An expectation-maximization program for determining allelic spectrum from CNV data (CoNVEM): insights into population allelic architecture and its mutational history

Abstract

Copy number variations (CNVs) are a common form of genetic variation in which the allelic population contains a distribution of copy numbers of a particular gene (or other large sequence/region). The simplest forms describe deletion (0 vs. 1 copy) or duplication (1 vs. 2) events. However, some CNV loci contain a much wider range of copy numbers, such as that seen for the CCL3L1 locus. CNV classification methods typically only describe the total (diploid) copy number, leaving the underlying genotypic and allelic frequency distribution unknown. We have developed an expectation-maximization approach for the analysis of data from tandem CNVs that enables estimation of both the allelic copy number frequency distribution and the expected copy number genotype and class distribution under the Hardy-Weinberg equilibrium (HWE). The CNV expectation-maximization algorithm is available in a Web-tool (CoNVEM, http://apps.biocompute.org.uk/convem/), which graphically and numerically presents CNV allele and genotype distributions. We have applied this approach to the analysis of salivary amylase (AMY1A, B, and C), CCL3L1, and SULT1A1 CNVs using published data, and present inferences about the evolutionary history of these loci based on CoNVEM results. Hum Mutat 31:414-420,

Copy Number Polymorphism of the Salivary Amylase Gene: Implications in Human Nutrition Research

“…In this study, CNV of AMY1 ranged from 2 to 20 diploid copies, with a mean and standard deviation of 6.4 ± 3.0 (percentiles 25, 50, and 75 were 4.0, 6.0, and 8.0, respectively). Our results indicate that CNV of AMY1 is highly polymorphic in Chileans, with estimated copy numbers similar to those found in other studies [20,30,31]. …”

“…In some countries, such as parts of China, a daily intake as high as 371 g per day has been reported [33], while considerable variation of starch intake and availability exists in different developed and underdeveloped countries [30]. In the USA, starch represents one half of the total carbohydrate content in the diet [31,34].…”

“…These frequencies are only slightly different from frequencies reported in European-Americans, where alleles of 4, 3, and 2 copies seems to be the most frequent ones. Among the Japanese population, alleles with 2 and 3 copies are the most common, with a possible contribution of the 5-copies allele [30]. It is possible that differences in the methodology of CNV determination may partially account for interpopulation variation in AMY1 copy number variant allele frequencies.…”

“…Although the fiber-FISH technique is able to determine allelic CNV composition [20], this procedure is not practical for large epidemiologic studies [22]. For this reason, once the CNV of AMY1 has been calculated in DNA samples from unrelated subjects, an algorithm is necessary to estimate allele frequencies, such as the one implemented in the program CONVEM [30] (http://apps.biocompute.org.uk/convem/). The computation of allele frequencies is based on the expectation-maximization algorithm and assumes Hardy-Weinberg equilibrium.…”

Amplification ratio control system for copy number variation genotyping

“…By plotting the CNV genotype of a large enough number of individuals, actual copy number can be determined through clustering (for example, the clusters for 0,1 and 2 copies being quite distinct and with central means that can be determined) without recourse to known positive controls. Prior knowledge of the proportions expected within each cluster can be obtained from the literature and used to anchor new data, and additional supporting information on expected allelic composition of the CNV classes can be obtained from re-analysis of existing data using expectation maximization programs such as CoNVEM (20). The ARCS approach has significant advantages over real time PCR in the large-scale genetic epidemiological follow up of CNVs in banks representing tens of thousands of study participants.…”