ASSOCIATION OF PECTORALIS MINOR MUSCLE LENGTH AND SHOULDER RANGE OF MOTION AMONG INDIVIDUALS WITH AND WITH OUT SHOULDER PAIN

Background and Aim: To evaluate the association of pectoralis minor muscle length and the shoulder range of motion with and without shoulder pain. Methodology: A sample of 214 participants with and without shoulder pain were enrolled in an analytical cross sectional study at Institute of physical medicine and rehabilitation, Dow University of health sciences, Karachi.  Questionnaire was provided to all participants after taking consent. Individuals were categorized into two equal groups i.e. one with and the other without pain). Shoulder active ranges were measured with universal goniometer and pectoralis minor length with measuring tape. Statistical Package of Social Sciences version 21 was used for data analysis. The descriptive variables were assessed for frequencies and percentages. Continuous variables were shown with mean and standard deviations and were correlated with bivariate correlation test. Considered significant was 0.05 p value. Results: Females were 176(82.2%) and males were 38 (17.8%). Mean ± SD of age, weight, height, and BMI were 26.82 ±7.50, 58.45 ±12.11, 160.59 ± 12.43, and 22.18 ±3.78 respectively. The pain intensity negatively correlated with shoulder range of motions (rs = -0.307 to -0.775, p< 0.05) except medial rotation.  Significant difference (p< 0.05) is found for length of pectoralis minor and range of motion between groups. There was also weak positive correlation between pectoralis minor index and shoulder lateral rotation (rs =0.215; p = 0.003). Conclusion: The shoulder pain affects shoulder joint range of motion and pectoralis minor length. Decreased pectoralis minor muscle length accompanies limited shoulder range of motion except, medial rotation.

Genetic Diversity and Genotype by Environment Studies in Upland Cotton

Field testing across different environments can help to identify genotypes with relatively stable performance. A total of 28 upland cotton genotypes were field tested during 2012 and 2013 at three locations (Peshawar, Dera Ismail Khan and Faisalabad, Pakistan). To ascertain QTL associations with various traits, the laboratory study was conducted at the National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Pakistan. Combined analysis of variance for genotypes across years and locations (G × Y × L) interactions revealed significant differences among genotypes for all the traits. Genotypic means over years had significant differences for all the traits except plant height, sympodia per plant, lint index and fiber traits. Genotypes over locations exhibited significant differences for all traits except days to first flowering and some fiber quality traits. Interactions due to G × Y × L were significant for monopodia and sympodia per plant, bolls per sympodia, bolls per plant, seeds per boll, seed index, ginning outturn and seed cotton yield per plant. Genotypic means for various traits across different environments (Y × L) revealed that NIBGE-4 and IR-NIBGE-2620 had maximum bolls per sympodia (2.33 and 2.45), bolls per plant (54.46 and 53.17), boll weight (3.16 and 3.03 g), seed index (8.42 and 8.18 g), seed cotton yield per plant (197.82 and 182.89 g), and desirable minimum plant height (132.04 and 125.29 cm). Genotypes IR-2379 and IR-NIBGE-5 showed maximum sympodia per plant (23.50 and 28.22), seeds per boll (28.18 and 27.93), lint index (4.32 and 4.90 g), fiber strength (30.58 and 32.59 g/tex), fiber uniformity ratio (80.72 and 81.86) and desirable minimum values for days to first flowering (51.56 and 52.72 days) and short fiber index (9.14 and 9.92). Genotypes CIM-554, CIM-473 and NIBGE-2472 showed maximum ginning outturn (38.72, 37.11 and 32.52%), fiber length (26.88, 25.89 and 27.07 mm), fiber elongation (6.09, 6.17 and 7.23%), fiber color (60.08, 58.19 and 58.21), and desirable minimum mean values for monopodia per plant (0.72, 1.10 and 1.32) and micronaire (4.19, 3.68 and 4.31 μg/inch). viii Comparative performance of genotypes across two years and three locations observed that all the studied genotypes showed best performance during 2013 at Peshawar. During 2013, on average all the genotypes expressed maximum mean values for sympodia per plant, bolls per sympodia, bolls per plant, seeds per boll, seed index, lint index, ginning outturn, seed cotton yield, fiber length, uniformity index and fiber elongation. Overall, the genotypes grown during 2012 revealed desirable minimum mean values for days-to-first flowering, plant height, monopodia per plant and micronaire. Analysis of locations revealed that on average at Peshawar, the cotton genotypes showed maximum mean values for bolls per plant, bolls per sympodia, bolls per plant, boll weight, seeds per boll, seed index, lint index, ginning outturn, seed cotton yield, fiber length, fiber strength, uniformity index, fiber elongation and fiber maturity. However, the cotton genotypes grown at NIBGE showed more earliness followed by D.I.Khan. In G × Y × L interactions, on average the genotypes CIM-473, CIM-499, NIBGE-4, NIBGE-5, IR-2379 and IR-NIBGE-5 grown during 2013 at Peshawar and D.I.Khan, showed maximum bolls per sympodia, bolls per plant, boll weight, seeds per boll, seed cotton yield and fiber length. Genotypes CIM-506, IR-NIBGE-5, NIBGE-2472 and IR-1526 showed maximum sympodia per plant, ginning outturn, fiber strength, fiber elongation when grown during 2012 at Peshawar followed by D.I.Khan. Overall, the genotypes IR-NIBGE-3, NIBGE-4 and NIBGE-115 grown during 2012 at NIBGE and D.I.Khan showed desirable minimum mean values for days to first flowering, plant height, monopodia and micronaire. Correlation coefficients of seed cotton yield were significant with days to first flowering, plant height, monopodia and sympodia per plant, bolls per sympodia, bolls per plant, boll weight, seeds per boll, seed index, lint index, ginning outturn, fiber length micronaire, short fiber index and fiber color. For molecular characterization of these 28 cotton genotypes, 100 simple sequence repeat (SSR) markers were used, out of which 22 markers were polymorphic. Major allele frequency for genotypes ranged from 0.29 (MGHES-20) to 0.93 (MGHES-15) with an average of 0.54, while the average gene diversity was 0.57 ranging from 0.13 (MGHES-15) to 0.78 (MGHES-20). Polymorphism information content (PIC) values ranged from 0.12 (MGHES-15) to 0.75 (BNL-3280) with an average of 0.53. Based on phylogenetic tree, all the genotypes were divided into two major groups with further division of five sub-groups. In population structure, all the genotypes at delta (K ix = 2) were divided into two main groups i.e. G1 (1-10) and G2 (11-28). In group first, three genotypes i.e. NIBGE-115, NN-3 and NIBGE-2472 showed some relatedness with genotypes in the second group. In association mapping, overall 63 quantitative trait loci (QTLs) were identified in which 53 QTLs were observed through general linear model (GLM) approach, while 10 QTLs were identified via mixed linear model (MLM) approach for various traits in these cotton genotypes. For morphological traits, chromosome 16, 9, 19 and 18 contained two QTLs while for yield and yield traits, seven QTLs were observed on chromosome 16 and five on chromosome 18. For fiber quality traits, nine QTLs were observed on chromosome 16. Overall, 18 QTLs were found on chromosome 16 followed by chromosome 18 having seven QTLs for various traits in upland cotton genotypes. Overall, the genotypes showed maximum seed cotton yield grown during 2013 at Peshawar followed by at D.I.Khan. The genotype NIBGE-4 showed best performance during both the years at all the locations. However, three other genotypes i.e., IR-NIBGE-2620, NIBGE-5 and IR-NIBGE-5 followed the above promising genotype and also showed earliness and increased seed cotton yield across all the environments. In phylogenetic analysis, all the 28 genotypes were divided into two major groups and further into five subgroups based on genetic distances. In structure analysis, based on pedigree all the cotton genotypes were divided into two major groups. Association mapping showed that 63 QTLs associated with different traits in these genotypes in which 53 QTLs were identified through GLM approach while 10 QTLs were recognized through MLM approach. Both GLM and MLM approaches identified some QTLs on same chromosome with same position for various traits, and confirmed that the identified QTLs were found on corresponding chromosomes. The detected QTLs will be helpful in identifying and understanding the genetic basis of different traits and diversity in these upland cotton genotypes. The favorable QTLs might facilitate in future high-yield breeding through genomic selection in upland cotton.