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        검색결과 4

        1.
        2011.05 구독 인증기관·개인회원 무료
        The differences in the immune response between body lice, Pediculus humanus humanus, and head lice, Pediculus humanus capitis, were regarded as primary factors determining their differential vector competence. To find any differences in genetic components in immune system between body and head lice, whole genome sequences of head lice were determined by both SBS [sequencing by synthesis, Illumina Genome Analyzer (Illumina-GA)] and pyrosequencing (Roche GS FLX), and compared with the reference genome sequences of body lice. The short DNA reads from Illumina-GA (an average mapping depth of 50-fold) were aligned first to the body louse reference genome, to which Roche GS FLX DNA reads (an average depth of 2.5-fold) were subsequently assembled to make up gaps between mapped consensus. Total consensus showed a size of 114 Mb and a coverage of 96% of the published body louse genome sequences. From this head louse genome sequences, a total of 12,651 genes were predicted and used for comparing with the 10,775 genes previously reported from the body louse genome. The homolog analysis identified 873 head louse-specific genes and 422 body lice-specific genes. Comparison of immune response genes between both louse species showed head lice have more number of immune-related genes than body lice. Head lice were determined to possess all of the 107 immune-related genes reported in the previous study (Kim et al., 2011), suggesting that there is no difference in genetic make-up in terms of the 107 immune-related genes between body and head lice.
        2.
        2009.10 구독 인증기관·개인회원 무료
        To search for hyper-variable genetic markers that can distinguish regional populations of head lice, we screened the inter simple sequence repeats (ISSR) based on the genome database of body louse, which is closely related conspecific species. An ISSR mining software, SciRoKo 3.4, was employed to excavate ISSR markers from the genome database under the MISA mode (≥ 60 bp repeats). Entire body louse genome (ca.100 Mb) was loaded to SciRoKo for ISSRs mining. A total of 5,336 ISSRs were obtained, and primers specific to individual ISSRs were designed by the Primer 3 and DesignPrimer 1.0 softwares. In order to prove the compatibility of body louse ISSRs to head lice, 31 PCR primers were randomly chosen out of a total of 613 pairs, and their appropriateness was tested by comparing the amplified PCR band patterns between body and head lice. Eleven primer pairs that resulted in poor or little amplification were excluded, and 20 primer pairs were further tested for three head louse populations (California, Panama and Chung-ju, Korea). Finally, nine primer pairs ensuring robust amplification of highly variable band patterns were selected to use for population genetic study of head lice.
        3.
        2008.05 구독 인증기관·개인회원 무료
        A quantitative sequencing (QS) protocol that detects the frequencies of sodium channel mutations (M815I, T917I and L920F) responsible for knockdown resistance in permethrin-resistant head lice was tested as a population genotyping method. Genomic DNA fragments of the sodium channel α-subunit gene that encompass the three mutation sites were PCR-amplified from individual head lice with either resistant or susceptible genotypes, and combined together in various ratios to generate standard DNA template mixtures for QS. Following sequencing, the signal ratios between resistant and susceptible nucleotides were calculated and plotted against the corresponding resistance allele frequencies. Quadratic regression coefficients of the plots were close to 1, demonstrating that QS is highly reliable for the prediction of resistance allele frequencies. Prediction of resistance allele frequencies by QS in several globally collected lice samples including 12 Korean lice populations suggested that permethrin resistance varied substantially amongst different geographical regions. Three local populations of Korean lice were determined to have 9.8-36.7% resistance allele frequencies, indicating that an urgent resistance management is needed. QS should serve as a preliminary resistance monitoring tool for proper management strategies by allowing early resistance detection.