13561nam a2200205Ia 4500005001700000008004000017041000800057082001100065100002500076110004200101245011700143260000900260502128510026965000481312065000231316870000371319194200071322899900151323595201051325020170807124605.0150525s2012 xx 000 0 und d aeng a1504,T aFayyaz Rasool934789 cProf. Dr. Naureen Aziz Qureshi934790 aStudies On Genetic Diversity Of Labeo Rohita And Cirrhinus Mrigala By Using Molecular Markers In Punjab-Pakistan c2012 aThe studies on genetic diversity of Labeo rohita and Cirrhinus mrigala by using molecular markers in Punjab-Pakistan were carried out to investigate the genetic structure of said Indian major carps by RAPAD marker and the levels of polymorphism and similarity amongst the different groups of five populations of wild and farmed types. The results obtained from the present study after statistical analyses are presented in section-4 of this dissertation. The samples were collected from the following sites; for farmed fish was collected from UVAS-Fish Hatchery, C-block Ravi campus Pattoki district Kasur and for wild fish; from Trimu Barrage at the junction of River Chenab and Jhelum near district Jhang, Taunsa Barrage at River Indus near tehsil Kot Adu district Muzaffar Garh, Qadirabad Barrage at River Chenab near district Mandi Bahuddin and Baloki Barrage at River Ravi near tehsil Bhai Phero district Kasur. Analysis of variance (ANOVA) for the different morphometric parameters of study and Pearson's correlation among the physico-chemical parameters of water quality was done by Minitab statistical computer software. The XLSTAT 2012 version 1.02 of the computer software was used for the Pearson correlation analysis of the morphometric parameters of study. The same computer program was used for Agglomerative Hierarchical Clustering (AHC) of the different genotype occurrence on the basis of differences in morphometric parameters was done by Agglomeration method by following the Unweighted Pair Group Method with Arithmetic Mean (UPGMA). The Principle Component Analysis (PCA) on the basis of differentiation in morphometric parameters by Eigenvalues and differentiation into factors of the different genotypes from the different environmental conditions was done by correlation bi-plot/coefficient of the correlation (n) method in the same program. This software was also used to analyze the RAPAD data for Jaccard's coefficient by following the Unweighted Pair Group Method with Arithmetic Mean (UPGMA) for Hierarchical Clustering of the similar groups on the basis of similarity amongst the genotypes and the dendrogram generated is presented in the next section. The Principal Component Analysis (PCA) for grouping of the different genotypes from the different environmental conditions was done by Spearman Varimax rotation method for bi-plot generation of the co-occurrence of the same genotypes with similar genetic properties and specificity of different primersin the same program.
Following results were obtained:
Morphometric Parameters
1. Morphometric parameters of L. rohitashowed following trends: body weight, total length and average length of paired pectoral fins were nonsignificantly different (p > 0.05), fork length, dorsal fin length, caudal fin length and average length of paired pectoral fins were highly significantly different (p < 0.01) while anal fin length was significant different (p < 0.05) among the experimental sites. In case of C. mrigala, the body weight was non-significantly different (p > 0.05) while all other parameters were highly significantly different (p < 0.01) except the dorsal fin length which was significantly different (p < 0.05) among the study sites.
2. The results of the Pearson correlation of morphometric parameters showed that body weight of L. rohita developed a positive and highly significant (p< 0.0001) correlation with all the remaining morphometric parameters, the fork length of the said species showed a positive and highly significant (p< 0.0001) correlation with all the parameters except with the caudal fin length where the correlation was also positive but non-significant (p = 161). In case of total length of the fish body, the correlation was highly significant (p< 0.0001) and positive with all the parameters of study.The length of the dorsal fin showed highly significant (p< 0.0001) and positive correlation with all the remaining morphometric parameters under study. The caudal fin length of L. rohita showed a positive and highly significant (p< 0.0001) correlation with all the other parameters except the fork length where the correlation was positive but non-significant (p = 161). The correlation of the anal fin length of the fish body showed a highly significant (p< 0.0001) and positive correlation trends. The average length of the paired pectoral fins showed a positive and highly significant (p< 0.0001) correlation with all the remaining morphometric parameters of study, the correlation of paired pelvic fins average length showed positive and highly significant (p< 0.0001) correlation with other parameters.
3. The body weight of C. mrigala developed a positive and highly significant (p< 0.0001) correlation with all the remaining morphometric parameters. The fork length of the said species showed a positive and highly significant (p< 0.0001) correlation with body weight, total length and dorsal fin length while this correlation was positive but non significant with the caudal fin length (p = 0.228), anal fin length (p = 0.168), average length of paired pectoral fins (p = 0.031) and average length of the paired pelvic fins (p = 0.106). In case of total length of the fish body, the correlation was highly significant (p< 0.0001) and positive with all the parameters of study. The length of the dorsal fin showed highly significant (p< 0.0001) and positive correlation with all the remaining morphometric parameters under study. The caudal fin length of C. mrigala showed a positive and highly significant (p< 0.0001) correlation with all the other parameters except the fork length where the correlation was positive but non-significant (p = 0.228).The correlation of the anal fin length of the fish body showed a highly significant (p< 0.0001) and positive correlation trends with all the parameters except the fork length where the correlation was positive but non-significant (p = 0.168). The average length of the paired pectoral fins showed a positive and highly significant (p< 0.0001) correlation with all the remaining morphometric parameters of study except the fork length where the correlation was positive but non-significant (p = 0.031). InC. mrigala, the correlation of paired pelvic fins average length showed positive and highly significant (p< 0.0001) correlation with other parameters except the fork length where the correlation was positive but non-significant (p = 0.106).
4. Dendrogram generated on the basis of morphometric parameters of study dividedL. rohita genotype in to five major clusters or classes with 19.24% for within class variation while 80.76% for the between class differences. While the dendrogram developed for C. mrigala divided the genotypes in to four major clusters or classes with 27.28% for within class variation while 72.72% for the between class differences.
5. The results obtained from the PCA for morphometric parameters of L. rohitaand C. mrigalaindicated clearly that the increase in the number of factors or components was correlated with the decrease in eigenvalues. The values showed that its trend reached its maximum at level of second factor. In the same way according to the Kaiser (1958) criterion based upon the eigenvalues greater than one, first two main factors accounted for 80.273% of cumulative variability for L. rohita and 82.558% for C.mrigala. The PCA grouped the tested variables or parameters of the L. rohita,the first group amongst the major two groups accounted for 64.245% of the cumulative variability while the second from these accounted for 16.028% of the cumulative variability. The PCA grouped C. mrigala,also into two groups, the first group amongst the major two groups accounted for 59.323% of the cumulative variability while the second from these accounted for 23.235% of the cumulative variability.
6. The physico-chemical parameters of the water samples of all study sites were analyzed for correlation among them. The results were as follows; the correlation of the pH with water temperature (r= 0.107) and dissolved oxygen (r = 0.905) was positively non-significant while the correlation with electrical conductivity (r = -0.798), salinity (r= -0.888), total dissolved solids (r = -0.857), total alkalinity (r = -0.736) and total hardness (r = -0.499) was negatively non-significant. The correlation of the dissolved oxygen with water temperature (r= 0.313) was positively non-significant while the correlation with electrical conductivity (r = -0.669), salinity (r= -0.828), total dissolved solids (r = -0.809), total alkalinity (r = -0.930) and total hardness (r = -0.300) was negative but also non-significant as like with the water temperature. The electrical conductivity was positively correlated with all the physic-chemical parameters as with water temperature (r= 0.482), salinity (r= 0.925), total dissolved solids (r = 0.889), total alkalinity (r = 0.452) and total hardness (r = 0.906) and this correlation was non significant.The salinity amongst the water parameters was correlated positively with water temperature (r = 193), total alkalinity (r = 0.717) and total hardness (r = 0.734) and it was non-significant but with total dissolved solids (r = 0.994) the correlation was also positive but highly significant (P < 0.001). The total dissolved solids values observed from the study sites were positively correlated with water temperature (r = 0.172), total alkalinity (r = 0.734) and total harness (r = 0.657) and this correlation was non-significant. The correlation between the total alkalinity and total hardness was also positive and non-significant (r = 0.048).
RAPAD Data
1. In case of L. rohita, OPB-1 polymorphism remained as 16.67%, OPB-3 polymorphism remained as 40.00%, OPB-4, polymorphism remained as 16.67%, OPB-5 polymorphism remained as 20.00%, OPB-7 polymorphism was 28.57%, OPB-8 polymorphism was 20.00%, OPB-9 polymorphism was 25.00%, OPB-10 polymorphism was 28.57%, OPC-19 polymorphism was 14.29% and OPD-4 showed 50.00% polymorphism in amplification. In case of C. mrigala, OPB-1 polymorphism remained as 16.67%, OPB-3 polymorphism remained as 16.67%, OPB-4 polymorphism remained as 25.00%, OPB-5 polymorphism remained as 14.29%, OPB-7 polymorphism was 14.29%, OPB-8 polymorphism was 20.00%, OPB-9 polymorphism was 20.00%, OPB-10 polymorphism was 20.00%, OPC-19 polymorphism was 28.57% and OPD-4 polymorphism remained as 33.33% in amplification.
2. The dendrogram generated by UPGMA of RAPAD data of L. rohita by the randomly selected individuals with high scorable bands of the five populations grouped themselves in the first class/cluster while a single sample designated as Indus2 from the population from River Indus collected from Taunsa Barrage represents the second class/cluster and in same way only single individual designated as Ravi2 collected from River Ravi from the Baloki Barrage represents the third class. The dendrogram generated by UPGMA of RAPAD data of C. mrigala by the randomly selected individuals of the five populations grouped themselves in the first class/cluster and two samples designated as Indus2 and Qad2 from the populations from River Indus collected from Taunsa Barrage and River Chenab from Qadirabad Barrage represents the second class/cluster while one individual from the Trimu Barrage at the junction of Jhelum and Chenab Rivers designated as Trimu2 represents the third class and in the same way only single individual designated as Ravi2 collected from River Ravi from the Baloki Barrage represents the third class.
3. The PCA resultsfor L. rohitait can be assumedthat PCA grouped the tested variables or parameters of the fish RAPAD amplification data into two main components which all together accounted for 58.177% of the cumulative variation among the factors. The first group (F1) amongst the major two groups accounted for 33.327% of the cumulative variability while the second (F2) from these accounted for 24.850% of the cumulative variability. These results were also confirmed after the varimax rotation. By the PCA resultsfor C. mrigalawe can assume after observing the results that the PCA grouped the tested variables or parameters of the fish RAPAD amplification data into two main components which all together accounted for 70.866% of the cumulative variation among the factors. The first group (F1) amongst the major two groups accounted for 51.115% of the cumulative variability while the second (F2) from these accounted for 19.751% of the cumulative variability.
This study in this way has provided the genetic information of the present fish species and how evolutionary processes are affecting the fish fauna. So this study along with the strengthening of the academic research area has also proven an applied research which will help the breeders to the chose most fit candidates for the breeding program in the Pakistan.
aDepartment of Fisheries & Aquaculture96203 aPhd. thesis934791 aProf. Dr. Muhammad Ashraf934792 cTH c3208d3208 00104061504T708VS94135aMAINbMAINcTHEd2015-05-29o1504,Tp1504,Tr2015-05-29w2015-05-29yTH