Investigation of the allele frequency of the G>A intron 10 ADAMTS17 mutation causing primary lens luxation in the Portuguese Podengo breed

Abstract Background Oncopanel genomic testing, which identifies important somatic variants, is increasingly common in medical practice and especially in clinical trials. Currently, there is a paucity of reliable genomic reference samples having a suitably large number of pre-identified variants for properly assessing oncopanel assay analytical quality and performance. The FDA-led Sequencing and Quality Control Phase 2 (SEQC2) consortium analyze ten diverse cancer cell lines individually and their pool, termed Sample A, to develop a reference sample with suitably large numbers of coding positions with known (variant) positives and negatives for properly evaluating oncopanel analytical performance. Results In reference Sample A, we identify more than 40,000 variants down to 1% allele frequency with more than 25,000 variants having less than 20% allele frequency with 1653 variants in COSMIC-related genes. This is 5–100× more than existing commercially available samples. We also identify an unprecedented number of negative positions in coding regions, allowing statistical rigor in assessing limit-of-detection, sensitivity, and precision. Over 300 loci are randomly selected and independently verified via droplet digital PCR with 100% concordance. Agilent normal reference Sample B can be admixed with Sample A to create new samples with a similar number of known variants at much lower allele frequency than what exists in Sample A natively, including known variants having allele frequency of 0.02%, a range suitable for assessing liquid biopsy panels. Conclusion These new reference samples and their admixtures provide superior capability for performing oncopanel quality control, analytical accuracy, and validation for small to large oncopanels and liquid biopsy assays.

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18 New method of assessing tumor heterogeneity utilizing both circulating tumor DNA and tissue DNA to predict the response to immunotherapy

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0018 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A18-A18

Author(s):

Jaeyoun Choi ◽

Myungwoo Nam ◽

Stanislav Fridland ◽

Jinyoung Hwang ◽

Chan Mi Jung ◽

...

Keyword(s):

Lung Cancer ◽

Immune Response ◽

Allele Frequency ◽

Scoring System ◽

Tumor Heterogeneity ◽

Metastatic Breast ◽

Circulating Tumor Dna ◽

List Type ◽

Multiple Biopsies ◽

Tumor Dna

BackgroundTumor heterogeneity assessment may help predict response to immunotherapy. In melanoma mouse models, tumor heterogeneity impaired immune response.1 In addition, among lung cancer patients receiving immunotherapy, the high clonal neoantigen group had favorable survival and outcomes.2 Ideal methods of quantifying tumor heterogeneity are multiple biopsies or autopsy. However, these are not feasible in routine clinical practice. Circulating tumor DNA (ctDNA) is emerging as an alternative. Here, we reviewed the current state of tumor heterogeneity quantification from ctDNA. Furthermore, we propose a new tumor heterogeneity index(THI) based on our own scoring system, utilizing both ctDNA and tissue DNA.MethodsSystematic literature search on Pubmed was conducted up to August 18, 2020. A scoring system and THI were theoretically derived.ResultsTwo studies suggested their own methods of assessing tumor heterogeneity. One suggested clustering mutations with Pyclone,3 and the other suggested using the ratio of allele frequency (AF) to the maximum somatic allele frequency (MSAF).4 According to the former, the mutations in the highest cellular prevalence cluster can be defined as clonal mutations. According to the latter, the mutations with AF/MSAF<10% can be defined as subclonal mutations. To date, there have been no studies on utilizing both ctDNA and tissue DNA simultaneously to quantify tumor heterogeneity. We hypothesize that a mutation found in only one of either ctDNA or tissue DNA has a higher chance of being subclonal.We suggest a scoring system based on the previously mentioned methods to estimate the probability for a mutant allele to be subclonal. Adding up the points that correspond to the conditions results in a subclonality score (table 1). In a given ctDNA, the number of alleles with a subclonality score greater than or equal to 2 divided by the total number of alleles is defined as blood THI (bTHI) (figure 1). We can repeat the same calculation in a given tissue DNA for tissue THI (tTHI) (figure 2). Finally, we define composite THI (cTHI) as the mean of bTHI and tTHI.Abstract 18 Table 1Subclonality scoreAbstract 18 Figure 1Hypothetical distribution of all alleles found in ctDNA bTHI = the number of alleles with a subclonality score greater than or equal to 2/the total number of alleles found in ctDNA = 10/20 =50%Abstract 18 Figure 2Hypothetical distribution of all alleles found in tissue DNA tTHI= the number of alleles with a subclonality score greater than or equal to 2/the total number of alleles found in tissue DNA = 16/40 = 40% cTHI= (bTHI + tTHI)/2 = 45%ConclusionsTumor heterogeneity is becoming an important biomarker for predicting response to immunotherapy. Because autopsy and multiple biopsies are not feasible, utilizing both ctDNA and tissue DNA is the most comprehensive and practical approach. Therefore, we propose cTHI, for the first time, as a quantification measure of tumor heterogeneity.ReferencesWolf Y, Bartok O. UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma. Cell 2019;179:219–235.McGranahan N, Swanton C. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 2016;351:1463–1469.Ma F, Guan Y. Assessing tumor heterogeneity using ctDNA to predict and monitor therapeutic response in metastatic breast cancer. Int J Cancer 2020;146:1359–1368.Liu Z, Xie Z. Presence of allele frequency heterogeneity defined by ctDNA profiling predicts unfavorable overall survival of NSCLC. Transl Lung Cancer Res 2019;8:1045–1050.

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Inferring Linkage Disequilibrium Between a Polymorphic Marker Locus and a Trait Locus in Natural Populations

Genetics ◽

10.1093/genetics/156.1.457 ◽

2000 ◽

Vol 156 (1) ◽

pp. 457-467 ◽

Cited By ~ 1

Author(s):

Z W Luo ◽

S H Tao ◽

Z-B Zeng

Keyword(s):

Linkage Disequilibrium ◽

Allele Frequency ◽

Random Mating ◽

Natural Populations ◽

Polymorphic Marker ◽

Marker Locus ◽

Model Parameters ◽

Phenotypic Variance ◽

Wide Range ◽

Trait Locus

Abstract Three approaches are proposed in this study for detecting or estimating linkage disequilibrium between a polymorphic marker locus and a locus affecting quantitative genetic variation using the sample from random mating populations. It is shown that the disequilibrium over a wide range of circumstances may be detected with a power of 80% by using phenotypic records and marker genotypes of a few hundred individuals. Comparison of ANOVA and regression methods in this article to the transmission disequilibrium test (TDT) shows that, given the genetic variance explained by the trait locus, the power of TDT depends on the trait allele frequency, whereas the power of ANOVA and regression analyses is relatively independent from the allelic frequency. The TDT method is more powerful when the trait allele frequency is low, but much less powerful when it is high. The likelihood analysis provides reliable estimation of the model parameters when the QTL variance is at least 10% of the phenotypic variance and the sample size of a few hundred is used. Potential use of these estimates in mapping the trait locus is also discussed.

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99 Breed authentication of five lines comparing Structure, Admixture, and an allele frequency method

Journal of Animal Science ◽

10.1093/jas/skaa054.044 ◽

2020 ◽

Vol 98 (Supplement_3) ◽

pp. 25-25

Author(s):

Austin M Putz ◽

Patrick Charagu ◽

Abe Huisman

Keyword(s):

Population Structure ◽

Allele Frequency ◽

Regression Coefficients ◽

Frequency Method ◽

Large White ◽

Reference Allele ◽

Software Packages ◽

The Matrix ◽

Snp Panel ◽

Compare And Contrast

Abstract Two commonly used population structure software packages are freely available for breed authentication, Structure and Admixture. Structure uses a Bayesian approach to model population structure, while Admixture uses a frequentist approach. More recently, an allele frequency method has been updated to use quadratic programming to constrain the multiple linear regression coefficients of the regression of genotype count (divided by two) on the matrix of allele frequencies for each known breed or line. This constraint forced coefficients to sum to one and be greater than or equal to 0 and less than or equal to 1. The goal of this research was to compare and contrast these three methods to determine the breed/line authenticity for each of the five genetic lines. These five lines included Large White, Landrace, a lean Duroc, a meat quality Duroc, and a Pietrain line. Only animals with a 50K SNP panel were used in this analysis. Analyses were run five times for Structure and Admixture to check repeatability. The allele frequency method did not need to be repeated because it remains the same as long as the reference allele frequency matrix stays constant. For Structure, results of breed composition were inconsistent across replicates. Structure separated at least one of the maternal lines in three out of the five replicates with only 500 animals and kept the Duroc lines together as one population. Only 500 animals could be utilized in each run of Structure due to computational restraints. Admixture was very consistent across runs for each animal, but also failed to separate the two Duroc lines, instead splitting one of the two maternal lines. Finally, the allele frequency method split all five lines correctly and was 100% reproducible as long as the reference allele frequency matrix stays the same across runs.

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Estimation of Cry3Bb1 resistance allele frequency in field populations of western corn rootworm using a genetic marker

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkaa013 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Alan Willse ◽

Lex Flagel ◽

Graham Head

Keyword(s):

Allele Frequency ◽

Western Corn Rootworm ◽

Allele Frequencies ◽

Chromosome 8 ◽

Corn Belt ◽

Corn Rootworm ◽

Resistance Allele ◽

Response To Selection ◽

The Us ◽

Causal Allele

Abstract Following the discovery of western corn rootworm (WCR; Diabrotica virgifera virgifera) populations resistant to the Bacillus thuringiensis (Bt) protein Cry3Bb1, resistance was genetically mapped to a single locus on WCR chromosome 8 and linked SNP markers were shown to correlate with the frequency of resistance among field-collected populations from the US Corn Belt. The purpose of this paper is to further investigate the relationship between one of these resistance-linked markers and the causal resistance locus. Using data from laboratory bioassays and field experiments, we show that one allele of the resistance-linked marker increased in frequency in response to selection, but was not perfectly linked to the causal resistance allele. By coupling the response to selection data with a genetic model of the linkage between the marker and the causal allele, we developed a model that allowed marker allele frequencies to be mapped to causal allele frequencies. We then used this model to estimate the resistance allele frequency distribution in the US Corn Belt based on collections from 40 populations. These estimates suggest that chromosome 8 Cry3Bb1 resistance allele frequency was generally low (<10%) for 65% of the landscape, though an estimated 13% of landscape has relatively high (>25%) resistance allele frequency.

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A simple method to estimate the in-house limit of detection for genetic mutations with low allele frequencies in whole-exome sequencing analysis by next-generation sequencing

BMC Genomic Data ◽

10.1186/s12863-020-00956-x ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Takumi Miura ◽

Satoshi Yasuda ◽

Yoji Sato

Keyword(s):

Next Generation Sequencing ◽

Allele Frequency ◽

Somatic Mutations ◽

Limit Of Detection ◽

Allele Frequencies ◽

Genetic Mutations ◽

Sequencing Data ◽

Simple Method ◽

Whole Exome ◽

Generation Sequencing

Abstract Background Next-generation sequencing (NGS) has profoundly changed the approach to genetic/genomic research. Particularly, the clinical utility of NGS in detecting mutations associated with disease risk has contributed to the development of effective therapeutic strategies. Recently, comprehensive analysis of somatic genetic mutations by NGS has also been used as a new approach for controlling the quality of cell substrates for manufacturing biopharmaceuticals. However, the quality evaluation of cell substrates by NGS largely depends on the limit of detection (LOD) for rare somatic mutations. The purpose of this study was to develop a simple method for evaluating the ability of whole-exome sequencing (WES) by NGS to detect mutations with low allele frequency. To estimate the LOD of WES for low-frequency somatic mutations, we repeatedly and independently performed WES of a reference genomic DNA using the same NGS platform and assay design. LOD was defined as the allele frequency with a relative standard deviation (RSD) value of 30% and was estimated by a moving average curve of the relation between RSD and allele frequency. Results Allele frequencies of 20 mutations in the reference material that had been pre-validated by droplet digital PCR (ddPCR) were obtained from 5, 15, 30, or 40 G base pair (Gbp) sequencing data per run. There was a significant association between the allele frequencies measured by WES and those pre-validated by ddPCR, whose p-value decreased as the sequencing data size increased. By this method, the LOD of allele frequency in WES with the sequencing data of 15 Gbp or more was estimated to be between 5 and 10%. Conclusions For properly interpreting the WES data of somatic genetic mutations, it is necessary to have a cutoff threshold of low allele frequencies. The in-house LOD estimated by the simple method shown in this study provides a rationale for setting the cutoff.

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Selection, Subdivision and Extinction and Recolonization

Genetics ◽

10.1093/genetics/166.2.1105 ◽

2004 ◽

Vol 166 (2) ◽

pp. 1105-1114 ◽

Cited By ~ 1

Author(s):

Joshua L Cherry

Keyword(s):

Frequency Dependence ◽

Allele Frequency ◽

Deleterious Alleles ◽

Subdivided Population ◽

Theoretical Predictions ◽

Subdivided Populations ◽

Fixation Probabilities ◽

Selection Parameters ◽

To Come ◽

Do So

Abstract In a subdivided population, the interaction between natural selection and stochastic change in allele frequency is affected by the occurrence of local extinction and subsequent recolonization. The relative importance of selection can be diminished by this additional source of stochastic change in allele frequency. Results are presented for subdivided populations with extinction and recolonization where there is more than one founding allele after extinction, where these may tend to come from the same source deme, where the number of founding alleles is variable or the founders make unequal contributions, and where there is dominance for fitness or local frequency dependence. The behavior of a selected allele in a subdivided population is in all these situations approximately the same as that of an allele with different selection parameters in an unstructured population with a different size. The magnitude of the quantity Nese, which determines fixation probability in the case of genic selection, is always decreased by extinction and recolonization, so that deleterious alleles are more likely to fix and advantageous alleles less likely to do so. The importance of dominance or frequency dependence is also altered by extinction and recolonization. Computer simulations confirm that the theoretical predictions of both fixation probabilities and mean times to fixation are good approximations.

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