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Whole-genome resequencing allows detection of many rare LINE-1 insertion alleles in humans.

ABSTRACT: High-throughput sequencing has recently begun to revolutionize the study of structural variants in the genomes of humans and other species. More recently, this technology and others have been applied to the study of human retrotransposon insertion polymorphisms (RIPs), yielding an unprecedented catalog of common and rare variants due to insertional mutagenesis. At the same time, the 1000 Genomes Project has released an enormous amount of whole-genome sequence data. In this article, we present evidence for 1016 L1 insertions across all studies to date that are not represented in the reference human genome assembly, many of which appear to be specific to populations or groups of populations, particularly Africans. Additionally, a cross-comparison of several studies shows that, on average, 27% of surveyed nonreference insertions is present in only one study, indicating the low frequency of many RIPs.

SUBMITTER: Ewing AD

PROVIDER: S-EPMC3106331 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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Whole-genome resequencing allows detection of many rare LINE-1 insertion alleles in humans.

Ewing Adam D AD Kazazian Haig H HH

Genome research 20101027 6

High-throughput sequencing has recently begun to revolutionize the study of structural variants in the genomes of humans and other species. More recently, this technology and others have been applied to the study of human retrotransposon insertion polymorphisms (RIPs), yielding an unprecedented catalog of common and rare variants due to insertional mutagenesis. At the same time, the 1000 Genomes Project has released an enormous amount of whole-genome sequence data. In this article, we present ev ...[more]

PMID: 20980553

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Project description:BackgroundOcclusions of intravenous (IV) tubing can prevent vital and time-critical medication or solutions from being delivered into the bloodstream of patients receiving IV therapy. At low flow rates (≤ 1 ml/h) the alarm delay (time to an alert to the user) can be up to 2 h using conventional pressure threshold algorithms. In order to reduce alarm delays we developed and evaluated the performance of two new real-time occlusion detection algorithms and one co-occlusion detector that determines the correlation in trends in pressure changes for multiple pumps.MethodsBench-tested experimental runs were recorded in triplicate at rates of 1, 2, 4, 8, 16, and 32 ml/h. Each run consisted of 10 min of non-occluded infusion followed by a period of occluded infusion of 10 min or until a conventional occlusion alarm at 400 mmHg occurred. The first algorithm based on binary logistic regression attempts to detect occlusions based on the pump's administration rate Q(t) and pressure sensor readings P(t). The second algorithm continuously monitored whether the actual variation in the pressure exceeded a threshold of 2 standard deviations (SD) above the baseline pressure. When a pump detected an occlusion using the SD algorithm, a third algorithm correlated the pressures of multiple pumps to detect the presence of a shared occlusion. The algorithms were evaluated using 6 bench-tested baseline single-pump occlusion scenarios, 9 single-pump validation scenarios and 7 multi-pump co-occlusion scenarios (i.e. with flow rates of 1 + 1, 1 + 2, 1 + 4, 1 + 8, 1 + 16, and 1 + 32 ml/h respectively). Alarm delay was the primary performance measure.ResultsIn the baseline single-pump occlusion scenarios, the overall mean ± SD alarm delay of the regression and SD algorithms were 1.8 ± 0.8 min and 0.4 ± 0.2 min, respectively. Compared to the delay of the conventional alarm this corresponds to a mean time reduction of 76% (P = 0.003) and 95% (P = 0.001), respectively. In the validation scenarios the overall mean ± SD alarm delay of the regression and SD algorithms were respectively 1.8 ± 1.6 min and 0.3 ± 0.2 min, corresponding to a mean time reduction of 77% and 95%. In the multi-pump scenarios a correlation > 0.8 between multiple pump pressures after initial occlusion detection by the SD algorithm had a mean ± SD alarm delay of 0.4 ± 0.2 min. In 2 out of the 9 validation scenarios an occlusion was not detected by the regression algorithm before a conventional occlusion alarm occurred. Otherwise no occlusions were missed.ConclusionsIn single pumps, both the regression and SD algorithm considerably reduced alarm delay compared to conventional pressure limit-based detection. The SD algorithm appeared to be more robust than the regression algorithm. For multiple pumps the correlation algorithm reliably detected co-occlusions. The latter may be used to localize the segment of tubing in which the occlusion occurs. Trial registration Not applicable.

Dataset Information

Whole-genome resequencing allows detection of many rare LINE-1 insertion alleles in humans.

Publications

Whole-genome resequencing allows detection of many rare LINE-1 insertion alleles in humans.

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