Pak. J. Biotechnol. Vol. 14 (4) 739-744 (2017) www.pjbt.org
ISSN Print: 1812-1837 ISSN Online: 2312-7791
GENETIC DIVERSITY ESTIMATION USING SSR MARKERS AND SOME YIELD COMPONENTS IN SEVEN FORAGE SORGHUM (SORGHUM BICOLOR (L.) MOENCH) Mohammed Hamdan Edan Al-Issawi Agriculture College, University of Anbar, IRAQ. E-mail:
[email protected] Article received 2.11.2017,
Revised 8.12.2017,
Accepted 14.12.2017
ABSTRACT Forage sorghum (Sorghum bicolor (L.) Moench) is a very important fodder crop, therefore the improvement of this crop productivity is required. This study investigated the genetic variability among seven forage sorghum progenies in an experiment that was laid out as CRD in the greenhouse. The genetic diversity was assessed by using SSRs technique as well as some agronomical traits. The results showed that a number of grains per head can be used as an indicator of selection in breeding programs of this crop. However, SSRs result showed that there is variability among progenies under study and showed that the progeny 5 and 6 can be used in breeding programs, as they were very divergent. It can be concluded that there are variability of those progenies and can be utilized in further studies. It can be also recommended using large number of progenies as well as using more DNA-based markers. Keywords: Forage sorghum, SSRs markers, Genetic diversity, cluster analysis.
INTRODUCTION Sorghum (Sorghum bicolor (L.) Moench) comes as fifth in the order of cereal crops production principally after wheat, maize, rice and barley (Cuevas et al., 2014) and it is a very important crop for food and feed for needy people who used to live in semi-arid areas in the world (Tariq et al., 2014). Sorghum also can be widely used as fodder, biofuel, and fiber (Elangovan et al., 2012). One of its genotypes is a forage sorghum that can be easy to establish, highly productive and very good regrowth ability that provides stand over forage in winter. Forage sorghum is vigorously growing and erects annuals as well as branched tillers reaching 2 or 3 meters. Forage sorghum can be grown in dry land and irrigated situations and also can be used for grazing, hay, and silage. However, forage sorghum requires special practices in order to enable it for re-growing and producing good vegetative growth from which high fertility soils, good soil moisture, and irrigation as well as it requires appropriate grazing management in order to maintain forage yield. The success in any plant breeding program is depending on the knowledge of genetic variability for the efficient selection process, therefore the study of genetic variability can be considered as one of the most important conditions for developing and improving new highly yielding verities (Ali et al., 2008, Yaqoob et al., 2015). The variability in the phenotype in a certain environment might be easily noticed, but it reflects all genetic and non-genetic effects on the phenotypic expression of a certain trait (Bello et al., 2007, Yaqoob et al., 2015, Hamza and Rashid, 2017, Abdul Sahib et al., 2017). The estimation of genetic similarity among progenies is helpful for selecting the parental combinations that might create good segregation populations in order to maintain genetic dive-
rsity in a crop breeding program and in the grouping of hybrids into heterotic groups (Van Becelaere et al., 2005). The heterotic groups can be found according to geographical regions, field traits, data of available pedigree as well as molecular markers (Melchinger, 1999). The study of DNAbased markers has been enhanced the utilization of crop improvement biotechnology which studies the genetic diversity among different genotypes, closely related species and GenBank accessions (Cholastova et al., 2011). However, there are many molecular markers that are available for genome analysis in the crops from which simple sequence repeats (SSRs). SSRs particularly are the loci that are comprised of highly variable arrays which are tandemly DNA repeating sequences (e.g. 2 to 6 base pairs long) (Senior et al., 1998). SSRs have advantages over other DNA markers such as they are abundant, uniformity in distribution, highly polymorphic, co-dominant; they can rapidly produced by PCR, they can be easy to interpret as well as they are accessible by laboratories via published sequences of primers (Maroof et al., 1994, Cholastova et al., 2011). However, the measurement of phenotypic and genotypic variability directly in the field is traditionally very common technique to investigate the genetic variation among crop lines, but as environmental effects cannot be avoided, DNA based marker has to be used e.g. SSRs. SSRs is a very powerful approach for studying the genetic diversity among sorghum progenies (Dje et al., 2000, Ghebru et al., 2002), Combining the molecular data analysis and phenotypic data will be very effective in determining the divergent inbred lines in sorghum breeding programs. Thus, this study came to shed light on the genetic variability between
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Mohammed Hamdan Edan Al-Issawi
Pak. J. Biotechnol.
seven forage sorghum progenies by using SSR technique as well as some agronomical traits. MATERIALS AND METHODS Seven local forage sorghum progenies were used in this study, sown on 4th April 2016 with three pots (10 Kg) for each genotype. The layout of the experiment was according to completely randomized design CRD. Plants flowered in 24 June. Samples for molecular analysis were taken at flowering stage. CTAB mini prep protocol was used in order to extract genomic DNA from fresh tissues according to Murray and Thompson (1980). Samples of 100 mg each were placed with 2-3 metal beads in locked tubes in a micro-centrifuge for 4 min. a pre-heat for the CTAB extraction buffer has been done, then 100 µl was added to the samples. The tubes were then placed in the Homogenizer for 3 min followed by a water bath at 60ºC for one hour. Then, 8 µl CIA was added to all samples and then they have been inverted for at least 50 times with the cap tight. Samples (tubes) were then cent-
rifuged at 5000 rpm for 10 min. The supernatant was then transferred to new clean tubes and 600µl of isopropanol (pre-cooled in the freezer) was added, well mixed then incubated on ice for one hour. Then the tubes were centrifuged at 9000 rpm for 5 min to pellet the DNA, the supernatant was then discarded, and tubes were dried. The pellets were washed with 600 of 70% cooled ethanol and incubated on ice for 15 min and again were centrifuged at 9000 rpm for 2 min and the supernatant was discarded and tubes were also dried. They were washed with 500µl of 90% cooled ethanol and placed on ice for another 15 min. then they were centrifuged at 9000 rpm for 2 min and ethanol was removed carefully with a pipette. Finally, DNA samples were dissolved in 100µl TE buffer. Six SSRs primers for sorghum were used as shown in Table 1.
Table 1: The sequences, melting temperature and products size of the primers used in this study. Primers primer 1 primer 2 primer 3 primer 4 primer 5 primer 6
Sequence 5 ------------→ 3’ TCAGTTTTGACTTGCGGTGT CCCTCCCTCAAAACTCTGTG TCACATTTTTGTGCCCAGTC GTTTCTGAGAGGCAGCGAAT TGCTTTGCTTTCTGATGGTG CCACACGGCCTGCTTATTAT TCTCTCAACCTCCGTTCAAAA TGATTTTCATTGGCCTCTGG CAATGCAAAAGGTGCACTACA CCGAGGTGTTTATTCTTCAA GGGAGACCAACGAGGAAAAT AGAGGCCGGACTAGGACTTT
A PCR reaction was performed in a total volume of 25µl, 12.2 master Mix, 2µl (10pmol µl-1) from each primer (Forward and reverse), 4µl of each DNA sample and then the volume was completed to 25 µl by nuclease-free water. The thermal cycle program was as the following: initial denaturation at 95ºC for 4 min, denaturation at 95ºC for 40 Second, Annealing at 55ºC for 1 min and 40 second, extension at 72ºC for 2 min and 30 second (denaturation, annealing, and extension were repeated for 40 cycles) and final extension at 72ºC for 10 min and after that hold at 4ºC. Samples were then checked by gel electrophoresis (2%). The amplified bands of each SSR marker were scored as 0 for the absence of the band and 1 for the presence of it as a Binary matrix. Genetic similarity among the seven forage sorghum progenies that was calculated according to (Nei and Li, 1979) and the clustering analysis was performed using unweighted pair group method
Tm (°C)
Product size (bp)
59
360
59.5
340
55
350
55
362
50
361
54
367
with arithmetic average (UPGMA) by using MVSP version 3.22. At the time of maturity, the observations were done on randomly chosen plants for the studied traits, namely: chlorophyll content (SPAD), stomatal conductance (mmol m-2 sec), number of grain per plant, grain weight (mg) and plant yield (g). Finally, data mean values were subjected to ANOVA analysis in order to assess the significant differences among means as well the genetic diversity according to the aforementioned traits by using Minitab v.18. RESULTS AND DISCUSSION Genetic diversity is a very useful approach in order to distinguish the better genetic materials of the plant that can pass on the desirable traits and neglect the undesirable ones. Based on some quantitative traits the genetic diversity among seven forage sorghum progenies was calculated as well
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as it was measured by using SSR markers. The analysis of variance shown in table 2 using CRD indicated that there are some traits can be used in highlighting the variation among forage sorghum progenies. It is clear that the progenies under study were varied according to the chlorophyll content. Progeny 5 recorded the highest value of chlorophyll (55.52 SPAD units) while progeny 4 recorded the lowest value (36.92 SPAD units) the rest were ranged between those two extremists. The high content of chlorophyll did not reflect high number of grains in the plant, where the progeny 2 recorded the highest number of grains per head indicating that some sorghum genotypes have a high content of chlorophyll which may results in high yield only when plants are exposed to environmental stresses (Harris et al., 2006). Unlike other traits, plant yield (g) was significantly high in progeny 1 and 7 as they gave 36.92 and 36.16 g respectively (Table 2), and that makes them good materials in crop improvement and breeding programs. As for stomatal conductance and grain weight, those two traits did not show significant differences among 7 progenies, therefore, they have to be neglected when genetic diversity among the forage sorghum progenies is required.
Genetic diversity estimation …..
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In order to investigate the variability pattern among the progenies under study, descriptive statistical analysis showed that the number of grains in plant recorded the highest value of mean, standard error mean, standard deviation and variance; 311.48, 9.84, 45.08 and 2030.40 for the aforementioned parameters respectively, while the stomatal conductance showed the highest value of coefficient of variance (34.09) (Table 3). The high variance in a number of grains in plant indicated the appearance of the morphological diversity among the forage sorghum progenies and this is suitable for crop improvement by hybridization or selection. In table 3, the coefficient of variance in grain weight and plant yield providing information that those traits are very sensitive to the environmental conditions. Table 4 showed the correlation between the studied traits, which all were non-significant, only the correlation between the grain weight and the number of grains per plant. They appear to be negatively and significantly correlated (-0.96, P
