A Meta-Analysis of the Use of Genetically Modified Cotton and Its Conventional in Agronomy Aspect and Economic Merits

Rising the area of growing Genetically Modified (GM) cotton mostly derived from the yield gain and income gain both GM cotton and conventional cotton is affected by seed cost, pesticide cost, management and labor cost. Therefore, planting GM cotton should be considering both agronomy aspect in yield gain and economic dimension in income gain. Those aspects are not only for GM cotton but also for conventional cotton. This paper is a meta-analysis as a synthesis of current research by searching literature both peer-reviewed and non peer-reviewed. A meta-analysis depicted that individual study mostly favor GM cotton in yield gain, seed cost and pesticide cost. However, in terms of pesticide cost a meta-analysis prone to favor non GM cotton. Moreover, a meta-analysis revealed that the positive impact in the differences of GM cotton and conventional cotton as the evidence of the publication is highly significant. Key Words : Genetically Modified, Cotton, Conventional, Yield, Income, Gain, Meta-Analysi

GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers

It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18–24.45 and 1.68–28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly “pleiotropic.” This study provided important information for MAS and candidate gene functional studies

Genetic Effects and Heterosis of Yield and Yield Component Traits Based on Gossypium Barbadense Chromosome Segment Substitution Lines in Two Gossypium Hirsutum Backgrounds.

We hybridized 10 chromosome segment substitution lines (CSSLs) each from two CSSL populations and produced 50 F1 hybrids according to North Carolina Design II. We analyzed the genetic effects and heterosis of yield and yield components in the F1 hybrids and parents in four environments via the additive-dominance genetic model. Yield and yield components of the CSSLs were controlled by combined additive and dominance effects, and lint percentage was mainly controlled by additive effects, but boll weight, boll number, seedcotton yield and lint yield were mainly controlled by dominance effects. We detected significant interaction effects between genetics and the environment for all yields traits. Similar interactions were detected between two CSSL populations (Pop CCRI 36 and Pop CCRI 45). Significant positive mid-parent heterosis was detected for all yield traits in both populations, and significant positive better-parent heterosis was also detected for all yield traits except lint percentage. The differences among parents were relatively small, but significant heterosis was detected for yield and yield components. Therefore, the relationship between heterosis and genetic distance for yield traits is complicated and requires further study. These CSSLs represent useful tools for improving yield and yield components in cotton

Biotechnology and Solutions: Insect-Pest-Resistance Management for Improvement and Development of Bt Cotton (<i>Gossypium hirsutum</i> L.)

Cotton (Gossypium spp. L.) is a major origin of natural fiber, and is projected at 117 million bales worldwide for 2021/22. A variety of biotic and abiotic stresses have considerable negative impacts on cotton. The significantly decreased applications of chemical insecticidal sprays in the agro-ecosystem have greatly affected the biodiversity and dynamics of primary and secondary insects. Various control measures were taken around the globe to increase production costs. Temperature, drought, and salinity, and biotic stresses such as bacteria, viruses, fungi, nematodes, insects, and mites cause substantial losses to cotton crops. Here, we summarize a number of biotic and abiotic stresses upsetting Bt cotton crop with present and future biotechnology solution strategies that include a refuge strategy, multi-gene pyramiding, the release of sterile insects, seed mixing, RNAi, CRISPR/Cas9, biotic signaling, and the use of bioagents. Surveillance of insect resistance, monitoring of grower compliance, and implementation of remedial actions can lead to the sustainable use of cotton across the globe

Transcriptome Analysis Suggests That Chromosome Introgression Fragments from Sea Island Cotton (Gossypium barbadense) Increase Fiber Strength in Upland Cotton (Gossypium hirsutum)

As high-strength cotton fibers are critical components of high quality cotton, developing cotton cultivars with high-strength fibers as well as high yield is a top priority for cotton development. Recently, chromosome segment substitution lines (CSSLs) have been developed from high-yield Upland cotton (Gossypium hirsutum) crossed with high-quality Sea Island cotton (G. barbadense). Here, we constructed a CSSL population by crossing CCRI45, a high-yield Upland cotton cultivar, with Hai1, a Sea Island cotton cultivar with superior fiber quality. We then selected two CSSLs with significantly higher fiber strength than CCRI45 (MBI7747 and MBI7561), and one CSSL with lower fiber strength than CCRI45 (MBI7285), for further analysis. We sequenced all four transcriptomes at four different time points postanthesis, and clustered the 44,678 identified genes by function. We identified 2200 common differentially-expressed genes (DEGs): those that were found in both high quality CSSLs (MBI7747 and MBI7561), but not in the low quality CSSL (MBI7285). Many of these genes were associated with various metabolic pathways that affect fiber strength. Upregulated DEGs were associated with polysaccharide metabolic regulation, single-organism localization, cell wall organization, and biogenesis, while the downregulated DEGs were associated with microtubule regulation, the cellular response to stress, and the cell cycle. Further analyses indicated that three genes, XLOC_036333 [mannosyl-oligosaccharide-α-mannosidase (MNS1)], XLOC_029945 (FLA8), and XLOC_075372 (snakin-1), were potentially important for the regulation of cotton fiber strength. Our results suggest that these genes may be good candidates for future investigation of the molecular mechanisms of fiber strength formation and for the improvement of cotton fiber quality through molecular breeding