Review and Progress

Biotechnology: Future Tools for Stable Insect Pest and Weed Control in Cotton  

Bushra Rashid , Samra Kousar , Mehwish Yousaf , Qurban Ali , Fareeha Fatima , Shehla Parveen , Arooj Arshad , Rimsh a , Nasim Ahmad , Tayyab Husnain
Centre for Excellence in Molecular Biology, University of the Punjab Lahore, 87 W Canal Bank Road, Thokar Niaz Baig, Lahore-53700, Pakistan
Author    Correspondence author
Cotton Genomics and Genetics, 2016, Vol. 7, No. 3   doi: 10.5376/cgg.2016.07.0003
Received: 06 Dec., 2016    Accepted: 29 Dec., 2016    Published: 31 Dec., 2016
© 2016 BioPublisher Publishing Platform
This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

Rashid B., Kousar S., Yousaf M., Ali Q., Fatima F., Parveen S., Arshad A., Rimsha, Ahmad N., and Husnain T., 2016, Biotechnology: future tools for stable insect pest and weed control in cotton, Cotton Genomics and Genetics, 7(3): 1-14 (doi: 10.5376/cgg.2016.07.0003)

Abstract
Cotton is known as a most important cash crop for countries depending on agriculture, thus, it always received importance in research and development sector. Pakistan economy is also dependent on cotton yield and production. Many insect pest and weeds attack on cotton and due to these there will be yield loss. Many methods have been used to manage these losses in which introduction of genetically modified cotton has special place. Bt cotton is developed from bacteria which has natural resistance against some insects and weeds and due to this Bt cotton there is increase of 30% in yield from conventional or desi cotton. A number of methods have been used to improve the yield and manage losses among which gene identification by using different methods is in use. Now a day more work is going on high-through put techniques including NGS, RNAi and VIGS. In addition, these new approaches will also provide an environmentally friendly method of plant genetic engineering and have good effect on economy of country.
Keywords
Biotechnology; Cotton; Agriculture; NGS; RNAi; VIGS; Genetically modified

Introduction
Cotton, (Gossypium hirsutum L, Gossypium arboretum) Backbone of Agriculture dependent countries belongs to family Malvaceae (Bakhsh et al., 2009). Cotton seed is the oldest known seed so far and been cultivated in Indus valley since 3500 BC, was first found near Bolan pass in Baluchistan (Khan et al., 2009; Abbas et al., 2013). It is larger profit earning crop produced in world and major share of GDP come from this crop (Chapagain et al., 2006). Research and Development area is working day and night on cotton. Two third of total countries of the world produce cotton but China, US, India and Pakistan are major producers (Sabir et al., 2011; Abbas et al., 2016). Figure 1 gives an insight regarding quantity of cotton produced by these countries from year 1980-81 to 2012-13.
 
 
Figure 1 World cotton production (in million tones) by major cotton producers 
Note: Source from National Cotton Council of America
 
Cotton “White Gold” of Pakistan as it contribute major share of foreign exchange earnings. Pakistan is at top in cotton, yarn and cloth export, and in yarn and cloth production (Source: International Cotton Advisory Committee, Washington D.C., USA). Pakistan is also 4th largest consumer of cotton in the world and a rough estimate shows that almost 26% of Pakistani farmers grow cotton every year. The economic survey of Pakistan shows that cotton crop production accounts for 1.5 percent in GDP and 7.1 percent in agriculture value addition. During July-March 2014-15, foreign exchange of US$ 10.22 billion was fetched by textile industry alone. During 2014-15, cotton was grown over 2961 thousand hectares, showing an increase of 5.5 percent over last year .In Cotton production there is increase of 9.5 percent for the year 2014-15. The area, production and yield of cotton for the last five years are shown in Figure 2 and Table 1.
 
 
Figure 2 Cotton production (000 bales) 
Note: Source from Pakistan Bureau of Statistics
 
 
Table 1 Area, production and yield of cotton
Note: Source: Pakistan Bureau of Statistics P: Provisional (July-March)
 
1 Usage
Textile industry is dependent on cotton where its fibers or 'lint’s' is harvested and woven into fabric to produce clothing, towels, bed sheets and many other textiles. Its seeds can be used to extract oil to use in the production of cooking oil, soaps and lubricants. The seed may be used as a feed for livestock. The byproduct of the ginning process can be used in the upholstery industry.
 
According to a survey extensive diversity of insects on cotton crop exists, in which bollworms and sucking insects are noticeable. According to an estimate 80 percent of insecticides use is on cotton crop alone (Akram et al., 2011; Abbas et al., 2015). In this regard, insecticide import has increased from 21, 255 tons to 27, 995 tones 2009-2010. Control on insect pest increases cotton cultivation as well as yield per acre (Pakistan economic survey 2014-25). 
 
Over last three decades control of the insect pests not only increased cotton cultivation area but also yield per acre significantly (Puspito et al., 2015; Azam et al., 2013). One reason for this inertia in yield was attributed to narrow genetic base of the cotton in the Pakistan, due to which efforts to breed resistant varieties has been overstated (Ahmad et al., 2011).
 
2 Agronomy
With the help of genetically modified cotton (Bt Cotton) the consumption of insecticides is significantly reduced as Bt provide resistance against insect pests. Its production was started in 2005 in Pakistan with a view to increase per acre yield as well as saving on pesticides and labor cost. Bt-cotton provide resistance against three bollworms i.e. American bollworm (Helicoverpa armigera Hub.), spotted bollworm (Earias spp.), and pink bollworm (Pectinophora gossypiella Saunders).Different studies have been conducted which compared the performance of Bt-type and non Bt-type varieties in Pakistan. In some cases Bt-cotton perform poor (Hayee, 2005). On the contrary better performance of existing unapproved Bt-cotton varieties is also came into notice (Nazli et al., 2010; Ali et al., 2014). Bt varieties were developed by various private sector plant breeders by transferring Bt trait to locally developed cotton varieties. These varieties are distributed to farmer without approval from regulatory authority therefore farmers face problems with seed quality (Abdullah et al., 2010; Akhtar et al., 2014). Besides sucking pests Cotton leaf curl virus (CLCV) is still a major threat to Pakistani cotton (Khan et al., 2015). Researchers are trying to develop resistant cotton variety against them.
 
Per acre yield of Bt cotton is significantly high than non Bt varieties of cotton. BT cotton is being grown with different names in Pakistan developed by different government as well as private sector companies of all these genotypes Bt-121 was relatively better than other BT cotton as regard to uniformity.
 
3 Pests of Cotton
3.1 Kinds of insect pests damaging cotton
Cotton can host a large variety of insect pests. Over 90 different insects and mites have been found to damage cotton crops in Pakistan. Highest loss of cotton crops in Pakistan is because of cotton curl leaf virus (CCLV), which is transmitted by small sucking insects called white fly. 2.3 million Cotton bolls per year are lost because to this deadly virus. The most prevailing insect pests in Pakistan are: Cotton leaf folder (Sylepta derogata), American (Helicoverpa armigera) and Pink (Pectinophora gossypiella) boll worm, Army worm (Spodoptera litura) White fly (Bemisia tabaci), spotted boll worm (Earias insulana) and Thrips (Thrips tabaci). Few of the common insect pests which damage cotton crops across the world are given in Table 2. Existing systems relay on the detection of these pests by the personal monitoring. This practice is flawed as one cannot detect the disease unless symptoms appear. Moreover, the only options used for eradication of these pests in Pakistan are herbicides and fungicides. There is need to explore more advance methods of detection and control of these insect pests (Azfar et al., 2015).
 
 

Table 2 Common pests which damage the cotton crops (Boyd et al., 2004)

 
3.2 Integrated pest management
Integrated pest management includes the group of techniques and tools that are used collectively to discourage the propagation of pest in the crop and prevent the use of harmful and hazardous pesticides in the crops. Resulting in the protection of many health risks in human (Farrell and Johnson, 2005).
 
3.3 Biological control
Biological control is the strategy in which natural enemies against the pest population is used to reduce the density and damage intensity of the pest in the crop. This strategy has been used for over 1,000 years. It is a non-toxic and safe approach to tackle with the pest population with effective results. It is a target specific but requires detail knowledge of pest and environment surrounding the crop. The crop itself is inhabited by vary number of predator and parasitoids, the important aspect of biological control is to device such matter that take into account these arthropod predator and parasitoids and fully utilize the potential of these organisms in pest control. The biological control system is not an absolute strategy as it depends on the availability of the pest in the crop for effective predation. But it can be used in association with other strategies effortlessly. Biological control is divided into three different types depending upon the approach of employment. First is importation which involves the introduction of the best natural predator against the pest that is not native to a particular region. Second is augmentation that attempts to decrease the pest density by increasing the density of the predator in the crop for a short time. Third and the last type is called conservation that deal with the intentional supplementation of the natural predator in the crop to increase their population and successful elimination of the pest from crop (Roche, 1994). The division of biological control is only arbitrary and interlinked with each other. 
 
Cotton is one of the most important crops of Asia economically. According to a recent study in China, which included experimental work on 76 species (53 genera) of arthropod predator and parasitoid of Lepidoptera pest and 46 species (29 genera) of natural enemies of sucking pest, increased density of natural enemies resulted in the prevention of the spread of cotton aphids (Sczostak, 2009). Biological control is a desirable safe method for the control of pest in crops but it has certain disadvantages. First, once the beneficial predator is introduced in the crops of particular region, it is possible that this insect becomes more dominant then the pest and localized itself in the crop permanently. It is also impossible to remove this natural enemy from the crops once the objective id accomplished. Secondly there is a probability that the insect or biological organism introduced to control pest do more harm to the crop then the pest itself. 
 
4 Weeds of Cotton
4.1 The damage of weed
The word ‘weed’ is used to describe the plants ‘out of place’ or undesirable or invaluable plant species. Many of the plants which are regarded as weeds now, have been used in prehistoric era for food and fiber but new varieties have superseded them.  Some of these weeds are still used for medicinal purposes, but their presence in the crops is always undesirable (Rajput et al., 2008; Rashid et al., 2016). All around the world, diverse flora of weeds associated with the cotton fields have been reported (Kalivas et al., 2010; Norsworthy et al., 2007). After insect pests, weeds are responsible for the highest yield loss in crops. The annual cotton yield resulted by weeds can go up to 90% (Oerke et al., 2006). 
 
When two plants of different species grow in association, the negative effect of one plant on the other is called ‘interference’. Interference is usually used to describe the undesirable influence of weeds on the crops, although crop can also have deleterious effect on the weed growth (Street et al., 1981). Two major components of weed interference are: allelopathy and competition. 
 
Competition occurs when two different plant species are relying on same, limited resource pool. Weeds and crops can compete for nutrients, water, light and carbon dioxide. Sometimes, weeds release deleterious substances in environment that halts the growth of the crop. This phenomenon is called allelopathy. Allelopathic substances are released from the roots or leaves in the form of exudates. They can also be added in the soil as a result of decaying plant material. In field, it is difficult to differentiate the interference induced by allelopathic and competition mechanisms (Munger et al., 1984). Other than competition and allelopathic effects, weeds also cause loss of crops indirectly by hindering harvesting, quality deterioration and harboring the cotton pests and pathogens (Doğan et al., 2014).
 
4.2 Competitive effects of weed on cotton
Oxygen and carbon dioxide are rarely a limiting source for plant growth, because of the continuous air movements. Main resources for which weeds and crops do compete are water, light and nutrients (Coble et al., 1992). Weed competition causes the reduction of bolls per plant of cotton, and thus reduces the quantity of the product (Arle et al., 1973). To device efficient control techniques for weeds, it is important to understand the mechanism of competition. Weed species can affect the level of interference, as few species are more competitive than the others (Coble et al., 1992). Weed density also affects the level of interference with the crop. Weed density and yield loss show linear behavior i.e. the more the weeds are dense the more prominent is the yield loss. However at higher weed densities, the intra-weed competition also dominates and the loss of the crop becomes less (Holshouser et al., 1992). Weed duration is another important factor of interference. Weeds that emerge earlier or at the same time of crop emergence, are more competitive then the later emerging weeds, and thus causes greater cop loss. Therefore the crop should be kept weed free for longer time from more competitive weeds (Keeley et al., 1986). In conclusion, weeds can damage the crops and reduces the yield both directly and indirectly. When a single weed control practice is applied, many perennial and competent weeds escape the control strategy. Therefore an integrated weed management practices are being developed to effectively tackle the issue (Doğan et al., 2014). 
 
Insect pests and weeds are major reason for major yield losses in crops and it can be costly to control them. There is approximately 10-20 percent loss in productivity of major crops worldwide due to insects attack. This percentage is far more than expected in developing countries because of lack of management. These insects can be so much disastrous that a single attack of insect such as cotton bollworm (helicoverpa) can destroy entire cotton crop if not controlled properly. In the same way, weed also act as a hindrance in the yield of the crops. Therefore in addition to insect control, weed control is also essential for high yield of crops (Fitt, 2000).
 
4.3 Integrated weed management
Integrated weed management includes the group of techniques and tools that are used collectively to prevent the advent of weed in the crop. These techniques are cost effective, environmental friendly as well as beneficial for the yield of the crops. IWM utilizes scientific knowledge and resources to avoid weed production in crops at all time (Buhler). Thorough information of the prevailing weed is necessary for the implementation of the IWM systems (Farrell and Johnson, 2005).
 
5 Agronomic Practices
5.1 Farm management
It is a group of farm management systems that help to improve texture, water content and nutrient rotation of the soil as well as provide favorable environment for crop by the use of fertilizer and other farming practices. In weed control farming management is manipulated in such a way that in hinders the seedling, growth and reproduction of the weed in the crop. The utilization of cleaned cotton seed in the clean and well managed cultivation conditions is one of the most important prevention measure in cotton crops (Labrada et al., 2006).
 
Repetition of the same weed control processes or crop may results in the resistance of a weed in the region. In order to avoid this crop rotation was also done (Farooq et al., 2011). In some area of the USA the cotton crop ground are covered with cereal crops in summer which is an effective approach to reduced weed population (Farooq et al., 2011; Reiter et al., 2008).
 
In the study done by Eiszner et al.(1996) on the cotton and soybean rotation it was observed that the population of Cyperus rotundus decreases considerably. After five year of this rotation the biomass of the weed was found to be lowest. Similarly the population of Cyperus esculentus L (yellow nutsedge) was reduced by the rotation of peanut with the cotton (Johnson and Mullinix, 1997).
 
In another approach to control weed population, the duration between tilling and seed bed preparation was prolonged so that all the present weed seed can germinate in the time being and can be removed effectively from the field before sowing cotton seed. This approach was tested and in one study it was reported that there was 90% less density of weed in the field as compare to conventional practice (Dogan et al., 2009). Plant spacing also play important role in weed control. According to study conducted by Webster the spacing of 25 cm in the cotton crop resulted in the reduction of weed by 80 % margin (Webster, 2007).
 
5.2 Chemical control: spray
The most common method of weed control is the use of herbicides. The herbicides are used pre and post emergence of the weed. The herbicides used preemergence are very successful in the control pf monocotyledonouse weed. Treatment of the field before the appearance of weed was observed to show very positive impact on the yield and health of the crops. In one study conducted by Everitt and Keeling on 2,4-D, dicamba and diflufenzopyr + dicamba against horseweed in cotton, it was reported that 2,4-D showed good control on the weed (Conyza canadensis) when sprayed before the cotton sowing wherese result with dicamba and diflufenzopyr + dicamba were discouraging. Pendimethalin is another herbicides which is very effective and is applied excessively for the weed control in wide variety of crops (Jabran et al., 2008).
 
Pendimethalin is used to suppress the population of Trianthema monogyna L, Digera arvensis Forsk, Willd and Dactyloctenium aegyptium etc. (Jarwar et al., 2005; Khaliq et al., 2007). In one study this herbicide reduces the weeg population by 78 % to the control crop (Khaliq et al., 2007). One addition example of preemergence herbicide is S-metalachor which showed great promises in weed control (Iqbal and Cheema, 2008). Postemergence herbicides are involve in the elimination of weed that escape all the other IWP. Burke el al. reported the work he done on the trifloxysulfron against C. rotundus and C. esculentus. He observed 56 % the reduction in the biomass of the weed. These herbicides are sprayed directly on the weed so that it does not affect the main crop. It is done to protect cotton from any damage of the spray. Number of studies indicated the effectiveness of the herbicide use after the emergence of weed (Ali et al., 2005). Likewise, the use of flumioxazin in cotton successfully eliminated weed i.e. Sida spinosa L, Amaranthus palmeri, C. album, Ambrosia artemisiifolia L. and Senna obtusifolia (Ali et al., 2005). Admiinistration of glyphosate reduces the weed intensity to a considerable rate but it was less productive then the flumioxazin. 
 
Both pre and post emergence herbicides can be used for the control and elimination of the weed from the crop but these herbicides have some disadvantages. The herbicides are not weed specific and can affect the crop if sprayed in an unguided manner. Also they can have effect on the normal environment of the crop resulting in the disruption of the local natural enemies and other predators. Lastly, the residual effect of the herbicides on the food crops can be dangerous for the human health.
 
6 Molecular Biotechnology for Stable Insect Pest and Weed Control in Cotton
6.1 Transgenic cotton (genetically modified cotton)
Transgenic cotton is the plant who’s DNA (genetic material) has been modified by the introduction of foreign gene using gene manipulation techniques to enable this plant to express the gene of interest which does not exist in the parent plant. In 1996, first GM cotton was approved for a commercial use containing a protein which was toxic for the Helicoverpa caterpillar pest (Downes et al., 2010). The GM cotton was introduced by Monsanto named Ingard® cotton. This cotton was also referred to as BT cotton because the gene was transferred from the bacterium called Bacillus thuringinesis. The second variety called Bollgard® II was commercialized in 2003 which replaced the Ingard very rapidly. The reason was the expression of two proteins of Bacillus thuringinesis that prevented the resistance of caterpillar against the protein toxin (Doyle, 2005).
 
GM cotton was alone responsible for the production of 90-95% of the cotton in Australia in 2006-7. Due to the designed resistance of Bollgard II against insecticides, the usage of spray was reduced by 75% compared with control cotton. Also the selection of spray became more specific and it helped in the growth of natural enemies normally in the crop. However, the yield level remains the same between the Bt cotton and the naturally preexisting cotton crops. It was observed that after the introduction of Bollgard II and good management practices the density of the pest decreased in the field area and the water resources around the field as well (Doyle, 2005).
 
Glyophosate use in the bt crops have greatly reduced the use of other herbicides as it is very effective, residual free, less toxic and non-mobile herbicide. Utilization of glyphosate provides more control on the weed growth. But still the extensive use of this herbicide id indicated to confer resistance in the Bt cotton at a rate higher than the conventional crops. Therefore preventive methodologies are adapted to avoid the resistance against this herbicide (Charles et al., 2004; Rizwan et al., 2015). In addition to this, studies are being made to make plant express glyphosate by following the same approach of genetic modification so that cotton can be made resistant against a broad spectrum of pest and this may even prevent the resistance against protein toxin in the pest (Reddy, 2004; Husnain, 2015). 
 
Also the approach to transfer the gene from one plant species to another plant species is underway to make crop more tolerant toward abiotic factors in addition to biotic factor in the environment (Ali et al., 2016; Ali et al., 2014; Josipović et al., 2014). Novel traits which are promising for enhancing the uniqueness of cotton based products, increasing the fiber productivity and products for improving the human health are being presented (Wilkins et al., 2000; Bhutta et al., 2015). In the recent study, the cotton variety MNH-786 was engineered in a different cassette under  35S GTGene and Cry1Ac+Cry2A insects and herbicide by promoter transformation then modified cotton shows resistant against lepidopteron (Awan et al., 2015; Aaliya et al., 2016).
 
GM cotton has been increased widespread which covers about 43% of world’s cotton. In China more than 68% of cotton has been genetically modified to produce a toxin which can protect it from harmful insects. Gene encoding for Cry proteins are now being added in the cotton plant to develop the BT cotton. This toxin gets dissolved when insects feeds on the plant due to high stomach pH of the insect. After getting dissolved the toxin gets activated and bound to cadherin like protein. Cadherin like proteins are present on the cells which comprise the brush border molecules in the gut of the insect. Brush border epithelial cells basically separate the gut from body cavity and allow the access to the nutrients. Ion channels are formed in the gut when cry protein binds to the specific locations on cadherin- like proteins. As a result, regulation of potassium is lost and epithelial cell dies and eventually death of the insect occurs. BT cotton is also been produced by Pakistan now. BT cotton has many beneficial and harmful effects on cotton crop. Increased yield, reduction in pesticides, cost , environmental pollution as well as early maturing capability are some advantages of BT cotton (YuLin et al., 2015).
 
Different enzymes are used in cotton to develop disease resistance. Glucanase, chitinase and glucose oxidases attack the cell wall of invading fungi. To develop disease resistant transgenics viral replicase or coat protein genes, Magainin 1 and 2 from frogs and antibacterial cecropins from silkmoth are also being used. For developing resistance to cotton leaf curl virus antisense DNA of CLCuV, antisense DNA of AC2 and AC3 along with DNA-A borne AC1 gene was used (Kouser and Qaim, 2015).
 
6.2 Genomics and molecular biology techniques
Traditional plant breeding methods were used to develop the non-transgenic herbicide resistant crops. Controlling the weeds and insects attack from plant would results in increased crop yield without additional inputs. Herbicides are “antimetabolites” which basically deals with key enzymes of the plant such as acetolactate synthase, dihydropteorate synthase, glutamine synthase, enol-pyruvate shikimate phosphate synthase and phyotene dasaturase. Genes encoding these enzymes have been isolated and and sequenced by next generation sequencing and then used in transgenic program. Advances in protein modeling and site specific mutations are supplemented by diagnostic techniques which detect resistance earlier will improve risk management of resistance. However before the agronomy would translate these practices in antiresistance strategies more resources would need to be develop to the cell biology and biochemistry of pests , insects and weeds to manage the resistance in future (Hollomon, 2012).
 
Genomics can be used to elucidate pharmaceutical drugs for affecting chemical targets which are spread to pesticide industry. Many enzymes in plants are not suitable for herbicide action on plants due to redundancy within and among different gene families. Some pesticides inhibit a whole pathway in plant and as a result plant die by starvation. Blockage imposed by herbicides cause accumulation of toxic products in the plant and weak the weeds then other factors kill the plants. That’s why incomplete gene suppression is carried out by antisense and over expression of gene is done which is better than to carry out knock out and gene deletion. In order to modify cotton crops, deleterious transposons should be dispersed throughout the weed population (Gressel, 2000).
 
6.3 Gene identification
A variety of methods can be used to discover genes although a significant approach is mainly to produce and sequence library of gene which are expressing (Table 3). This library mostly has thousands of cDNA which are express by that plant under specific conditions. Once cDNAs are sequence they are called 13expressed sequence tags. An enormous amount of ESTs are present in many databases of many model plants and crops. These EST databases from different plants are comparing to find more diversity in coding genes and to find genes that can provide resistance against biotic stresses like pest, insect and weeds. When a high intensity of similar sequences are found between a gene of known function in other plant species and an EST, function of that gene in a species of interest can be deduced (da Silva and Yücel, 2008). Though, the definite explanation of gene function finally requires experimental verification. To understand the entire organism gene function and to incorporate novel genes to increase genetic diversity, plant biotechnology is now paying attention on ultra-high throughput techniques by means of in vitro mutagenesis, microarrays, marker-assisted selection and proteomics. In the end the recognized genes of known functions 13 will expressed in genetically engineered plants. Many high throughput techniques provide new ways to discover genes and to find polymorphic sites in genes at whole genome level at a very low price (Sharma et al., 2002).
 
SNPs are DNA polymorphisms causes’ genetic changes up to 90% in any organism, therefore DNA based markers are mostly grouped into SNPs and non-SNP markers. SNPs are genomic sequences accessible in the databases. Once SNPs are revealed, these markers genotyping can be done by using any one of >30 different existing methods, though only minority of these methods are microarray based, given that most wanted ultra- high throughput (Gupta et al., 2008). To use the molecular markers in cotton breeding, main reason is 100% heritability of the markers in next generation and their cost effectiveness. Therefore, molecular markers are widely being use in assortment of traits like insects, pest and weed resistance. In cotton breeding, marker-assisted selection is a pretty new concept. Efficient MAS require very saturated map of genes. Both intraspecific and interspecific linkage investigation showed that the cotton genetic map is approximately 5000 cM. In cotton a well saturated gene map with a genome of length 5000 cM will need 3000 DNA markers to map at 1 cM density (Boopathi et al., 2011).
 
 

Table 3 Major classes of markers used for indirect selection in plant breeding (Sharma et al., 2002)

 
6.4 Microarray based DNA markers 
It is anticipated that in near future, Microarray based techniques and many other non-array high-throughput genotyping schemes like Simple sequence repeat length polymorphism (SSR), EST MassArray and SNPlex9 will come into practice for a number of tasks such as for the development of genomic maps and in functional and evolutionary studies. It is also reported  that many RAD, DarT and SFPs markers are in effect (Boopathi et al., 2011). For many crops,  GeneChips for SFP genotyping and the diverse microarrays for DArT markers have been developed but are cost effective (Udall et al., 2007). At present the leading competitors for microarray-based genotyping are Illumina and Affymetrix GoldenGate genotyping (Gupta et al., 2008).
 
6.5 GoldenGate genotyping
Illumina’s GoldenGate assay is one of the most well-liked BeadArray technology is also cost effective 2 (expenses are $0.03/genome) for an huge amount of samples for genotyping with an optimized collection of SNP markers separately (Gupta et al., 2008). Every assay engage a multiplexed SNP genotyping reaction, having a locus-specific oligonucleotide and two allele-specific oligonucleotides for every SNP, an anti-tag sequence is present on locus-specific oligonucleotide which will be detected by the BeadArray. 96 or 384 BeadArrays are placed 22in a matrix called Sentrix Arrays Matrix, in one reaction where upto 384 samples can be processed for 1536 SNPs, at the same time. Golden Gate technology is nowadays use in the improvement of biotic and abiotic factors in many crops (Gupta et al., 2008). 
 
6.6 Infinium assay for whole genome genotyping
Illumina’s Bead Chip-based assay is a universal method for genotyping.  Bead Array technology and is directly used to identify most SNPs in a genome. It eliminate the multiplexing restricted access in sample preparation, significantly  used in Golden Gate (Gupta et al., 2008). Bead Arrays contain the total hybridized genomic sequence in the form of bead chip on a microscope slide with 12 sections where each section contains 1.1 million beads, with decoded oligonucleotides. 96 Bead Chips can be used at the same time in a temperature controlled chamber act as an automated assay of many DNA samples concurrently, in this way permit genotyping of thousands of SNPs of many genotypes at once (Steemers and Gunderson, 2007).
 
6.7 MegAllele genotyping system (molecular inversion probe or MIP technology) 
MegAllele genotyping system of Affymetrix for each assay four reaction tubes are used and in each tube 9 tens of thousands of genotyping reactions are allowed in each of four tubes. A single particular nucleotide is added. On the contrary, Golden Gate uses allele specific primer extension to achieve SNPs. A single circular probe called padlock probe is also used in MIP, while upstream and downstream probes are separate in Golden Gate assay. Still, MIP looks like GoldenGate assay in utilizing tags present in in MIP in the form of glass GenFlex Tag Array and Bead Arrays in Golden Gate assay, that are used to reveal the products of SNP genotyping reactions. Recently bread wheat use a technology that make use of customized padlock probes as used in MegAllele system and it will be used in future in other crops like cotton (Gupta et al., 2008; Reid, 2007). 
 
6.8 GeneChip and allele-specific oligonucleotide tiling arrays
GeneChip and allele-specific oligonucleotide tiling arrays Tiling arrays are Affymetrix GeneChip policy based. In this technique known sequence are used to find and detect SNP in several organisms. These tiling assays can be used for re-sequencing of precise genomic regions for SNP genotyping or cross- examine each nucleotide in a template genomic sequence by different probes present in  the array (Gupta et al., 2008). 
 
7 Future Prospects 
The pest resistance developed by Bt crops is considered to limit field durability (Gatehous et al., 2002), so the pyramiding of genes encoding different Bt toxins has been developed for controlling the development of pest resistance. Expressing insecticidal proteins from sources other than B. thuringiensis in crop plants reduce the chances for development of insect resistance to toxins. Therefore, other methods based on the expression of toxins produced by foreign genes from plants (e.g. lectins and enzyme inhibitors) (Ceci et al., 2003; Mohamed et al., 2015) and from animal sources including insects (e.g. biotin-binding proteins) (Burgess et al., 2002; Ahmad et al., 2015), neurohormones (Fitches et al., 2002) and enzyme inhibitors (Christeller et al., 2002) are being developed. Toxins from other pathogens are also opening new ways to transgenic pest control. To increase the spectrum and durability of resistance the use of fusion proteins is actively being pursued, such as the development of hybrid Cry proteins (Naimov et al., 2001) that has increased activities against insect pest. A key challenge that is still facing the biotechnologist is the identification of novel genes that will produce insecticidal products with desired characteristics that will be used in transgenic plants. So for this following tools may become successful in future.
 
Next generation techniques by providing with high throughput, low cost alternatives compared to the Sanger sequencing methods has revolutionized. These techniques developed gradually from first-generation to fourth-generation with extremely large number of applications. They are unrevealing the complexity of the genome, in terms of genetic variations. They have huge impact in plant protection (Mardis, 2008). NGS includes several technologies having distinct sequencing biochemical approaches and is highly used because of its ability to simultaneously perform millions of reactions. The large applications of NGS are whole transcriptome sequencing and the targeted sequencing (Bras et al., 2012; Mardis and Wilson, 2009). Although NGS have a large range of biological impact, the costs per sample limit the use these techniques. High-throughput techniques have reduced the burden of the costs of sequencing. For example, sequencing costs have greatly reduced from $5,292.39/Mb in 2001 to $0.06/Mb in April 2013 (Spurdle et al., 2010). The sequencing costs will further reduce by using advancing techniques.
 
Post transcriptional gene silencing or RNAi to target specific pests while not affecting other species is an absolute method for pest management. Another desirable prospect of RNAi is that it may not be necessary to directly kill pests. The communication system of pests for mating or their host plant-seeking behaviors can be blocked, if the insect’s pheromone receptors are silenced by using RNAi and as the pest population will greatly be controlled. One day the transgene-encoded ingestible dsRNA may stand alongside Bt transgenes in insect pest management programs (Gordon et al., 2007; Shahid et al., 2016). Keeping in view of high capacity of chloroplasts to express and accumulate foreign proteins, transgene stacking in operons and a lack of epigenetic interference with the stability of transgene expression, chloroplast transformation is very emerging and useful in cotton protection. In addition, this technology provides an environmentally friendly method of plant genetic engineering, because plastids are maternally inherited in most crops (Bock, 2007).
 
References
Aaliya K., Qamar Z., Nasir I.A., Ali Q., Munim A.F., 2016, Transformation, evaluation of gtgene and multivariate genetic analysis for morpho-physiological and yield attributing traits in Zea mays, Genetika, 48(1): 423-443
https://doi.org/10.2298/GENSR1601423A
 
Abbas H., Mahmood A., and Ali Q., 2013, Genetic variability, heritability, genetic advance and correlation studies in cotton (Gossypium hirsutum L.), Int. Res. J. Microbiol., 4(6): 156-161
 
Abbas H.G., Mahmood A., and Ali Q., 2015, Genetic variability and correlation analysis for various yield traits of cotton (Gossypium hirsutum L.), J Agric Res., 53(4): 481-491
 
Abbas H.G., Mahmood A., and Ali Q., 2016, Zero tillage: A potential technology to improve cotton yield, Genetika,48(2): 761-776
https://doi.org/10.2298/GENSR1602761A
 
Abdullah A., Brobst S., Pervaiz I., Umer M., and Nisar A., Agri Data Mining/Warehousing, Innovative Tools for Analysis of Integrated Agricultural & Meteorological Data, pp. 1-10
 
Abdullah A., 2010, An analysis of Bt cotton cultivation in Punjab, Pakistan using the agriculture Decision Support System (ADSS), AgBioForum, 13(3): 274-287
 
Ahmad H.M., Rahman M., and Ali Q.A.S., 2015, Plant cuticular waxes: a review on functions, composition, biosyntheses mechanism and transportation, Life Sci. J., 12(4s): 60-67
 
Ahmad M., Khan N.U., Muhammad F., Khan S.A., Munir I., and Bibi Z., 2011, Genetic potential and heritability studies for some polygenic traits in cotton (Gossypium hirsutum L.), Pak. J. Bot., 43(3): 1713-1718
 
Akhtar S., Shahid A.A., Rao A.Q., Bajwa K.S., Muzaffar A., and Latif A., 2014, Genetic effects of Calotropis procera CpTIP1 gene on fiber quality in cotton (Gossypium hirsutum), Advancements in Life Sciences, 1(4): 223-230
 
Akram N., ul Husnain M.I., Qureshi S.A., 2011, Poverty-Environment Nexus: Use of Pesticide in Cotton Zone of Punjab, Pakistan, Journal of Sustainable Development, 4(3): 163
 
Ali H., Muhammad D., and Abid S.A., 2005, Weed control practices in cotton (G ossypium h irsutum L.) planted on bed and furrow, Pak. J. Weed Sci. Res., 11(1-2): 43-48
 
Ali M.A., Rehman I., Iqbal A., Din S., Rao A.Q., and Latif A., 2014, Nanotechnology, a new frontier in Agriculture, Adv. life Sci., 1(3): 129-138
 
Ali Q., Ahsan M., Kanwal N., Ali F., Ali A., and Ahmed W., 2016, Screening for drought tolerance: comparison of maize hybrids under water deficit condition, Advancements in Life Sciences, 3(2): 51-58
 
Ali Q., Ali A., Ahsan M., Nasir I.A., Abbas H.G., and Ashraf M.A., 2014, Line× Tester analysis for morpho-physiological traits of Zea mays L. seedlings, Advancements in Life Sciences, 1(4): 242-253
 
Arle H., and Hamilton K., 1973, Effect of annual weeds on furrow-irrigated cotton, Weed Science, 325-327
 
Awan M., Abass M., Muzaffar A., Ali A., Tabassum B., and Rao A., 2015, Transformation of insect and herbicide resistance genes in cotton (Gossypium hirsutum L.), Journal of Agricultural Science and Technology, 17(2): 287-298
 
Azam S., Samiullah T.R., Yasmeen A., ud Din S., Iqbal A., and Rao A.Q., 2013, Dissemination of Bt cotton in cotton growing belt of Pakistan, Advancements in Life Sciences, 1(1): 18-26
 
Azfar S., Nadeem A., and Basit A., 2015, Pest detection and control techniques using wireless sensor network: A review, Journal of Entomology and Zoology Studies, 2(3): 92-99
 
Bakhsh A., Rao A.Q., Shahid A.A., Husnain T., and Riazuddin S., 2009, Insect resistance and risk assessment studies in advance lines of Bt cotton harboring Cry1Ac and Cry2A genes, American-Eurasian Journal of Agricultural and Environmental Sciences, 6(1): 1-11
 
Bhutta M., Muhammad K., Muhammad K., Mahmood A., Malook S., and Ali Q., 2015, Oxidative damage caused by Reactive Oxygen Species under drought stress in Gossypium hirsutum, Life Sci. J., 12(4s): 51-59
 
Bock R., 2007, Plastid biotechnology: prospects for herbicide and insect resistance, metabolic engineering and molecular farming, Current Opinions in Biotechnology, 18(2): 100-106
https://doi.org/10.1016/j.copbio.2006.12.001
PMid:17169550
 
Boopathi N.M., Thiyagu K., Urbi B., Santhoshkumar M., Gopikrishnan A., and Aravind S., 2011, Marker-assisted breeding as next-generation strategy for genetic improvement of productivity and quality: can it be realized in cotton? International Journal of Plant Genomics, Article ID 670104, pp.16
http://dx.doi.org/10.1155/2011/670104
 
Boyd M.L., Phipps B.J., and Wrather J.A., 2004, Cotton pests: scouting & management, Columbia: MU Extension, University of Missouri-Columbia
 
Bras J., Guerreiro R., and Hardy J., 2012, Use of next-generation sequencing and other whole-genome strategies to dissect neurological disease, Nat. Rev. Neurosci., 13(7): 453-464
https://doi.org/10.1038/nrn3271
PMid:22714018
 
Burgess E.P., Malone L.A., Christeller J.T., Lester M.T., Murray C., and Philip B.A., 2002, Avidin expressed in transgenic tobacco leaves confers resistance to two noctuid pests, Helicoverpa armigera and Spodoptera litura, Transgenic Res., 11(2): 185-198
https://doi.org/10.1023/A:1015297302990
PMid:12054352
 
Ceci L.R., Volpicella M., Rahbe Y., Gallerani R., Beekwilder J., and Jongsma M.A., 2003, Selection by phage display of a variant mustard trypsin inhibitor toxic against aphids, Plant J., 33(3): 557-566
https://doi.org/10.1046/j.1365-313X.2003.01645.x
PMid:12581313
 
Chapagain A., Hoekstra A., Savenije H., and Gautam R., 2006, The water footprint of cotton consumption: An assessment of the impact of worldwide consumption of cotton products on the water resources in the cotton producing countries, Ecological Economics, 60(1): 186-203
https://doi.org/10.1016/j.ecolecon.2005.11.027
 
Charles G., Taylor I., and Roberts G., 2004, The impact of the cotton farming system on weed succession: implications for herbicide resistance and adoption of an integrated weed management approach, 14th Australian Weeds Conference’ Wagga, NSW (Eds BM Sindel, SB Johnson)
 
Christeller J.T., Burgess E.P., Mett V., Gatehouse H.S., Markwick N.P., and Murray C., 2002, The expression of a mammalian proteinase inhibitor, bovine spleen trypsin inhibitor in tobacco and its effects on Helicoverpa armigera larvae, Transgenic Res., 11(2): 161-173
https://doi.org/10.1023/A:1015210919077
PMid:12054350
 
Coble H.D., and Byrd J.D., 1992, Interference of weeds with cotton, Weeds of Cotton: Characterization and Control Memphis, TN: The Cotton Foundation, 73-84
 
da Silva J.A.T., and Yücel M., 2008, Revealing response of plants to biotic and abiotic stresses with microarray technology, Genes, Genomes and Genomics, 2(1): 14-48
 
Dogan M., Ünay A., Boz Ö., and Ögüt D., 2009, Effect of pre-sowing and pre-emergence glyphosate applications on weedsin stale seedbed cotton. Crop Protection, 28(6): 503-507
https://doi.org/10.1016/j.cropro.2009.01.013
 
Doğan M.N., Jabran K., and Unay A., 2014, Integrated Weed Management in Cotton, Recent Advances in Weed Management: Springer; pp.197-222
PMid:23463344
 
Downes S., Mahon R.J., Rossiter L., Kauter G., Leven T., and Fitt G., 2010, Adaptive management of pest resistance by Helicoverpa species (Noctuidae) in Australia to the Cry2Ab Bt toxin in Bollgard II® cotton. Evolutionary Applications, 3(5): 574-584
https://doi.org/10.1111/j.1752-4571.2010.00146.x
PMid:25567948 PMCid:PMC3352500
 
Doyle B., 2005, The performance of Ingard and Bollgard II cotton in Australia during the 2002/2003 and 2003/2004 seasons. Armidale, Australia: University of New England
 
Eiszner H., Blandón V., and Pohlan J., 1996, Agronomic and ecological impacts on cotton with changing crop rotation, Der Tropenlandwirt-Journal of Agriculture in the Tropics and Subtropics, 97(1): 75-83
 
Elahi M., Cheema S., Basra M.A., and Ali Q., 2011, Use of Allelopathic water extract of field crops for weed control in Wheat, Int. Res. J. Plant Sci., 2(9): 262-270
 
Farooq M., Jabran K., Cheema Z.A., Wahid A., and Siddique K.H., 2011, The role of allelopathy in agricultural pest management, Pest Management Science, 67(5): 493-506
https://doi.org/10.1002/ps.2091
PMid:21254327
 
Farrell T., and Johnson A., 2005, Cotton pest management guide 2005/06, NSW Department of Primary Industries
 
Fitches E., Audsley N., Gatehouse J.A., and Edwards J.P., 2002, Fusion proteins containing neuropeptides as novel insect contol agents: snowdrop lectin delivers fused allatostatin to insect haemolymph following oral ingestion, Insect Biochem Mol Biol., 32(12): 1653-1661
https://doi.org/10.1016/S0965-1748(02)00105-4
 
Fitt G.P., 2000, An Australian approach to IPM in cotton: integrating new technologies to minimise insecticide dependence, Crop Protection, 19(8): 793-800
https://doi.org/10.1016/S0261-2194(00)00106-X
 
Gatehouse A.M., Ferry N., and Raemaekers R.J., 2002, The case of the monarch butterfly: a verdict is returned, Trends Genet., 18(5): 249-251
https://doi.org/10.1016/S0168-9525(02)02664-1
 
Gordon K.H., and Waterhouse P.M., 2007, RNAi for insect-proof plants. Nature biotechnology, 25(11): 1231-1232
https://doi.org/10.1038/nbt1107-1231
PMid:17989682
 
Gressel J., 2000, Molecular biology of weed control, Transgenic Research, 9(4-5): 355-382
https://doi.org/10.1023/A:1008946628406
PMid:11131013
 
Gupta P., Rustgi S., and Mir R., 2008, Array-based high-throughput DNA markers for crop improvement, Heredity, 101(1): 5-18
https://doi.org/10.1038/hdy.2008.35
PMid:18461083
 
Hayee A., 2005, Cultivation of Bt cotton-Pakistan’s experience’, Actionaid-Pakistan, Islamabad
 
Hollomon D.W., 2012, Do we have the tools to manage resistance in the future? Pest Management Science, 68(2): 149-154
https://doi.org/10.1002/ps.2291
PMid:22223198
 
Holshouser D., and Chandler J., eds, 1992, Influence of Johnsongrass density and period of competition on corn yield, Proc. South Weed Sci. Soc.
 
Husnain T., 2015, Transformation and transgenic expression studies of glyphosate tolerant and cane borer resistance genes in sugarcane (Sccharum officinarum L.), Molecular Plant Breeding, 6(12)
 
Iqbal J., and Cheema Z.A., 2008, Purple nutsedge (Cyperus rotundus L.) management in cotton with combined application of sorgaab and s-metolachlor, Pak. J. Bot., 40: 2383-2391
 
Jabran K., Cheema Z., Farooq M., Basra S., Hussain M., and Rehman H., 2008, Tank mixing of allelopathic crop water extracts with pendimethalin helps in the management of weeds in canola (Brassica napus) field, Int. J. Agric. Biol., 10(3): 293-296
 
Jarwar A., Baloch G., Memon M., and Rajput L., 2005, Efficacy of pre and post-emergence herbicides in cotton, Pakistan Journal of Weed Science Research, 11(3/4): 141-145
 
Johnson III W.C., and Mullinix Jr B., 1997, Population dynamics of yellow nutsedge (Cyperus esculentus) in cropping systems in the southeastern coastal plain, Weed Science, 166-171
 
Josipović M., Plavšić H., Kovačević V., Marković M., and Iljkić D., 2014, Impacts of irrigation and genotype on yield, protein, starch and oil contents in grain of maize inbred lines. Genetika, 46(1): 243-253
https://doi.org/10.2298/GENSR1401243J
 
Kalivas D.P., Economou G., and Vlachos C.E., 2010, Using geographic information systems to map the prevalent weeds at an early stage of the cotton crop in relation to abiotic factors, Phytoparasitica, 38(3): 299-312
https://doi.org/10.1007/s12600-010-0101-0
 
Keeley P.E., Thullen R.J., and Carter C.H., 1986, Influence of planting date on growth of ivyleaf morningglory (Ipomoea hederacea) in cotton (Gossypium hirsutum), Weed Science, 906-910
 
Khaliq A., Jabran K., Mushtaq M., Razzaq A., and Cheema Z., 2007, Reduction of herbicide dose using allelopathic crop/plant water extracts with lower rates of pendimethlin in cotton, Gossypium hirsutum. In: 8th National Weed Science Conference, G. C. University, Lahore, 25–27
 
Khan A.I., Fu Y.B., and Khan I.A., 2009, Genetic diversity of Pakistani cotton cultivars as revealed by simple sequence repeat markers, Communications in Biometry and Crop Science, 4(1): 21-30
 
Khan M.A.U., Shahid A.A., Rao A.Q., Shahid N., Latif A., and ud Din S., 2015, Defense strategies of cotton against whitefly transmitted CLCuV and Begomoviruses, Advancements in Life Sciences, 2(2): 58-66
 
Kouser S., and Qaim M., 2015, Bt Cotton, pesticide use and environmental efficiency in Pakistan, Journal of Agricultural Economics, 66(1): 66-86
https://doi.org/10.1111/1477-9552.12072
 
Labrada R, Singh H, Batish D, and Kohli R., 2006, Weed management: a basic component of modern crop production. Handbook of sustainable weed management, 21-49
 
Mardis E.R., and Wilson R.K., 2009, Cancer genome sequencing: a review, Hum. Mol. Genet., 18(R2)
https://doi.org/10.1093/hmg/ddp396
PMid:19808792 PMCid:PMC2758710
 
Mardis E.R., 2008, The impact of next-generation sequencing technology on genetics, Trends Genet., 24(3): 133-141
https://doi.org/10.1016/j.tig.2007.12.007
PMid:18262675 PMCid:PMC2680276
 
Mohamed B.B., Sarwar M.B., Hassan S., Rashid B., Aftab B., and Husnain T., 2015, Tolerance of roselle (Hibiscus sabdariffa L.) genotypes to drought stress at vegetative stage, Advancements in Life Sciences, 2(2): 74-82
 
Munger P., Abernathy J., and Gipson J., eds., 1984, The influence of selected plant residues on cotton and sorghum establishment, Proceeding of Southern Weed Science Socoety
 
Naimov S., Weemen-Hendriks M., Dukiandjiev S., and de Maagd R.A., 2001, Bacillus thuringiensis delta-endotoxin Cry1 hybrid proteins with increased activity against the Colorado potato beetle, Appl. Environ. Microbiol., 67(11): 5328-5330
https://doi.org/10.1128/AEM.67.11.5328-5330.2001
PMid:11679364 PMCid:PMC93309
 
Nazli H., Sarker R., Meilke K.D., and Orden D., eds., 2010, Economic performance of Bt cotton varieties in Pakistan. conference paper
 
Norsworthy J.K., Smith K.L., Scott R.C., and Gbur E.E., 2007, Consultant perspectives on weed management needs in Arkansas cotton, Weed Technology, 21(3): 825-831
http://dx.doi.org/10.1614/WT-06-204.1
 
Oerke E.C., 2006, Crop losses to pests, The Journal of Agricultural Science, 144(1): 31-43
https://doi.org/10.1017/S0021859605005708
 
Puspito A.N., Rao A.Q., Hafeez M.N., Iqbal M.S., Bajwa K.S., and Ali Q., 2015, Transformation and Evaluation of Cry1Ac+ Cry2A and GTGene in Gossypium hirsutum L., Frontiers in Plant Science, 6
https://doi.org/10.3389/fpls.2015.00943
 
Rajput M.T., Tahir S.S., Ahmed B., and Arain M.A., 2008, Check list of the weeds found in cotton crops, cultivated in Taluka Ubauro, district Sukkur, Pakistan, Pakistan Journal of Botany, 40(1): 65
 
Rashid B.H.T., Yousaf I., Rasheed Z., Ali Q., Javed F., and Husnain T., 2016, Roadmap to sustainable cotton production, Life Science Journal, 13(11): 41-48
 
Reddy K.N., 2004, Weed control and species shift in Bromoxynil and Glyphosate resistant cotton (Gossypium hirsutum) rotation systems.Weed Technology, 18(1): 131-139
http://dx.doi.org/10.1614/WT-03-059R
 
Reid R., 2007, Identification of boron transporter genes likely to be responsible for tolerance to boron toxicity in wheat and barley, Plant and Cell Physiology, 48(12): 1673-1678
https://doi.org/10.1093/pcp/pcm159
PMid:18003669
 
Reiter M., Reeves D., Burmester C., and Torbert H., 2008, Cotton nitrogen management in a high-residue conservation system: cover crop fertilization, Soil Science Society of America Journal, 72(5): 1321-1329
https://doi.org/10.2136/sssaj2007.0313
 
Rizwan M., and Akhtar S., 2015, Development of herbicide resistant crops through induced mutations, Advancements in Life Sciences, 3(1): 1-8
 
Roche J., 1994, The international cotton trade: Woodhead Publishing
https://doi.org/10.1016/b978-1-85573-104-2.50014-3
 
Sabir H.M., Tahir S.H., and Khan M.B., 2011, BT cotton and its impact on cropping pattern in Punjab, Pakistan Journal of Social Sciences, 31(1): 127-134
 
Sczostak A., ed., 2009, Cotton linters: an alternative cellulosic raw material, Macromolecular Symposia, 280(1): 45-53
Shahid A.A., Bano S., Khalid S., Samiullah T.R., Bajwa K.S., and Ali M.A., 2016, Biosafety assessment of transgenic Bt cotton on model animals. Advancements in Life Sciences, 3(3): 97-108
 
Sharma H., Crouch J., Sharma K., Seetharama N., and Hash C., 2002, Applications of biotechnology for crop improvement: prospects and constraints, Plant Science, 163(3): 381-395
https://doi.org/10.1016/S0168-9452(02)00133-4
 
Spurdle A.B., Lakhani S.R., Da Silva L.M., Balleine R.L., and Goldgar D.E., 2010, Bayes analysis provides evidence of pathogenicity for the BRCA1 c.135-1G>T (IVS3-1) and BRCA2 c.7977-1G>C (IVS17-1) variants displaying in vitro splicing results of equivocal clinical significance, Hum. Mutat., 31(2): 21181
https://doi.org/10.1002/humu.21181
PMid:20020529 PMCid:PMC2852636
 
Steemers F.J., and Gunderson K.L., Whole genome genotyping technologies on the BeadArray™ platform, Biotechnology Journal, 2(1): 41-49
https://doi.org/10.1002/biot.200600213
PMid:17225249
 
Street J., Buchanan G., Crowley R., and McGuire J., 1981, Influence of cotton (Gossypium hirsutum) densities on competitiveness of pigweed (Amaranthus spp.) and sicklepod (Cassia obtusifolia), Weed science, 253-256
 
Udall J.A., Flagel L.E., Cheung F., Woodward A.W., Hovav R., and Rapp R.A., 2007, Spotted cotton oligonucleotide microarrays for gene expression analysis. Bmc Genomics, 8(1): 81
https://doi.org/10.1186/1471-2164-8-81
PMid:17389046 PMCid:PMC3225879
 
Webster T.M., ed., 2007, Cotton row spacing and plant population affect weed seed production, International Cotton Advisory Committee (ICAC), World Cotton Research Conference-4, Lubbock, Texas, USA, pp.10-14
 
Wilkins T.A., Rajasekaran K., and Anderson D.M., 2000, Cotton biotechnology, Critical Reviews in Plant Sciences, 19(6): 511-550
https://doi.org/10.1016/S0735-2689(01)80007-1
 
YuLin G., ChenXi L., YiDong W., KongMing W., Soberón M., and Gao A., 2015, Status of resistance to Bt cotton in China: cotton bollworm and pink bollworm. Bt resistance: characterization and strategies for GM crops producing Bacillus thuringiensis toxins, 15-25
Cotton Genomics and Genetics
• Volume 7
View Options
. PDF(404KB)
. FPDF(win)
. HTML
. Online fPDF
Associated material
. Readers' comments
Other articles by authors
. Bushra Rashid
. Samra Kousar
. Mehwish Yousaf
. Qurban Ali
. Fareeha Fatima
. Shehla Parveen
. Arooj Arshad
. Rimsh a
. Nasim Ahmad
. Tayyab Husnain
Related articles
. Biotechnology
. Cotton
. Agriculture
. NGS
. RNAi
. VIGS
. Genetically modified
Tools
. Email to a friend
. Post a comment