Genetic relationships among 20 elite wheat genotypes were studied using microsatellite markers and pedigree analysis. A total of 93 polymorphic bands were obtained with 25 microsatellite primer pairs. Coefficient of parentage (COP) values were calculated using parentage information at the expansion level of 5. The pedigree-based similarity (mean 0.115, range 0.00?0.53) was lower than the similarity assessed using microsatellite markers (mean 0.70, range 0.47?0.91). Similarity estimates were used to construct dendrograms by using the unweighted pair-group method with arithmetic averages (UPGMA). Clustering of genotypes in respect of marker-based similarity revealed two groups. Genotype PBW442 diverged and appeared as distinct from all other genotypes in both marker-based and pedigree-based analysis. The correlation of COP values with genetic similarity values based on microsatellite markers is low (r = 0.285, p < 0.05). The results indicate a need to develop wheat varieties with a diverse genetic background and to incorporate new variability into the existing wheat gene pool.
A common wheat (Triticum aestivum L.) mutation that produces 3 pistils (TP) per floret may result in formation of up to 3 kernels per floret. The TP trait may be important for increasing the number of grains per spike and for improving the yield potential through breeding. This trait is determined by the dominant Pis1 gene. Genetic mapping of Pis1 involved 234 microsatellite markers and bulk segregant analysis of a cross of the TP line with Novosibirskaya 67. The Pis1 gene is located on chromosome 2DL, between markers Xgwm539 and Xgwm349. This result does not agree with a previously published localization of the Pis1 gene on chromosome 5B. The possible importance of TP wheat as an alternative genetic resource is discussed.
In search for new markers of insulin-dependent diabetics (IDDM) susceptibility we studied the CATT tetranucleotide repeat in intron 1 of tyrosine hydroxylase (TH) gene on chromosome 11p, the CA repeat at T-cell receptor alpha chain (TCRA) locus on chromosome 14q region containing glutamic acid decarboxylase (GAD2) gene.Alleles at these microsatellite loci were indentified in a population of diabetic children and unrelated healthy controlos originationg from Wielkopolska, a midwestern region of Poland.We found significant association of certain alleles at TH, TCRA and D10S211 loci with diabetes in the population under study.On the contrary, none of the alleles at D10S213 locus was associated with the disease.Our findings indicate that typing of microsatellite markers may represent useful additional tool for identifying individuals at high risk of developing IDDM.Regarding loci on chromosome 10 our data and data publishing by other autors may suggest the existence of two separate regions of associatin with IDDM susceptibility on this chromosome.
Patients with the long QT syndrome (LQTS) suffer from cardiac arrhythmias that can lead to abrupt loss of consciousness and sudden death, already in young individuals. Thus, an early diagnosis of LQTS is essential for patients and their family members. So far, six genes (KCNQ1, HERG, SCN5A, ANK2, KCNE1, KCNE2) have been demonstrated to be involved in the development of LQTS. Since this syndrome is genetically heterogeneous and large-sized families are often not available for linkage analysis, alternative tools are required for a genetic diagnosis. To investigate genes with numerous exons, like KCNQ1, HERG, SCN5A and ANK2, segregation analysis of a Polish Romano-Ward family with eight members was performed as a reliable method faster than linkage analysis or direct sequencing. To test these four LQT loci, an appropriate selection of microsatellite markers covering different chromosomal regions was applied. Furthermore, two small genes KCNE1 and KCNE2 (at the LQT5 and LQT6 loci), and the SGK1 gene (encoding a kinase regulating KCNE1 and SCN5A channels) were sequenced. All six LQT loci and the SGK1 gene were excluded by these analyses, thus a different pathogenic mechanism of LQT syndromes can be presumed.
No information is available on the transferability and amplification quality of microsatellite (SSR) markers of the public domain in Brassica carinata A. Braun. The objective of the presented research was to study the amplification of a set of 73 SSRs from B. nigra (L.) Koch and B. napus L. in B. carinata, and to compare the results with those obtained in the amplification of the same markers in other Brassica species of the U triangle. This set of SSRs from B. nigra (B genome) and B. napus (AC genome) allows the identification of the 3 basic genomes of the Brassica species tested. 94.3% of the SSR markers from B. nigra and 97.4% of those from B. napus amplified SSR-specific products in B. carinata. Very high-quality amplification with a strong signal and easy scoring in B. carinata was recorded for 52.8% of the specific loci from B. nigra SSRs and 59.3% of the specific loci from B. napus SSRs, compared to 66.7% in B. nigra and 62.8% in B. napus. Genome specificity and amplification quality of B. nigra and B. napus SSR markers in the 6 species under study is reported. High-quality transferable SSR markers provide an efficient and cost-effective platform to advance in molecular research in B. carinata.
The aim of this study was to compare the inheritance of the chromosomal SSLP markers with the inheritance of sperm movement parameters in order to map genes responsible for these quantitative traits (QTs). Chromosome 7 and 14 SSLP markers were tested to obtain the strain distribution pattern (SDP) for recombinant inbred (RI) strains developed from two progenitors, KE and CBA/Kw, which differ significantly in gamete quality. Sperm motility characteristics were determined using the computer assisted semen analysis (CASA) system. The Map manager software was used in order to assess linkage between the analyzed motility parameters and chromosome regions. The marker regression, interval mapping and permutation tests matched the QT loci of BCF with chromosome 7q11. The likelihood ratio statistic for this association was 18.1 with 79% of the total trait variance explained by QTL at this locus. These mapping results suggest that the BCF trait depends on the genetic factor(s) located in this region.
Genetic diversity among 35 rice accessions, which included 19 landraces, 9 cultivars and 7 wild relatives, was investigated by using microsatellite (SSR) markers distributed across the rice genome. The mean number of alleles per locus was 4.86, showing 95.2% polymorphism and an average polymorphism information content of 0.707. Cluster analysis based on microsatellite allelic diversity clearly demarcated the landraces, cultivars and wild relatives into different groups. The allelic richness computed for the clusters indicated that genetic diversity was the highest among wild relatives (0.436), followed by landraces (0.356), and the lowest for cultivars. Allelic variability among the SSR markers was high enough to categorize cultivars, landraces and wild relatives of the rice germplasm, and to catalogue the genetic variability observed for future use. The results also suggested the necessity to introgress genes from landraces and wild relatives into cultivars, for cultivar improvement.
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