Identification of yield QTLs of lentil and its introgression in local cultivar through marker assisted selection to enhance productivity

By

Background

Lentil (Lens culinaris Medik.) is a self-pollinated, diploid (2n = 14), cool-season pulse crop generally grown in temperate semiarid regions. It is widely cultivated on a global basis as an important legume crop for its high-quality plant proteins, fibres, livestock feed, and forage. Lentil is the only crop commodity that is exported from Nepal (MoAD, 2015). It is the most important winter legume crop grown in the country. Lentil is used as Dal with rice, which is a staple food of the Nepalese. The yield of lentils in the country is very low compared to other countries. Yield is a complex trait and is an important factor for the lentil breeding program. Knowledge of QTL for the yield trait is of major interest to plant breeders because it facilitates the efficient utilization of marker genes in crop improvement programs to enhance yield. Knowledge about yield QTL of economic attributes with easily scorable breeding neutral traits can be used to improve breeding efficiency. Molecular breeding strategies have been adopted for crop improvement programs and are suitable for application in lentil.

 Objective

The major objective of this project/research is to identify marker tagging genomic regions containing quantitative trait loci of lentil. The QTL will be introgressed into a popular local cultivar through marker-assisted selection (MAS) to enhance productivity.

Methodology

Development of Recombinant Inbred Lines (RILs)

The mapping population will be raised. The RIL population will be used for tagging the QTLs. Crosses will be made between a single genotype of a cultivated high-yielding variety and a popular low-yielding local cultivar of Victoria, Australia. F2 progeny will be produced. Single seed descent method will be undertaken up to 4 generations from F2 progeny derived genotypes in the glasshouse. The resulting F6 mapping population will consist of more than 100 RILs. Frozen leaf tissue from each progeny genotype will be ground, and genomic DNA will be extracted. The CBTAB method of DNA extraction will be used for DNA extraction, and the Polymerase Chain Reaction (PCR) will be used for amplification of the gene.

(Note: RIL populations can be obtained from the university or from other researchers to shorten the research time period.)

DNA markers and genetic linkage map

A genetic linkage map of lentil using RIL populations will be developed. The linkage map will be used to locate QTL that control yield in lentil.

QTL mapping

QTL analysis will be performed using Qgene 3.0 (Nelson, 1997) and MapManager QT 2.8 (Manly, 2001). Qgene will be used for simple interval mapping (SIM) and multiple regressions, and to determine epistatic interactions. MapManager QT will be used to check data quality and to confirm the results generated by other programs. QTL positions will be determined by the peak LOD score. Simple interval mapping (SIM) and composite interval mapping (CIM) methods will be used to identify and confirm QTLs associated with high yield. Multiple peaks within 30 cM will be considered as a single QTL (Kearsey and Pooni, 1996). The percentage of the phenotypic variation (R2) explained by the detected QTL will be determined by multiple regression analysis using those markers explaining the peak response of individual QTLs.

 Candidate gene selection

The sequences underpinning SNP loci flanking the QTL containing intervals will be BLAST analysed against the M. truncatula genome to identify genomic regions containing putative candidate genes.

Introgression of the candidate gene through marker-assisted selection

After identification of the candidate gene through QTL analysis, markers will be developed; a large number of lentil cultivars will be screened based on their objective. And crossing with the marker identified high-yielding genotype will be done with popular local cultivars. The F3 generation will be checked in the field conditions. The foreground and background selection will be done to screen the segregating population.

Expected Output

Quantitative trait loci of lentil will be identified and analysed to find a candidate gene that will be used in marker-assisted selection to enhance yield in Victoria.

1)     Mapping populations will be developed.

2)     SSR marker will be identified for major and minor QTL

3)     Yield quantitative trait loci will be found out

4)     Candidate gene will be identified.

5)     A good high-yielding variety will be developed.

Keywords: lentil, MAS, introgressed line, QTL, marker-assisted selection, quantitative trait loci

References

 

Kearsey M.J., Pooni H.S., 1996. The genetic analysis of quantitative traits. Chapman & Hall, London, UK. 381 pp.

 

Manly, K.F., Cudmore, Jr., R.H., and Meer, J.M. 2001. MapManager QTX, a cross-platform software for genetic

mapping. Mammalian Genome, 12: 930-932.

 

www.moad.gov.np. Ministry of Agriculture and Development, Nepal

 

Nelson, J.C. 1997. Qgene software for marker-based genomic analysis and breeding. Mol. Breed., 3: 239–245


(Note: This proposal was developed by Dr. UKS Kushwaha)

Comments

Post a Comment

Popular posts from this blog

Understanding transgenics application

By
Image
Introduction The crops that are developed through genetic engineering techniques are called transgenic crops. Transgenic crops are popularly known as transgenics or genetically modified (GM) crops. In transgenics, the target gene of one organism is inserted into a crop to obtain a desirable change in its physiology. The first transgenic crop was developed in cotton and commercialized as Bt cotton. The transgenic era started with the insertion of a soil bacterium,  Bacillus thuringenesis gene into a cotton genotype, which showed resistance to the devastating cotton insect Helicoverpa armigera. The use of genetic engineering techniques in plant science has revolutionized agriculture, and it has shifted to a new era. Earlier, about three decades ago, it was not possible to sequence genes and understand the biochemical and genetic mechanisms of action of genes, but now everybody is familiar with genetic tools and techniques. It is now possible to sequence genes and understand the pr...
Read more

EVALUATION OF LENTIL GERMPLASM FOR RESISTANCE TO WILT, RUST AND STRMPHYLIUM BLIGHT

By
Introduction Lentils are considered to be one of the oldest food crops of mankind that   researchers have traced back to 7000-8000 BC (Hawtin, et al. , 1980; Cubero, 1981; Lev- Yadun et al., 2000). Worldwide, lentil is grown on a total area of 1.8 million hectares, of which 60% is in the South Asian region which includes the lentil producing countries of Bangladesh, Burma, India, Nepal and Pakistan (Nazir et al., 1994). High protein content, starch, low level of antinutrients and ability to grow in water stress conditions are main attributes that make lentil an important crop (Anonymous, 2003). Morphological characterization is the first step in the classification and description of any crop germplasm (Ghafoor et al., 2001; Upadhyaya et al., 2001). Use of botanical descriptors for genotyping has advantages and disadvantages (Ramanatha & Riley, 1994; Watanabe et al., 1995). Among biochemical techniques, seed proteins and isozymes are pr...
Read more

MOLECULAR CHARACTERIZATION OF LENTIL GERMPLASM

By
INTRODUCTION Lentil ( Lens culinaris Medik.) is an important cool-season crop in North Africa, West Asia, the Middle East, the Indian Subcontinent and North America (Erskine 1996). Lentils are an old world legume and were probably one of the first plant species to be domesticated (Bahl et al ., 1993).   Cultivated lentil ( Lens culinaris Medik) is thought to have originated in the Fertile Crescent of the Mediterranean region in Western Asia, dating back to the beginnings of agriculture, from where it spread to the rest of world (Ladizinsky, 1979; Duke, 1981). Lentil is unique because it can be grown in marginal environments in which other crops cannot be cultivated (Cubero, 1981). It is one of the oldest food crops of mankind that researchers have traced back to 7000 - 8000 BC and probably originated from fertile crescent from where it spread to adjacent regions of west Asia and Africa and later to Europe and north America (Hawtin et ...
Read more

ORIGIN OF WHEAT AND ITS INTRODUCTION IN NEPAL

By
INTRODUCTION Scientific Classification Kingdom: Plantae (unranked): Angiosperms (unranked): Monocots (unranked): Commelinids Order: Poales Family: Poaceae Subfamily: Pooideae Tribe: Triticeae Genus: Triticum Botanical Name: Triticum sp. Common Name: Wheat, gehun Wheat is etymologically the ‘ white ’ grain . The word comes from prehis to ric Germanic khva it jaz (German weizen , Dutch weit , Swedish hvete , and Danish hvede ), which was derived from a variant of the base khwīt , source of English white . It alludes to the ‘white’ flour produced by grinding the grain . Wheat     ( Triticum spp. ) is a grass , originally from the Fertile Crescent region of the Near East , but now cultivated worldwide (Belderok et al., 2000). There are many kinds of wheat in the world today. The two most common are common wheat, Triticum aestivum , also known as bread wheat and accounting for some ...
Read more

DNA is a Packet of Memory

By
Image
 It is a profound and perceptive metaphor to describe DNA as "a packet of memory," encapsulating its fundamental role as the "biological information storage system of life." The entire set of instructions required to create, function, care for, and procreate an organism is stored in its DNA. This comprises regulatory instructions for when and where to build proteins, the blueprints for all proteins (the cell's workhorses), and crucial structural components. A four-letter chemical alphabet (A, T, C, and G, which stand for nucleotides) is used to store the data digitally. Certain combinations of these letters create "words" (codons) that serve as regulatory signals, indicating which amino acid should be used in the construction of a protein. Hereditary traits are transferred from parents to children via DNA. It contains the collective or generational "memory" of traits and evolutionary adaptations that a species has developed over millions...
Read more