A total of 2414 new di-, tri- and tetra-nucleotide non-redundant SSR primer pairs, representing 2240 unique marker loci, have been developed and experimentally validated for rice (Oryza sativa L.). Duplicate primer pairs are reported for 7% (174) of the loci. The majority (92%) of primer pairs were developed in regions flanking perfect repeats > or = 24 bp in length. Using electronic PCR (e-PCR) to align primer pairs against 3284 publicly sequenced rice BAC and PAC clones (representing about 83% of the total rice genome), 65% of the SSR markers hit a BAC or PAC clone containing at least one genetically mapped marker and could be mapped by proxy. Additional information based on genetic mapping and "nearest marker" information provided the basis for locating a total of 1825 (81%) of the newly designed markers along rice chromosomes. Fifty-six SSR markers (2.8%) hit BAC clones on two or more different chromosomes and appeared to be multiple copy. The largest proportion of SSRs in this data set correspond to poly(GA) motifs (36%), followed by poly(AT) (15%) and poly(CCG) (8%) motifs. AT-rich microsatellites had the longest average repeat tracts, while GC-rich motifs were the shortest. In combination with the pool of 500 previously mapped SSR markers, this release makes available a total of 2740 experimentally confirmed SSR markers for rice, or approximately one SSR every 157 kb.
Recent development of DNA markers provides powerful tools for population genetic analyses. Amplified fragment length polymorphism (AFLP) markers result from a polymerase chain reaction (PCR)-based DNA fingerprinting technique that can detect multiple restriction fragments in a single polyacrylamide gel, and thus are potentially useful for population genetic studies. Because AFLP markers have to be analysed as dominant loci in order to estimate population genetic diversity and genetic structure parameters, one must assume that dominant (amplified) alleles are identical in state, recessive (unamplified) alleles are identical in state, AFLP fragments segregate according to Mendelian expectations and that the genotypes of an AFLP locus are in Hardy-Weinberg equilibrium (HWE). The HWE assumption is untestable for natural populations using dominant markers. Restriction fragment length polymorphism (RFLP) markers segregate as codominant alleles, and can therefore be used to test the HWE assumption that is critical for analysing AFLP data. This study examined whether the dominant AFLP markers could provide accurate estimates of genetic variability for the Aedes aegypti mosquito populations of Trinidad, West Indies, by comparing genetic structure parameters using AFLP and RFLP markers. For AFLP markers, we tested a total of five primer combinations and scored 137 putative loci. For RFLP, we examined a total of eight mapped markers that provide a broad coverage of mosquito genome. The estimated average heterozygosity with AFLP markers was similar among the populations (0.39), and the observed average heterozygosity with RFLP markers varied from 0.44 to 0.58. The average FST (standardized among-population genetic variance) estimates were 0.033 for AFLP and 0.063 for RFLP markers. The genotypes at several RFLP loci were not in HWE, suggesting that the assumption critical for analysing AFLP data was invalid for some loci of the mosquito populations in Trinidad. Therefore, the results suggest that, compared with dominant molecular markers, codominant DNA markers provide better estimates of population genetic variability, and offer more statistical power for detecting population genetic structure.
Transgenic animals are an important source of protein and nutrition for most humans and will play key roles in satisfying the increasing demand for food in an ever-increasing world population. The past decade has experienced a revolution in the development of methods that permit the introduction of specific alterations to complex genomes. This precision will enhance genome-based improvement of farm animals for food production. Precision genetics also will enhance the development of therapeutic biomaterials and models of human disease as resources for the development of advanced patient therapies.
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