Mode of reproduction and amplified fragment length polymorphism variation in purple needlegrass (Nassella pulchra): utilization of natural germplasm sources

A dominant plant of the California grasslands, purple needlegrass [Nassella pulchra (Hitchc.) Barkworth] is an important revegetation species in its native range. The amplified fragment length polymorphism (AFLP) method was used to elucidate mode of reproduction and nucleotide variation among 11 natural populations and three selected natural germplasm releases of N. pulchra. A total of 12 co-dominant AFLPs, informative within eight populations, failed to reveal any heterozygous individuals, indicating very high selfing rates (S(H)=1). Estimates of nucleotide diversity within populations ranged from 0 to 0.00069 (0.00035 average), whereas the total nucleotide divergence among populations ranged from 0.00107 to 0.00382 (0.00247 average). Measures of population differentiation (GS) in terms of Shannon-Weaver diversity values and estimated nucleotide substitutions were 0.90 and 0.86, respectively. Although some of the sample populations contained a mixture of true breeding genotypes, most populations could be distinguished unambiguously. Moreover, geographical distance between the natural source populations was significantly correlated with genetic distance (r = 0.60) among the corresponding sample populations. Results indicate that inbreeding, combined with founder effects and/or selection, has contributed to the differentiation of N. pulchra populations. Foundation seed populations of the selected natural germplasm releases were genetically well defined and most similar to natural seed collected near the corresponding source populations. Thus, these commercial germplasm sources will be made practically available and useful for conservation plantings within the intended areas of utilization.     

On different approximations to multilocus identity-by-descent calculations and the resulting power of variance component-based linkage analysis

An empirical comparison between three different methods for estimation of pair-wise identity-by-descent (IBD) sharing at marker loci was conducted in order to quantify the resulting differences in power and localization precision in variance components-based linkage analysis. On the examined simulated, error-free data set, it was found that an increase in accuracy of allele sharing calculation resulted in an increase in power to detect linkage. Linkage analysis based on approximate multi-marker IBD matrices computed by a Markov chain Monte Carlo approach was much more powerful than linkage analysis based on exact single-marker IBD probabilities. A "multiple two-point" approximation to true "multipoint" IBD computation was found to be roughly intermediate in power. Both multi-marker approaches were similar to each other in accuracy of localization of the quantitative trait locus and far superior to the single-marker approach. The overall conclusions of this study with respect to power are expected to also hold for different data structures and situations, even though the degree of superiority of one approach over another depends on the specific circumstances. It should be kept in mind, however, that an increase in computational accuracy is expected to go hand in hand with a decrease in robustness to various sources of errors.     

Release characteristics of novel pH-sensitive p(HEMA-DMAEMA) hydrogels containing 3-(trimethoxy-silyl) propyl methacrylate

An amphiphilic hydrogel of poly(2-hydroxyethyl methacrylate) cross-linked with tetraethyleneglycol diacrylate (TEGDA) was synthesized to contain the hydrophobic monomer 3-(trimethoxy-silyl) propyl methacrylate (PMA) and the pH-responsive, hydrophilic monomer N',N'-dimethylaminoethyl methacrylate (DMAEMA). The gels were separately loaded with two biomolecular probes, insulin and protamine, via both physical entrapment and equilibrium imbibition methods. The release profiles for these biomolecular probes, possessing similar MW (5.7 and 4-6 kDa, respectively) but different pI's (5.3 and 10.0, respectively), were investigated with respect to variation in the pH of the bathing medium as well as the DMAEMA content, and the cross-link density of the hydrogel. Gels exhibited classical Fickian diffusion release profiles. For a typical gel composition 66:15:10:09 mol % (HEMA:DMAEMA:PMA:TEGDA), as the pH of the release media decreased from 7.3 to 4.0, the rate of release of both biomolecular probes increased. When loaded via entrapment, the insulin release rate increased ca. 4-fold (1.0-3.7 x 10(-7) cm(2) s(-1)), whereas that of protamine increased 10-fold (0.3-3.3 x 10(-7) cm(2) s(-1)). When loaded by imbibition, the insulin diffusion coefficient increased 2-fold (3.8-7.2 x 10(-7) cm(2) s(-1)), whereas that of protamine increased 3-fold (1.9-5.5 x 10(-7) cm(2) s(-1)). The reduction of pH, through its protonation of the gel network, has a more dramatic influence on protamine release, the result of its higher pI (10.0) compared to that of insulin (5.3). As the DMAEMA content of the hydrogel was increased from 0 to 20 mol %, the diffusion coefficient of protamine increased by ca. 7-fold (1.7-12.2 x 10(-7) cm(2) s(-1)), whereas that of insulin increased only ca. 2-fold (1.7-4.0 x 10(-7) cm(2) s(-1)). This differential release confirms the role of internal protonation in effecting the greater release of the protonated drug molecule. Increasing the TEGDA content from 3 to 15 mol % reduced the diffusion coefficient ca. 3-fold for insulin (1.6-0.5 x 10(-7) cm(2) s(-1)) and 5-fold for protamine (4.0-0.8 x 10(-7) cm(2) s(-1)). The final D(ip) at 15 mol % TEGDA suggests that the smaller mesh size offsets any differential release that arises from protonation. The presence of PMA in the hydrogel formulation, which contributes additional cross-links by reason of the formation of siloxane macromers, did not change the usually observed Fickian diffusion mechanism.