizes. Polygenic scores (PGS), which combine these effects into one genetic summary measure, are increasingly used to investigate polygenic effects in independent samples. Whereas PGS explain a considerable amount of variance in intelligence, it is largely unknown how brain structure and function mediate this relationship. Here, we show that individuals with higher PGS for educational attainment and intelligence had higher scores on cognitive tests, larger surface area, and more efficient fiber connectivity derived by graph theory. Fiber network efficiency as well as the surface of brain areas partly located in parieto-frontal regions were found to mediate the relationship between PGS and cognitive performance. These findings are a crucial step forward in decoding the neurogenetic underpinnings of intelligence, as they identify specific regional networks that link polygenic predisposition to intelligence.

Many loci make light work: High individual diversity despite low population diversity and random mating at class I MHC in a Critically Endangered island songbird.

Multi-cellular organisms are under constant attack from parasites, making immune defence a critical aspect of fitness. In vertebrate animals, genes of the major histocompatibility complex (MHC) determine the breadth of pathogens to which individuals can respond. Having many MHC alleles can confer better protection against infectious disease, and balancing selection at MHC is widespread. Indeed, MHC loci are famously variable, with some populations harbouring thousands of alleles (Biedrzycka et al., 2018; Robinson, Soormally, Hayhurst, & Marsh, 2016). MHC has also long fascinated behavioural ecologists because mate choice-for example, preferring MHC-dissimilar partners-may amplify the effects of natural selection (Penn & Potts, 1999). But despite keen interest in the evolutionary ecology of MHC, extensive duplication (Minias, Pikus, Whittingham, & Dunn, 2019) has made these genes challenging to study. In a From the Cover article in this issue of Molecular Ecology, Stervander, Dierickx, Thorley, Brooke, and Westerdahl (2020) characterizes class I MHC in a Critically Endangered songbird, relating genotype to mate choice and survivorship. By inferring copy number and patterns of allelic co-segregation, the authors pave the way to elucidating the genomic architecture of MHC in this bottlenecked population. These insights help reconcile apparently counterintuitive findings: no effect of MHC genotype on mate choice or survival, and high MHC diversity within individuals despite low diversity at the population level. The latter finding is cause for optimism regarding conservation prospects. Moreover, these results suggest that ancient duplication events can have longstanding effects on the adaptive landscapes of natural and sexual selection.

Autism-associated missense genetic variants impact locomotion and neurodevelopment in Caenorhabditis elegans.

Autism spectrum disorder (ASD) involves thousands of alleles in over 850 genes, but the current functional inference tools are not sufficient to predict phenotypic changes. As a result, the causal relationship of most of these genetic variants in the pathogenesis of ASD has not yet been demonstrated and an experimental method prioritizing missense alleles for further intensive analysis is crucial. For this purpose, we have designed a pipeline that uses Caenorhabditis elegans as a genetic model to screen for phenotype-changing missense alleles inferred from human ASD studies. We identified highly conserved human ASD-associated missense variants in their C. elegans orthologs, used a CRISPR/Cas9-mediated homology-directed knock-in strategy to generate missense mutants and analyzed their impact on behaviors and development via several broad-spectrum assays. All tested missense alleles were predicted to perturb protein function, but we found only 70% of them showed detectable phenotypic changes in morphology, locomotion or fecundity. Our findings indicate that certain missense variants in the C. elegans orthologs of human CACNA1D, CHD7, CHD8, CUL3, DLG4, GLRA2, NAA15, PTEN, SYNGAP1 and TPH2 impact neurodevelopment and movement functions, elevating these genes as candidates for future study into ASD. Our approach will help prioritize functionally important missense variants for detailed studies in vertebrate models and human cells.

Privacy-Preserving Search of Similar Patients in Genomic Data

Abstract The growing availability of genomic data holds great promise for advancing medicine and research, but unlocking its full potential requires adequate methods for protecting the privacy of individuals whose genome data we use. One example of this tension is running Similar Patient Query on remote genomic data: In this setting a doctor that holds the genome of his/her patient may try to find other individuals with “close” genomic data, and use the data of these individuals to help diagnose and find effective treatment for that patient’s conditions. This is clearly a desirable mode of operation. However, the privacy exposure implications are considerable, and so we would like to carry out the above “closeness” computation in a privacy preserving manner. In this work we put forward a new approach for highly efficient secure computation for computing an approximation of the Similar Patient Query problem. We present contributions on two fronts. First, an approximation method that is designed with the goal of achieving efficient private computation. Second, further optimizations of the two-party protocol. Our tests indicate that the approximation method works well, it returns the exact closest records in 98% of the queries and very good approximation otherwise. As for speed, our protocol implementation takes just a few seconds to run on databases with thousands of records, each of length thousands of alleles, and it scales almost linearly with both the database size and the length of the sequences in it. As an example, in the datasets of the recent iDASH competition, after a one-time preprocessing of around 12 seconds, it takes around a second to find the nearest five records to a query, in a size-500 dataset of length- 3500 sequences. This is 2-3 orders of magnitude faster than using state-of-the-art secure protocols with existing edit distance algorithms.

The Nature of Nurture: Using a Virtual-Parent Design to Test Parenting Effects on Children's Educational Attainment in Genotyped Families.

Research on environmental and genetic pathways to complex traits such as educational attainment (EA) is confounded by uncertainty over whether correlations reflect effects of transmitted parental genes, causal family environments, or some, possibly interactive, mixture of both. Thus, an aggregate of thousands of alleles associated with EA (a polygenic risk score; PRS) may tap parental behaviors and home environments promoting EA in the offspring. New methods for unpicking and determining these causal pathways are required. Here, we utilize the fact that parents pass, at random, 50% of their genome to a given offspring to create independent scores for the transmitted alleles (conventional EA PRS) and a parental score based on alleles not transmitted to the offspring (EA VP_PRS). The formal effect of non-transmitted alleles on offspring attainment was tested in 2,333 genotyped twins for whom high-quality measures of EA, assessed at age 17 years, were available, and whose parents were also genotyped. Four key findings were observed. First, the EA PRS and EA VP_PRS were empirically independent, validating the virtual-parent design. Second, in this family-based design, children's own EA PRS significantly predicted their EA (β = 0.15), ruling out stratification confounds as a cause of the association of attainment with the EA PRS. Third, parental EA PRS predicted the SES environment parents provided to offspring (β = 0.20), and parental SES and offspring EA were significantly associated (β = 0.33). This would suggest that the EA PRS is at least as strongly linked to social competence as it is to EA, leading to higher attained SES in parents and, therefore, a higher experienced SES for children. In a full structural equation model taking account of family genetic relatedness across multiple siblings the non-transmitted allele effects were estimated at similar values; but, in this more complex model, confidence intervals included zero. A test using the forthcoming EA3 PRS may clarify this outcome. The virtual-parent method may be applied to clarify causality in other phenotypes where observational evidence suggests parenting may moderate expression of other outcomes, for instance in psychiatry.

Pathway-wide association study identifies five shared pathways associated with schizophrenia in three ancestral distinct populations

Genome-wide association studies have confirmed the polygenic nature of schizophrenia and suggest that there are hundreds or thousands of alleles associated with increased liability for the disorder. However, the generalizability of any one allelic marker of liability is remarkably low and has bred the notion that schizophrenia may be better conceptualized as a pathway(s) disorder. Here, we empirically tested this notion by conducting a pathway-wide association study (PWAS) encompassing 255 experimentally validated Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways among 5033 individuals diagnosed with schizophrenia and 5332 unrelated healthy controls across three distinct ethnic populations; European-American (EA), African-American (AA) and Han Chinese (CH). We identified 103, 74 and 87 pathways associated with schizophrenia liability in the EA, CH and AA populations, respectively. About half of these pathways were uniquely associated with schizophrenia liability in each of the three populations. Five pathways (serotonergic synapse, ubiquitin mediated proteolysis, hedgehog signaling, adipocytokine signaling and renin secretion) were shared across all three populations and the single-nucleotide polymorphism sets representing these five pathways were enriched for single-nucleotide polymorphisms with regulatory function. Our findings provide empirical support for schizophrenia as a pathway disorder and suggest schizophrenia is not only a polygenic but likely also a poly-pathway disorder characterized by both genetic and pathway heterogeneity.

A GWAS of 170,000 Individuals Identifies Thousands of Alleles Perturbing Blood Cell Traits, Many of Which Are in Super Enhancers Setting Cell Identity

Adults release ~1011 blood cells into circulation every day. These cells derive, by clonal expansion, from a minuscule population of hematopoietic stem cells (HSCs), which differentiate into mature cells through progressively fate-restricted progenitor cells. In order to identify the genetic loci controlling these processes, we performed a hypothesis-free genome-wide association study (GWAS) of complete blood count data measured on 170,000 subjects in the UK Biobank and INTERVAL cohorts. This identified almost 3,000 causally distinct variants (hits) modulating hematopoiesis or blood cell clearance, including several hundred low frequency variants (minor allele frequencies <5%) with very large effect sizes.Over three quarters of the GWAS hits have no coding consequence and analysis of the 700 platelet hits showed a striking enrichment in the DNAse-I hypersensitivity sites of HSC-derived megakaryocytes (MKs) compared to those of HSC-derived erythroblasts (EBs), suggesting that a substantial proportions of blood trait heritability can be explained by variants modulating cell type specific genetic regulators.To understand the nature of gene regulation in the erythroid-megakaryocytic lineage we firstly used long-range chromosomal interaction data (from genome-wide promoter-capture chromosome conformation assays) and found that the platelet trait hits are enriched in regulatory elements that interact with a gene promoter in MKs. We then scanned the genome for super-enhancers (SEs) (regions characterized by a high density of enhancer elements and a strong H3K27ac histone modification). We identified 1067 SEs in MKs and 1294 SEs in EBs, with an overlap count of 400. Platelet GWAS hits were strongly enriched in MK SEs over MK typical enhancers (TEs) relative to red cell hits and were frequently localised in SEs specific to MKs. Finally, we found that SE (but not TE) MK-interacting genes are significantly enriched for gene-ontology (GO) terms for megakaryopoiesis, platelet function and hemostasis, supporting the notion that SEs play a major role in the determination of cell identity.To corroborate this, we focused on the second (SE2) of three SEs for the CD9-VWF gene cluster, which contained the GWAS hit rs2363877. We recalled 100 individuals by genotype at rs2363877 and found that the minor allele was associated with decreased expression of CD9 and increased expression of VWF in platelets. By flowing blood over collagen and a VWF-binding collagen-mimetic we showed this allele has a significant effect on the extent of ex-vivo thrombus formation. Finally, using CRISPR/Cas9 we eliminated SE2 from IPSC derived MKs and showed an increase in VWF expression.In summary, recently generated epigenetic and long-range chromosomal interaction data suggest that a significant fraction of platelet GWAS hits perturb super-enhancer activity in MKs with downstream effect on networks of genes. In the light of this the maxim that 'a GWAS hit acts through a single gene' cannot be sustained. DisclosuresNo relevant conflicts of interest to declare.

Abstract 5572: Tracking the functional analysis of cancer risk variants

Abstract Genome-wide association studies (GWAS) have identified thousands of alleles associated with cancer risk, but understanding the functional effects of these variants has proceeded more slowly. In addition, although catalogs of variants exist, tracking progress to determine variant function is challenging. We conducted a literature search and review to assess the trajectory of functional characterization of GWAS results and describe the types of analysis conducted and tools and databases used. We used the PubTator Web-based tool, which uses advanced text-mining techniques to accelerate manual literature curation, to search the literature for articles describing functional annotation of cancer GWAS hits. We generated a list of 646 unique SNPs from the Cancer Genomics and Epidemiology Navigator (CGEN) and imported the list to PubTator. We identified a total of 292 articles that included both variant discovery by GWAS and functional analysis, and reviewed the articles for information including cancer type, variant functional class (e.g., intron, exon, intergenic, etc.), and type of functional analysis conducted. These articles included 40 different cancer types or subtypes. The majority of cancer risk variants were intronic or intergenic, with only a small number located in coding regions. Most of the functional analyses were focused on the potential modification/disruption of regulatory processes by the risk allele (e.g., alteration of transcription factor binding sites, putative expressed quantitative trait loci), in line with current hypotheses regarding cancer risk variant function. Most studies also described effects of variants at the molecular, or cellular, rather than organismal level. We also reviewed the literature pertaining to variants identified for three cancers with possible pleiotropy - ovarian, breast, and prostate - to understand the trajectory of functional analyses beyond the initial discovery of the variants. We describe our use of the PubTator tool and provide a literature-based overview of progress in understanding the function of cancer risk variants identified via GWAS. Citation Format: Sharna Tingle, Danielle Carrick, Sheri Schully, Mindy Clyne, Stefanie A. Nelson. Tracking the functional analysis of cancer risk variants. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5572. doi:10.1158/1538-7445.AM2015-5572

High Resolution HLA Typing by Next Generation Exome Sequencing

AbstractAbstract 4166 BackgroundHigh resolution typing of HLA-A, B, C, DQB1 and DRB1 at the allelic level allows transplantation of hematopoietic progenitor cells (HPC) from matched allogeneic donors. The extent of matching has been recognized as one of the most important predictors of survival. High resolution typing relies on Sanger sequence-based typing (SBT) and PCR with sequence-specific primers (SSP), both of which detect nucleotide changes in exons that alter the HLA antigens. Next generation exome sequencing (NGES) offers the potential for rapid and less expensive HLA typing for transplantation of matched allogeneic HPC, but the role of NGES for high resolution HLA typing has not been examined. In this study, we designed a bioinformatic pipeline to account for the hundreds to thousands of alleles at each HLA locus in the population, and used it to explore the possibility of high resolution HLA typing using NGES data. MethodsIndexed sequencing libraries were constructed from 3 HapMap samples (NA19129, NA18507, and NA19240), target enriched with SureSelect Human All Exon V3 kit (Agilent Technologies), and sequenced in multiplex as paired-end 2×101 bp reads on an Illumina HiSeq2000. The above process was repeated for NA19240 to assure reproducibility. The NGES-based HLA typing consisted of 3 major steps: 1) Filtering reads: cDNA and genomic sequences of all alleles of each HLA locus [ImMunoGeneTics project (IMGT)/HLA database] were concatenated to form five references, to which input reads were aligned using NovoalignMPI V.2.07.07 with standard options and no more than 1 mismatch per read. 2) Eliminating unsupported alleles: Curated alignment of all alleles of each HLA locus was obtained from IMGT/HLA database. Each polymorphic position was termed a D position. K-mers (a DNA sequence with length k), each containing a D position, was searched against the reads from step 1. Alleles were credited or penalized based on presence or absence of their k-mers in the reads. Alleles with negative overall scores were eliminated and this step was repeated until no elimination occurred. 3) Ranking allele pairs: all possible pairs of candidate alleles from step 2 were evaluated; a pair was credited at each D position if k-mers of both alleles were supported by the reads or penalized if otherwise. The allele pair (or pairs if a tie) ranked at the top was the presumed type of the locus examined. The NGES-based high resolution typing was run on a computing node (IBM x3650-m2). The results were compared with the results of conventional typing (SBT and SSP), followed by examination of the disagreement between the methods and adjustment of k. ResultsThe conventional high resolution typing results comprised 15 pairs of alleles that were uniquely different (one pair of alleles at each locus of HLA-A, B, C, DQB1 and DRB1 for 3 samples). The method was established using the information on HLA-A alleles of NA19129, leaving 14 pairs of alleles for validation. Initial NGES-based typing indicated that the specificity of the method was dependent on k-mer length, with increased length required to eliminate interference from mimicking reads (e.g. mimics of an HLA-C allele). Thus, with a k-mer length of 50 bp, NGES-based typing correctly determined 12 of 14 pairs of alleles, while with k-mer lengths of 60 or 65 bp, it correctly determined 14 of 14 pairs of alleles. All 5 pairs of alleles of NA19240 were also correctly determined with the longer k-mers using reads from the replicate sequencing. After read filtering, the typing took approximately 5 minutes per sample. ConclusionIn this first proof-of-concept study, high resolution HLA typing was successfully performed using NGES data. With k-mer lengths of 60 or 65 bp, NGES-based typing correctly identified 100% of tested allele pairs, and demonstrated a similar level of resolution and accuracy as conventional high resolution typing.Note: C.L. and X.Y. contributed equally to this work. Disclosures:No relevant conflicts of interest to declare.

HLA DNA typing: past, present, and future

The human leukocyte antigen (HLA) class I and class II loci are the most polymorphic genes in the human genome, with a highly clustered and patchwork pattern of sequence motifs. In the three decades since the first HLA gene was isolated by molecular cloning (a cDNA clone of HLA-B7), thousands of alleles have been identified and the names and sequences of all known alleles have been curated in the IMGT/HLA database. This extensive allelic diversity made and continues to make high-resolution HLA DNA typing very challenging. The first attempt at HLA DNA typing involved restriction fragment length polymorphism (RFLP) analysis, but this approach had many limitations. The development of PCR in 1985 allowed for the amplification of the polymorphic exons of the HLA class I and class II genes and the analysis of the polymorphic sequence motifs with sequence-specific oligonucleotide (SSO) hybridization probes. The immobilization of these probes on membranes and later on beads, along with primer sets for sequence-specific priming (SSP), gave rise to the current set of HLA typing reagents. Sanger sequencing has provided high-resolution typing but, in many cases, genotyping 'ambiguity' remains an issue. In the past few years, the introduction of next-generation sequencing, with the critical properties of massively parallel and clonal sequencing, has significantly reduced HLA genotyping ambiguity. Here, our lab's efforts to develop high-resolution and high-throughput HLA DNA typing using the 454 Sequencing System are reviewed, and the potential future developments and applications of HLA DNA typing are discussed.

What can we learn about the distribution of fitness effects of new mutations from DNA sequence data?

We investigate several questions concerning the inference of the distribution of fitness effects (DFE) of new mutations from the distribution of nucleotide frequencies in a population sample. If a fixed sequencing effort is available, we find that the optimum strategy is to sequence a modest number of alleles (approx. 10). If full genome information is available, the accuracy of parameter estimates increases as the number of alleles sequenced increases, but with diminishing returns. It is unlikely that the DFE for single genes can be reliably estimated in organisms such as humans and Drosophila, unless genes are very large and we sequence hundreds or perhaps thousands of alleles. We consider models involving several discrete classes of mutations in which the selection strength and density apportioned to each class can vary. Models with three classes fit almost as well as four class models unless many hundreds of alleles are sequenced. Large numbers of alleles need to be sequenced to accurately estimate the distribution's mean and variance. Estimating complex DFEs may therefore be difficult. Finally, we examine models involving slightly advantageous mutations. We show that the distribution of the absolute strength of selection is well estimated if mutations are assumed to be unconditionally deleterious.

Update to Terwilliger and Göring's "Gene Mapping in the 20th and 21st Centuries" (2000): Gene Mapping When Rare Variants Are Common and Common Variants Are Rare

Update to Terwilliger and Göring's "Gene Mapping in the 20th and 21st Centuries" (2000):Gene Mapping When Rare Variants Are Common and Common Variants Are Rare Joseph D. Terwilliger and Harald H. H. Göring Keywords Gene Mapping, Common Variant/Common Disease (CVCD) Hypothesis, Complex Disease Genetics, Study Design Our Lasker Prize winning article from 2000 was a discussion of the myriad factors that influence the success or failure of gene mapping studies, and in it we suggested that the reasons we geneticists have had so little success in unraveling the etiology of complex traits had more to do with biology than technology and that many of the decisions about future strategies were being made based on unrealistic and untested assumptions. At the time, the common variant/common disease (CVCD) hypothesis (Reich and Lander 2001) was widely believed to provide a plausible model for complex disease genetics, in which common alleles [defined at the time as greater than 0.10 MAF (minor allele frequency)] with high attributable fractions, such as APOE4 and Alzheimer disease, would dominate trait etiology (Fallin et al. 2001; Pennisi 1998). As argued by Risch and Merikangas (1996: 1516), "Despite the small effects of such genes, the magnitude of their attributable risk may be large because they are quite frequent in the population, making them of public health significance." The discussions at the time proposed that such alleles should be ubiquitous across world populations, predating the expansion of human populations out of Africa (Goldstein and Weale 2001; Lander 1996). We argued that this was inconsistent with what we know about the nature of the evolution of genetic variation (Terwilliger 2001; Terwilliger and Weiss 1998; Weiss and Terwilliger 2000) and "that a larger number of less common alleles is likely to be involved in the etiology of complex disease" (Terwilliger and Göring 2000: 122) with individually trivial attributable fractions. At the time, we were accused of being naysayers and extremists for suggesting that genome-wide association studies would not be uncovering APOE-like effects for schizophrenia and most other complex traits (Brookes 1999; Emahazion et al. 2001; Pennisi 1998). Leading proponents of the CVCD hypothesis predicted in 1998 that "it would be surprising if most of the major genetic factors involved in human disease were not defined over the next 5–10 years" (Bell 1998: 618) and that "the widespread redefinition [End Page 729] of disease through genetics will be accompanied by the use of genetics for prediction and diagnosis and to optimize treatment in most common diseases. This is likely to occur within the next decade" (Bell 1998: 620). Ten years and billions of taxpayer dollars later, our once "extreme" position has replaced the mainstream opinion of a decade ago, as the recent flood of empirical data from genome-wide association studies consistently yields results that are inconsistent with the CVCD hypothesis and rosy scenarios about personalized medicine. In recent months, papers have been trumpeting the success of genome-wide association studies in finding new rare (i.e., p < 0.1) variants with individually minuscule attributable risks, forcing investigators to admit that their results effectively prove that there must be hundreds or thousands of alleles of small effect influencing schizophrenia and bipolar disorder (Purcell et al. 2009), height (Aulchenko et al. 2009), hypertension (Levy et al. 2009), type 2 diabetes (Zeggini et al. 2007), and virtually every other complex trait examined. Perhaps the only common variant of high attributable fraction that has proven to be a useful predictor of disease in the past decade is the lactase-persistence allele identified through family studies in Finland (Enattah et al. 2002), and the allelic simplicity of this locus has more to do with the fact that the new mutation added a useful function—ability to digest lactose in adulthood—rather than making a gene work less efficiently, as most random mutations tend to do. Even the most trumpeted "success stories" in genome-wide association studies, such as Crohn's disease (Barrett et al. 2008), end up implicating tens of specific rare variants, which put together explain only a few percent of the overall genetic contribution to the disease, putting the promised personalized medicine and "gene-chip...

A Nonparametric Test Reveals Selection for Rapid Flowering in the Arabidopsis Genome

The detection of footprints of natural selection in genetic polymorphism data is fundamental to understanding the genetic basis of adaptation, and has important implications for human health. The standard approach has been to reject neutrality in favor of selection if the pattern of variation at a candidate locus was significantly different from the predictions of the standard neutral model. The problem is that the standard neutral model assumes more than just neutrality, and it is almost always possible to explain the data using an alternative neutral model with more complex demography. Today's wealth of genomic polymorphism data, however, makes it possible to dispense with models altogether by simply comparing the pattern observed at a candidate locus to the genomic pattern, and rejecting neutrality if the pattern is extreme. Here, we utilize this approach on a truly genomic scale, comparing a candidate locus to thousands of alleles throughout the Arabidopsis thaliana genome. We demonstrate that selection has acted to increase the frequency of early-flowering alleles at the vernalization requirement locus FRIGIDA. Selection seems to have occurred during the last several thousand years, possibly in response to the spread of agriculture. We introduce a novel test statistic based on haplotype sharing that embraces the problem of population structure, and so should be widely applicable.

Numbers and distribution of individuals and mating type alleles in populations of Coriolus versicolor

SUMMARYA natural population of the tetrapolar fungus Coriolus versicolor (L. ex Fr.) Quel, in a small woodland was observed over 3 years. Dikaryotic members of the population were identified using intraspecific antagonism and mating type markers. Records were kept of the distribution, longevity and fruiting behaviour of 44 individuals. Zone lines between individuals were found to remain constant in position throughout the study, but rates of decay and fruiting times varied between dikaryons and did not seem related to resource size. Detailed maps of the genetic structure of the populations in two stumps are presented. In general the results indicated thousands of alleles at both mating type loci. Repeated occurrences of alleles were very rare, when the data were interpreted rigorously in terms of the probable origins of the nuclei found in individuals. This approach was also applied critically to some published data. Comparisons were made between alleles found in local and more widely gathered samples, and led to estimation of worldwide frequencies but it is concluded that such exercises are of limited value.