Genome-wide identification of TBL gene family and functional analysis of GhTBL84 under cold stress in cotton.

Cotton fiber, the mainstay of the world's textile industry, is formed by the differentiation of epidermal cells on the outer peridium of the ovule. The TBL gene family is involved in the regulation of epidermal hair development as well as response to abiotic stress. However, the function of TBL genes in cotton has not been systematically studied yet. Here, we identified 131 and 130 TBL genes in TM-1 (Gossypium hirsutum) and Hai7124 (Gossypium barbadense), respectively. Phylogenetic, gene structure, expression pattern and cis-element of promoter analysis were performed and compared. Single gene association analysis indicated that more TBL genes related to fiber quality traits were found in G. barbadense, whereas more genes associated with yield traits were found in G. hirsutum. One gene, GhTBL84 (GH_D04G0930), was induced by treatment at 4°C for 12 and 24 h in G. hirsutum and silencing of the GhTBL84 gene by VIGS technology in TM-1 can significantly improve the resistance of cotton seedlings to low temperature stress. In sum, our study conducted a genome-wide identification and comparative analysis of TBL family genes in G. hirsutum and G. barbadense and demonstrated a group of TBL genes significantly associated with fiber quality and excavated cold stress responsive gene, such as GhTBL84, providing a theoretical basis for further improving cotton agronomic traits.

Cotton transposon-related variome reveals roles of transposon-related variations in modern cotton cultivation.

INTRODUCTION: Transposon plays a vital role in cotton genome evolution, contributing to the expansion and divergence of genomes within the Gossypium genus. However, knowledge of transposon activity in modern cotton cultivation is limited. OBJECTIVES: In this study, we aimed to construct transposon-related variome within Gossypium genus and reveal role of transposon-related variations during cotton cultivation. In addition, we try to identify valuable transposon-related variations for cotton breeding. METHODS: We utilized graphical genome construction to build up the graphical transposon-related variome. Based on the graphical variome, we integrated t-test, eQTL analysis and Mendelian Randomization (MR) to identify valuable transposon activities and elite genes. In addition, a convolutional neural network (CNN) model was constructed to evaluate epigenomic effects of transposon-related variations. RESULTS: We identified 35,980 transposon activities among 10 cotton genomes, and the diversity of genomic and epigenomic features was observed among 21 transposon categories. The graphical cotton transposon-related variome was constructed, and 9,614 transposon-related variations with plasticity in the modern cotton cohort were used for eQTL, phenotypic t-test and Mendelian Randomization. 128 genes were identified as gene resources improving fiber length and strength simultaneously. 4 genes were selected from 128 genes to construct the elite gene panel whose utility has been validated in a natural cotton cohort and 2 accessions with phenotypic divergence. Based on the eQTL analysis results, we identified transposon-related variations involved in cotton's environmental adaption and human domestication, providing evidence of their role in cotton's adaption-domestication cooperation. CONCLUSIONS: The cotton transposon-related variome revealed the role of transposon-related variations in modern cotton cultivation, providing genomic resources for cotton molecular breeding.

Genetic improvement of Egyptian cotton (Gossypium barbadense L.) for high yield and fiber quality properties under semi arid conditions.

Between 2016 and 2018, the Agriculture Research Center's Sakha Agriculture Research Station conducted two rounds of pedigree selection on a segregating population of cotton (Gossypium barbadense L.) using the F2, F3, and F4 generations resulting from crossing Giza 94 and Suvin. In 2016, the top 5% of plants from the F2 population were selected based on specific criteria. The superior families from the F3 generation were then selected to produce the F4 families in 2017, which were grown in the 2018 summer season in single plant progeny rows and bulk experiments with a randomized complete block design of three replications. Over time, most traits showed increased mean values in the population, with the F2 generation having higher Genotypic Coefficient of Variance (GCV) and Phenotypic Coefficient of Variance (PCV) values compared to the succeeding generations for the studied traits. The magnitude of GCV and PCV in the F3 and F4 generations was similar, indicating that genotype had played a greater role than the environment. Moreover, the mean values of heritability in the broad sense increased from generation to generation. Selection criteria I2, I4, and I5 were effective in improving most of the yield and its component traits, while selection criterion I1 was efficient in improving earliness traits. Most of the yield and its component traits showed a positive and significant correlation with each other, highlighting their importance in cotton yield. This suggests that selecting to improveone or more of these traits would improve the others. Families number 9, 13, 19, 20, and 21 were the best genotypes for relevant yield characters, surpassing the better parent, check variety, and giving the best values for most characters. Therefore, the breeder could continue to use these families in further generations as breeding genotypes to develop varieties with high yields and its components.

Fashion meets science: how advanced breeding approaches could revolutionize the textile industry.

Natural fibers have garnered considerable attention owing to their desirable textile properties and advantageous effects on human health. Nevertheless, natural fibers lag behind synthetic fibers in terms of both quality and yield, as these attributes are largely genetically determined. In this article, a comprehensive overview of the natural and synthetic fiber production landscape over the last 10 years is presented, with a particular focus on the role of scientific breeding techniques in improving fiber quality traits in key crops like cotton, hemp, ramie, and flax. Additionally, the article delves into cutting-edge genomics-assisted breeding techniques, including QTL mapping, genome-wide association studies, transgenesis, and genome editing, and their potential role in enhancing fiber quality traits in these crops. A user-friendly compendium of 11226 available QTLs and significant marker-trait associations derived from 136 studies, associated with diverse fiber quality traits in these crops is furnished. Furthermore, the potential applications of transcriptomics in these pivotal crops, elucidating the distinct genes implicated in augmenting fiber quality attributes are investigated. Additionally, information on 11257 candidate/characterized or cloned genes sourced from various studies, emphasizing their key role in the development of high-quality fiber crops is collated. Additionally, the review sheds light on the current progress of marker-assisted selection for fiber quality traits in each crop, providing detailed insights into improved cultivars released for different fiber crops. In conclusion, it is asserted that the application of modern breeding tools holds tremendous potential in catalyzing a transformative shift in the textile industry.

Natural fibers possess desirable properties, but they often lag behind synthetic fibers in terms of both quality and quantity. Genomic-assisted breeding has the potential to improve fiber quality traits in cotton, hemp, ramie, and flax. Utilizing available QTLs, marker-trait associations, and candidate genes can contribute to the development of superior fiber crops, underscoring the significance of advanced breeding tools.

Genetic linkage analysis of stable QTLs in Gossypium hirsutum RIL population revealed function of GhCesA4 in fiber development.

INTRODUCTION: Upland cotton is an important allotetrapolyploid crop providing natural fibers for textile industry. Under the present high-level breeding and production conditions, further simultaneous improvement of fiber quality and yield is facing unprecedented challenges due to their complex negative correlations. OBJECTIVES: The study was to adequately identify quantitative trait loci (QTLs) and dissect how they orchestrate the formation of fiber quality and yield. METHODS: A high-density genetic map (HDGM) based on an intraspecific recombinant inbred line (RIL) population consisting of 231 individuals was used to identify QTLs and QTL clusters of fiber quality and yield traits. The weighted gene correlation network analysis (WGCNA) package in R software was utilized to identify WGCNA network and hub genes related to fiber development. Gene functions were verified via virus-induced gene silencing (VIGS) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 strategies. RESULTS: An HDGM consisting of 8045 markers was constructed spanning 4943.01 cM of cotton genome. A total of 295 QTLs were identified based on multi-environmental phenotypes. Among 139 stable QTLs, including 35 newly identified ones, seventy five were of fiber quality and 64 yield traits. A total of 33 QTL clusters harboring 74 QTLs were identified. Eleven candidate hub genes were identified via WGCNA using genes in all stable QTLs and QTL clusters. The relative expression profiles of these hub genes revealed their correlations with fiber development. VIGS and CRISPR/Cas9 edition revealed that the hub gene cellulose synthase 4 (GhCesA4, GH_D07G2262) positively regulate fiber length and fiber strength formation and negatively lint percentage. CONCLUSION: Multiple analyses demonstrate that the hub genes harbored in the QTLs orchestrate the fiber development. The hub gene GhCesA4 has opposite pleiotropic effects in regulating trait formation of fiber quality and yield. The results facilitate understanding the genetic basis of negative correlation between cotton fiber quality and yield.

QTL Verification and Candidate Gene Screening of Fiber Quality and Lint Percentage in the Secondary Segregating Population of Gossypium hirsutum.

Fiber quality traits, especially fiber strength, length, and micronaire (FS, FL, and FM), have been recognized as critical fiber attributes in the textile industry, while the lint percentage (LP) was an important indicator to evaluate the cotton lint yield. So far, the genetic mechanism behind the formation of these traits is still unclear. Quantitative trait loci (QTL) identification and candidate gene validation provide an effective methodology to uncover the genetic and molecular basis of FL, FS, FM, and LP. A previous study identified three important QTL/QTL cluster loci, harboring at least one of the above traits on chromosomes A01, A07, and D12 via a recombinant inbred line (RIL) population derived from a cross of Lumianyan28 (L28) × Xinluzao24 (X24). A secondary segregating population (F2) was developed from a cross between L28 and an RIL, RIL40 (L28 × RIL40). Based on the population, genetic linkage maps of the previous QTL cluster intervals on A01 (6.70-10.15 Mb), A07 (85.48-93.43 Mb), and D12 (0.40-1.43 Mb) were constructed, which span 12.25, 15.90, and 5.56 cM, with 2, 14, and 4 simple sequence repeat (SSR) and insertion/deletion (Indel) markers, respectively. QTLs of FL, FS, FM, and LP on these three intervals were verified by composite interval mapping (CIM) using WinQTL Cartographer 2.5 software via phenotyping of F2 and its derived F2:3 populations. The results validated the previous primary QTL identification of FL, FS, FM, and LP. Analysis of the RNA-seq data of the developing fibers of L28 and RIL40 at 10, 20, and 30 days post anthesis (DPA) identified seven differentially expressed genes (DEGs) as potential candidate genes. qRT-PCR verified that five of them were consistent with the RNA-seq result. These genes may be involved in regulating fiber development, leading to the formation of FL, FS, FM, and LP. This study provides an experimental foundation for further exploration of these functional genes to dissect the genetic mechanism of cotton fiber development.

Development of High-Yielding Upland Cotton Genotypes with Reduced Regrowth after Defoliation Using a Combination of Molecular and Conventional Approaches.

Cotton is an economically important crop. However, the yield gain in cotton has stagnated over the years, probably due to its narrow genetic base. The introgression of beneficial variations through conventional and molecular approaches has helped broaden its genetic base to some extent. The growth habit of cotton is one of the crucial factors that determine crop maturation time, yield, and management. This study used 44 diverse upland cotton genotypes to develop high-yielding cotton germplasm with reduced regrowth after defoliation and early maturity by altering its growth habit from perennial to somewhat annual. We selected eight top-scoring genotypes based on the gene expression analysis of five floral induction and meristem identity genes (FT, SOC1, LFY, FUL, and AP1) and used them to make a total of 587 genetic crosses in 30 different combinations of these genotypes. High-performance progeny lines were selected based on the phenotypic data on plant height, flower and boll numbers per plant, boll opening date, floral clustering, and regrowth after defoliation as surrogates of annual growth habit, collected over four years (2019 to 2022). Of the selected lines, 8×5-B3, 8×5-B4, 9×5-C1, 8×9-E2, 8×9-E3, and 39×5-H1 showed early maturity, and 20×37-K1, 20×37-K2, and 20×37-D1 showed clustered flowering, reduced regrowth, high quality of fiber, and high lint yield. In 2022, 15 advanced lines (F8/F7) from seven cross combinations were selected and sent for an increase to a Costa Rica winter nursery to be used in advanced testing and for release as germplasm lines. In addition to these breeding lines, we developed molecular resources to breed for reduced regrowth after defoliation and improved yield by converting eight expression-trait-associated SNP markers we identified earlier into a user-friendly allele-specific PCR-based assay and tested them on eight parental genotypes and an F2 population.

Effects of forage quality and particle size on feed intake and ruminoreticulum content of goats.

The aim was to evaluate the effect of particle size and hay quality on feed intake, granulometric profile, and composition of the ruminoreticulum content in goats. We used 54 Alpine bucks in a completely randomized design with a factorial arrangement of 3 × 3. Treatments were a combination of Bermuda grass hay (Cynodon dactylon) with three quality levels: high (35 days), medium (50 days), and low (65 d) harvested at regrowth times. Were evaluated three particle sizes: small (16% ≥4.76 mm), medium (48% ≥4.76 mm), and large (75% ≥4.76 mm), which accounted for 66%, 75%, and 94% of physically effective fiber, respectively. Samples of offered diet, intake, and ruminoreticulum content were used to generate the granulometric profile. The offered diet, intake, and ruminoreticulum content presented different granulometric profiles regarding hay quality and particle size. Dry matter intake (DMI) and neutral detergent fiber intake (NDFI) increased (P < 0.05) when low-quality hay and large particles were offered. However, when particle size in low-quality hay was reduced, DMI and NDF decreased (P < 0.05). When analyzing the ruminoreticulum content (DM, NDF, peNDF, and indigestible DM), we did not observe any effect (P > 0.05) of hay quality or particle size on the variables. Thus, reducing hay quality and increasing particle size increase dry matter and fiber intake, presenting an interaction between forage quality and particle size. Forage quality and particle size promote intense selective behavior and chewing, which leads to a homogeneous content of particle profile in ruminoreticulum and a uniform average retention time.

Morphological and physio-biochemical responses under heat stress in cotton: Overview.

Cotton is an important cash crop in addition to being a fiber commodity, and it plays an essential part in the economies of numerous nations. High temperature is the most critical element affecting its yield from fertilization to harvest. The optimal temperature for root formation is 30 C -35 °C; however, root development ends around 40 °C. Increased temperature, in particular, influences different biochemical and physiological processes associated with cotton plant, resulting in low seed cotton production. Many studies in various agroecological zones used various agronomic strategies and contemporary breeding techniques to reduce heat stress and improve cotton productivity. To attain desired traits, cotton breeders should investigate all potential possibilities, such as generating superior cultivars by traditional breeding, employing molecular techniques and transgenic methods, such as using genome editing techniques. The main objective of this review is to provide the recent information on the environmental factors, such as temperature, heat and drought, influence the growth and development, morphology and physio-chemical alteration associated with cotton. Furthermore, recent advancement in cotton breeding to combat the serious threat of drought and heat stress.

Detection of epistasis interaction loci for fiber quality-related trait via 3VmrMLM in upland cotton.

Cotton fiber quality-related traits, such as fiber length, fiber strength, and fiber elongation, are affected by complex mechanisms controlled by multiple genes. Determining the QTN-by-QTN interactions (QQIs) associated with fiber quality-related traits is therefore essential for accelerating the genetic enhancement of cotton breeding. In this study, a natural population of 1,245 upland cotton varieties with 1,122,352 SNPs was used for detecting the main-effect QTNs and QQIs using the 3V multi-locus random-SNP-effect mixed linear model (3VmrMLM) method. A total of 171 significant main-effect QTNs and 42 QQIs were detected, of which 22 were both main-effect QTNs and QQIs. Of the detected 42 QQIs, a total of 13 significant loci and 5 candidate genes were reported in previous studies. Among the three interaction types, the AD interaction type has a preference for the trait of FE. Additionally, the QQIs have a substantial impact on the enhancement predictability for fiber quality-related traits. The study of QQIs is crucial for elucidating the genetic mechanism of cotton fiber quality and enhancing breeding efficiency.

Effects on the yield and fiber quality components of Bt cotton inoculated with Azotobacter chroococcum under elevated CO2.

Background: The raising trend of cultivation of Bacillus thuringiensis (Bt)-transgenic cotton is faced with a new challenge what effects on the growth and yield of Bt cotton under elevated CO2. Methods: Rhizobacteria is the significant biological regulator to increase environmental suitability and ameliorate soil-nitrogen utilization efficiency of crops, especially Bt cotton. Pot-culture experiments investigated the effects on the yield and fiber quality components of Bt cotton (transgenic Line SCRC 37) inoculated with Azotobacter chroococcum (AC) under elevated CO2. Results: The findings indicated that the inoculation of azotobacter significantly improved the yield and fiber quality components of Bt cotton, the elevated CO2 significantly increased the soil density of A. chroococcum and the partial yield indexes (as cottonweightper 20 bolls, lint yield per 20 bolls and boll number per plant), and non-significant decrease the fiber quality components of Bt cotton except uniform. Discussion: Overall results obviously depicted that the inoculation of azotobacter and the elevated CO2 had positive effects on the yield and fiber quality components of Bt cotton. Presumably, azotobacter inoculation can be used to stimulate plant soil-nitrogen uptake and promote plant growth for Bt cotton under elevated CO2 in the future.

Density and row spacing of short-season cotton suitable for machine picking in the cotton region of Yellow River Basin.

To determine the suitable planting density and row spacing of short-season cotton suitable for machine picking in the Yellow River Basin of China, we conducted a two-year field experiment in Dezhou during 2018-2019. The experiment followed a split-plot design, with planting density (82500 plants·hm-2 and 112500 plants·hm-2) as the main plots and row spacing (equal row spacing of 76 cm, wide-narrow row spacing of 66 cm+10 cm, equal row spacing of 60 cm) as the subplots. We examined the effects of planting density and row spacing on growth and development, canopy structure, seed cotton yield and fiber quality of short-season cotton. The results showed that plant height and LAI under high density treatment were significantly greater than those under low density treatment. The transmittance of the bottom layer was significantly lower than under low density treatment. Plant height under 76 cm equal row spacing was significantly higher than that under 60 cm equal row spacing, while that under wide-narrow row spacing (66 cm +10 cm) was significantly smaller than that under 60 cm equal row spacing in peak bolling stage. The effects of row spacing on LAI varied between the two years, densities, and growth stages. On the whole, the LAI under the wide-narrow row spacing (66 cm+10 cm) was higher, with the curve declining gently after the peak, and it was higher than that in the two cases of equal row spacing in the harvest time. The change in transmittance of the bottom layer presented the opposite trend. Density, row spacing, and their interaction had significant effects on seed cotton yield and its components. In both years, seed cotton yield was the highest (3832 kg·hm-2 in 2018, 3235 kg·hm-2 in 2019) under wide-narrow row spacing (66 cm+10 cm), and it was more stable at high densities. Fiber quality was less affected by density and row spacing. To sum up, the optimal density and row spacing of short-season cotton were as follows: density with 112500 plants·hm-2 and wide-narrow row spacing (66 cm+10 cm).

Estimating the combining ability and genetic parameters for growth habit, yield, and fiber quality traits in some Egyptian cotton crosses.

It is crucial to understand how targeted traits in a hybrid breeding program are influenced by gene activity and combining ability. During the three growing seasons of 2015, 2016, and 2017, a field study was conducted with twelve cotton genotypes, comprised of four testers and eight lines. Thirty-two F1 crosses were produced in the 2015 breeding season using the line x tester mating design. The twelve genotypes and their thirty-two F1 crosses were then evaluated in 2016 and 2017. The results demonstrated highly significant differences among cotton genotypes for all the studied traits, showing a wide range of genetic diversity in the parent genotypes. Additionally, the line-x-tester interaction was highly significant for all traits, suggesting the impact of both additive and non-additive variations in gene expression. Furthermore, the thirty-two cotton crosses showed high seed cotton output, lint cotton yield, and fiber quality, such as fiber length values exceeding 31 mm and a fiber strength above 10 g/tex. Accordingly, selecting lines and testers with high GCA effects and crosses with high SCA effects would be an effective approach to improve the desired traits in cotton and develop new varieties with excellent yield and fiber quality.

Supplementary Feeding of Grazing Inner Mongolian Cashmere Goats during Pregnancy-Based on "Nutrient Requirements of Cashmere Goats".

This study aimed to conduct precise supplementation for pregnant cashmere goats under grazing based on the feeding standard. Eight Inner Mongolian pregnant cashmere goats of near-average body weight were selected at early gestation (44.41 ± 4.03 kg) and late gestation (46.54 ± 4.02 kg) to measure their nutrient intake. Then, two pregnant cashmere goat flocks, No. 10 (control group, on-farm supplement) and No. 11 (supplemented group, supplement based on standard), with the same goat herd structure and grassland type, were chosen to conduct the supplemental feeding experiment. The results showed that pregnant cashmere goats lacked daily the intake of dry matter, digestive energy, crude protein and most essential mineral elements under grazing. After supplemental feeding, the supplementation based on the feeding standard increased the cashmere length and cashmere length growth volume and decreased the cashmere fineness, with no statistical significance. The goat cashmere yield, goat weight after shearing, single and twin-birth kid weight and kids' mature secondary hair follicle density were significantly higher in the supplemented group (p < 0.05). In conclusion, supplementation in accordance with "Nutrient Requirements of Cashmere Goats" can enhance pregnant cashmere goats' fiber production, growth performance, fertility and kids' secondary hair follicles development, which is of great importance for the healthy and precise nutrition and management of cashmere goats.

Genome-wide artificial introgressions of Gossypium barbadense into G. hirsutum reveal superior loci for simultaneous improvement of cotton fiber quality and yield traits.

INTRODUCTION: The simultaneous improvement of fiber quality and yield for cotton is strongly limited by the narrow genetic backgrounds of Gossypium hirsutum (Gh) and the negative genetic correlations among traits. An effective way to overcome the bottlenecks is to introgress the favorable alleles of Gossypium barbadense (Gb) for fiber quality into Gh with high yield. OBJECTIVES: This study was to identify superior loci for the improvement of fiber quality and yield. METHODS: Two sets of chromosome segment substitution lines (CSSLs) were generated by crossing Hai1 (Gb, donor-parent) with cultivar CCRI36 (Gh) and CCRI45 (Gh) as genetic backgrounds, and cultivated in 6 and 8 environments, respectively. The kmer genotyping strategy was improved and applied to the population genetic analysis of 743 genomic sequencing data. A progeny segregating population was constructed to validate genetic effects of the candidate loci. RESULTS: A total of 68,912 and 83,352 genome-wide introgressed kmers were identified in the CCRI36 and CCRI45 populations, respectively. Over 90 % introgressions were homologous exchanges and about 21 % were reverse insertions. In total, 291 major introgressed segments were identified with stable genetic effects, of which 66(22.98 %), 64(21.99 %), 35(12.03 %), 31(10.65 %) and 18(6.19 %) were beneficial for the improvement of fiber length (FL), strength (FS), micronaire, lint-percentage (LP) and boll-weight, respectively. Thirty-nine introgression segments were detected with stable favorable additive effects for simultaneous improvement of 2 or more traits in Gh genetic background, including 6 could increase FL/FS and LP. The pyramiding effects of 3 pleiotropic segments (A07:C45Clu-081, D06:C45Clu-218, D02:C45Clu-193) were further validated in the segregating population. CONCLUSION: The combining of genome-wide introgressions and kmer genotyping strategy showed significant advantages in exploring genetic resources. Through the genome-wide comprehensive mining, a total of 11 clusters (segments) were discovered for the stable simultaneous improvement of FL/FS and LP, which should be paid more attention in the future.

Identification of elite fiber quality loci in upland cotton based on the genotyping-by-target-sequencing technology.

Genome-wide association studies (GWAS) of fiber quality traits of upland cotton were conducted to identify the single-nucleotide polymorphic (SNP) loci associated with cotton fiber quality, which lays the foundation for the mining of elite] cotton fiber gene resources and its application in molecular breeding. A total of 612 upland cotton accessions were genotyped using the ZJU Cotton Chip No. 1 40K chip array via the liquid-phase probe hybridization-based genotyping-by-target-sequencing (GBTS) technology. In the present study, five fiber quality traits, namely fiber length, fiber strength, micronaire, uniformity and elongation, showed different degrees of variation in different environments. The average coefficient of variation of fiber strength was the greatest, whereas the average coefficient of variation of uniformity was the least. Significant or extremely significant correlations existed among the five fiber quality traits, especially fiber length, strength, uniformity and elongation all being significantly negative correlated with micronaire. Population cluster analysis divided the 612 accessions into four groups: 73 assigned to group I, 226 to group II, 220 to group III and 93 to group IV. Genome-wide association studies of five fiber quality traits in five environments was performed and a total of 42 SNP loci associated with target traits was detected, distributed on 19 chromosomes, with eight loci associated with fiber length, five loci associated with fiber strength, four loci associated with micronaire, twelve loci associated with fiber uniformity and thirteen loci associated with fiber elongation. Of them, seven loci were detected in more than two environments. Nine SNP loci related to fiber length, fiber strength, uniformity and elongation were found on chromosome A07, seven loci related to fiber length, fiber strength, micronaire and elongation were detected on chromosome D01, and five loci associated with fiber length, uniformity and micronaire were detected on chromosome D11. The results from this study could provide more precise molecular markers and genetic resources for cotton breeding for better fiber quality in the future.

Outlook for Implementation of Genomics-Based Selection in Public Cotton Breeding Programs.

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.

Improved Upland Cotton Germplasm for Multiple Fiber Traits Mediated by Transferring and Pyramiding Novel Alleles From Ethyl Methanesulfonate-Generated Mutant Lines Into Elite Genotypes.

Ethyl methanesulfonate (EMS) mutagenesis offers important advantages for improving crops, such as cotton, with limited diversity in elite gene pools. EMS-induced point mutations are less frequently associated with deleterious traits than alleles from wild or exotic germplasm. From 157 mutant lines that have significantly improved fiber properties, we focused on nine mutant lines here. A total of eight populations were developed by crossing mutant lines in different combinations into GA230 (GA2004230) background. Multiple lines in each population were significantly improved for the fiber trait that distinguished the donor parent(s), demonstrating that an elite breeding line (GA230) could be improved for fiber qualities using the mutant lines. Genotypes improved for multiple fiber traits of interest suggesting that allele pyramiding is possible. Compared to midparent values, individual progeny in the population conferred fiber quality improvements of as much as 31.7% (in population O) for micronaire (MIC), 16.1% (in population P) for length, 22.4% (in population K) for strength, 4.1% (in population Q) for uniformity, 45.8% (in population N) for elongation, and 13.9% (in population O) for lint percentage (lint%). While further testing for stability of the phenotype and estimation of yield potential is necessary, mutation breeding shows promise as an approach to reduce the problem of the genetic bottleneck of upland cotton. The populations developed here may also contribute to identifying candidate genes and causal mutations for fiber quality improvement.

Identification of Candidate Genes for Lint Percentage and Fiber Quality Through QTL Mapping and Transcriptome Analysis in an Allotetraploid Interspecific Cotton CSSLs Population.

Upland cotton (Gossypium hirsutum) has long been an important fiber crop, but the narrow genetic diversity of modern G. hirsutum limits the potential for simultaneous improvement of yield and fiber quality. It is an effective approach to broaden the genetic base of G. hirsutum through introgression of novel alleles from G. barbadense with excellent fiber quality. In the present study, an interspecific chromosome segment substitution lines (CSSLs) population was established using G. barbadense cultivar Pima S-7 as the donor parent and G. hirsutum cultivar CCRI35 as the recipient parent. A total of 105 quantitative trait loci (QTL), including 85 QTL for fiber quality and 20 QTL for lint percentage (LP), were identified based on phenotypic data collected from four environments. Among these QTL, 25 stable QTL were detected in two or more environments, including four for LP, eleven for fiber length (FL), three for fiber strength (FS), six for fiber micronaire (FM), and one for fiber elongation (FE). Eleven QTL clusters were observed on nine chromosomes, of which seven QTL clusters harbored stable QTL. Moreover, eleven major QTL for fiber quality were verified through analysis of introgressed segments of the eight superior lines with the best comprehensive phenotypes. A total of 586 putative candidate genes were identified for 25 stable QTL associated with lint percentage and fiber quality through transcriptome analysis. Furthermore, three candidate genes for FL, GH_A08G1681 (GhSCPL40), GH_A12G2328 (GhPBL19), and GH_D02G0370 (GhHSP22.7), and one candidate gene for FM, GH_D05G1346 (GhAPG), were identified through RNA-Seq and qRT-PCR analysis. These results lay the foundation for understanding the molecular regulatory mechanism of fiber development and provide valuable information for marker-assisted selection (MAS) in cotton breeding.

Development and Utilization of Functional Kompetitive Allele-Specific PCR Markers for Key Genes Underpinning Fiber Length and Strength in Gossypium hirsutum L.

Fiber length (FL) and fiber strength (FS) are the important indicators of fiber quality in cotton. Longer and stronger fibers are preferred for manufacturing finer yarns in the textile industry. Functional markers (FMs) designed from polymorphic sites within gene sequences attributing to phenotypic variation are highly efficient when used for marker-assisted selection (MAS) in breeding superior varieties with longer FL and higher FS. The aims of this study were to develop FMs via kompetitive allele-specific PCR (KASP) assays and to validate the efficacy of the FMs for allele discrimination and the potential value in practice application. We used four single-nucleotide polymorphism markers and 360 cotton accessions and found that two FMs, namely, D11_24030087 and A07_72204443, could effectively differentiate accessions of different genotypes with higher consistency to phenotype. The appeared frequencies of varieties harbored Hap2 (elite alleles G and T) with longer FL (> the mean of accessions with non-elite allele, 28.50 mm) and higher FS (> the mean of accessions with non-elite allele, 29.06 cN•tex-1) were 100 and 72.7%, respectively, which was higher than that of varieties harbored only on a single elite allele (G or T, 77.9 or 61.9%), suggesting a favorable haplotype for selecting varieties with superior FL and FS. These FMs could be valuable for the high-throughput selection of superior materials by providing genotypic information in cotton breeding programs.