PHFinder: Assisted detection of point heteroplasmy in Sanger sequencing chromatograms

Heteroplasmy is the presence of two or more organellar genomes (mitochondrial or plastid DNA) in an organism, tissue, cell or organelle. Heteroplasmy can be detected by visual inspection of Sanger sequencing chromatograms, where it appears as multiple peaks of fluorescence at a single nucleotide position. Visual inspection of chromatograms is both consuming and highly subjective, as heteroplasmy is difficult to differentiate from background noise. Few software solutions are available to automate the detection of point heteroplasmies, and those that are available are typically proprietary, lack customization or are unsuitable for automated heteroplasmy assessment in large datasets. Here, we present PHFinder, a Python-based, open source tool to assist in the detection of point heteroplasmies in large numbers of Sanger chromatograms. PHFinder automatically identifies point heteroplasmies directly from the chromatogram trace data. The program was tested with Sanger sequencing data from 100 humpback whale (Megaptera novaeangliae) tissue samples with known heteroplasmies. PHFinder detected most (90%) of the known heteroplasmies thereby greatly reducing the amount of visual inspection required. PHFinder is flexible, enabling explicit specification of key parameters to infer double peaks (i.e., heteroplasmies)

Finding the right coverage:The impact of coverage and sequence quality on single nucleotide polymorphism genotyping error rates

Restriction-enzyme-based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in nonmodel organisms. However, in contrast to traditional genetic markers, genotyping error rates in SNPs derived from restriction-enzyme-based methods remain largely unknown. Here, we estimated genotyping error rates in SNPs genotyped with double digest RAD sequencing from Mendelian incompatibilities in known mother-offspring dyads of Hoffman's two-toed sloth (Choloepus hoffmanni) across a range of coverage and sequence quality criteria, for both reference-aligned and de novo-assembled data sets. Genotyping error rates were more sensitive to coverage than sequence quality and low coverage yielded high error rates, particularly in de novo-assembled data sets. For example, coverage &gt;= 5 yielded median genotyping error rates of &gt;= 0.03 and &gt;= 0.11 in reference-aligned and de novo-assembled data sets, respectively. Genotyping error rates declined to = 30, but remained &gt;= 0.04 in the de novo-assembled data sets. We observed approximately 10- and 13-fold declines in the number of loci sampled in the reference-aligned and de novo-assembled data sets when coverage was increased from &gt;= 5 to &gt;= 30 at quality score &gt;= 30, respectively. Finally, we assessed the effects of genotyping coverage on a common population genetic application, parentage assignments, and showed that the proportion of incorrectly assigned maternities was relatively high at low coverage. Overall, our results suggest that the trade-off between sample size and genotyping error rates be considered prior to building sequencing libraries, reporting genotyping error rates become standard practice, and that effects of genotyping errors on inference be evaluated in restriction-enzyme-based SNP studies.</p

Совершенствование управления закупками на предприятии (на примере СОАО «Гомелькабель»)

Kinship analyses are important pillars of ecological and conservation genetic studies with potentially far-reaching implications. There is a need for power analyses that address a range of possible relationships. Nevertheless, such analyses are rarely applied, and studies that use genetic-data-based-kinship inference often ignore the influence of intrinsic population characteristics. We investigated 11 questions regarding the correct classification rate of dyads to relatedness categories (relatedness category assignments; RCA) using an individual-based model with realistic life history parameters. We investigated the effects of the number of genetic markers; marker type (microsatellite, single nucleotide polymorphism SNP, or both); minor allele frequency; typing error; mating system; and the number of overlapping generations under different demographic conditions. We found that (i) an increasing number of genetic markers increased the correct classification rate of the RCA so that up to &gt;80% first cousins can be correctly assigned; (ii) the minimum number of genetic markers required for assignments with 80 and 95% correct classifications differed between relatedness categories, mating systems, and the number of overlapping generations; (iii) the correct classification rate was improved by adding additional relatedness categories and age and mitochondrial DNA data; and (iv) a combination of microsatellite and single-nucleotide polymorphism data increased the correct classification rate if &lt;800 SNP loci were available. This study shows how intrinsic population characteristics, such as mating system and the number of overlapping generations, life history traits, and genetic marker characteristics, can influence the correct classification rate of an RCA study. Therefore, species-specific power analyses are essential for empirical studies

Utility of telomere length measurements for age determination of humpback whales

This study examines the applicability of telomere length measurements by quantitative PCR as a tool for minimally invasive age determination of free-ranging cetaceans. We analysed telomere length in skin samples from 28 North Atlantic humpback whales (Megaptera novaeangliae), ranging from 0 to 26 years of age. The results suggested a significant correlation between telomere length and age in humpback whales. However, telomere length was highly variable among individuals of similar age, suggesting that telomere length measured by quantitative PCR is an imprecise determinant of age in humpback whales. The observed variation in individual telomere length was found to be a function of both experimental and biological variability, with the latter perhaps reflecting patterns of inheritance, resource allocation trade-offs, and stochasticity of the marine environment

Genetics, overview

This chapter provides an overview of genetics, which is the study of the transmission of and variation in hereditary traits. In the case of genetic analyses of natural animal populations at the level of organisms or above, most studies draw their inferences from the relative degree of difference in consanguinity among individuals, populations, and species. The confidence with which such inferences can be relied upon depends on the accuracy of the genetic estimates derived from the collected genetic data, which in turn is linked to the amount of genetic data as well as the underlying assumptions made during the analysis of the data. The most common source of genomic DNA is from soft tissue samples. Soft tissue samples are readily available from dead animals, e.g., stranded or killed specimens. The advantage of PCR-based techniques is that only a minute amount of target DNA is required, and hence adequate amounts of DNA are readily obtained from skin biopsies, sloughed skin, hair, and even feces, which can be collected from free-ranging marine mammals with relative ease. © 2009</p