Sorghum maize and grain (Motlhaodi et al., 2014).

 

 

Sorghum (Sorghum bicolor L. Moench) is fifth most
economically important cereal crop of the world. Sorghum is a multipurpose
crop, its uses extend from being an important source of food, feed, and forage,
it supplies raw materials for industrial use. Sorghum has diverse germplasm
grouped into sweet, forage, energy and grain sorghum types depending on its
uses. Knowledge of genetic diversity helps breed important crop varieties.
Sorghum germplasm has been explored via morphological, biochemical, proximate
and molecular markers. Biotechnological methods like axenic culture,
transformation, molecular breeding, genomics and proteomics have been
successfully utilized in sorghum improvement. Documenting the crop germplasm
with morphological traits variability is considered less efficient as
environmental conditions influence the results. Whereas, DNA markers provide an
accurate alternative for assessing the similarities and differences among
genotypes of any crop germplasm. This study deals with estimation of diversity
of high biomass sorghum germplasm procured from USDA. The morphological data
will be used to screen the proficient genotypes, which will be later analysed
by microsatellite markers. The study will help identify sorghums having
potential for breeding of improved energy sorghum varieties in Pakistan.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

UNIVERSITY
OF AGRICULTURE, FAISALABAD

 

Centre of
Agri. Biochemistry and Biotechnology

(Synopsis
for M.Phil. Biotechnology)

 

I.           
Title:  Understanding genetic diversity of sorghum
using quantitative traits

II.           
(a) Date of Admission                 
:                                        
22-09-2016

(b) Date of Initiation           :                                     22-09-2016

(c) Probable Duration                   :                                     4 semesters

III.           
Personnel:

(a)
Name of the Student      :                                     Muhammad
Imran Farooq

(b) Registration Number     :                                     2016-ag-2144

(c) Supervisory Committee:        

i)                  
Dr. Bushra Sadia                                        (Supervisor)

ii)               
Dr. Faisal Saeed Awan                               (Member)

iii)             
Dr. Jafar Jaskani                                        (Member)

 

 

 

IV. Need for
the Project

(Sorghum
bicolor L. Moench) is the world’s fifth most vital product after wheat, rice,
maize and grain (Motlhaodi et al., 2014). It has a place with the family
Poaceae and the variety Sorghum with a few animal categories and sub-species.
It is notable C-4 trim and developed in warm and parched climatic regions of
the world. It is an imperative sustenance, nourish and scavenge edit. In Africa
and Asia, 80% of the overall sorghum is developed as an essential sustenance
and the lingering 16-20% is being developed in the propelled conditions of the
world as feedstuff. There is an extensive variety of hereditary variety
introduce in sorghum (Hariprasanna and Patil, 2015). In addition being a huge
grain edit, it gives crude material to the amalgamation of starch, fiber,
dextrose syrup, biofuels, liquor, and different items. (Li et al.,  2010).

Sorghum
is being developed as a grain edit in Pakistan. It is developed on a territory
of 171,000 hectares with generation of 103,000 tons and normal yield of 26.9
tons for each hectare (Sher et al., 2016).

 

Conventional
breeding systems have brought about the successful improvement of high
yielding, profoundly altered sorghum cultivars. Be that as it may, it has a few
impediments because of normal sexual contrariness boundaries and the tight
hereditary variety in sorghum. Consequently, facilitate advancement of
generation, quality and protection from biotic and abiotic focuses on needs
earnest consideration. Morphological, biochemical and sub-atomic procedures
have been misused for surveying these assets. Biochemical markers then again
uncover all the more really the hereditary fluctuation, as they are the
immediate results of qualities. (Iqbal et al., 2010).

The
improvement in subjective and quantitative attributes of sorghum expands
biomass highlights and biofuel generation which significantly diminishes the
fuel inadequacy (Iqbal et al., 2010).

Hereditary
deviation can be surveyed by distinguishing the gatherings which have
comparative genotypes for the evaluation and safeguarding. Evaluation of
hereditary assorted variety is noteworthy to cultivar change and for deciding
particular phenotypes and genotypes. In any reproducing program hereditary
assorted variety assumes critical part. Hereditary examination and DNA fingerprinting
can be viably considered by DNA based atomic systems (Geleta et al., 2006).

Hereditary
assorted variety can likewise be controlled by morphological markers. These
morphological markers are regularly affected by ecological variables,
accordingly the data got isn’t extremely dependable (Shehzad et al., 2009). DNA
markers are getting to be plainly solid device to examine decent variety and
control agronomic characters for the change of sorghum cultivars. These markers
are useful in enhancing reproducing programs through various ways. Hereditary
stocks and cultivars can be recognized by hereditary fingerprints. Reproducers
are presently permitted to assess the decent variety and hereditary relatedness
by looking at uncommon hereditary signs in germplasm. Quantitative quality loci
(QTL) for some, mind boggling characters can be assessed by utilizing
sub-atomic markers (Ejeta and Knoll, 2007). The little and altogether genome of
sorghum makes it a model reap for the use of genomics-based reproducing systems
(Batley and Edwards, 2007).

Distinctive
sorts of atomic markers have been effectively utilized for the appraisal of
hereditary assorted variety in sorghum genotypes. Among these, Simple Sequence
Repeats (SSRs) are to a great degree valuable inalienable markers attributable
to their primary legacy, high polymorphism and reproducibility. In like manner,
ESTs are potentially silly reason for SSRs that uncover polymorphisms not just
in the source taxon, but rather in related taxa, also.

 

Objectives:

 

•      Genetic
diversity analysis of sorghum genotypes using morphological markers

 

•      Genetic
diversity analysis of selected sorghum genotypes using SSR markers

 

•      Selection
of promising sorghum genotypes

 

V.  Review of Literature

 

Brown et al. (2011)  applied structure and principal components
analysis for genetic evaluation based on
physical appearance. In order to check the genetic similarities on
the basis of physical appearance, 434 SNP and SSR allele were genotyped from
216 sorghum lines. The structure and principal component study aided in better
characterization.

Burow et al. (2012) performed a study to investigate sorghum landraces that were 159 collected from regions
of china that had a cool temperature by means of 41 SSR markers. These results
indicated that 40 out of 41 SSRs were polymorphic and extremely useful. The PIC
was in a normal range of 0.04-0.91. The genomic resemblance coefficients
predictable range was 0.4-0.9 that indicated variation in sorghum lines.

Olweny
et al. (2014) conducted an experiment to check the hereditary uniqueness
and correlation among various sorghum genotypes from various nations by
utilizing straightforward arrangement rehashes markers. 11 microsatellites were
utilized to identify 86 sorghum types. Results indicated 8 alleles per locus
with 86 alleles in total. The scored PIC value was 0.53, that coordinated the
arrangement of direct decent variety 0.09~0.89.

Adugna (2014) studied 8 land races of sorghum for estimation of the
hereditary pattern and in-situ assortment of around 8 sorghum
landraces. They exploited 12 exceptionally polymorphic SSRs of sorghum and 7
phenotypic traits for this work. The study indicated high variation among
phenological traits of different sorghums. They reported 123 alleles, out of
which 78 were novel. Each loci accommodated on average 10.25 alleles, generated
by twelve microsatellites. The normal heterozygosity and hereditary estimation ranged
from 0.04-0.33.

 

Mofokeng et al. (2014) utilized SSR markers to assess
hereditary deviation in sorghum genotypes. 103 landraces and reproducing lines
were genotyped by utilizing 30 SSR preliminaries. The allele size ran from 90
to 294bp indicated hereditary deviation in the sorghum. The quantity of alleles
was in the scope of 2-15 with mean of 6.4 for each locus. The mean polymorphic
data content was 0.5031 with the mean heterozygosity of 0.5483.

 

Aminon et al.
(2015) contemplated the hereditary uniqueness in sorghum utilizing 142
increases gathered from North Benin and described utilizing 10 subjective and
14 quantitative characteristics. More extensive inconstancy were appeared among
grain yield (0.72-10.57 tons/ha), panicle weight (15-215.95 g), days to half
blooming (50-195 days), and plant tallness (153.27-636.5 cm). The outcome will
expand the creation and decent variety of sorghum.

Ryu et al.
(2016) gathered high-seed-yield sorghum from 3 nations to assess the assortment
and concoction examination. By utilizing 10 SSRs to assess hereditary decent
variety distinguished 37 alleles having 2-7 alleles for every locus. Three
primary arrangements of sorghum cultivars were made based on phylogenetic
examination by SSR markers. These gatherings were then contrasted and those
gatherings in light of substance organization. Real fluctuations were found in
the whole grain and substance of all cultivars.

Muui et al.
(2016) utilized 44 landraces of sorghum from Kenya to assess the hereditary
variety of sorghum. By utilizing 20 SSR markers 4 assortments out of 44 were
broke down. The normal estimation of hereditary assortment accomplished was 0.35.
The allelic array was 4-12 with normal estimation of 6.05. Investigation of
atomic deviation demonstrated more noteworthy deviation inside populaces than
among the gatherings.

Sinha and Kumar
(2016) inspected forty distinctive sorghum promotions for hereditary decent
variety utilizing quantitative attributes. Perceptions were recorded on 14
quantitative attributes, out of which 9 distinct qualities demonstrated high
variability were chosen for hereditary assorted variety examination.

Silva et al.
(2017) utilized 100 sorghum increases gathered from the germplasm bank of the
Embrapa Maize and Sorghum rearing project to ponder the phenotypic and atomic
assorted variety of sorghum. Morphological characteristics identified with
sugar and biomass generation were utilized for phenotypic characterizat. Low
connection (0.35) was seen amongst phenotypic and sub-atomic decent variety
grids. The outcome showed complementarity between the sub-atomic and the
phenotypic characterization to help a breeding system.

 

 

 

 

 

 

 

VI. Material and Methods

 

The planned research study will
be carried out in Somatic Cell Genetics Laboratory, Centre of Agricultural
Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad.

Plant Material and Cultivation:

The sorghum germplasm used in the
study are provided by Agriculture Research Service, United Sates Department of
Agriculture (ARS-USDA), USA. These varieties will be screened based on their
biomass related traits. Then diversity analysis of these varieties will be done
by using molecular markers.

 

Lay out and Phenotyping:

The Sorghum germplasm trial will
be sown at the research field area of University of Agriculture, Faisalabad, by
using Randomized Complete Block Design (RCBD) with three replications using
dibbler method. The row × row and plant × plant distances will be 30 cm and 10
cm respectively. Fifteen plants will be planted in a line. Identified best performing
plants from each genotype per replication will be selected on biomass related
traits.

 

Biomass related traits:

 

1.                 
Germination Percentage (%)

2.                 
No. of Leaves per Plant (n)

3.                 
No. of Nodes (n)

4.                 
Days to 50% Flowering

5.                 
Brix Value

6.                 
Fresh Biomass (g)

7.                 
Dry Biomass (g)

8.                 
Days to Maturity (n)

 

9.                 
Plant Height (cm)

 

Molecular Analysis:

 

1.                 
The fresh leaf samples will be
used for DNA extraction following the method reported by Khan et al.
(2004).

2.                 
The DNA quantification will be optimized

 

3.                 
The genetic divergence of sorghum germplasm will be
assessed by SSR.

 

 

 

 

 

 

Statistical Analysis:

 

The data will be analyzed using POPGENE 32 computer
software (ver. 1.44) (Yeh et al., 1999) and the efficiency of SSR markers regarding no. of loci, no. of bands
and degree of polymorphism will be estimated.

 

 

 

 

 

 

References

 

 

Adugna, A. 2014. Analysis of in situ diversity and
population structure in Ethiopian cultivated Sorghum bicolor (L.) landraces using phenotypic traits and SSR
markers. Springerplus. 3:212.

Aminon I, L.Y. Loko, A. Adjatin, E. E.
Ewédjè, A. Dansi, S. Rakshit, N. Cissé, J. V. Patil, C. Agbangla and A. Sanni.
2015. Scientific World J.

Brown, P. J., S. Myles and S. Kresovich. 2011. Genetic
support for phenotype-based racial classification in sorghum. Crop Sci. 51(1):
224-230.

Burow, G., C. D. Franks, Z. Xin and J. J. Burke. 2012.
Genetic diversity in a collection of Chinese sorghum landraces assessed by
microsatellites. Amer. Plant Sci. 3(12): 1722-1729.

Ejeta, G. and J. E. Knoll. 2007. Marker-assisted selection
in sorghum. Genomics-assisted crop improvement. Springer Netherlands, USA. 2: 187-205.

Geleta, N., M. T. Labuschagne and C. D. Viljoen. 2006.
Genetic diversity analysis in sorghum germplasm as estimated by AFLP, SSR and
morpho-agronomical markers. Biodivers. Conserv. 15(10): 3251-3265.

Hariprasanna, K. and J. Patil. 2015.
Sorghum: origin, classification, biology and improvement sorghum molecular
breeding. Springer India, India. 1: 3-20.

Iqbal, A., B. Sadia, A. Khan, F.
Awan, R. Kainth and H. Sadaqat. 2010. Biodiversity in the sorghum (Sorghum bicolor L. Moench) germplasm of
Pakistan. Genet. Mol. Res. 9(2): 756-764.

Khan, I., F. Awan, A. Ahmad and A. Khan. 2004. A modified
mini-prep method for economical and rapid extraction of genomic DNA in plants.
Plant Mol. Bio. 22(1): 89-89.

Mofokeng, A., H. Shimelis, P. Tongoona and M. Laing. 2014. A
genetic diversity analysis of South African sorghum genotypes using SSR
markers. S. Afri. J. Plant Soil. 31(3): 145-152.

Muui, C. W., R. M. Muasya, D. T. Kirubi, S. M. Runo and A.
Karugu. 2016. Genetic variability of sorghum landraces from lower Eastern Kenya
based on simple sequence repeats (SSRs) markers. Afri. J. Biotech. 15(8):
264-271.

Olweny, C., J. Jamoza, M. Dida, W. Kimani, J. Njuguna, D.
Githae, B. Kiawa, N. Yao, L. Kosambo and C. Sally. 2014. High genetic diversity
for improvement of sweet sorghum (Sorghum
bicolor (L.) Moench) genotypes for sugar and allied products. Mol. Plant
Breed. 5(6): 29-35.

Rao, S., S. Rao, N. Seetharama, A. Umakath, P. S. Reddy, B.
Reddy and C. Gowda. 2009. Sweet sorghum for biofuel and strategies for its
improvement. Manual. Int. Crops Res. Inst. Semi-Arid Tropic.

Ryu, J., S. Im, S. Kwon, J. Ahn, S. Jeong and S. Kang. 2016.
Chemical and genetic diversity of high-seed-yield sorghum (Sorghum bicolor M.) germplasms. Genet. Mol. Res. 15(3).

Shehzad, T., H. Okuizumi, M. Kawase and K. Okuno. 2009.
Development of SSR-based sorghum (Sorghum
bicolor (L.) Moench) diversity research set of germplasm and its evaluation
by morphological traits. Genet. Resour. Crop Evol. 56(6): 809-827.

Sher, A., F. U. Hassan, H. Ali and W. Hassan. 2016. Seed
rate and nitrogen application effects on production and brix value of forage
sorghum cultivars. Grassland Sci. 62(2): 119-127.

 

Silva, M.J., M. M. Pastina. R. E. Schaffert, P. C. S.
Carneiro, R. W. Noda, J. E. S. Carneiro, C. M. B. Damasceno and Parrella, R. A.
D. C. 2017. Phenotypic and molecular characterization of sweet sorghum
accessions for bioenergy production. PloS one. 12(8).

Sweta, S and N. Kumaravadivel. 2016. Understanding Genetic Diversity of Sorghum Using
Quantitative Traits. Scientifica.

Yeh, F., R. Yang and T. Boyle. 1999. Microsoft Windows-based
freeware for population genetic analysis. Release 1.31. University of Alberta,
Edmonton.