The use of microsatellites for detecting DNA polymorphism, genotype identification and genetic diversity in wheat

A set of 20 wheat microsatellite markers was used with 55 elite wheat genotypes to examine their utility (1) in detecting DNA polymorphism, (2)in the identifying genotypes and (3) in estimating genetic diversity among wheat genotypes. The 55 elite genotypes of wheat used in this study originated in 29 countries representing six continents. A total of 155 alleles were detected at 21 loci using the above microsatellite primer pairs (only 1 primer amplified 2 loci; all other primers amplified 1 locus each). Of the 20 primers amplifying 21 loci, 17 primers and their corresponding 18 loci were assigned to 13 different chromosomes (6 chromosomes of the A genome, 5 chromosomes of the B genome and 2 chromosomes of the D genome). The number of alleles per locus ranged from 1 to 13, with an average of 7.4 alleles per locus. The values of average polymorphic information content (PIC) and the marker index (MI) for these markers were estimated to be 0.71 and 0.70, respectively. The (GT)_n microsatellites were found to be the most polymorphic. The genetic similarity (GS) coefficient for all possible 1485 pairs of genotypes ranged from 0.05 to 0.88 with an average of 0.23. The dendrogram, prepared on the basis of similarity matrix using the UPGMA algorithm, delineated the above genotypes into two major clusters (I and II), each with two subclusters (Ia, Ib and IIa, IIb). One of these subclusters (Ib) consisted of a solitary genotype (E3111) from Portugal, so that it was unique and diverse with respect to all other genotypes belonging to cluster I and placed in subcluster Ia. Using a set of only 12 primer pairs, we were able to distinguish a maximum of 48 of the above 55 wheat genotypes. The results demonstrate the utility of microsatellite markers for detecting polymorphism leading to genotype identification and for estimating genetic diversity. Received: 15 May 1999 / Accepted: 27 July 1999     

A multi-step phosphorelay two-component system impacts on tolerance against dehydration stress in common wheat

Wheat is an important staple crop, and its productivity is severely constrained by drought stress (DS). An understanding of the molecular basis of drought tolerance is necessary for genetic improvement of wheat for tolerance to DS. The two-component system (TCS) serves as a common sensor-regulator coupling mechanism implicated in the regulation of diverse biological processes (including response to DS) not only in prokaryotes, but also in higher plants. In the latter, TCS generally consists of two signalling elements, a histidine kinase (HK) and a response regulator (RR) associated with an intermediate element called histidine phosphotransferase (HPT). Keeping in view the possible utility of TCS in developing water use efficient (WUE) wheat cultivars, we identified and characterized 62 wheat genes encoding TCS elements in a silico study; these included 7 HKs, 45 RRs along with 10 HPTs. Twelve of the 62 genes showed relatively higher alterations in the expression under drought. The quantitative RT-PCR (qRT-PCR)-based expression analysis of these 12 TCS genes was carried out in wheat seedlings of a drought sensitive (HD2967) and a tolerant (Dharwar Dry) cultivar subjected to either dehydration stress or cytokinin treatment. The expression of these 12 genes under dehydration stress differed in sensitive and tolerant genotypes, even though for individual genes, both showed either up-regulation or down-regulation. In response to the treatment of cytokinin, the expression of type-A RR genes was higher in the tolerant genotype, relative to that in the sensitive genotype, the situation being reverse for the type-B RRs. These results have been discussed in the context of the role of TCS elements in drought tolerance in wheat.     

Genetic dissection of grain weight in bread wheat through quantitative trait locus interval and association mapping

Genetic dissection of grain weight in bread wheat was undertaken through both genome-wide quantitative trait locus (QTL) interval mapping and association mapping. QTL interval mapping involved preparation of a framework linkage map consisting of 294 loci {194 simple sequence repeats (SSRs), 86 amplified fragment length polymorphisms (AFLPs) and 14 selective amplifications of microsatellite polymorphic loci (SAMPL)} using a bi-parental recombinant inbred line (RIL) mapping population derived from Rye Selection111 × Chinese Spring. Using the genotypic data and phenotypic data on grain weight (GW) of RILs collected over six environments, genome-wide single locus QTL analysis was conducted to identify main effect QTL. This led to identification of as many as ten QTL including four major QTL (three QTL were stable), each contributing >20% phenotypic variation (PV) for GW. The above study was supplemented with association mapping, which allowed identification of 11 new markers in the genomic regions that were not reported earlier to harbour any QTL for GW. It also allowed identification of closely linked markers for six known QTL, and validation of eight QTL reported earlier. The QTL identified through QTL interval mapping and association mapping may prove useful in marker-assisted selection (MAS) for the development of cultivars with high GW in bread wheat.     

AFLP-Based Genetic Diversity and Its Comparison with Diversity Based on SSR, SAMPL, and Phenotypic Traits in Bread Wheat

Data on AFLP (eight primer pairs) and 14 phenotypic traits, collected on 55 elite and exotic bread wheat genotypes, were utilized for estimations of genetic diversity. We earlier used these 55 genotypes for a similar study using SSRs and SAMPL. As many as 615 scorable AFLP bands visualized included 287 (46.6%) polymorphic bands. The phenotypic traits included yield and its component traits, as well as physiomorphological traits like flag leaf area. Dendrograms were prepared using cluster analysis based on Jaccard's similarity coefficients in case of AFLP and on squared Euclidean distances in case of phenotypic traits. PCA was conducted using AFLP data and a PCA plot was prepared, which was compared with clustering patterns in two dendrograms, one each for AFLP and phenotypic traits. The results were also compared with published results that included studies conducted elsewhere using entirely different wheat germplasm and our own SSR and SAMPL studies based on the same 55 genotypes used in the present study. It was shown that molecular markers are superior to phenotypic traits and that AFLP and SAMPL are superior to other molecular markers for estimation of genetic diversity. On the basis of AFLP analysis and keeping in view the yield performance and stability, a pair of genotypes (E3876 and E677) was recommended for hybridization in order to develop superior cultivars.     

The effect of different implant biomaterials on the behavior of canine bone marrow stromal cells during their differentiation into osteoblasts

We investigated the effects of different implant biomaterials on cultured canine bone marrow stromal cells (BMSC) undergoing differentiation into osteoblasts (dBMSC). BMSC were isolated from canine humerus by marrow aspiration, cultured and differentiated on calcium phosphate scaffold (CPS), hydroxyapatite, hydroxyapatite in gel form and titanium mesh. We used the MTT method to determine the effects of osteogenic media on proliferation. The characteristics of dBMSC were assessed using alizarin red (AR), immunocytochemistry and osteoblastic markers including alkaline phosphatase/von Kossa (ALP/VK), osteocalcin (OC) and osteonectin (ON), and ELISA. The morphology of dBMSC on the biomaterials was investigated using inverted phase contrast microscopy and scanning electron microscopy. We detected expression of ALP/VK, AR, OC and ON by day 7 of culture; expression increased from day 14 until day 21. CPS supported the best adhesion, cell spreading, proliferation and differentiation of BMSCs. The effects of the biomaterials depended on their surface properties. Expression of osteoblastic markers showed that canine dBMSCs became functional osteoblasts. Tissue engineered stem cells can be useful clinically for autologous implants for treating bone wounds.     

Association of AFLP and SSR markers with agronomic and fibre quality traits in <Emphasis Type="Italic">Gossypium hirsutum</Emphasis> L.

Molecular markers linked to QTL contributing to agronomic and fibre quality traits would be useful for cotton improvement. We have attempted to tag yield and fibre quality traits with AFLP and SSR markers using F₂ and F₃ populations of a cross between two Gossypium hirsutum varieties, PS56-4 and RS2013. Out of 50 AFLP primer combinations and 177 SSR primer pairs tested, 32 AFLP and four SSR primers were chosen for genotyping F₂ individuals. Marker-trait associations were studied for eight agronomic and five fibre quality traits through simple and multiple regression analysis (MRA) using a set of 92 AFLP polymorphic loci and four SSR markers. Simple linear regression analysis (SLRA) identified 23 markers for eight different traits whereas multiple regression analysis identified 30 markers for at least one of the 13 traits. SSR marker BNL 3502 was consistently identified to be associated with fibre strength. While all the markers identified in SLRA were also detected in MRA, as many as 16 of the 30 markers were identified to be associated with respective traits in both F₂ and F₃ generations. The markers explained up to 41 per cent of phenotypic variation for individual traits. A number of markers were found to be associated with multiple traits suggesting clustering of QTLs for fibre quality traits in cotton.