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Within-sample variation in cotton fiber length is a major factor influencing the production and quality of yarns. The textile industry has been searching for approaches of improving the long fiber fraction and minimizing the short fiber fraction within a cotton sample to produce superior fiber and yarn quality. USTER® High Volume Instrument (HVI) has been widely used for a rapid assessment of cotton fiber length traits from a fiber bundle. However, its effectiveness for genetic studies has been questioned due to the indirect estimations of the cotton fiber traits that cannot be measured from a fiber bundle. To overcome the limits of the HVI fiber length traits, we utilized the Advanced Fiber Information System (AFIS) measuring fiber length traits directly from individual fibers based on weight or number. Comparative fiber length analyses showed AFIS provided higher sensitivity in detecting the fiber length variations within and among cotton samples than HVI. The weight-based AFIS length traits were strongly correlated with the corresponding HVI lengths, whereas the number-based AFIS mean length showed a relatively weaker correlation with the HVI lengths. Integrations of the weight based-length traits with genome-wide association studies (GWAS) enabled classifying the QTLs specifically associated with long, mean, or short fiber length traits and identified a false positive associated with the indirectly estimated HVI short fiber trait. Unlike the weight based-AFIS length traits, the number-based AFIS length trait did not show a negative correlation with a weight related-HVI property, and identified a single QTL that was not detected by the corresponding HVI trait. These results suggested that integrating the AFIS method with GWAS helped discoveries of the genome loci involved in the within-sample variation in cotton fiber length and characterizations of the fiber length QTLs. [ABSTRACT FROM AUTHOR]

Cotton (Gossypium spp.) is the primary source of natural textile fiber in the U.S. and a major crop in the Southeastern U.S. Despite constant efforts to increase the cotton fiber yield, the yield gain has stagnated. Therefore, we undertook a novel approach to improve the cotton fiber yield by altering its growth habit from perennial to annual. In this effort, we identified genotypes with high-expression alleles of five floral induction and meristem identity genes (FT, SOC1, FUL, LFY, and AP1) from an Upland cotton mini-core collection and crossed them in various combinations to develop cotton lines with annual growth habit, optimal flowering time, and enhanced productivity. To facilitate the characterization of genotypes with the desired combinations of stacked alleles, we identified molecular markers associated with the gene expression traits via genome-wide association analysis using a 63 K SNP Array. Over 14,500 SNPs showed polymorphism and were used for association analysis. A total of 396 markers showed associations with expression traits. Of these 396 markers, 159 were mapped to genes, 50 to untranslated regions, and 187 to random genomic regions. Biased genomic distribution of associated markers was observed where more trait-associated markers mapped to the cotton D sub-genome. Many quantitative trait loci coincided at specific genomic regions. This observation has implications as these traits could be bred together. The analysis also allowed the identification of candidate regulators of the expression patterns of these floral induction and meristem identity genes whose functions will be validated. [ABSTRACT FROM AUTHOR]

Researchers have used quantitative genetics to map cotton fiber quality and agronomic performance loci, but many alleles may be population or environment-specific, limiting their usefulness in a pedigree selection, inbreeding-based system. Here, we utilized genotypic and phenotypic data on a panel of 80 important historical Upland cotton (Gossypium hirsutum L.) lines to investigate the potential for genomics-based selection within a cotton breeding program's relatively closed gene pool. We performed a genome-wide association study (GWAS) to identify alleles correlated to 20 fiber quality, seed composition, and yield traits and looked for a consistent detection of GWAS hits across 14 individual field trials. We also explored the potential for genomic prediction to capture genotypic variation for these quantitative traits and tested the incorporation of GWAS hits into the prediction model. Overall, we found that genomic selection programs for fiber quality can begin immediately, and the prediction ability for most other traits is lower but commensurate with heritability. Stably detected GWAS hits can improve prediction accuracy, although a significance threshold must be carefully chosen to include a marker as a fixed effect. We place these results in the context of modern public cotton line-breeding and highlight the need for a community-based approach to amass the data and expertise necessary to launch US public-sector cotton breeders into the genomics-based selection era. [ABSTRACT FROM AUTHOR]

The environmental impact of genetically modified crops has been extensively investigated. However, few reports on the influence of transgenic traits on genetic structure have been reported in the literature. It is unknown how or if transgenic cultivars have affected genotypic variation in upland cotton (Gossypium hirsutum L.) since its rise to dominance in cotton production. In this study, the genotypic variance components, g, of lint yield (LY) and fiber quality were compared among transgenic and nontransgenic cotton in the USDA Regional High Quality (RHQ) tests from 2002 through 2018. The popular transgenic and nontransgenic cultivars/lines developed by the major private and public cotton breeding programs in the United States during this period were included. Testing cycles within the RHQ protocol consist of standardized control cultivars plus experimental entries. Variance components were dissected in each testing year within six such testing cycles. Lint yield of the transgenic cotton was generally higher than nontransgenic cotton. Fiber quality of the nontransgenic cotton was generally higher than the transgenic cotton. For LY, the proportion of g to the total variance was lower in the transgenic cotton than in the nontransgenic cotton, but the difference diminished in the recent two cycles. The proportion of g was lower in the transgenic cotton compared with the nontransgenic cotton for fiber length, fiber strength, fiber uniformity, and micronaire. The discrepancy between the two types of cotton in the RHQ tests reflects the influences of differential breeding schemes in the private and public breeding programs on means and genotypic variance of LY and fiber quality. Core Ideas: Transgenic cotton affected genotypic variation in cotton cultivars.Differences in breeding schemes in public and private programs influenced genotypic variations.There has been an increase of genotypic variation for yield of transgenic cultivars in recent years.The yield gap between transgenic cotton and nontransgenic cotton has narrowed in recent years. [ABSTRACT FROM AUTHOR]

Determination of an efficient number of testing locations in multiple-location tests for cotton (Gossypium hirsutum L.) fiber quality can allow removal of unnecessary locations while maintaining the statistical power in detection of genotype (g) by environment (e) interactions. Fiber quality data from Regional High-Quality (RHQ) tests from 2011 to 2016 were used to determine an ef- ficient number of locations in the tests for fiber quality and relationships among locations for their representativeness and ability to discriminate among genotypes. Covariance parameters of g, location (l), and gl in the original RHQ tests were estimated in a random model. The simulating data with varying number of locations omitted from the original tests were created by performing 100 unique simulations. When locations were reduced to five, the standard deviations (std) of gl increased from 18 to 37% compared to the original tests. Further reduction of locations to four or less increased std of gl from 30 to 217% compared to the original tests. Therefore, five locations were determined to be an efficient number of locations in tests for fiber quality. The discriminating ability and representativeness of the eight locations for fiber properties were calculated as their distances to an "ideal environment", which was designed as a center in GGE biplot graphs for representativeness and discriminating ability. The relationships among locations were different across years. However, by averaging the distances across testing years, the locations of Stoneville, MS; Keiser, AR; Lubbock, TX; and College Station, TX were identified as the most representative testing sites for fiber properties. [ABSTRACT FROM AUTHOR]

Competition with manmade fibers has increased focus on upland cotton (Gossypium hirsutum L.) fiber quality, especially upper half mean length (FL), for industry stakeholders and breeders. The purpose of this study was to characterize the effect of qFL‐Chr.25, a quantitative trait locus (QTL) introgressed from G. barbadense L. originally identified in 'Sealand 883'. The QTL was deployed within four genetic backgrounds: Acala SJ4, Paymaster HS26, Deltapine 50 (DP 50), and Georgia 2004089 (GA089), each representing the gene pools of the major US cotton‐growing regions: the US Southwest, Texas High Plains, Mississippi Delta, and US Southeast, respectively. In highly related bulked sister lines (BSLs), the effect of qFL‐Chr.25 was significant in the DP 50 (1.4 mm) and GA089 (1 mm) backgrounds in trials grown in Tifton, GA, in 2014 and 2015. In multilocation trials planted across the Cotton Belt in 2011 of 25 lines from each of the four backgrounds carrying the G. barbadense allele and 25 without the introgressed allele, FL of the QTL(+) lines were numerically higher than the QTL(−) lines by 0.9 mm, though not statistically significant. Recombinant genotypes recovered from the Paymaster HS26 and GA089 backgrounds, and development of additional simple sequence repeat (SSR) markers within the QTL region, allowed further refinement of the qFL‐Chr.25 region's boundaries from ∼2.2 to 0.8 Mb. Although variable effects were seen from this QTL, observation in a more isogenic state such as the BSLs and recombinant lines made the effect of the QTL more apparent. Incorporation of this QTL into breeding programs aided by these newly developed SSR markers should help in the utilization of this introgression to improve cotton fiber quality. [ABSTRACT FROM AUTHOR]

Interspecific introgression lines are important resources for plant breeders to access novel alleles from exotic germplasm. The Pee Dee breeding program developed several extra‐long staple "Sealand" germplasm lines that presumably contain sea island cotton (Gossypium barbadense L.) chromatin introgressed into upland cotton (Gossypium hirsutum L.). The objectives of this study were to identify the G. barbadense chromatins in the Sealand lines, 542 and 883, and evaluate their effects on fiber quality. A total of 31 putative G. barbadense chromatins were detected, including 12 segments on seven chromosomes that were unique to Sealand 542 and 10 segments on five chromosomes that were unique to Sealand 883, and the remaining nine segments were common to both the Sealand lines. Sealand 542 and 883 mapping populations were created to identified 28 quantitative trait locus (QTL) regions associated with fiber quality traits, including six for elongation, four for fineness, five for short fiber content, five for strength, three for length, and five for fiber uniformity. At least 13 QTLs were detected on the G. barbadense introgressed chromosomal segments. Favorable alleles for 17 QTLs were contributed by the Sealand lines, and the genetic effects of five loci were stably expressed across environment and generation. Stable expression of G. barbadense fiber quality alleles in the Sealand lines and the absence of these alleles in upland germplasm make these introgression lines a valuable resource for fiber quality improvement. In particular, marker‐assisted introgression of the qFL‐Chr25 locus from Sealand 883 should result in improved fiber length, whereas that of qMIC‐Chr24 from Sealand 542 should result in finer fiber. [ABSTRACT FROM AUTHOR]

Key message: Significant associations between candidate genes and six major cotton fiber quality traits were identified in a MAGIC population using GWAS and whole genome sequencing. Upland cotton (Gossypium hirsutum L.) is the world's major renewable source of fibers for textiles. To identify causative genetic variants that influence the major agronomic measures of cotton fiber quality, which are used to set discount or premium prices on each bale of cotton in the USA, we measured six fiber phenotypes from twelve environments, across three locations and 7 years. Our 550 recombinant inbred lines were derived from a multi-parent advanced generation intercross population and were whole-genome-sequenced at 3× coverage, along with the eleven parental cultivars at 20× coverage. The segregation of 473,517 single nucleotide polymorphisms (SNPs) in this population, including 7506 non-synonymous mutations, was combined with phenotypic data to identify seven highly significant fiber quality loci. At these loci, we found fourteen genes with non-synonymous SNPs. Among these loci, some had simple additive effects, while others were only important in a subset of the population. We observed additive effects for elongation and micronaire, when the three most significant loci for each trait were examined. In an informative subset where the major multi-trait locus on chromosome A07:72-Mb was fixed, we unmasked the identity of another significant fiber strength locus in gene Gh_D13G1792 on chromosome D13. The micronaire phenotype only revealed one highly significant genetic locus at one environmental location, demonstrating a significant genetic by environment component. These loci and candidate causative variant alleles will be useful to cotton breeders for marker-assisted selection with minimal linkage drag and potential biotechnological applications. [ABSTRACT FROM AUTHOR]