Pollen identification and classification are important not only for palynologists, but also for systematists and ecologists. Because palynological methods for the identification of pollen in surface soil until now could resolve at best to the generic level, we have developed a molecular approach to species-level identification of Chenopodiaceae pollen in surface soils. Surface soil samples were collected in the central area of Junggar Desert Basin, Xinjiang, China. Fresh leaves of 19 Chenopodiaceae species were sampled for DNA sequencing, establishing a database of internal transcribed spacer (ITS) regions of nuclear ribosomal DNA for Chenopodiaceae. Individual chenopod pollen grains in a soil sample were separated from the soil and the ITS1 region of each pollen grain was amplified using nested PCR and sequenced. By comparing the amplified ITS1 sequences to those in the Chenopodiaceous database, we identified the pollen in the soil samples to the level of species. The new method provides a technical reference for species identification of soil surface pollen for other families. This work is necessary for further efforts to interpret the relationship of surface soil pollen to vegetation characteristics. It also has significant potential for enhancing the ability to identify pollen in clinical airborne allergen or criminological studies.
Association rule mining among frequent items has been extensively studied in data mining research. However, in recent years, there is an increasing demand for mining infrequent items (such as rare but expensive items). Since exploring interesting relationships among infrequent items has not been discussed much in the literature, in this chapter, the authors propose two simple, practical and effective schemes to mine association rules among rare items. Their algorithms can also be applied to frequent items with bounded length. Experiments are performed on the well-known IBM synthetic database. The authors’ schemes compare favorably to Apriori and FP-growth under the situation being evaluated. In addition, they explore quantitative association rule mining in transactional databases among infrequent items by associating quantities of items: some interesting examples are drawn to illustrate the significance of such mining.
ABSTRACT. In order to examine DNA sequence variation, the cause of geographic patterns and historical demography of populations, we sampled 69 individuals of Midday gerbil Meriones meridianus. Among the comparable sequences of 396 bp, 52 haplotypes were defined, 97 nucleotide sites were variable (24.5% in the full sequences). Phylogenetic tree constructed using the neighbor-joining (NJ) of haplotypes demonstrated three clades associated with geographical regions. There were no shared haplotypes found among regions. Time of gene divergence between three clades of Midday gerbil was estimated by mean nucleotide difference, suggesting the divergence of three clades during the Middle Pleistocene. The pattern of phylogenetic discontinuity is a result of both factors which is associated with the uplift of the Qinghai-Tibet Plateau and climate change in Quaternary ice ages. We also examined the historical demography of the clades using stepwise and exponential expansion models, both of which indicated recent rapid population growth. The pairwise mismatch distribution suggested a pattern of population expansion. The population expansion analysis indicated that the present distribution of the population was probably shaped through the rapid range expansion during the last interglaciation stage from the refugium.KEY WORDS: Midday gerbil, mitochondrial DNA control region, phylogeography, historical demography.
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