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CROP BREEDING, GENETICS & CYTOLOGY

Genetic Distance among Selected Cotton Genotypes and Its Relationship with F₂ Performance

^a Jr., USDA-ARS, Crop Science Res. Lab., Genetics and Precision Agriculture Research Unit, Mississippi State, MS 39762
^b Dep. of Plant and Soil Sciences, Mississippi State Univ., Mississippi State, MS 39762
^c USDA-ARS, Small Fruit Res. Stn., Poplarville, MS 39470
^d Delta and Pine Land Company, Scott, MS 38772

* Corresponding author (ssaha{at}msa-msstate.ars.usda.gov)

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Knowledge of genetic diversity and relationships among breeding materials has a significant impact on crop improvement. Association between parental divergence and progeny performance has not been well documented in cotton (Gossypium hirsutum L.). The objectives of this study were to estimate genetic diversity among selected cotton genotypes on the basis of simple sequence repeat (SSR) markers, and to investigate the relationship between genetic diversity and F₂-bulk population performance. Five U.S. and four Australian cultivars, and two day-neutral converted lines of G. hirsutum were genotyped by means of 90 SSR primer pairs providing 69 polymorphic marker loci. Genetic distance (GD) between genotypes ranged from 0.06 to 0.34 for the 11 parental genotypes. The highest GD (0.34) was observed between ST474 and the day-neutral converted line B1388. The lowest GD (0.06) was detected between cultivars FM832 and FM975. The GD between day-neutral converted lines and cultivars ranged from 0.26 to 0.34. Among the Australian cultivars, GD ranged from 0.06 to 0.19 while GD among U.S. cultivars varied from 0.10 to 0.22, indicating a narrow genetic base. Significant correlations between agronomic and fiber traits of F₂-bulk populations and GD ranged from negative to positive depending on the traits, genetic background, and environment. On the basis of SSR markers, GD revealed a lack of genetic diversity among all genotypes and it was a poor predictor of overall F₂ performance. However, when genotypes with maximum range of GD were present, it was a better predictor for some traits.

Abbreviations: GD, genetic distance • SSR, simple sequence repeats

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
INFORMATION about the degree and distribution of genetic diversity and relationships among breeding materials has a significant effect on crop improvement. Selection of suitable parents is one of the most important criteria used to allocate resources to the most promising crosses and increase the efficiency of breeding programs. Molecular markers increasingly play an important role in crop improvement programs. They have been used to predict genetic variance among inbred lines (Manjarrez-Sandoval et al., 1997), estimate genetic diversity in crops (Wendel et al., 1992; Tatineni et al., 1996), protect plant cultivar rights (Smith and Smith, 1992), classify heterotic groups (Dudley et al., 1991; Senior et al., 1998), study phylogenetic relationships among crops and their wild relatives (Li et al., 2000), analyze pedigrees (Smith et al., 1997), and select desired traits (Young, 1999).

Simple sequence repeats, also called microsatellites, are tandem repetitive DNA sequences. The availability and abundance of SSR markers throughout the cotton genome, their polymorphic nature, codominance, and polymerase chain reaction (PCR)-based assay make SSRs useful in detecting genetic diversity (Reddy et al., 2001).

The usefulness of GD as a predictor of hybrid performance has been studied in several crops. In maize (Zea mays L.) and sunflower (Helianthus annuus L.), significant correlations between GD and hybrid performance were observed by Lee et al. (1989), Smith et al. (1990), Lanza et al. (1997), and Cheres et al. (2000). In contrast, Godshalk et al. (1990) and Dudley et al. (1991) observed weak correlations between marker genotype and hybrid performance in maize. Furthermore, Martin et al. (1995) working with wheat (Triticum aestivum L.) found no association between measures of diversity and hybrid performance. Meredith and Brown (1998) using restriction fragment length polymorphic (RFLP) markers reported that in cotton the correlations between yield of F₂ hybrids, heterosis, and GD were very low (r = 0.07).

The utilization of heterosis for lint yield and fiber quality in F₂ hybrids has eluded most researchers because of inconsistent expression of heterosis and lack of economically effective means of delivering F₂ seeds to growers. Nonetheless, it has been demonstrated that F₂ hybrids can exhibit superior performance for agronomic and fiber traits when compared with their parental lines. Meredith (1990) reported that F₂ hybrids yielded 8% higher than their parents and no differences in adaptation were detected; however, the F₂ hybrids had significantly shorter fiber. Moreover, Tang et al. (1992)(1993a,b) observed that almost all F₂ hybrids developed from crosses between selected pest-resistant germplasms and cultivars were equal to their highest parent for most fiber traits. Perhaps the greatest motivation to investigate prediction of F₂ performance is to spur cotton improvement. Presently, F₂-bulk population performance is used in about 24% of commercial cotton breeding programs in the USA for early generation testing and identification of populations upon which to focus selection (Bowman, 2000).

The objectives of this study were to estimate GD on the basis of SSR markers among selected cotton genotypes, and to investigate the association between GD and fiber and agronomic characteristics of F₂-bulk populations.

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Plant Materials and Field Experiments
Eleven cotton genotypes, five U.S. cultivars, four cultivars developed by the CSIRO cotton breeding program in Australia, and two day-neutral converted lines of G. hirsutum derived from photoperiodic wild accessions were selected for this study (Calhoun et al., 1994) (Table 1) . The U.S. cultivars are a representative sample of those grown in the Delta region and some represent the most influential breeding programs in terms of genetic contributions to modern cultivars (Bowman et al., 1996). The Australian cultivars were obtained from Cotton Seed International. These four were used because they were offered for sale to growers in the USA and their GD from U.S. cultivars was unknown.

The mating design used for this experiment was an 11 parent half diallel. Crosses were made during 1998 at the R. R. Foil Plant Science Research Center, at Mississippi State University. The F₁ generation was grown in the USDA-ARS winter nursery at Tecoman, Colima, Mexico, to produce F₂ seed. Seed from the 54 F₂ hybrids (one cross was lost) and the eleven parents were grown at the Plant Science Research Center, Mississippi State, MS, in the summers of 1999 and 2000 at two locations which differ in soil type and rainfall pattern.

The experimental design was a randomized complete block design with four replications within each location. The experiments were planted on 11 and 12 May 1999, and 11 and 15 May 2000. Trials were planted in 9- or 12-m single-row plots with 10 plants m^-1 of row and a row spacing of 0.97 m. The soil type at the first location was a Leeper silty clay loam (fine, smectitic, nonacid, thermic, Vertic Epiaquepts) and at the second location was a Marietta loam (fine-loamy, siliceous, active, thermic, Fluvaquentic Eutrudepts) soil. Standard cultural practices were followed during the growing season.

Plots were harvested with a mechanical picker for yield determination on 7 and 8 Oct. 1999 and 20 Sept. and 10 Oct. 2000. Samples containing 50 bolls were hand-harvested both years from each plot before mechanical harvesting. The boll samples were weighed and ginned on a 10-saw laboratory gin for lint percentage calculations (100 x lint weight/seed cotton weight). A lint sample (20 g) from each boll sample represented a fiber sample. Fiber samples were sent to STARLAB Inc. (Knoxville, TN) for measurements of elongation (%), fiber strength (kN m kg^-1), 2.5% span length (mm), 50% span length (mm), and micronaire reading by single-instrument testing.

SSR Markers
Leaves were collected from field plots in summer 1999. Samples of 20 young leaves from each of the 11 parents were collected and freeze dried (Saha et al., 1997). The freeze-dried tissue was then ground into dry powder and stored at -20°C. Freeze-dried, powdered tissue was ground further with liquid nitrogen just before extraction following the manufacturer's protocol. DNA was isolated from 40 mg (dry weight) of cotton leaf tissue with the DNeasy Plant mini kit (Qiagen, Santa Clarita, CA) following the manufacture's protocol. The DNA concentration was measured with a spectrophotometer. The purity of the uncut DNA samples was also visually determined by means of agarose gel electrophoresis.

The 90 SSR primer pairs were received from Research Genetics Inc., Huntsville, AL. The PCR was performed with 80 ng DNA as template, 0.15 µM each, fluorescent-labeled and nonlabeled specific SSR primer pairs labeled either HEX (4,7,2,'4',5',7'-hexacloro-6-carboxyfluorescein), NED (7'8'-benzo-5'fluoro-2',4,7-trichloro-5- carboxyfluorescein), or FAM (6-carboxyfluorescein), 0.2 mM each dNTP, 1x GeneAmp PCR Gold Buffer, 2.5 mM MgCl₂, and 0.5 units AmpliTaq Gold (Perkin-Elmer, Norwak, CT) DNA polymerase in a 10-µL reaction solution. PCR was carried out in a thermal cycler with the following profile: 7 min at 95°C, followed by 15 s at 94°C for denaturation, 30 s at 55°C for annealing and 2 min at 72°C for synthesis. The PCR amplification was continued for 40 cycles with a final extension for 30 min at 72°C. Samples were stored at -20°C until needed.

Capillary electrophoretic analysis of fluorescently-labeled, amplified DNA markers were visualized as peaks on electropherograms with the automated ABI PRISM 310 Genetic Analyzer (Perkin-Elmer Corp., Norwalk, CT) equipped with genotyping and Genescan analysis software (PE Applied Biosystems, Foster City, CA, USA). Because of the high sensitivity of the system, a DNA marker was considered valid if it had a peak height of at least 100 fluorescent units and plus or minus one base size difference with the nearest DNA fragment peak. Fluorescently labeled PCR products (1:30 diluted in sterile water) were mixed in 10 µL formamide (AMRESCO Inc., Solon, OH) and 0.2 µL of an internal size standard DNA labeled with a ROX dye, denatured at 95°C for 5 min, kept on ice at least for 4 min and loaded on the automated ABI PRISM 310 Genetic Analyzer. Variation in the amplified products was compared with an internal size standard DNA labeled with the ROX dye different from that of the sample. Computer-assisted analysis of the data was performed with GeneScan software using local southern method. Additional parameters in the ABI 310 system were injection time 10 to 15 s, electrophoresis voltage 13 kV, injection voltage 15 kV, collection time 26 min, run temperature 60°C, and syringe pump time 180 s.

Data Analysis
Final analyses were performed on a total of 90 primer pairs. Peaks, representative of bands in the electropherograms were then coded as 1 or 0 for presence or absence of the band, respectively. Genetic distances between all pairs of parents were calculated with the PAUP* 4.0b5 software (Swofford, 2000) as GD = 1 - S_xy according to the method developed by Nei and Li (1979):

where S_xy = measure of genetic similarity between pairs of parents, n_xy = number of bands common in parents X and Y, n_x = number of bands in parents X, and n_y = number of bands in parents Y.

A phylogenetic tree (Fig. 1) and matrix of GD (Table 2) were constructed by the Unweighted Pair Group Mean Average (UPGMA) method of Saitou and Nei (1987) by PAUP* 4.0b5 software (Swofford, 2000). Heterosis of F₂-bulk population for all traits was calculated by comparing each F₂-bulk population with the respective midparent (F₂-MP) mean per replication at each location.

View larger version (13K): [in this window] [in a new window]   Fig. 1. Dendogram presenting the association of 11 cotton genotypes determined by Unweighted Paired Group Method using Arithmetic Averages (UPGMA) cluster analysis of 69 polymorphic SSR marker loci.

	RESULTS AND DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Genetic Diversity among the Parental Lines
Sixty of the 90 SSR primer pairs amplified 69 polymorphic marker loci among 11 cotton genotypes of diverse genetic background (Table 1). Nine primer pairs (CML66, BNL530, BNL1417, BNL1551, BNL1897, BNL2440, BNL2448, BNL2646, and BNL3599) amplified two loci each and 51 primer pairs (CML43, CML63, CML68, BNL119, BNL169, BNL193, BNL256, BNL285, BNL409, BNL597, BNL632, BNL840, BNL1053, BNL1059, BNL1064, BNL1162, BNL1231, BNL1414, BNL1423, BNL1440, BNL1495, BNL1672, BNL1681, BNL1694, BNL1707, BNL2499, BNL2530, BNL2590, BNL2597, BNL2895, BNL2986, BNL3065, BNL3084, BNL3090, BNL3264, BNL3279, BNL3280, BNL3368, BNL3383, BNL3400, BNL3441, BNL3442, BNL3479, BNL3482, BNL3649, BNL3792, BNL3816, BNL3895, BNL3955, BNL3971, and BNL3994) amplified one locus each. Similar results were previously obtained by Liu et al. (2000a)( b) who mapped many of these SSR loci to different chromosomes. A total of 139 different alleles were amplified by 60 SSR primer pairs yielding an average of two SSR alleles per marker locus. The SSR markers used in this study were reported to be present on at least 13 of the 26 chromosomes of the cotton genome. Approximately 55% of the SSR markers have been assigned to the A genome and 46% to the D genome of tetraploid cotton.

Genetic distance coefficients based on the polymorphic SSR marker loci ranged from 0.06 to 0.34 for the 11 parental lines (Table 2). The highest GD (0.34) was detected between the cultivar ST474 and the day-neutral converted line B1388. The lowest GD (0.06) was observed between Australian cultivars, FM832 and FM975. The GD between cultivars and day-neutral converted lines ranged from 0.26 to 0.34. Among the U. S. cultivars, GD ranged from 0.10 to 0.22 while GD of Australian cultivars varied from 0.06 to 0.19, indicating the presence of a narrow genetic base among the Australian and U.S. cultivars. Multani and Lyon (1995) observed GD of 0.01 to 0.08 among nine Australian cultivars which also showed a lack of genetic diversity. Iqbal et al. (1997) also found very high genetic similarity of 0.82 to 0.93 among 17 G. hirsutum cultivars on the basis of random amplified polymorphic DNA (RAPD) markers. On the basis of SSR markers, Ulloa et al. (1999) observed a GD of 0.18 within Acala and Delta cottons while the GD within the Pima PS series was approximately 0.16. The monoculture of a few successful cotton cultivars and the extensive use of them as parents in breeding programs has limited genetic diversity, possibly contributing to yield stagnation in the 1990s (Van Esbroeck et al., 1998). Furthermore, Bowman (2000) suggested that the present situation of high genetic uniformity in cotton is unlikely to change. He reported that genetic uniformity of cotton cultivars reflects reselection within cultivars, disregard for coefficient of parentage in commercial breeding programs, and reduced efforts in germplasm enhancement. Low GD values indicate that it is necessary to introgress new alleles into the U.S. cotton germplasm base to enhance its genetic diversity.

The GD between day-neutral converted lines of wild race stocks, A239 and B1388, was 0.21. This is somewhat surprising because their recurrent parental accessions were collected in different countries, and they have different donor parents for the day-neutral flowering trait (DP16 and DES56, respectively). These results are in agreement with the findings of Liu et al. (2000a), who reported a very narrow genetic base in a subset of day-neutral selections from crosses of race-stock accessions and upland cultivars compared with the G. hirsutum genetic standard TM-1. The lack of diversity between A239 and B1388 could be due to the fact that these accessions were selected for the same traits of insensitivity to photoperiod and high fiber strength. During this process, large chromosomal blocks surrounding genes for fiber strength, earliness, and day neutrality may be introgressed as common alleles in both lines. Lack of enough recombination in portions of the cotton genome could be also responsible for the small GD.

The UPGMA tree generated from genetic distance coefficients, grouped the 11 cotton genotypes into two major clusters (Fig. 1). Cluster A (denoted as Subclusters A1-A4 in Fig. 1) represents the cultivars, and Cluster B the day-neutral converted lines. Within Cluster A, there were four subclusters, A1 (ST474), A2 (‘SG501’, ‘PM1560’, and ‘DP50’), A3 (FM975, FM832, ‘FM989’, and ‘DP90’), and A4 (‘FM963’) (Fig. 1). Although PM1560, SG501, and ST474 have one parent in common, ‘DES119’ (Calhoun et al., 1994) (Table 1), ST474 was in a separate subcluster. DP 90 was included with the Australian cultivars in the A3 cluster. DP 90 was more closely related to the Australian cultivars compared with the U.S. cultivars indicating that the Australian cultivars and DP 90 may have a similar genetic background, or DP 90 is a frequent parent in the pedigree of Australian cultivars. Subcluster A4 consists only of the Australian cultivar, FM 963. The Australian cultivars were distinguished by clustering close together compared with the U.S. cultivars, indicating their origin from similar genetic backgrounds. Long-term selection for similar agronomically desirable traits may have caused the cultivars to be genetically more uniform and thus to cluster close together. Even though pedigree information on the Australian cultivars was not available, the majority of the groups resulting from cluster analysis were as expected on the basis of their pedigree and geographic information which further supports the strength of SSR markers for the detection of GD.

Relationship of Genetic Distance with F₂-Bulk Performance
There were significant differences (P < 0.001) among entries (i.e., parents and F₂ bulk) for all agronomic and fiber traits in each environment. There were changes in the rank of the crosses from environment to environment. The number of F₂-bulk population means differing from environment to environment demonstrated the strong impact of environment on fiber properties, yield, and yield components (Table 3) . The effects of severe dry conditions in Environments 3 and 4 during 2000 perhaps affected the performance of F₂-bulk populations, since several of them performed better than their mid-parents in agronomic and fiber traits.

In regards to fiber properties, significant negative correlations for micronaire reading were observed only in Set 5 in two environments indicating that day-neutral converted line A239, which has a low micronaire reading, could be used to develop lower micronaire reading germplasm. This also agrees with Cheatham (2001) who observed that predicted micronaire values for crosses with A239 decreased in advanced generations of selection. A negative correlation was observed between fiber elongation and GD in Set 1 despite parents with desirable fiber elongation.

In summary, commercial cultivars exhibited little genetic diversity with GD ranging from 0.06 to 0.22. The GD between the day-neutral converted lines A239 and B1388 was 0.21, which was similar to the greatest GD between commercial cultivars. The day-neutral converted lines, A239 and B1388, had lower yield, lower lint percentage, and shorter and stronger fibers than the cultivars, but their fiber strength were nearly as high as that of FM 832. Crosses of A239 and B1388 with the cultivars should gain alleles for higher fiber strength, but to use the strength genes from A239 and B1388, careful attention should be given to fiber length, lint percentage, and lint yield to avoid negatively affecting these traits.

An assessment of the usefulness of SSR markers in breeding cotton for yield improvement and fiber quality needs further consideration. We must acknowledge that a limited number of SSR markers were used to make this experiment cost effective. Perhaps more SSR markers covering all 26 chromosomes and at higher density are needed to better predict F₂ population performance with GD. Improving the association between SSR marker diversity and F₂-bulk population performance also would require SSR markers linked to QTLs for agronomic traits and fiber properties. Our results also demonstrated that the performance of F₂-bulk populations does not always depend on the GD, but on the genetic background of the parental germplasm. Genetic diversity has to be incorporated in any breeding program with a proper plan, so that maximum potential can be achieved by incorporating favorable QTLs in a crossing program and removing the unfavorable ones from parental lines (Liu and Wu, 1998). Finally, our study also revealed very low genetic diversity among improved commercial cultivars and, thus the need for new germplasm introgression.

	ACKNOWLEDGMENTS

 
The authors express thanks to Mr. Douglas Dollar, Dr. Mehmet Karaca, Ms. Chethana Bezawada, and Mr. Russ Hayes for their technical assistance. We also thank Drs. Roy G. Cantrell, Michael Lee, James B. Holland, Mauricio Ulloa, Lloyd May, and three anonymous reviewers for their critical evaluation of the manuscript and helpful comments. Finally, we are grateful to Dr. Clarence E. Watson, Jr., for his valuable assistance with the statistical analyses.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Contribution of the USDA-ARS in cooperation with the Mississippi Agric. and Forestry Exp. Stn. Journal paper No. J 9891.

Received for publication July 9, 2001.

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