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Katna, G.
- Emergence of Genome Wide Association Studies as a Major Plant Breeding Tool
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Authors
Affiliations
1 Department of Crop Improvement, CSK Himachal Pradesh Krishi Vishvavidyalaya, Palampur - 176 062, IN
1 Department of Crop Improvement, CSK Himachal Pradesh Krishi Vishvavidyalaya, Palampur - 176 062, IN
Source
Himachal Journal of Agricultural Research, Vol 44, No 1&2 (2018), Pagination: 125-127Abstract
Identification of genes responsible for complex traits has been revolutionized with the advent and association of high throughput sequencing with association studies. GWAS takes the full advantage of ancient recombination events occurred in the natural population and exploits simple association of polymorphism with the trait of interest. Further, the genetic basis of phenotypic variations is detected by rapid highthroughput sequencing, accelerating the genome assisted breeding. The high density SNPs generated through GWAS allow whole genome scanning to identify haplotype blocks correlated with desired QTLs, thereby establishing itself as a major plant breeding tool.Keywords
GWAS, Linkage Disequilibrium, SNPs.Full Text
References
- Anonymous. 2016.http://www.ricehapmap.org/index.aspx. Branca A, Paape T, Briskine R, Zhou P, Wang S, Denny R, Mudge J, Bharti AK, Farmer A, May GD, Tiffin PL and Young ND. 2010. The Medicago truncatula HapMap project: deep coverage sequencing of 30 inbred lines using Illumina's Solexa technology. Plant & Animal Genomes XVIII Conference, San Diego, CA pp: 417.
- Hazzouri KM, Khraiwesh B, Amiri KMA, Pauli D, Blake T, Shahid M, Mullath SK, Nelson D, Mansour A, Ashtiani KS, Purugganan M and Masmoudi K. 2018 . Mapping of HKT1;5 gene in barley using GWAS approach and its implications in salt tolerance mechanism. Frontiers in Plant Science. https://doi.org/10.3389/fpls.2018.00156.
- Han K, Lee, HY, Ro NY, Hur OS, Lee JH, Kwon JK and Kang BC. 2018. QTL mapping and GWAS reveal candidate gene controlling capsaicinoid content in Capsicum. Plant Biotechnology. https://doi.org/10.1111/pbi.12894.
- Batayeva D, Labaco B, Ye C, Li X, Usenbekov B, Rysbekova A, Dyuskalieva G, Vergara G, Reinke R and Leung H. 2018. Genome wide association study of seedling stage salanity tolerance in temperate japonica rice germplasm. BMC Genetics 19:2
- Wilson PB, Streich JC, Murray KD, Eichten SR, Cheng R, Aitken NC, Spokas K, Warthmann N and Borevitz JO. 2018. Population structure of the Brachypodium species complex and genome wide association of agronomic traits in response to climate. bioRxiv. https:// doi.org/10.1101/246074.
- Sanchez DL, Liu Sisi, Ibrahim R, Blanco M and Lubberstedt T. 2018. Genome-wide association studies of doubled haploid exotic introgression lines for ischolar_main system architecture traits in maize (Zea mays L.). Plant Science 268: 30-38.
- Zhong Z, Marcel TC, Hartmann FE, Ma X, Plissonneau C, Zala M, Ducasse A, Confais J, Compain J, Lapalu N and Amselem J. 2017. A small secreted protein in Zymoseptoria tritici is responsible for avirulence on wheat cultivars carrying the Stb6 resistance gene. New Phytologist 214: 619-631.
- Li YH, Reif JC, Hong HL, Li HH, Liu ZX, Ma YS, Li J, Tian Y, Li YF, Li WB and Qiu LJ. 2018. Genome wide association mapping of QTS underlying seed oil and protein contents of a diverse panel of soybean accessions. Plant Science 266: 95-101.
- Li F, Xie J, Zhu X, Wang X, Zhao Y, Ma X, Zhang Z, Rashid MAR, Zhang Z, Zhi L, Zhi L, Zhang S, Li J, Li Z and Znag H. 2018. Genetic basis underlying correlations among growth duration and yield traits revealed by GWAS in rice (Oryza sativa L.). Frontiers in Plant Science. https://doi.org/10.3389/fpls.2018.00650.
- Diversity Analysis of Advanced Chickpea (Cicer arietinum L.) Derivatives
Abstract Views :57 |
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Authors
Affiliations
1 Department of Genetics and Plant Breeding, CSK Himachal Pradesh Krishi Vishvavidyalaya, Palampur-176 062, IN
1 Department of Genetics and Plant Breeding, CSK Himachal Pradesh Krishi Vishvavidyalaya, Palampur-176 062, IN
Source
Himachal Journal of Agricultural Research, Vol 47, No 1 (2021), Pagination: 88-94Abstract
Genetic diversity analysis of 130 advanced interspecific chickpea derivatives derived from four wide crosses (Cross I: PUSA 372 X ILWC 229, Cross II: PBG 5 X ILWC 229, Cross III: PBG 5 X ILWC 246 and Cross IV: BGD 72 X ILWC 246) was estimated at CSK HPKV, Research Sub-Station, Berthin, Bilaspur during rabi 2019-20. On the basis of Mahalanobis D2-statistics these interspecific derivatives along with 4 checks were grouped into 8 main clusters. Cluster I was the largest cluster among all having forty six derivatives. Maximum inter-cluster distance was observed between cluster IV and cluster VI and maximum intra cluster distance was showed by cluster IV. Therefore, a hybridization programme involving lines from cluster IV and cluster VI can be devised to yield desirable transgressive segregants. The principal component analysis, revealed that 75.27 per cent of total variation has been contributed by the first three principal components i.e., PC1 explained 45.15 per cent, PC2 explained 17.57 per cent and PC3 explained 12.55 per cent of total variation. The positive correlation between days to 50 per cent flowering, days to 75 per cent maturity, inter-node length and branches per plant as revealed by two-dimensional ordination bi-plot can be utilized effectively for the indirect selection of lines with early maturity and high yield.Keywords
Chickpea, Divergence, Principal Component Analysis, Variability.Full Text
References
- Alipoor Yamchi HM, Bihamta MR, Peyghambari SA, Naghavi MR and Majnoon Hoseini N. 2013. Grouping of Kabuli chickpea genotypes using multivariate statistical methods. Iranian Journal of Pulses Research 4: 21-34.
- Dwivedi KK and Gaibriyal ML. 2009. Assessment of genetic diversity of cultivated chickpea (Cicer arietinum L.). Asian Journal of Agricultural Science 1: 7-8.
- Farshadfar M and Farshadfar E. 2008. Genetic variability and path analysis of chickpea (Cicer arietinum L.) Landraces and Lines. Journal of Applied Sciences 8: 3951-3956.
- Federer WT. 1955. Augmented Designs. Hawaiir Planters Records 55: 191-208.
- Ghorbani T, Chegharnirza K, Brdideh K and Basiri Shoar P. 2013. Recognition and determination of related traits importance with seed yield in chickpea (Cicer arietinum L.). Plant Breeding and Seed Science 68: 15-24.
- Karl Pearson. 1901. Principal components analysis. The London, Edinburgh and Dublin Philosophical Magazine and Journal of Science 6 (2): 559.
- Kashyap OP and Rastogi NK. 2003. Genetic divergence in chickpea (Cicer arietinum L.). Journal of Plant Genetic Research 16:1-3.
- Mahalanobis PC. 1936. On the generalized distances in statistics. Proceedings of the National Institute of Sciences of India 2: 49-55.
- Malik SR, Shabbir G, Zubir M, Iqbal SM and Ali A. 2014. Genetic diversity analysis of morpho-genetic traits in desi chickpea (Cicer arietinumm L.). International Journal of Agricultural and Biological Engineering 16: 956-960.
- Nimbalkar RD, Katre YY and Phad DS. 2017. Genetic diversity in chickpea (Cicer arietinum L.). BIOINFOLET-A Quarterly Journal of Life Sciences 14: 60-63.
- Rao CR. 1952. D2 Analysis. In: Advanced Statistical Methods in Biometrical Research. John Wiley and sons Inc., NewYork Edition 1.
- Singh RK and Choudhary BD. 1977. D2 Analysis. In: Biometrical Methods in Quantitative Genetic Analysis. Kalyani publishers, New Delhi, pp 288-94.
- Singh RP, Singh I, Singh S and Sandhu JS. 2012. Assessment of genetic diversity among interspecific derivatives in chickpea. Journal of Food Legumes 25: 150-152.
- Sharifi P, Astereki H and Pouresmael M. 2018. Evaluation of variation in chickpea (Cicer arietinum L.) yield and yield components by multivariate technique. Annals of Agrarian Science 16: 136-142.
- Sharma PK, Gupta PK and Balyan HS. 1998. Genetic diversity in a large collection of wheat (Triticum spp.). Indian Journal of Genetics and Plant Breeding 58:271-278.
- Syed MA, Islam MR, Hossain MS, Alam MM and Amin MN. 2012. Genetic divergence in chickpea (Cicer arietinum L.). Bangladesh Journal of Agricultural Research 37: 129-136.
- Talebi R and Rokhzadi A. 2013. Genetic diversity and interrelationships between agronomic traits in landrace chickpea accessions collected from “Kurdistan” province, north-west of Iran. International Journal of Agriculture and Crop Sciences 5: 2203-2209.
- Toker C and Cagirgan MI. 2004. The use of phenotypic correlations and factor analysis in determining characters for grain yield selection in chickpea (Cicer arietinum L.). Hereditas 140: 226-228.
- Verma AK, Singh D, Kumar J, Rizvi AH, Andrewa M and Yadav SS. 2008. Impact of Genetic divergence on the expression of individual trait in chickpea (Cicer arietinum L.). American-Eurasian Journal of Sustainable Agriculture 2: 205-11.