New Microsatellite DNA Primers for Chimonanthus grammatus Peculiarly Distributed in Southern China

Chimonanthus grammatus M.C.Liu is an endangered and national-protected medicinal plant species with highly restricted geographical distribution and disjunctly locates in the border area of Anyuan and Huichang county of Jiangxi province, China. In this study, we developed ten microsatellite loci for this species for the first time. Nine of them was screened by combining biotin capture method to enrich (CA)15 /(GA)15 microsatellites, and one primer is designed from one EST sequence (DW222670) of Chimonanthus praecox. Ten microsatellite primers were found to be polymorphic through screening 30 individuals. Na was from two to eighteen. Ho and He ranged from 0.233 to 0.933 and 0.326 to 0.898, respectly. Polymorphic information content (PIC) was from 0.316 to 0.890. Ten microsatellite primers will be useful to investigate the genetic structure of Chimonanthus grammatus M.C.Liu and to explain its morphological differentiation from another species in Chimonanthus.

Asymptotic Behavior of k-Word Matches Between two Uniformly Distributed Sequences

Given two sequences of length n over a finite alphabet A of size |A| = d, the D 2 statistic is the number of k-letter word matches between the two sequences. This statistic is used in bioinformatics for EST sequence database searches. Under the assumption of independent and identically distributed letters in the sequences, Lippert, Huang and Waterman (2002) raised questions about the asymptotic behavior of D 2 when the alphabet is uniformly distributed. They expressed a concern that the commonly assumed normality may create errors in estimating significance. In this paper we answer those questions. Using Stein's method, we show that, for large enough k, the D 2 statistic is approximately normal as n gets large. When k = 1, we prove that, for large enough d, the D 2 statistic is approximately normal as n gets large. We also give a formula for the variance of D 2 in the uniform case.

Asymptotic Behavior of k-Word Matches Between two Uniformly Distributed Sequences

Given two sequences of length n over a finite alphabet A of size |A| = d, the D2 statistic is the number of k-letter word matches between the two sequences. This statistic is used in bioinformatics for EST sequence database searches. Under the assumption of independent and identically distributed letters in the sequences, Lippert, Huang and Waterman (2002) raised questions about the asymptotic behavior of D2 when the alphabet is uniformly distributed. They expressed a concern that the commonly assumed normality may create errors in estimating significance. In this paper we answer those questions. Using Stein's method, we show that, for large enough k, the D2 statistic is approximately normal as n gets large. When k = 1, we prove that, for large enough d, the D2 statistic is approximately normal as n gets large. We also give a formula for the variance of D2 in the uniform case.