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Cotton (Gossypium L.) is the most important fiber crop worldwide. Here, transcriptome analysis was conducted on developing fibers of a G. mustelinum introgression line, IL9, and its recurrent parent, PD94042, at 17 and 21 days post-anthesis (dpa). Differentially expressed genes (DEGs) of PD94042 and IL9 were identified. Gene Ontology (GO) enrichment analysis showed that the annotated DEGs were rich in two main biological processes and two main molecular functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis likewise showed that the annotated DEGs were mainly enriched in metabolic pathways and biosynthesis of secondary metabolites. In total, 52 DEGs were selected as candidate genes based on comparison of the DEGs and GO function annotation information. Quantitative real-time PCR (RT-qPCR) analysis results for 12 randomly selected DEGs were consistent with transcriptome analysis. SNP identification based on G. mustelinum chromatin segment introgression showed that 394 SNPs were identified in 268 DEGs, and two genes with known functions were identified within fiber strength quantitative trait loci (QTL) regions or near the confidence intervals. We identified 52 key genes potentially related to high fiber strength in a G. mustelinum introgression line and provided significant insights into the study of cotton fiber quality improvement.

Gene introgression from wild species has been shown to be a feasible approach for fiber quality improvement in Upland cotton. Previously, we developed an interspecific G. mustelinum × G. hirsutum advanced-backcross population and mapped over one hundred QTL for fiber quality traits. In the current study, a trait-based selective genotyping approach was utilized to prioritize a small subset of introgression lines with high phenotypic values for different fiber quality traits, to simultaneously validate multiple fiber quality QTL in a single experiment. A total of 75 QTL were detected by CIM and/or single-marker analysis, including 11 significant marker-trait associations (P < 0.001) and three putative associations (P < 0.005) also reported in earlier studies. The QTL that have been validated include three each for fiber length, micronaire, and elongation, and one each for fiber strength and uniformity. Collectively, about 10% of the QTL previously reported have been validated here, indicating that selective genotyping has the potential to validate multiple marker-trait associations for different traits, especially those with a moderate to large-effect detected simultaneously in one experimental population. The G. mustelinum alleles contributed to improved fiber quality for all validated loci. The results from this study will lay the foundation for further fine mapping, marker-assisted selection and map-based gene cloning.

Three-dimensional high throughput plant phenotyping techniques provide an opportunity to measure plant organ-level traits which can be highly useful to plant breeders. The number and locations of cotton bolls, which are the fruit of cotton plants and an important component of fiber yield, are arguably among the most important phenotypic traits but are complex to quantify manually. Hence, there is a need for effective and efficient cotton boll phenotyping solutions to support breeding research and monitor the crop yield leading to better production management systems. We developed a novel methodology for 3D cotton boll mapping within a plot in situ. Point clouds were reconstructed from multi-view images using the structure from motion algorithm. The method used a region-based classification algorithm that successfully accounted for noise due to sunlight. The developed density-based clustering method could estimate boll counts for this situation, in which bolls were in direct contact with other bolls. By applying the method to point clouds from 30 plots of cotton plants, boll counts, boll volume and position data were derived. The average accuracy of boll counting was up to 90% and the R2 values between fiber yield and boll number, as well as fiber yield and boll volume were 0.87 and 0.66, respectively. The 3D boll spatial distribution could also be analyzed using this method. This method, which was low-cost and provided improved site-specific data on cotton bolls, can also be applied to other plant/fruit mapping analysis after some modification.

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.

Eight upland cotton (Gossypium hirsutum L.) germplasm lines, GA qFL25-A1 (Reg.no. GP-1063, PI 690458), GA qFL25-A2 (Reg. no. GP-1064, PI 690459), GA qFL25-P1 (Reg. no. GP-1066, PI 690461), GA qFL25-P2 (Reg. no. GP-1065, PI 690460), GA qFL25-D1 (Reg. no. GP-1070, PI 690465), GA qFL25-D2 (Reg. no. GP-1069, PI 690464), GA qFL25-G1 (Reg. no. GP-1068, PI 690463), and GA qFL25-G2 (Reg. no. GP-1067, PI 690462), were developed by the Molecular Cotton Breeding Laboratory, Department of Crop and Soil Sciences, at the University of Georgia in Tifton, GA. These eight germplasm lines resulted from crossing 'Sealand 883' (SL883), a G. hirsutum line with significant introgression from G. barbadense L., with four diverse G. hirsutum parents, 'Acala SJ-4', 'Paymaster HS 26', 'Deltapine 50', andGA 2004089, an unreleased breeding line. Previous work identified qFL-Chr.25, a quantitative trait locus (QTL) inherited from G. barbadense with significant effect on fiber upper-half mean length (FL) carried by SL883. Bulked sister lines were selected with the aid of marker-assisted selection from several F3:5 segregating families from each of these four cross combinations to quantify the effect of the allele in sister lines with and without the QTL. The presence of the SL883 allele for qFL-Chr.25 resulted in FL increases of 0.6 mm (1.9%) to 3.5 mm (11.7%) compared with the corresponding sister lines without the QTL. These eight lines should be useful for marker-assisted improvement of fiber length Made available in DSpace on 2022-02-11T02:02:35Z (GMT). No. of bitstreams: 1 RESGISTRATION-OF-EIGTH-UPLANT-COTTON.pdf: 204323 bytes, checksum: 08da3d8da8da5c54f40d8e37ffc3a2ff (MD5) Previous issue date: 2020

Cotton (

Quantitative trait loci (QTLs) qMi-C11 and qMi-C14 impart a high level of resistance to Meloidogyne incognita in cotton. Breeders had previously backcrossed both QTLs into the susceptible Coker 201 to create the highly resistant M-120 RNR, and we crossed Coker 201 and M-120 RNR to create near-isogenic lines with either qMi-C11 or qMi-C14. Previous work suggests different modes of action for qMi-C11 and qMi-C14. To document individual and combined effects of the QTLs on nematode development and reproduction, Coker 201 (neither QTL), M-120 RNR (both QTLs), CH11 near isoline (qMi-C11), and CH14 near isoline (qMi-C14) were inoculated with M. incognita. At 4, 8, 12, 16, 20, 25, and 30 days after inoculation (DAI), roots were stained to observe nematode developmental stages (second-stage juvenile [J2], swollen second-stage juvenile [SJ2], third-stage juvenile [J3], fourth-stage juvenile [J4], and female), and the number of galls was counted. At 20, 25, 30, and 40 DAI, M. incognita eggs were harvested and counted. At 30 DAI, 80% of the nematodes on Coker 201 were female compared with 50, 40, and 33% females on CH14, CH11, and M-120 RNR, respectively, and greater proportions of nematodes remained in J2 in M-120 RNR (41%), CH11 (58%), and CH14 (27%) than in Coker 201 (9%). More nematodes progressed to J3 or J4 on Coker 201 and CH14 than on CH11 or M-120 RNR. Coker 201 and CH14 had more galls than M-120 RNR. Coker 201 had more eggs than the other genotypes at 30 DAI. Nematode development beyond J2 or SJ2 was significantly reduced by qMi-C11, and development beyond J3 or J4 was significantly reduced by qMi-C14. This study confirms that qMi-C11 and qMi-C14 act at different times and have different effects on the development of M. incognita, and therefore, they have different modes of action.

Pathogens are imminent threats to crop production. Among the management tools available to protect crops from diseases, the use of host-plant resistance had been hindered by a lack of tools and resources to identify resistance genes (R-genes). Genomic technologies have empowered acquisition of a new level and quality of information on plant-pathogen interactions. Next generation sequencing, differential transcriptome analysis, gene editing, and use of bioinformatics have greatly expanded the numbers of R-genes identified, enriched understanding of R-avirulence gene interactions, and disease diagnosis. In this review, we highlight the application of genomic technologies to identification of pathogen machinery for future improvement of host plant resistance.

Cotton is widely grown in the southern US and Meloidogyne incognita is its most significant pathogen. The germplasm line M-120 RNR is highly resistant to M. incognita due to two resistance QTLs (quantitative trait loci), qMi-C11 and qMi-C14. Both QTLs reduce total egg production, but the QTLs affect M. incognita development at different life stages. The QTLs do not appear to affect initial penetration of M. incognita but genotypes containing qMi-C11 had fewer nematodes in the roots 8 days after inoculation than near isolines without qMi-C11, which may indicate M. incognita egression from roots. Three greenhouse trials were conducted using cotton isolines to determine whether qMi-C11 and qMi-C14 affect egression of M. incognita juveniles from roots. On each of the five sampling dates (4, 6, 8, 10, and 12 DAI), nematodes that egressed from roots were counted and roots were stained to count nematodes that remained in the roots. The effect of resistance QTLs on M. incognita egression from the roots differed among the trials. Nematode egression was consistently numerically greater, but inconsistently statistically different, from plants with both QTLs than from plants with neither QTL. Plants with only one QTL generally did not differ from plants with both QTLs, and the effects of qMi-C11 and qMi-C14 did not differ in any consistent way. In a separate experiment, plants with neither QTL had more eggs per egg mass than did plants with both QTLs, whereas plants with only one QTL had an intermediate number. Root gall size was measured in two trials and no consistent differences in gall size were observed. We conclude that (1) qMi-C11 and qMi-C14 do not stimulate nematode egression from cotton roots, (2) both qMi-C11 and qMi-C14 reduce M. incognita eggs/egg mass, and (3) neither qMi-C11 nor qMi-C14 affect gall size.

The Gossypium genus consists of about 50 diploid species distributed in 8 genome groups (A–G and K) and 7 known tetraploid species derived from the fusion of the A and D genomes. Recently, the genomes of allotetraploid cotton and its progenitors have been sequenced. Cotton (Gossypium sp.) is grown primarily for fiber and to a lesser extent its oilseed. The phenolic compound, gossypol, needs to be removed to make cottonseed oil edible. The oil composition is approximately two-thirds unsaturated to one-third saturated fatty acids. Understanding the genetic network of oil production and genes related to oil traits is important to develop a healthy edible product to fight global food scarcity. Studies pertaining to structural variation in genome and positional cloning have increased with the availability of genome sequence, enormous -omics data, and current low-cost next-generation sequencing techniques. Further, with the availability of functional verification tools like RNA-Seq and gene editing via RNAi or CRISPR/CAS9, one can effectively decipher the function of gene/s and their role in complex biosynthesis process of oil production. Whole-genome sequencing will serve as a foundation in developing cotton germplasm that can improve cottonseed oil without disturbing lint yield components.

Cotton leafroll dwarf virus (CLRDV) is an emerging virus in cotton production in Georgia and several other Southeastern states in the USA. To better understand the genetic diversity of the virus population, the near complete genome sequences of six isolates from Georgia and one from Alabama were determined. The isolates sequenced were 5,866 nucleotides with seven open reading frames (ORFs). The isolates from Georgia were >94% identical with other isolates from the USA and South America. In the silencing suppressor protein (P0), at amino acid position 72, the isolates from Georgia and Alabama had a valine (V), similar to resistant-breaking ‘atypical’ genotypes in South America, while the Texas isolate had isoleucine (I), similar to the more aggressive ‘typical’ genotypes of CLRDV. At position 120, arginine (R) is unique to Georgia and China isolates, but absent in Alabama, Texas and South American isolates. Ten potential recombinant events were detected in the isolates sequenced. An increased understanding of CLRDV population structure and genetic diversity will help develop management strategies for CLRDV in the USA cotton belt.

Three-dimensional (3D) point cloud based plant phenotyping facilitates the extraction of the structural information of phenotypic traits and reduces the effects of occlusion. In this study, we describe a cotton plant architectural component segmentation and phenotypic trait extraction method. Point cloud data of cotton plants were collected using a terrestrial LiDAR. Individual branches were segmented using a cylinder-fitting method. Next, plant architectural phenotypic traits were extracted at both plant and branch levels, including plant volume, branch length, diameter, volume, and branch angle. Two cotton plants with different shapes were used to demonstrate the performance of the proposed method. Results demonstrated that the method could process plants with not only an upright main stem but also a lodged main stem and the extracted phenotypic traits were reasonable. The proposed method could provide useful information and improve efficiency for plant breeding studies.

Dense three-dimensional point clouds provide opportunities to retrieve detailed characteristics of plant organ-level phenotypic traits, which are helpful to better understand plant architecture leading to its improvements via new plant breeding approaches. In this study, a high-resolution terrestrial LiDAR was used to acquire point clouds of plants under field conditions, and a data processing pipeline was developed to detect plant main stalks and nodes, and then to extract two phenotypic traits including node number and main stalk length. The proposed method mainly consisted of three steps: first, extract skeletons from original point clouds using a Laplacian-based contraction algorithm; second, identify the main stalk by converting a plant skeleton point cloud to a graph; and third, detect nodes by finding the intersection between the main stalk and branches. Main stalk length was calculated by accumulating the distance between two adjacent points from the lowest to the highest point of the main stalk. Experimental results based on 26 plants showed that the proposed method could accurately measure plant main stalk length and detect nodes; the average R2 and mean absolute percentage error were 0.94 and 4.3% for the main stalk length measurements and 0.7 and 5.1% for node counting, respectively, for point numbers between 80,000 and 150,000 for each plant. Three-dimensional point cloud-based high throughput phenotyping may expedite breeding technologies to improve crop production.

QTLs for fiber length mapped in three generations of advanced backcross populations derived from crossing Gossypium hirsutum and Gossypium mustelinum showed opportunities to improve elite cottons by introgression from wild relatives. The molecular basis of cotton fiber length in crosses between Gossypium hirsutum and Gossypium mustelinum was dissected using 21 BC3F2 and 12 corresponding BC3F2:3 and BC3F2:4 families. Sixty-five quantitative trait loci (QTLs) were detected by one-way analysis of variance. The QTL numbers detected for upper-half mean length (UHM), fiber uniformity index (UI), and short fiber content (SFC) were 19, 20, and 26 respectively. Twenty-three of the 65 QTLs could be detected at least twice near adjacent markers in the same family or near the same markers across different families/generations, and 32 QTLs were detected in both one-way variance analyses and mixed model-based composite interval mapping. G. mustelinum alleles increased UHM and UI and decreased SFC for five, one, and one QTLs, respectively. In addition to the main-effect QTLs, 17 epistatic QTLs were detected which helped to elucidate the genetic basis of cotton fiber length. Significant among-family genotypic effects were detected at 18, 16, and 16 loci for UHM, UI, and SFC, respectively. Six, two, and two loci showed genotype × family interaction for UHM, UI and SFC, respectively, illustrating complexities that might be faced in introgression of exotic germplasm into cultivated cotton. Co-location of many QTLs for UHM, UI, and SFC accounted for correlations among these traits, and selection of these QTLs may improve the three traits simultaneously. The simple sequence repeat (SSR) markers associated with G. mustelinum QTLs will assist breeders in transferring and maintaining valuable traits from this exotic source during cultivar development.

Pod and seed size are important characteristics for the peanut industry and have been under strong selection pressure since peanut domestication. In order to dissect the genetic control of peanut pod and seed size, a recombinant inbred mapping population from a cross of Florida-07 by GP-NC WS 16 was used to determine the genomic regions associated with traits including 100 pod weight, 100 seed weight, pod weight of double-seeded pods, seed weight of double-seeded pods, and area of double-seeded pods. Nine QTL on linkage groups (LGs) A05, A06, A09, B10, B04, A03, B05, and B08 were associated with pod and seed size. A majority of the QTL have small effects except the locus on LG A05 (93 to 102 Mbp) which explained up to 66% phenotypic variation for all measured pod and seed traits. A comparison of QTL previously reported for yield component traits showed a common QTL on LG A05 was detected in two genetic populations whose parentage is distinct from those used in this study. The markers tightly linked to this major QTL were informative in distinguishing large versus small-seeded germplasm lines in the mini core collection originating from thirty-one countries, suggesting selection for this seed size QTL in large-seeded ecotypes. However, the large seed size allele appeared to co-segregate with a late leaf spot disease susceptibility allele inherited from the Florida-07 parent. Therefore, peanut breeders need to weigh the pros and cons before integrating the large seed size QTL from Florida-07 in their breeding program.

Early and late leaf spots are the major foliar diseases of peanut responsible for severely decreased yield in the absence of intensive fungicide spray programs. Pyramiding host resistance to leaf spots in elite cultivars is a sustainable solution to mitigate the diseases. In order to determine the genetic control of leaf spot disease resistance in peanut, a recombinant inbred line population (Florida-07 x GP-NC WS16) segregating for resistance to both diseases was used to construct a SNP-based linkage map consisting of 855 loci. QTL mapping revealed three resistance QTLs for late leaf spot qLLSA05 (phenotypic variation explained, PVE=7-10%), qLLSB03 (PVE=5-7%), and qLLSB05 (PVE=15-41%) that were consistently expressed over multi-year analysis. Two QTL, qLLSA05 and qLLSB05, confirmed our previously published QTL-seq results. For early leaf spot, three resistance QTLs were identified in multiple years, two on chromosome A03 (PVE=8-12%) and one on chromosome B03 (PVE=13-20%), with the locus qELSA03_1.1 coinciding with the previously published genomic region for LLS resistance in GPBD4. Comparative analysis of the genomic regions spanning the QTLs suggests that resistance to early and late leaf spots are largely genetically independent. In addition, QTL analysis on yield showed that the presence of resistance allele in qLLSB03 and qLLSB05 loci might result in protection from yield loss caused by LLS disease damage. Finally, post hoc analysis of the RIL subpopulation that was not utilized in the QTL mapping revealed that the flanking markers for these QTLs can successfully select for resistant and susceptible lines, confirming the effectiveness of pyramiding these resistance loci to improve host-plant resistance in peanut breeding programs using marker-assisted selection.

Host plant resistance is the most practical approach to control the Southern root-knot nematode (Meloidogyne incognita; RKN), which has emerged as one of the most serious economic pests of Upland cotton (Gossypium hirsutum L.). Previous QTL analyses have identified a resistance locus on chromosome 11 (qMi-C11) affecting galling and another locus on chromosome-14 (qMi-C14) affecting egg production. Although these two QTL regions were fine mapped and candidate genes identified, expression profiling of genes would assist in further narrowing the list of candidate genes in the QTL regions. We applied the comparative transcriptomic approach to compare expression profiles of genes between RKN susceptible and resistance genotypes at an early stage of RKN development that coincides with the establishment of a feeding site and at the late stage of RKN development that coincides with RKN egg production. Sequencing of cDNA libraries produced over 315 million reads of which 240 million reads (76%) were mapped on to the Gossypium hirsutum genome. A total of 3,789 differentially expressed genes (DEGs) were identified which were further grouped into four clusters based on their expression profiles. A large number of DEGs were found to be down regulated in the susceptible genotype at the late stage of RKN development whereas several genes were up regulated in the resistant genotype. Key enriched categories included transcription factor activity, defense response, response to phyto-hormones, cell wall organization, and protein serine/threonine kinase activity. Our results also show that the DEGs in the resistant genotype at qMi-C11 and qMi-C14 loci displayed higher expression of defense response, detoxification and callose deposition genes, than the DEGs in the susceptible genotype.

Among the seven tetraploid cotton species, little is known about transmission genetics and genome organization in Gossypium mustelinum, the species most distant from the source of most cultivated cotton, G. hirsutum. In this research, an F2 population was developed from an interspecific cross between G. hirsutum and G. mustelinum (HM). A genetic linkage map was constructed mainly using simple sequence repeat (SSRs) and restriction fragment length polymorphism (RFLP) DNA markers. The arrangements of most genetic loci along the HM chromosomes were identical to those of other tetraploid cotton species. However, both major and minor structural rearrangements were also observed, for which we propose a parsimony-based model for structural divergence of tetraploid cottons from common ancestors. Sequences of mapped markers were used for alignment with the 26 scaffolds of the G. hirsutum draft genome, and showed high consistency. Quantitative trait locus (QTL) mapping of fiber elongation in advanced backcross populations derived from the same parents demonstrated the value of the HM map. The HM map will serve as a valuable resource for QTL mapping and introgression of G. mustelinum alleles into G. hirsutum, and help clarify evolutionary relationships between the tetraploid cotton genomes.

Premise of the study Introgression is widely acknowledged as a potential source of valuable genetic variation, and growing effort is being invested in analysis of interspecific crosses conferring transgressive variation. Experimental backcross populations provide an opportunity to study transmission genetics following interspecific hybridization, identifying opportunities and constraints to introgressive crop improvement. The evolutionary consequences of introgression have been addressed at the theoretical level, however, issues related to levels and patterns of introgression among (plant) species remain inadequately explored, including such factors as polyploidization, subgenome interaction inhabiting a common nucleus, and the genomic distribution and linkage relationships of introgressant alleles. Methods We analyze introgression into the polyploid Gossypium hirsutum (upland cotton) from its sister G. tomentosum and compare the level and pattern with that of G. barbadense representing a different clade tracing to the same polyploidization. Key results Across the genome, recurrent backcrossing to Gossypium hirsutum yielded only one-third of the expected average frequency of the G. tomentosum allele, although one unusual region showed preferential introgression. Although a similar rate of introgression is found in the two subgenomes of polyploid (AtDt) G. hirsutum, a preponderance of multilocus interactions were largely within the Dt subgenome. Conclusions Skewed G. tomentosum chromatin transmission is polymorphic among two elite G. hirsutum genotypes, which suggests that genetic background may profoundly affect introgression of particular chromosomal regions. Only limited correspondence is found between G. hirsutum chromosomal regions that are intolerant to introgression from the two species, G. barbadense and G. tomentosum, concentrated near possible inversion polymorphisms. Complex transmission of introgressed chromatin highlights the challenges to utilization of exotic germplasm in crop improvement.

The interaction between Fusarium oxysporum f. sp. vasinfectum (Fov) and Meloidogyne incognita (root-knot nematode) resulting in Fusarium wilt (FW) of cotton is well-known. Although Belonolaimus longicaudatus (sting nematode) can also interact with Fov and cause FW, it has long been believed that virtually all of the FW in Georgia is caused by the interaction of Fov with M. incognita. In recent years, FW has been reported more frequently in Georgia, which suggests that something affecting the disease complex may have changed. In 2015 and 2016, a survey of 27 Georgia cotton fields in 10 counties was conducted. At least 10 soil and stem samples per field were collected from individual plants showing symptoms of FW to quantify plant-parasitic nematode levels and identify Fov races. Fov race 1 was identified in all samples in 2015, but one sample also had the LA110 genotype and another sample also had the LA108 genotype. In 2016, all Fov races and genotypes found in 2015 were present, however, MDS–12 and LA127/140 also were found. Meloidogyne incognita was present in 18% of fields in 2015 and 40% in 2016, whereas B. longicaudatus was present in all fields in 2015 and 75% of fields in 2016. Regardless of whether they occurred separately or together, M. incognita and B. longicaudatus were present, respectively, in 18% and 55% of individual samples in 2015 and 40% and 51% in 2016. However, M. incognita without B. longicaudatus was found in 7% of samples in 2015 and 34% in 2016, whereas B. longicaudatus without M. incognita was found in 45% of samples in 2015 and 44% in 2016. We conclude that Fov race 1 continues to be the dominant race in Georgia and many instances of FW in Georgia may be due to Fov interacting with B. longicaudatus and not M. incognita as previously believed.

The molecular genetic basis of cotton fiber strength and fineness in crosses between Gossypium mustelinum and Gossypium hirsutum (Upland cotton) was dissected using 21 BC3F2 and 12 corresponding BC3F2:3 and BC3F2:4 families. The BC3F2 families were genotyped with simple sequence repeat markers from a G. hirsutum by G. mustelinum linkage map, and the three generations of BC3-derived families were phenotyped for fiber strength (STR) and fineness (Micronaire, MIC). A total of 42 quantitative trait loci (QTLs) were identified through one-way analysis of variance, including 15 QTLs for STR and 27 for MIC, with the percentage of variance explained by individual loci averaging 13.86 and 14.06%, respectively. Eighteen of the 42 QTLs were detected at least twice near the same markers in different generations/families or near linked markers in the same family, and 28 of the 42 QTLs were identified in both mixed model-based composite interval mapping and one-way variance analyses. Alleles from G. mustelinum increased STR for eight of 15 and reduced MIC for 15 of 27 QTLs. Significant among-family genotypic effects (P < 0.001) were detected in 13 and 10 loci for STR and MIC respectively, and five loci showed significant (P < 0.001) genotype × family interaction for MIC. These results support the hypothesis that fiber quality improvement for Upland cotton could be realized by introgressing G. mustelinum alleles although complexities due to the different effects of genetic background on introgressed chromatin might be faced. Building on prior work with G. barbadense, G. tomentosum, and G. darwinii, QTL mapping involving introgression of G. mustelinum alleles offers new allelic variation to Upland cotton germplasm.

Introgressive breeding to introduce both obvious variation into a gene pool, and to unmask cryptic variation masked by close linkage or epistatic interactions, has repeatedly been attempted to improve fiber traits in Gossypium hirsutum by employing Gossypium barbadense as a donor parent. This study reports genetic variation for fiber quality traits in reciprocal advanced backcross populations between G. hirsutum cultivar Acala Maxxa and G. barbadense cultivar Pima S6. Micronaire (MIC), elongation (ELO), strength (STR), upper half mean length (UHM), and uniformity index (UI) showed significant genotypic variance, albeit different in the respective backgrounds for all traits except UI. Different levels of variation among genotypes for the same traits in reciprocal backgrounds suggest different levels of epistatic interactions, a hypothesis supported by a significant difference in transgressive segregants in Acala Maxxa and Pima S6 backgrounds. In Acala Maxxa background, 18, 18, 7, and 3 genotypes had significantly better MIC, ELO, STR and UHM, respectively, than Acala Maxxa. In Pima S6 background 10, 5, 8, and 11 genotypes had significantly better MIC, ELO, STR, and UHM, respectively, than Pima S6. Increased genetic variation and improved fiber quality in both backgrounds appears attainable using reciprocal introgression; however, the number of genotypes with simultaneous improvement for multiple fiber quality traits was higher in Acala Maxxa than Pima S6 background. Reciprocal populations provide a platform to study cytoplasmic effects on genetic variation and heritability of fiber quality traits, and estimate the size of base populations required to obtain genotypes with genetic gain by backcross breeding.

MicroRNAs (miRNAs) are small 20-24nt molecules that have been well studied over the past decade due to their important regulatory roles in different cellular processes. The mature sequences are more conserved across vast phylogenetic scales than their precursors and some are conserved within entire kingdoms, hence, their loci and function can be predicted by homology searches. Different studies have been performed to elucidate miRNAs using de novo prediction methods but due to complex regulatory mechanisms or false positive in silico predictions, not all of them express in reality and sometimes computationally predicted mature transcripts differ from the actual expressed ones. With the availability of a complete genome sequence of Gossypium arboreum, it is important to annotate the genome for both coding and noncoding regions using high confidence transcript evidence, for this cotton species that is highly resistant to various biotic and abiotic stresses. Here we have analyzed the small RNA transcriptome of G. arboreum leaves and provided genome annotation of miRNAs with evidence from miRNA/miRNA* transcripts. A total of 446 miRNAs clustered into 224 miRNA families were found, among which 48 families are conserved in other plants and 176 are novel. Four short RNA libraries were used to shortlist best predictions based on high reads per million (RPM). The size, origin, copy numbers and transcript depth of all miRNAs along with their isoforms and targets has been reported. The highest gene copy number was observed for gar-miR7504 followed by gar-miR166, gar-miR8771, gar-miR156 and gar-miR7484. Altogether, 1274 target genes were found in G. arboreum that are enriched for 216 KEGG pathways. The resultant genomic annotations are provided in UCSC, BED format.

This study reports transmission genetics of chromosomal segments into Gossypium hirsutum from its most distant euploid relative, Gossypium mustelinum . Mutilocus interactions and structural rearrangements affect introgression and segregation of donor chromatin. Wild allotetraploid relatives of cotton are a rich source of genetic diversity that can be used in genetic improvement, but linkage drag and non-Mendelian transmission genetics are prevalent in interspecific crosses. These problems necessitate knowledge of transmission patterns of chromatin from wild donor species in cultivated recipient species. From an interspecific cross, Gossypium hirsutum × Gossypium mustelinum, we studied G. mustelinum (the most distant tetraploid relative of Upland cotton) allele retention in 35 BC3F1 plants and segregation patterns in BC3F2 populations totaling 3202 individuals, using 216 DNA marker loci. The average retention of donor alleles across BC3F1 plants was higher than expected and the average frequency of G. mustelinum alleles in BC3F2 segregating families was less than expected. Despite surprisingly high retention of G. mustelinum alleles in BC3F1, 46 genomic regions showed no introgression. Regions on chromosomes 3 and 15 lacking introgression were closely associated with possible small inversions previously reported. Nonlinear two-locus interactions are abundant among loci with single-locus segregation distortion, and among loci originating from one of the two subgenomes. Comparison of the present results with those of prior studies indicates different permeability of Upland cotton for donor chromatin from different allotetraploid relatives. Different contributions of subgenomes to two-locus interactions suggest different fates of subgenomes in the evolution of allotetraploid cottons. Transmission genetics of G. hirsutum × G. mustelinum crosses reveals allelic interactions, constraints on fixation and selection of donor alleles, and challenges with retention of introgressed chromatin for crop improvement.

Cotton boll number is an important component of fiber yield, arguably the most important phenotypic trait to plant breeders and growers alike. In addition, boll number provides a better understanding on the physiological and genetic mechanisms of crop growth and development, facilitating timely decisions on crop management to maximize profit. Traditional in-field cotton boll number counting by visual inspection is time consuming and labor-intensive. In this work, we presented novel image processing algorithms for automatic single cotton boll recognition and counting under natural illumination in the field. A digital camera mounted on a robot platform was used to acquire images with a 45° downward angle on three different days before harvest. A double-thresholding with region growth algorithm combining color and spatial features was applied to segment bolls from background, and three geometric-feature-based algorithms were developed to estimate boll number. Line features detected by linear Hough Transform and the minimum boundary distance between two regions were used to merge disjointed regions split by branches and burrs, respectively. The area and the elongation ratio between major and minor axes were used to separate bolls overlapping in clusters. A total of 210 images captured under sunny and cloudy illumination conditions on three days were used to validate the performance of the cotton boll recognition method, with an F1 score of around 0.98; whereas, the best accuracy for boll counting was around 84.6%. At the whole plot level, fifteen plots were used to build a linear regression model between the estimated boll number and the overall fiber yield with a R2 value of 0.53. The performance was evaluated by another ten plots with a mean absolute percentage error of 8.92% and a root mean square error of 99 g. The methodology developed in this study provides a means to estimate cotton boll number from color images under field conditions and would be helpful to predict crop yield and understand genetic mechanisms of crop growth.

During the 2018 growing season, cotton plants in several fields in Georgia were observed with symptoms that included leaf curling, reddening and drooping of leaves, subsequent distortion of leaf growth above the nodes where reddened leaves were first observed, and shortening of upper internodes and their discoloration to deep green. These symptoms were visible in the upper portion of the plants, resembling “cotton blue” disease caused by cotton leafroll dwarf virus (CLRDV) (family Luteoviridae, genus Polerovirus). The symptoms were observed sporadically with less than 10% disease incidence within affected fields. CLRDV is a phloem-limited virus with single-stranded, positive-sense RNA genome, transmitted by aphids (Aphis gossypii) in a persistent, circulative, nonpropagative manner (Distefano et al. 2010; Sharman et al. 2015). A total of 93 symptomatic and asymptomatic leaves and petioles were collected from several different commercial cotton fields in the southern part of the state. Total RNA was extracted using the modified cetyltrimethylammonium bromide method (Sharman et al. 2015). Complementary DNA (cDNA) was synthesized from 2.5 µg of total RNA using Superscript III reverse transcription (Invitrogen, U.S.A.) and specific reverse primers targeting different open reading frames (ORFs) of the virus genome. The cDNA was used for polymerase chain reaction (PCR) with primers CLRDV3675F and Pol3982R targeting ORF 3 of the virus (310-bp product, Sharman et al. 2015) and primers 17 and 18 targeting ORF 5 (1,065-bp product, Distefano et al. 2010). A new set of primers, SB11F (5′-AGGTTTTCTGGTAGCAGTACCAATATCAACGTTA-3′) and SB11R (5′-TATCTTGCATTGTGGATTTCCCTCATAA-3′), was developed to amplify the 803-bp fragment spanning complete ORF 3 and ORF 4, encoding virus coat protein and movement protein genes. Using the three different sets of primers, products of predicted sizes were amplified from the symptomatic tissues, but not from asymptomatic tissues collected from fields and negative controls including asymptomatic leaves from plants grown in an insect-free controlled growth chamber and DNase/RNase free water (Invitrogen). Reverse transcription PCR products were gel purified, cloned into TOPO-TA cloning vector (Invitrogen), and sequenced using Sanger sequencing (GeneScript, NJ). The consensus sequence of three clones for ORF 3 and 4 from this study (MK290759 and MK290760) when analyzed using NCBI-BLASTn showed 97% sequence identity with the Brazilian and Argentinean isolates (KF906261.1 and KF359947.1, respectively) and many other isolates from South American and Asian countries. ORF 3 and 4 sequences from Georgia shared 98 to 99% identity among themselves. The partial sequences for ORF 5 (MK513938 and MK513939) shared 95% identity with the isolate from Argentina (KF359946.1 and KF359947.1). The presence of the virus was detected in all the symptomatic samples collected from 14 counties in Georgia, covering the entire cotton growing region of the state. To the best of our knowledge, this is the first report of CLRDV in Georgia, U.S.A. CLRDV infection of cotton has been reported in other cotton-growing regions in Africa, Asia, South America, and, more recently, in Alabama, U.S.A. (Avelar et al. 2018; Correa et al. 2005; Distefano et al. 2010; Mukherjee et al. 2012). With its rapid spread, this virus could pose an imminent threat and cause severe economic losses to the cotton industry. Further research is needed to elucidate epidemiology, symptomatology, vector transmission, and crop losses owing to CLRDV in the United States.

Published in Agron. J. 105:1635–1644 (2013) doi:10.2134/agronj2013.0264 Copyright © 2013 by the American Society of Agronomy, 5585 Guilford Road, Madison, WI 53711. All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. C is an economically important crop and provides the world’s leading natural fiber for the textile industry (Smith et al., 1999; Ulloa et al., 2007). The future of cotton improvement depends on plant characteristics conferring not only improved water-use efficiency and heat tolerance but also disease resistance. Integrating disease resistance into high-yielding, high-fiber-quality cultivars is one of the most important objectives in cotton breeding programs (Smith et al., 1999; Ulloa et al., 2009). Host-plant resistance can be a highly effective and economical approach for dealing with disease threats such as FOV and limiting yield loss in cotton (Hutmacher et al., 2011; Ulloa et al., 2010, 2011, 2013). Eight genotypes of FOV, called races, have been described (Skovgaard et al., 2001; Kim et al., 2005). Before 1986, only Races 1 and 2 were known to occur on significant acreage in the United States (DeVay, 1986). Since FOV disease in cotton was first reported in California in 1959 (Garber and Paxman, 1963), FOV Races 1 or 2 were recognized as the causal organism and were typically found in sandy soils with root-knot nematode (RKN) [Meloidogyne incognita (Kofoid and White) Chitwood] (Garber et al., 1979; Veech, 1984; Bell, 1984). The FOV fungal pathogen is a soil inhabitant that can survive for long periods in the absence of a host. Consequently, it is nearly impossible to eradicate from a field. A marked increased in the susceptibility of cultivars to FOV Race 1 was noted in the presence of RKN (Garber et al., 1979). Cotton developed for resistance to FOV on soils infested with RKN usually maintained their resistance when simultaneously challenged by both organisms, FOV Race 1 and RKN (Sasser, 1972; Heald and Orr, 1982). In 2005, University of California-Davis scientists (Kim et al., 2005) identified additional FOV races (1, 3, 4, and 8) in California soils. During the past 9 yr, FOV Race 4 has increasingly impacted cotton fields in the San Joaquin Valley (SJV) of California (Hutmacher et al., 2011). In field soils with relatively high levels of FOV Race 4, extensive disease symptoms AbStrAct During the past 9 yr, a new race of Fusarium (Fusarium oxysporum f. sp. vasinfectum [FOV Race 4]) has increasingly impacted cotton (Gossypium spp.) in the San Joaquin Valley of California. To assess the vulnerability of upland cotton (G. hirsutum L.) in California to FOV disease, elite upland germplasm lines from 13 U.S. public breeding programs across the Cotton Belt and commercial cultivars were evaluated for disease resistance to FOV Races 1 and 4. Ten independent replicated field trials were conducted: three in 2008, four in 2010, and three in 2011. Significant differences (P £ 0.05) were observed for disease severity index of leaves, vascular root staining, and plant survival values among the elite germplasm lines in all 3 yr for the levels of resistance–response to FOV Races 1 and 4. Also, significant interactions among germplasm lines, FOV races (1 and 4), and evaluation sites indicated that germplasm lines differed in mechanisms of plant-defense response for the two FOV races. Selected lines from programs in the states of Alabama, Arkansas, Louisiana, and Mississippi showed at least a moderate level of tolerance to both FOV races; however, several of these lines produced weak and coarse fibers. Based on these evaluations, many of the entries in public breeders’ current elite upland germplasm pools may be more susceptible than expected to some FOV races, and sources of acceptable levels of resistance may be limited when tested under infestation levels that resulted in only 5 to 35% plant survival in susceptible check cultivars.

A fiber length QTL, qFL-chr1, was fine mapped to a 0.9 cM interval of cotton chromosome 1. Two positional candidate genes showed positive correlation between gene expression level and fiber length. Prior analysis of a backcross-self mapping population derived from a cross between Gossypium hirsutum L. and G. barbadense L. revealed a QTL on chromosome 1 associated with increased fiber length (qFL-chr1), which was confirmed in three independent populations of near-isogenic introgression lines (NIILs). Here, a single NIIL, R01-40-08, was used to develop a large population segregating for the target region. Twenty-two PCR-based polymorphic markers used to genotype 1672 BC4F2 plants identified 432 recombinants containing breakpoints in the target region. Substitution mapping using 141 informative recombinants narrowed the position of qFL-chr1 to a 1.0-cM interval between SSR markers MUSS084 and CIR018. To exclude possible effects of non-target introgressions on fiber length, different heterozygous BC4F3 plants introgressed between SSR markers NAU3384 and CGR5144 were selected to develop sub-NILs. The qFL-chr1 was further mapped at 0.9-cM interval between MUSS422 and CIR018 by comparisons of sub-NIL phenotype, and increased fiber length by ~1 mm. The 2.38-Mb region between MUSS422 and CIR018 in G. barbadense contained 19 annotated genes. Expression levels of two of these genes, GOBAR07705 (encoding 1-aminocyclopropane-1-carboxylate synthase) and GOBAR25992 (encoding amino acid permease), were positively correlated with fiber length in a small F2 population, supporting these genes as candidates for qFL-chr1.