Comparative Analysis for the Performance of Variant Calling Pipelines on Detecting the de novo Mutations in Humans

Despite of the low occurrence rate in the entire genomes, de novo mutation is proved to be deleterious and will lead to severe genetic diseases via impacting on the gene function. Considering the fact that the traditional family based linkage approaches and the genome-wide association studies are unsuitable for identifying the de novo mutations, in recent years, several pipelines have been proposed to detect them based on the whole-genome or whole-exome sequencing data and were used for calling them in the rare diseases. However, how the performance of these variant calling pipelines on detecting the de novo mutations is still unexplored. For the purpose of facilitating the appropriate choice of the pipelines and reducing the false positive rate, in this study, we thoroughly evaluated the performance of the commonly used trio calling methods on the detection of the de novo single-nucleotide variants (DNSNVs) by conducting a comparative analysis for the calling results. Our results exhibited that different pipelines have a specific tendency to detect the DNSNVs in the genomic regions with different GC contents. Additionally, to refine the calling results for a single pipeline, our proposed filter achieved satisfied results, indicating that the read coverage at the mutation positions can be used as an effective index to identify the high-confidence DNSNVs. Our findings should be good support for the committees to choose an appropriate way to explore the de novo mutations for the rare diseases

Detecting Snowfall Events over Mountainous Areas Using Optical Imagery

Snowfall over mountainous areas not only has important implications on the water cycle and the Earth’s radiation balance, but also causes potentially hazardous weather. However, snowfall detection remains one of the most difficult problems in modern hydrometeorology. We present a method for detecting snowfall events from optical satellite data for seasonal snow in mountainous areas. The proposed methodology is based on identifying expanded snow cover or suddenly declined snow grain size using time series images, from which it is possible to detect the location and time of snowfall events. The methodology was tested with Moderate Resolution Imaging Spectroradiometer (MODIS) daily radiance data for an entire hydrologic year from July 2014 to June 2015 in the mountainous area of the Manas River Basin, Northwest China. The study evaluated the recordings of precipitation events at eighteen meteorological stations in the study area prove the effectiveness of the proposed method, showing that there was more liquid precipitation in the second and third quarter, and more solid precipitation in the first and fourth quarter

Exposure to heavy metal elements may significantly increase serum prostate-specific antigen levels with overdosed dietary zinc

Background: Serum prostate-specific antigen (PSA) is a primary metric for diagnosis and prognosis of prostate cancer (PCa). Exposure to heavy metals, such as lead, cadmium, mercury, and zinc can impact PSA levels in PCa patients. However, it is unclear whether this effect also occurs in men without PCa, which may lead to the overdiagnosis of PCa. Method: Data on a total of 5089 American men who had never been diagnosed with PCa were obtained from the National Health and Nutrition Examination Survey performed from 2003–2010. The relationship between serum PSA levels (dependent variable) and concentrations of lead (μmol/L), cadmium (nmol/L), and mercury (μmol/L) were investigated with dietary zinc intake being used as a potential modifier or covariate in a weighted linear regression model and a generalized additive model. A series of bootstrapping analyses were performed to evaluate sensitivity and specificity using these models. Results: Regression analyses suggested that, in general, lead, cadmium, or mercury did not show an association with PSA levels, which was consistent with the results of the bootstrapping analyses. However, in a subgroup of participants with a high level of dietary zinc intake (≥14.12 mg/day), a significant positive association between cadmium and serum PSA was identified (1.06, 95% CI, P = 0.0268, P for interaction=0.0249). Conclusions: With high-level zinc intake, serum PSA levels may rise in PCa-free men as the exposure to cadmium increases, leading to a potential risk of an overdiagnosis of PCa and unnecessary treatment. Therefore, environmental variables should be factored in the current diagnostic model for PCa that is solely based on PSA measurements. Different criteria for PSA screening are necessary based on geographical variables. Further investigations are needed to uncover the biological and biochemical relationship between zinc, cadmium, and serum PSA levels to more precisely diagnose PCa