Genetic analysis of dormancy and shattering traits in the backcross inbred lines derived from Oryza sativa cv. Swarna / O. nivara Ac. CR100008

2020 ◽  
Vol 57 (1) ◽  
pp. 1-13
Author(s):  
Anusha Galimudi ◽  
Eswari KB ◽  
Lakshmidevi Gandhudi ◽  
Jai Vidhya LRK ◽  
Narender Reddy S ◽  
...  

Seed dormancy and shattering are important traits influencing the economics of rice farming. The genetic basis of dormancy and shattering traits were investigated in 174 Backcross Inbred Lines (BILs) derived from Oryza sativa cv. Swarna and O. nivara ac. CR100008. Significant variation was observed among the BILs for dormancy and shattering traits. Dormancy of 4-40 days was observed among BILs harvested at 35 days after heading and all the BILs attained > 80% germination by 6th week. Among all the BILs, least dormancy period (4 days) was found in SN-1, 13, 23, 25 and SN-28. Highest dormancy period (40 days) was found in 4 BILs i.e., SN-108, SN-116, SN-117 and SN-122 (40 days). None of the BILs were found to have non-shattering trait, while 2 BILs (SN-38 and SN-163) showed low shattering and 18 BILs were found with very high grain shattering percent. Of the 312 SSRs screened, 94 were polymorphic between the parents. A strategy of combining the DNA pooling from phenotypic extremes and genotyping was employed to detect the putative markers associated with dormancy and shattering traits. Single marker analysis revealed co-segregation of two putative markers RM488 on chromosome 1 and RM247 on chromosome 12 were with dormancy and shattering traits respectively. The putative marker RM488 identified is suitable for the marker-assisted transfer of the dormancy shown by O. nivara accession CR100008 for addressing pre harvest sprouting in modern cultivars. Interestingly, O. nivara type allele at RM247 was observed in BILs with low shattering phenotype.

2020 ◽  
Vol 79 (04) ◽  
Author(s):  
Yashpal . ◽  
D. R. Rathod ◽  
Subhash Chandra ◽  
Anil Kumar ◽  
Raju Ratan Yadav ◽  
...  

Quantitative trait loci (QTL) mapping and analyses were conducted for yield and six yield-related traits in soybean using 184 inter-specific recombinant inbred lines (RILs) derived from a cross involving wild type (Glycine soja Sieb. and Zucc.) accession DC2008-1 and cultivated (Glycine max L. Merr.) variety DS9712. A Linkage map of 1639.55 cM length was constructed with 167 SSR markers (65.65% polymorphism) with an average marker interval of 9.82 cM. Using three years phenotypic data 34 QTLs were mapped for 7 traits using Inclusive Composite Interval Mapping approach. The number of QTLs mapped for a trait varied from year to year, however, QTLs for days-to-50% flowering (qDFF5), 100-seed weight (qHSW9-1, qHSW9-2 and qHSW19) and yield (qYLD17) were mapped consistently over the three years of testing. Identified QTLs were validated through single marker analysis in 92 germplasm lines. The study demonstrated the potential of wild type soybean to harness QTLs for yield-related traits. The identified QTLs could be utilized for genetic improvement of soybean through molecular breeding.


2018 ◽  
Author(s):  
S. Ramchander ◽  
Andrew Peter Leon ◽  
Jesima Khan Yasin ◽  
Vinod KK ◽  
Arumugam Pillai

Rice variety, Improved White Ponni is a medium duration crop, but highly susceptible to lodging impacting maximum yield losses. The present investigation aimed to identify early and early semi-dwarf mutants in Improved White Ponni by inducing variations using gamma rays without altering its native grain quality traits. Seeds were treated with various doses of after fixation of the LD50 value of gamma radiation and reported that most of the traits exhibit variations in the mutants at various levels of irradiation. The selection for earliness and dwarf plant height was imposed in M2 and it was confirmed by evaluation of M3 generation. Apart from semi-dwarf early mutants, high tillering habit, narrow rolled leaf, upper albino leaf and grassy stunt and extreme dwarf mutants were also identified. Characterization of mutants using already reported genic and linked microsatellite markers associated with semi-dwarfism and earliness resulted that PIC value ranges between 0.037 and 0.949 with an average of 0.382. Single marker analysis revealed that RM302 and RM310 on chromosome 1 and 8 had exhibited an association with the traits plant height, culm and internodal lengths. Of these gene-specific markers, GA20Oxi_1 and GA20Oxi_2 have shown polymorphism among mutants. GA20Oxi_2 showed null alleles in the dwarf mutants and this clearly emphasized that there are some base deletions exists in the region of exon 2 of sd1 region. GA3 response study shown that identified mutants were GA3 responsive except IWP 11-2, IWP 48-2, IWP 50-11 and IWP 33-2 which showed very low responsive. Agar plate assay revealed that, IWP 50-11, IWP 33-2, IWP 43-1, IWP 47-2 and IWP 18-1 had low production of α- amylase. Scanning electron microscope examination on confirmed mutants exhibited larger cell size and a lesser number of cells per unit area than the wild-type which shows that these mutants are defective in GA mediated pathway


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 933.2-934
Author(s):  
A. Julià ◽  
M. Lopez Lasanta ◽  
F. Blanco ◽  
A. Gómez ◽  
I. Haro ◽  
...  

Background:Blocking of the Tumor Necrosis Factor (TNF) activity is a successful therapeutic approach for 2 out of 3 Rheumatoid Arthritis patients. Identifying the patients that will not respond to this therapeutic approach is a major translational goal in RA. Association of seropositivity to rheumatoid factor (RF) or anti-cyclic-citrullinated antibodies (anti-CCP) with anti-TNF response has proven inconclusive, suggesting that other yet unexplored biomarkers could be more informative for this goal.Objectives:We tested the association of two recently introduced biomarkers in RA: anti-carbamylated protein antibodies (anti-CarP) and anti-peptidylarginine deiminase type 4 (anti-PAD4).Methods:A prospective cohort of n=80 RA patients starting anti-TNF therapy was recruited and levels for all four autoantibodies -RF, anti-CCP, anti-CarP and anti-PAD4- were measured at baseline. The change in DAS28 score between baseline and week 12 of therapy was used as the clinical endpoint.Results:Single marker-analysis showed no significant association with drug response. However, when testing for interactions between autoantibodies, we found highly significant associations with drug response. Anti-CCP and RF showed a positive interaction with the response to anti-TNF therapy (P=0.00068), and anti-PAD4 and antiCarP titers showed a negative interaction with the clinical response at week 12 (P=0.0062). Using an independent retrospective sample (n=199 patients), we validated the interaction between anti-CCP and RF with the clinical response to anti-TNF agents. (P=0.044).Conclusion:The results of this study show that interactions between antibodies are important in the response to anti-TNF therapy and suggest potential pathogenic relationships.Acknowledgments :We would like to thank the clinical researchers and patients participating in the IMID Consortium for their collaborationDisclosure of Interests:Antonio Julià: None declared, Maria Lopez Lasanta: None declared, Francisco Blanco: None declared, Antonio Gómez: None declared, Isabel Haro: None declared, Antonio Juan Mas: None declared, Alba Erra: None declared, Mª Luz García Vivar: None declared, Jordi Monfort: None declared, Simon Sánchez Fernandez: None declared, Isidoro González-Álvaro Grant/research support from: Roche Laboratories, Consultant of: Lilly, Sanofi, Paid instructor for: Lilly, Speakers bureau: Abbvie, MSD, Roche, Lilly, Mercedes Alperi-López: None declared, Raúl Castellanos: None declared, Antonio Fernandez-Nebro: None declared, Cesar Diaz Torne: None declared, Núria Palau: None declared, Raquel M Lastra: None declared, Jordi Lladós: None declared, Raimon Sanmarti: None declared, Sara Marsal: None declared


2019 ◽  
Vol 11 (29) ◽  
pp. 65-84
Author(s):  
Seyedeh Minoo Mirarab Razi ◽  
Reza Shirzadian-Khorramabad ◽  
Hossein Sabouri ◽  
Babak Rabiei ◽  
Hossein Hosseini Moghadam ◽  
...  

2018 ◽  
Vol 9 ◽  
Author(s):  
Jie Jin ◽  
Weixiong Long ◽  
Liuting Wang ◽  
Xingdan Liu ◽  
Guojing Pan ◽  
...  

2012 ◽  
Vol 12 (1) ◽  
pp. 137 ◽  
Author(s):  
Balram Marathi ◽  
Smriti Guleria ◽  
Trilochan Mohapatra ◽  
Rajender Parsad ◽  
Nagarajan Mariappan ◽  
...  

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