Clonal Proportions Research Articles

TLsub: A transfer learning based enhancement to accurately detect mutations with wide-spectrum sub-clonal proportion.

Mutation detecting is a routine work for sequencing data analysis and the trading of existing tools often involves the combinations of signals on a set of overlapped sequencing reads. However, the subclonal mutations, which are reported to contribute to tumor recurrence and metastasis, are sometimes eliminated by existing signals. When the clonal proportion decreases, signals often present ambiguous, while complicated interactions among signals break the IID assumption for most of the machine learning models. Although the mutation callers could lower the thresholds, false positives are significantly introduced. The main aim here was to detect the subclonal mutations with high specificity from the scenario of ambiguous sample purities or clonal proportions. We proposed a novel machine learning approach for filtering false positive calls to accurately detect mutations with wide spectrum subclonal proportion. We have carried out a series of experiments on both simulated and real datasets, and compared to several state-of-art approaches, including freebayes, MuTect2, Sentieon and SiNVICT. The results demonstrated that the proposed method adapts well to different diluted sequencing signals and can significantly reduce the false positive when detecting subclonal mutations. The codes have been uploaded at https://github.com/TrinaZ/TL-fpFilter for academic usage only.

Clonal Evolution of Cutaneous T Cell Lymphoma Revealed at Single Cell Resolution

Background: Patients with Cutaneous T Cell Lymphoma (CTCL) subtypes Mycosis Fungoides and Sézary Syndrome (MF/SS) who progress to advanced stage disease have a 20% 5-year overall survival rate. Current treatments for CTCL range from localized therapies for skin lesions to systemic treatments, including histone deacetylase inhibitors, chemotherapy, and immunotherapy. While many treatments are initially effective, patients often develop resistance to ongoing treatment. Though recent studies have comprehensively profiled the genomic landscape of CTCL, no clear driver mutation has been identified and the molecular factors that drive MF/SS progression remain undefined. To address these outstanding questions, we collected longitudinal tumor and normal samples from 10 MF/SS patients and subjected them to high resolution genome and transcriptome analyses (exome, whole genome and single-cell RNA sequencing, eWGS and scRNAseq) to define the clonal evolution and temporal progression of CTCL. Methods: We collected 52 serial tumor samples (peripheral blood, skin and lymph node biopsies, 49-1050 days apart) and matched, purified non-malignant cells from 10 MF/SS patients (3 - 8 specimens per patient) representative of patients seen at the Washington University School of Medicine Cutaneous Lymphoma clinic (mean age 56.1 years, 50% female, 60% Caucasian and 40% African American). All were diagnosed with advanced MF and/or SS and half of first specimens were collected within 60 days of diagnosis. Subsequent specimens were collected at progression or lack of response to therapy, on average 20 months between specimens (1.4 - 60, SD = 11.8); patients had received 1-11 different CTCL therapies. For eWGS, specimens were purified by flow cytometry as follows, tumor: CD3+CD4+CD7- and normal: CD4+CD7+ (non-malignant T cells) or CD3-CD14+ (monocytes) or CD3-CD56+ (NK cells). Specimens were subjected to scRNAseq, exome sequencing plus low coverage whole genome sequencing (eWGS), and patient specific TCR clonotype assignment (scRepertoire). Results: Clustering and cell type inference of scRNAseq (UMAP/Seurat/singleR) from 92,496 total cells showed canonical CTCL marker genes and high clonal proportions (1-100%) of patient specific TCR clonotypes. Somatic genome copy number variants (CNV) from eWGS (cnvkit) and scRNAseq (copykat) and deleterious/damaging single nucleotide variants (SNV) (eWGS, GATK/Mutect2; scRNAseq, cb_sniffer) were identified in CTCL versus matched, non-malignant cells. To segregate early genomic events from those that were progression-associated, we developed an integrative analysis pipeline to prioritize somatic CNV and SNV that were detected in samples collected at timepoints with lack of response to therapy and/or progression in ≥30% of patients. This novel approach revealed alterations in T-cell activation pathways as early events that were maintained in subsequent CTCL samples. Loss of some chromatin-modifying enzymes were early events, while gains of others (DNMT3A, EZH2, KMT2C) were acquired with therapy resistance/progression (Fig. 1A). Copy number amplifications of STAT3/STAT5 are frequent and we demonstrate a novel-to-CTCL single nucleotide mutation in STAT3 that has gain-of-function activity. Progression-associated genomic changes were enriched in cell cycle (CDK genes), DNA damage/repair (TP53BP1, RAD51C), RAS and Rho signaling pathways, and transcriptional regulators (FOXO genes). Expression of mutant alleles was detectable in scRNAseq and variant levels fluctuated with progression or lack of therapy response (Fig. 1B). Conclusion: To date, there have been limited studies defining temporal changes in the genomes and transcriptomes of CTCL due in part to low tumor burden in the skin and blood. Using innovative sequencing and informatic approaches, we identified recurrent alterations in CDK11A, DNMT3A, EZH2, FOXO1, RAD51C, STAT3/STAT5, and TP53BP1, among others, with clonal evolution in CTCL. Many of these have therapeutic implications. Taken together, these findings represent new insights into MF/SS progression, reveal new markers for response assessment, and identify new targets for therapeutic development. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

40. Clonal evolution of Cutaneous T Cell Lymphoma (CTCL) revealed at single cell resolution

Patients with CTCL subtypes Mycosis Fungoides and Sézary Syndrome (MF/SS) frequently progress to advanced stage disease, which has a 20% 5-year survival. The molecular factors that drive MF/SS progression remain undefined. To address this, we subjected 41 longitudinal tumor samples (peripheral blood, skin and lymph node biopsies, 49-1050 days apart) and matched, purified non-malignant cells from 10 MF/SS patients to single-cell (sc)RNA-seq and exome+whole genome sequencing (eWGS). and patient-specific TCR clonotype assignment (scRepertoire). Clustering and cell type inference of scRNAseq (UMAP/Seurat/singleR) showed canonical CTCL marker genes and high clonal proportions (1-100%) of patient-specific TCR clonotypes. Somatic genome copy number variants (CNV) from scRNAseq (copykat) and eWGS (cnvkit), and deleterious/damaging single nucleotide variants (SNV) (eWGS, GATK/Mutect2) were identified in CTCL versus matched, non-malignant cells. To segregate early genomic events from progression-associated, we developed an integrative analysis pipeline to prioritize somatic CNV/SNV in genes with altered expression in >=30% of patients. This novel approach revealed alterations in NF-KB and T-cell receptor pathways (NFKB2, STAT3/5, TOX) as early events that were maintained in subsequent CTCL samples. We demonstrate gain-of-function activity in a novel-to-CTCL mutation in STAT3. Losses of some chromatin-modifying enzymes (DNMT3A, KDM6B) are early events, while gains of others (EZH2) are acquired with progression. Strikingly, progression-associated mutations were enriched in cell metabolism, growth, and motility genes, some of which are new to MF/SS: HIF1A, ITPR3, GTPase/RAS (IQGAP1/2, RASA1), and PI kinase (AKT1, MTOR, PIK3R1). These findings represent new insights into MF/SS progression and identify new precision medicine targets for currently available therapies.

Abstract 255: TransVAF: A transfer learning approach for recognize genomic mutations with various tumor purity and clonal proportions

Abstract Mutation detection, via genomic sequencing, has become a routine in cancer diagnosis and precision treatments. Although the existing bioinformatics approaches alter the algorithms and strategies for the detection, they always rely on the combinations of statistical features on a set of overlapped reads to recognize the real mutations from false positives. It may be the Achilles heel of such recognition mechanisms, that their preset thresholds are often stiff and ambiguous and the feature combinations with adaptive thresholds could only be enabled by machine learning frameworks. Unfortunately, the learning models have to overcome the challenges caused by tumor heterogeneity. For mutations from different subclones, most of the sequencing features associate with the tumor purity and clonal proportions. It introduces complicated interactions among the features and breaks the independent co-distribution assumption of classic learning models. In addition, both the tumor purity and clonal proportions are variables, thus, any training sets cannot enumerate all possible values. These challenges hurt the specificities of the existing approaches applying to cancer sequencing data. Here, we propose an approach for the scenario of various tumor purity and clonal proportions. The proposed approach incorporates a comprehensive set of the features according to the existing strategies. Then, it requires at least two training sets with different proportions. For any given set, we have fixed tumor purity and clonal proportions. The framework first trains the models according to one set. The trained models focus on the associations between the features and true mutations. These models are defined as a source domain. Next, when the other set is input for training, the framework not only trains another source domain, but focuses on the transformations among the features between the source domains as well. Now, when another fixed tumor purity and clonal proportions are considered, the framework is able to generate, maybe roughly, the models for the new group of the purity and proportions according to the source domains and the transformations. To enhance the performance, we propose to integrate a few source domains to control the systematic errors during the transfer processes. The Boyer-Moore majority-vote algorithm is introduced to achieve the integration. We have carried out a series of experiments on both simulated and real datasets, and compared to the state-of-the-art approaches, including MuTect2, Sentieon, VarScan2, Freebayes and SiNVICT. The results demonstrated that the proposed method adapts well to different diluted sequencing signals and can significantly reduce the false positive. It is implemented as TransVAF. The software package has been uploaded at https://github.com/TrinaZ/TL-fpFilter for academic usage only. Citation Format: Tian Zheng, Jiayin Wang, Xiao Xiao, Xiaoyan Zhu, Xuanping Zhang, Xin Lai, Yanfang Guan, Xin Yi. TransVAF: A transfer learning approach for recognize genomic mutations with various tumor purity and clonal proportions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 255.

Integrating Quantitative Assays with Biologically Based Mathematical Modeling for Predictive Oncology.

SummaryWe provide an overview on the use of biological assays to calibrate and initialize mechanism-based models of cancer phenomena. Although artificial intelligence methods currently dominate the landscape in computational oncology, mathematical models that seek to explicitly incorporate biological mechanisms into their formalism are of increasing interest. These models can guide experimental design and provide insights into the underlying mechanisms of cancer progression. Historically, these models have included a myriad of parameters that have been difficult to quantify in biologically relevant systems, limiting their practical insights. Recently, however, there has been much interest calibrating biologically based models with the quantitative measurements available from (for example) RNA sequencing, time-resolved microscopy, and in vivo imaging. In this contribution, we summarize how a variety of experimental methods quantify tumor characteristics from the molecular to tissue scales and describe how such data can be directly integrated with mechanism-based models to improve predictions of tumor growth and treatment response.

A hidden Markov modeling approach for identifying tumor subclones in next-generation sequencing studies.

Allele-specific copy number alteration (ASCNA) analysis is for identifying copy number abnormalities in tumor cells. Unlike normal cells, tumor cells are heterogeneous as a combination of dominant and minor subclones with distinct copy number profiles. Estimating the clonal proportion and identifying mainclone and subclone genotypes across the genome are important for understanding tumor progression. Several ASCNA tools have recently been developed, but they have been limited to the identification of subclone regions, and not the genotype of subclones. In this article, we propose subHMM, a hidden Markov model-based approach that estimates both subclone region and region-specific subclone genotype and clonal proportion. We specify a hidden state variable representing the conglomeration of clonal genotype and subclone status. We propose a two-step algorithm for parameter estimation, where in the first step, a standard hidden Markov model with this conglomerated state variable is fit. Then, in the second step, region-specific estimates of the clonal proportions are obtained by maximizing region-specific pseudo-likelihoods. We apply subHMM to study renal cell carcinoma datasets in The Cancer Genome Atlas. In addition, we conduct simulation studies that show the good performance of the proposed approach. The R source code is available online at https://dceg.cancer.gov/tools/analysis/subhmm. Expectation-Maximization algorithm; Forward-backward algorithm; Somatic copy number alteration; Tumor subclones.

Abstract 1670: A hidden markov modeling approach for identifying tumor subclones in next-generation sequencing studies

Abstract Allele-specific copy number alteration (ASCNA) analysis is for identifying copy number abnormalities in tumor cells. Unlike normal cells, tumor cells are heterogeneous with a combination of dominant and minor subclones with distinct copy number profiles. Estimating the clonal proportion and identifying main and subclone genotypes across the genome is important for understanding tumor progression. Several ASCNA tools have recently been developed, but they have been limited to the identification of subclone regions, and not the genotype of the subclones. In this paper, we propose subHMM, a hidden Markov model-based approach that estimates both subclone region as well as region-specific subclone genotype and clonal proportion. We specify a hidden state variable representing the conglomeration of clonal genotypes and subclone status. We propose a two-step algorithm for parameter estimation, where in the first step, a standard hidden Markov model with this conglomerated state space is fit. Then, in the second step, region-specific estimates of the clonal proportions are obtained by maximizing region-specific pseudo-likelihoods. We apply subHMM to a renal cell carcinoma dataset from The Cancer Genome Atlas. In addition, we conduct simulation studies that show the good performance of the proposed approach. Citation Format: Bin Zhu, Hyoyoung Choo-Wosoba, Paul Albert. A hidden markov modeling approach for identifying tumor subclones in next-generation sequencing studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1670.

A mathematical solution to Peto\u2019s paradox using Polya\u2019s urn model: implications for the aetiology of cancer in general

Ageing is the leading risk factor for the emergence of cancer in humans. Accumulation of pro-carcinogenic events throughout life is believed to explain this observation; however, the lack of direct correlation between the number of cells in an organism and cancer incidence, known as Peto’s Paradox, is at odds with this assumption. Finding the events responsible for this discrepancy can unveil mechanisms with potential uses in prevention and treatment of cancer in humans. On the other hand, the immune system is important in preventing the development of clinically relevant tumours by maintaining a fine equilibrium between reactive and suppressive lymphocyte clones. It is suggested here that the loss of this equilibrium is what ultimately leads to increased risk of cancer and to propose a mechanism for the changes in clonal proportions based on decreased proliferative capacity of lymphocyte clones as a natural phenomenon of ageing. This mechanism, being a function of the number of cells, provides an explanation for Peto’s Paradox.

Mixed-phenotype large granular lymphocytic leukemia: a rare subtype in the large granular lymphocytic leukemia spectrum

Large granular lymphocytic leukemia (LGLL) is a chronic proliferation of cytotoxic lymphocytes in which more than 70% of patients develop cytopenia(s) requiring therapy. LGLL includes T-cell LGLL and chronic lymphoproliferative disorder of natural killer (NK) cells. The neoplastic cells in LGLL usually exhibit a single immunophenotype in a patient, with CD8-positive/αβ T-cell type being the most common, followed by NK-cell, γδ T-cell, and CD4-positive/αβ T-cell types. We investigated a total of 220 LGLL cases and identified 12 mixed-phenotype LGLLs (5%): 7 cases with coexistent αβ T-cell and NK-cell clones and 5 with coexistent αβ and γδ T-cell clones. With a median follow-up of 48 months, the clinicopathological characteristics of these patients seemed similar to those of typical LGLL patients. Treatment was instituted in 9 patients, and 5 patients (55%) attained complete hematologic response or partial response. The therapeutic response rate of this cohort is comparable to the reported overall response rate of 40% to 60% in typical LGLL patients. Three patients who did not receive any treatment had progressive or persistent cytopenias. Interestingly, inverted proportions of 2 clones at disease recurrence were identified in 4 patients (36%) and stable clonal proportions in 7 patients (64%). Mixed-phenotype LGLL is rare, and this study underscores the importance of recognizing this rare type of LGLL in patients who may benefit from LGLL treatment.

Multiple-clone infections of Plasmodium vivax: definition of a panel of markers for molecular epidemiology.

BackgroundPlasmodium vivax infections commonly contain multiple genetically distinct parasite clones. The detection of multiple-clone infections depends on several factors, such as the accuracy of the genotyping method, and the type and number of the molecular markers analysed. Characterizing the multiplicity of infection has broad implications that range from population genetic studies of the parasite to malaria treatment and control. This study compared and evaluated the efficiency of neutral and non-neutral markers that are widely used in studies of molecular epidemiology to detect the multiplicity of P. vivax infection.MethodsThe performance of six markers was evaluated using 11 mixtures of DNA with well-defined proportions of two different parasite genotypes for each marker. These mixtures were generated by mixing cloned PCR products or patient-derived genomic DNA. In addition, 51 samples of natural infections from the Brazil were genotyped for all markers. The PCR-capillary electrophoresis-based method was used to permit direct comparisons among the markers. The criteria for differentiating minor peaks from artifacts were also evaluated.ResultsThe analysis of DNA mixtures showed that the tandem repeat MN21 and the polymorphic blocks 2 (msp1B2) and 10 (msp1B10) of merozoite surface protein-1 allowed for the estimation of the expected ratio of both alleles in the majority of preparations. Nevertheless, msp1B2 was not able to detect the majority of multiple-clone infections in field samples; it identified only 6 % of these infections. The merozoite surface protein-3 alpha and microsatellites (PvMS6 and PvMS7) did not accurately estimate the relative clonal proportions in artificial mixtures, but the microsatellites performed well in detecting natural multiple-clone infections. Notably, the use of a less stringent criterion to score rare alleles significantly increased the sensitivity of the detection of multi-clonal infections.ConclusionsDepending on the type of marker used, a considerable amplification bias was observed, which may have serious implications for the characterization of the complexity of a P. vivax infection. Based on the performance of markers in artificial mixtures of DNA and natural infections, a minimum panel of four genetic markers (PvMS6, PvMS7, MN21, and msp1B10) was defined, and these markers are highly informative regarding the genetic variability of P. vivax populations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-015-0846-5) contains supplementary material, which is available to authorized users.

Recurrent Abnormal Clones in Myelodysplastic Syndrome Marrow Originate from Cells at a Pluripotent Stem Level and Maintain Their Early Differentiation Potency

Objective: The present study aimed to investigate the origins and differentiation potencies of 4 common malignant clonal cell types (+8, 5q−/−5, 20q−/−20, 7q−/−7) in myelodysplastic syndrome (MDS) and to investigate whether the trisomy of chromosome 8 occurs subsequently to other chromosomal abnormalities. Methods: The present study analyzed a total of 46 cases of chromosomal abnormalities in MDS patients. The magnetic activated cell sorting technique (MACS) was used to sort the CD34+CD38− (pluripotent hematopoietic stem cells) and CD34+CD38+ cells (committed progenitor cells) from the bone marrow mononuclear cells (BMNCs) of these patients; the sorted cells were then individually smeared. Meanwhile, cytospins were prepared from the remaining CD34− BMNCs after cell sorting. The clonal cell proportions in these three types of smears were detected by fluorescence in situ hybridization (FISH). Cases in which +8 was associated with another abnormality (2 cases each in combination with abnormalities in chromosomes 7, 5, and 20) were dually hybridized with the cep8 probe and another corresponding probe. Results: (1) for abnormalities of +8, 5q−/−5, 20q−/−20 or chromosome 7 involvements, clonal cells above the baseline level were detected in the pluripotent stem cell level. (2) The average clonal cell proportion in the committed progenitor cells of the 46 cases increased to 75.3% from 57.3% at the level of stem cell (p < 0.001). The groups with +8 and chromosome 5 abnormalities showed a statistically significant increase in clonal cells at the progenitor cell stage. At the individual level, 33 of 46 cases showed significant increases in clonal cells at the progenitor cell stage relative to the stem cell stage, whereas the clonal cell proportion in the CD34− BMNCs generally did not increase relative to the committed progenitor cell population. (3) The dual hybridization analysis showed that if +8 and another abnormality were present in the same abnormal clone according to G-banding, +8 always coexisted with the other chromosomal abnormality at the single cell level; there were no situations in which +8 occurred later than the other chromosomal abnormality. Conclusion: It seems that the all malignant MDS clones originated at the pluripotent hematopoietic stem cell stage and that the proliferation and differentiation potencies were retained partly in these clonal cells. The present study failed to confirm that the trisomy 8 occurred subsequently to the other abnormalities, but some in vitro or transplant experiments maybe prove the succession of clonal origination.

Dynamics of clonal diversity in natural infections of the malaria parasite Plasmodium mexicanum in its free-ranging lizard host

Within mixed-genotype infections of malaria parasites (Plasmodium), the number of genetic clones present is associated with variation in important life history traits of the infection, including virulence. Although the number of clones present is important, how the proportion of those clones varies over time is poorly known. Clonal proportions of the lizard malaria parasite, Plasmodium mexicanum, were assessed in naturally infected free-ranging lizards followed in a mark-recapture program over as long as two warm seasons, the typical life span of the lizard. Clonal proportions were determined by amplifying two microsatellite markers, a method previously verified for accuracy. Most blood samples had been stored for over a decade, so a verification test determined that these samples had not degraded. Although the environment experienced by the parasite (its host) varies over the seasons and transmission occurs over the entire warm season, 68% of infections were stable over time, harboring a single clone (37% of infections) or multiple clones changing only 1-12% maximum comparing any two samples (31% of infections). The maximum change seen in any infection (comparing any two sample periods) was only 30%. A new clone entered three infections (only once successfully), and a clone was lost in only three infections. These results mirror those seen for a previous study of experimentally induced infections that showed little change in relative proportions over time. The results of this study, the first look at how clonal proportions vary over time for any malaria parasite of a nonhuman vertebrate host for natural infections, were surprising because experimental studies show clones of P. mexicanum appear to interact, yet relative proportions of clones typically remain constant over time.

Establishment Efficiency Among Clones of the Malaria Parasite,Plasmodium mexicanum, for Mixed-Clone Infections in Its Natural Lizard Host

Within genetically diverse infections of malaria parasites ( Plasmodium spp.), the relative proportions of genetic clones in the vertebrate host's blood can influence clonal competition, transmission success, gametocyte sex ratio, and virulence. Clonal proportions depend on establishment success of each clone when they enter a new host and on subsequent differences in rates of asexual replication and clearance. Both of these life history traits could be influenced by clone genotype. To assess genetic (clonal) influences on both establishment success and later changes in relative proportion for the lizard malaria parasite Plasmodium mexicanum , 7 naturally infected fence lizards harboring a single clone of P. mexicanum served as donors to initiate replicate experimental infections containing each of the clones and combinations of 2 clones. Measured were relative establishment success of each clone, change in relative proportions over time, and rate of increase of parasite density and total parasitemia. Relative clonal proportions were determined using microsatellite markers. Rates of increase in the parasitemia and degree of change in relative proportions were not correlated, so both rapidly and slowly growing infections could show either little or substantial change in clonal proportions over time. There was a significant clone effect on establishment efficiency but not on later changes in relative proportions. These results argue for a combination of genetic and environmental (host) effects on the success of P. mexicanum clones in genetically complex infections. The maintenance of genetic variation for establishment success, but not subsequent replication rate or shifts in relative proportion, suggests trade-offs between these traits during life history evolution of malaria parasites.

Relative clonal proportions over time in mixed-genotype infections of the lizard malaria parasite Plasmodium mexicanum

Vertebrate hosts of malaria parasites ( Plasmodium) often harbour two or more genetically distinct clones of a single species, and interaction among these co-existing clones can play an important role in Plasmodium biology. However, how relative clonal proportions vary over time in a host is still poorly known. Experimental mixed-clone infections of the lizard malaria parasite, Plasmodium mexicanum, were followed in its natural host, the western fence lizard using microsatellite markers to determine the relative proportions of two to five co-existing clones over time (2–3 months). Results for two markers, and two PCR primer pairs for one of those, matched very closely, supporting the efficacy of the method. Of the 54 infections, 67% displayed stable relative clonal proportions, with the others showing a shift in proportions, usually with one clone outpacing the others. Infections with rapidly increasing or slowly increasing parasitemia were stable, showing that all clones within these infections reproduced at the same rapid or slow rate. Replicate infections containing the same clones did not always reveal the same growth rate, final parasitemia or dominant clone; thus there was no clone effect for these life history measures. The rate of increase in parasitemia was not associated with stable versus unstable relative proportions, but infections with four to five clones were more likely to be unstable than those with two to three clones. This rare look into events in genetically complex Plasmodium infections suggests that parasite clones may be interacting in complex and unexpected ways.

Relative Clonal Density of Malaria Parasites in Mixed-Genotype Infections: Validation of a Technique Using Microsatellite Markers for Plasmodium falciparum and P. mexicanum

Quantifying the relative proportion of coexisting genotypes (clones) of a malaria parasite within its vertebrate host's blood would provide insights into critical features of the biology of the parasite, including competition among clones, gametocyte sex ratio, and virulence. However, no technique has been available to extract such data for natural parasite-host systems when the number of clones cycling in the overall parasite population is likely to be large. Recent studies find that data from genetic analyzer instruments for microsatellite markers allow measuring clonal proportions. We conducted a validation study for Plasmodium mexicanum and Plasmodium falciparum by mixing DNA from single-clone infections to simulate mixed infections of each species with known proportions of clones. Results for any mixture of DNA gave highly reproducible results. The relationship between known and measured relative proportions of clones was linear, with high regression r² values. Known and measured clone proportions for simulated infections followed over time (mixtures) were compared with 3 methods: using uncorrected data, with uncorrected data and confidence intervals constructed from observed experimental error, and using a baseline mixture of equal proportions to calibrate all other results. All 3 methods demonstrated value in studies of mixed-genotype infections sampled a single time or followed over time. Thus, the method should open new windows into the biology of malaria parasites.

Detecting number of clones, and their relative abundance, of a malaria parasite (Plasmodium mexicanum) infecting its vertebrate host

Microsatellites, short tandem repeats of nucleotides in the genome, are useful markers to detect clonal diversity within Plasmodium infections. However, accuracy in determining number of clones and their relative proportions based on standard genetic analyzer instruments is poorly known. DNA extracted from lizards infected with a malaria parasite, Plasmodium mexicanum, provided template to genotype the parasite based on three microsatellite markers. Replicate genotyping of the same natural infections demonstrated strong repeatability of data from the instrument. Mixing DNA extracted from several infected lizards simulated mixed-clone infections with known clonal diversity and relative proportions of clones (N = 56 simulations). The instrument readily detected at least four alleles (clones), even when DNA concentrations among clones differed up to tenfold, but alleles of similar size can be missed because they fall within the "stutter" artifact, and rarely does an allele fail to be detected. For simulations of infections that changed their relative proportions over time, changes in relative peak heights on the instrument output closely followed the known changes in relative proportions. Such data are useful for a broad range of studies on the ecology of malaria parasites.

Selective transmission of hepatitis C virus genotypes and quasispecies in humans and experimentally infected chimpanzees

This study determined whether selective transmission of hepatitis C virus (HCV) species occurred among human and chimpanzee recipients of contaminated blood products or plasma containing multiple genotypes, subgenotypes and quasispecies. Commercially prepared factor VIII concentrate (lot DO56), produced prior to HCV testing and inactivation, was subsequently found by direct cloning to contain the following subgenotypes: 1a and 1b (73 % of clones), 2a (13 % of clones), 2b (11 % of clones) and 3a (4 % of clones). A patient transfused with factor VIII concentrate DO56 was diagnosed with clinical non-A, non-B hepatitis and subsequently found to be infected with HCV subgenotype 1b. Among five chimpanzees inoculated experimentally with the same factor VIII concentrate, two were infected only with HCV subgenotype 1a and three were infected with approximately equivalent clonal proportions of subgenotypes 1a and 1b. HCV hypervariable region 1 (HVR1) quasispecies analysis of the DO56 factor VIII concentrate and a serum specimen from the single chimpanzee that developed a chronic HCV infection following inoculation with DO56 showed 0-56 % nucleotide variation. However, specimens from chimpanzees infected in the second to fourth passages of the DO56 inoculum had 0-8 % HVR1 quasispecies nucleotide variation. The high HVR1 quasispecies variation in the factor VIII concentrate and its first passage in chimpanzees indicates the presence of multiple HCV isolates, whereas the low variation in the second to fourth chimpanzee passages suggests transmission of a single HCV isolate. These findings strongly suggest selective transmission of HCV isolates during experimental chimpanzee infection and among humans exposed to multiple HCV species.

Height–age and height–diameter relationships for monocultures and mixtures of eastern cottonwood clones

Data from an eastern cottonwood clonal mixing study in Mississippi and Kentucky, USA, were used to test the effects of planting locations and genetics (clonal proportions) on height–age and height–dbh functions. Planting locations, which accounted for 5.6% of the variation in observed dominant height growth ( p=0.0001), were more important than clonal proportions, which accounted for only 1.0% of the variation ( p=0.0077). Interactions between clones in mixtures were not significant ( p=0.9178), but three cases of over- and undercompensation paralleled those observed for basal area. Planting locations were associated with differences in maximum height in the height–dbh function and clonal proportions were associated with differences in height of trees with smaller than average dbh. Although statistically significant, the effects of planting locations and clonal proportions were not important enough to incorporate into the final height–dbh model.

Cytogenetic abnormalities in an in situ ductal carcinoma and five prophylactically removed breasts from members of a family with hereditary breast cancer

Short-term cultures of tissue samples from three bilateral prophylactic mastectomies and onein situ ductal carcinoma from four women belonging to a family with hereditary breast cancer were cytogenetically analyzed. Clonal chromosome abnormalities were detected in five of the six prophylactically removed breasts, all of which had the histologic diagnosis epithelial hyperplasia without atypia, and in thein situ carcinoma. The same karyotypic imbalance, a loss of 3p12–14, was detected in thein situ carcinoma as well as in one of the hyperplasias, indicating that these bands may harbor a pathogenetically relevant gene in this breast cancer family. The finding of chromosome aberrations in clonal proportions in the prophylactically removed breasts indicates that a neoplastic process was already present, lending support to the view that prophylactic bilateral mastectomy in these high-risk individuals prevented the development of breast carcinoma.

Eastern cottonwood clonal mixing study: predicted diameter distributions

A parameter recovery procedure for the Weibull distribution function was modified to incorporate monocultures and mixtures of eastern cottonwood (Populusdeltoides Bartr.) clones planted in Mississippi and Kentucky. Components of the system included functions to predict stand-level basal area and four percentiles (0th, 25th, 50th, and 95th) of the cumulative diameter distribution. Basal area was predicted as a function of surviving number of trees, dominant height, age, planting location, and the proportion of each clone planted. Clonal proportions, which accounted for 3.6% of the variation in observed basal area, were more important than differences in planting locations, which accounted for 3.0% of the variation. Interactions between clones in mixtures were not significant (p = 0.5676), but some cases of both over- and under-compensation appeared to be developing. Percentiles of the cumulative diameter distribution were predicted as functions of quadratic mean diameter, and therefore included indirect effects of both genetic and planting site differences. Only the minimum diameter (D0) was directly affected by proportions of clones planted. Most of the monocultures and mixtures of clones had smaller minimum diameters than expected for a given value of quadratic mean diameter. The predicted quadratic mean diameter and percentiles were used to recover parameters of the Weibull distribution such that the predicted diameter distribution has the same quadratic mean diameter as obtained from the stand basal area model. The predicted distributions indicated that a common stand-level model was not sufficient for accounting for variations in diameter distributions of eastern cottonwood clones. As a result of the differences in diameter distributions, monocultures and mixtures of the Texas clones appeared to have less volume and greater stand variance than the Mississippi clones.