Fine mapping QMi-C11 a major QTL controlling root-knot nematodes resistance in Upland cotton

The Past, Present, and Future of Host Plant Resistance in Cotton: An Australian Perspective

Cotton is a key global fiber crop. However, yield potential is limited by the presence of endemic and introduced pests and diseases. The introduction of host plant resistance (HPR), defined as the purposeful use of resistant crop cultivars to reduce the impact of pests and diseases, has been a key breeding target for the Commonwealth Scientific and Industrial Research Organisation (CSIRO) cotton breeding program. The program has seen success in releasing cultivars resistant to Bacterial blight, Verticillium wilt, Fusarium wilt, and Cotton bunchy top. However, emerging biotic threats such as Black root rot and secondary pests, are becoming more frequent in Australian cotton production systems. The uptake of tools and breeding methods, such as genomic selection, high throughput phenomics, gene editing, and landscape genomics, paired with the continued utilization of sources of resistance from Gossypium germplasm, will be critical for the future of cotton breeding. This review celebrates the success of HPR breeding activities in the CSIRO cotton breeding program and maps a pathway for the future in developing resistant cultivars.

Sequence Composition of Bacterial Chromosome Clones in a Transgressive Root-Knot Nematode Resistance Chromosome Region in Tetraploid Cotton

Plants evolve innate immunity including resistance genes to defend against pest and pathogen attack. Our previous studies in cotton (Gossypium spp.) revealed that one telomeric segment on chromosome (Chr) 11 in G. hirsutum cv. Acala NemX (rkn1 locus) contributed to transgressive resistance to the plant parasitic nematode Meloidogyne incognita, but the highly homologous segment on homoeologous Chr 21 had no resistance contribution. To better understand the resistance mechanism, a bacterial chromosome (BAC) library of Acala N901 (Acala NemX resistance source) was used to select, sequence, and analyze BAC clones associated with SSR markers in the complex rkn1 resistance region. Sequence alignment with the susceptible G. hirsutum cv. TM-1 genome indicated that 23 BACs mapped to TM-1-Chr11 and 18 BACs mapped to TM-1-Chr 21. Genetic and physical mapping confirmed less BAC sequence (53-84%) mapped with the TM-1 genome in the rkn1 region on Chr 11 than to the homologous region (>89%) on Chr 21. A 3.1-cM genetic distance between the rkn1 flanking markers CIR316 and CIR069 was mapped in a Pima S-7 × Acala NemX RIL population with a physical distance ∼1 Mbp in TM-1. NCBI Blast and Gene annotation indicated that both Chr 11 and Chr 21 harbor resistance gene-rich cluster regions, but more multiple homologous copies of Resistance (R) proteins and of adjacent transposable elements (TE) are present within Chr 11 than within Chr 21. (CC)-NB-LRR type R proteins were found in the rkn1 region close to CIR316, and (TIR)-NB-LRR type R proteins were identified in another resistance rich region 10 cM from CIR 316 (∼3.1 Mbp in the TM-1 genome). The identified unique insertion/deletion in NB-ARC domain, different copies of LRR domain, multiple copies or duplication of R proteins, adjacent protein kinases, or TE in the rkn1 region on Chr 11 might be major factors contributing to complex recombination and transgressive resistance.

A novel variant of Gh_D02G0276 is required for root-knot nematode resistance on chromosome 14 (D02) in Upland cotton

MAGIC population sequencing and virus-induced gene silencing identify Gh_D02G0276 as a novel root-knot nematode resistance gene on chromosome 14 in Upland cotton. The southern root-knot nematode [RKN; Meloidogyne incognita (Kofoid & White)] remains the primary yield-limiting biotic stress to Upland cotton (Gossypium hirsutum L.) throughout the southeastern USA. While useful genetic markers have been developed for two major RKN resistance loci on chromosomes 11 (A11) and 14 (D02), these markers are not completely effective because the causative genes have not been identified. Here, we sequenced 550 recombinant inbred lines (RILs) from a multi-parent advanced generation intercross (MAGIC) population to identify five RILs that had informative recombinations near the D02-RKN resistance locus. The RKN resistance phenotypes of these five RILs narrowed the D02-RKN locus to a 30-kb region with four candidate genes. We conducted virus-induced gene silencing (VIGS) on each of these genes and found that Gh_D02G0276 was required for suppression of RKN egg production conferred by the Chr. D02 resistance gene. The resistant lines all possessed an allele of Gh_D02G0276 that showed non-synonymous mutations and was prematurely truncated. Furthermore, a Gh_D02G0276-specific marker for the resistance allele variant was able to identify RKN-resistant germplasm from a collection of 367 cotton accessions. The Gh_D02G0276 peptide shares similarity with domesticated hAT-like transposases with additional novel N- and C-terminal domains that resemble the target of known RKN effector molecules and a prokaryotic motif, respectively. The truncation in the resistance allele results in a loss of a plant nuclear gene-specific C-terminal motif, potentially rendering this domain antigenic due to its high homology with bacterial proteins. The conclusive identification of this RKN resistance gene opens new avenues for understanding plant resistance mechanisms to RKN as well as opportunities to develop more efficient marker-assisted selection in cotton breeding programs.

QTL Analysis of Transgressive Nematode Resistance in Tetraploid Cotton Reveals Complex Interactions in Chromosome 11 Regions

Transgressive segregation in cotton (Gossypium spp.) provides an important approach to enhance resistance to the major pest root-knot nematode (RKN) Meloidogyne incognita. Our previous studies reported transgressive RKN resistance in an intraspecific Gossypium hirsutum resistant NemX × susceptible SJ-2 recombinant inbred line (RIL) population and early generations of interspecific cross Gossypium barbadense (susceptible Pima S-7) × G. hirsutum (NemX). However, the underlying functional mechanisms for this phenomenon are not known. In this study, the region of RKN resistance gene rkn1 on chromosome (Chr) 11 and its homoeologous Chr 21 was fine mapped with G. raimondii D₅ genome reference sequence. Transgressive resistance was found in the later generation of a new RIL population F_2:7 (Pima S-7 × NemX) and one interspecific F₂ (susceptible Pima S-7 × susceptible SJ-2). QTL analysis revealed similar contributions to root-galling and egg-production resistance phenotypes associated with SSR marker CIR316 linked to resistance gene rkn1 in NemX on Chr 11 in all seven populations analyzed. In testcross NemX × F₁ (Pima S-7 × SJ-2) marker allele CIR069-271 from Pima S-7 linked to CIR316 contributed 63% of resistance to galling phenotype in the presence of rkn1. Similarly, in RIL population F_2:8 (NemX × SJ-2), SJ-2 markers closely linked to CIR316 contributed up to 82% of resistance to root-galling. These results were confirmed in BC₁F₁ SJ-2 × F₁ (NemX × SJ-2), F₂ (NemX × SJ-2), and F₂ (Pima S-7 × SJ-2) populations in which up to 44, 36, and 15% contribution in resistance to galling was found, respectively. Transgressive segregation for resistance was universal in all intra- and inter-specific populations, although stronger transgressive resistance occurred in later than in early generations in the intraspecific cross compared with the interspecific cross. Transgressive effects on progeny from susceptible parents are possibly provided in the rkn1 resistance region of chromosome 11 by tandemly arrayed allele (TAA) or gene (TAG) interactions contributing to transgressive resistance. Complex TAA and TAG recombination and interactions in the rkn1 resistance region provide three genes and a model to study disease and transgressive resistance in polyploid plants, and novel genotypes for plant breeding.

Fine mapping and identification of candidate genes for a QTL affecting Meloidogyne incognita reproduction in Upland cotton

Background

The southern root-knot nematode (Meloidogyne incognita; RKN) is one of the most important economic pests of Upland cotton (Gossypium hirsutum L.). Host plant resistance, the ability of a plant to suppress nematode reproduction, is the most economical, practical, and environmentally sound method to provide protection against this subterranean pest. The resistant line Auburn 623RNR and a number of elite breeding lines derived from it remain the most important source of root-knot nematode (RKN) resistance. Prior genetic analysis has identified two epistatically interacting RKN resistance QTLs, qMi-C11 and qMi-C14, affecting gall formation and RKN reproduction, respectively.

Results

We developed a genetic population segregating only for the qMi-C14 locus and evaluated the genetic effects of this QTL on RKN resistance in the absence of the qMi-C11 locus. The qMi-C14 locus had a LOD score of 12 and accounted for 24.5 % of total phenotypic variation for egg production. In addition to not being significantly associated with gall formation, this locus had a lower main effect on RKN reproduction than found in our previous study, which lends further support to evidence of epistasis with qMi-C11 in imparting RKN resistance in the Auburn 623RNR source. The locus qMi-C14 was fine-mapped with the addition of 16 newly developed markers. By using the reference genome sequence of G. raimondii, we identified 20 candidate genes encoding disease resistance protein homologs in the newly defined 2.3 Mb region flanked by two SSR markers. Resequencing of an RKN resistant and susceptible G. hirsutum germplasm revealed non-synonymous mutations in only four of the coding regions of candidate genes, and these four genes are consequently of high interest.

Conclusions

Our mapping results validated the effects of the qMi-C14 resistance locus, delimiting the QTL to a smaller region, and identified tightly linked SSR markers to improve the efficiency of marker-assisted selection. The candidate genes identified warrant functional studies that will help in identifying and characterizing the actual qMi-C14 defense gene(s) against root-knot nematodes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2954-1) contains supplementary material, which is available to authorized users.

Mapping by sequencing in cotton (Gossypium hirsutum) line MD52ne identified candidate genes for fiber strength and its related quality attributes

Three QTL regions controlling three fiber quality traits were validated and further fine-mapped with 27 new single nucleotide polymorphism (SNP) markers. Transcriptome analysis suggests that receptor-like kinases found within the validated QTLs are potential candidate genes responsible for superior fiber strength in cotton line MD52ne. Fiber strength, length, maturity and fineness determine the market value of cotton fibers and the quality of spun yarn. Cotton fiber strength has been recognized as a critical quality attribute in the modern textile industry. Fine mapping along with quantitative trait loci (QTL) validation and candidate gene prediction can uncover the genetic and molecular basis of fiber quality traits. Four previously-identified QTLs (qFBS-c3, qSFI-c14, qUHML-c14 and qUHML-c24) related to fiber bundle strength, short fiber index and fiber length, respectively, were validated using an F3 population that originated from a cross of MD90ne × MD52ne. A group of 27 new SNP markers generated from mapping-by-sequencing (MBS) were placed in QTL regions to improve and validate earlier maps. Our refined QTL regions spanned 4.4, 1.8 and 3.7 Mb of physical distance in the Gossypium raimondii reference genome. We performed RNA sequencing (RNA-seq) of 15 and 20 days post-anthesis fiber cells from MD52ne and MD90ne and aligned reads to the G. raimondii genome. The QTL regions contained 21 significantly differentially expressed genes (DEGs) between the two near-isogenic parental lines. SNPs that result in non-synonymous substitutions to amino acid sequences of annotated genes were identified within these DEGs, and mapped. Taken together, transcriptome and amino acid mutation analysis indicate that receptor-like kinase pathway genes are likely candidates for superior fiber strength and length in MD52ne. MBS along with RNA-seq demonstrated a powerful strategy to elucidate candidate genes for the QTLs that control complex traits in a complex genome like tetraploid upland cotton.

Fine mapping and RNA-Seq unravels candidate genes for a major QTL controlling multiple fiber quality traits at the T1 region in upland cotton

BACKGROUND

Improving fiber quality is a major challenge in cotton breeding, since the molecular basis of fiber quality traits is poorly understood. Fine mapping and candidate gene prediction of quantitative trait loci (QTL) controlling cotton fiber quality traits can help to elucidate the molecular basis of fiber quality. In our previous studies, one major QTL controlling multiple fiber quality traits was identified near the T1 locus on chromosome 6 in Upland cotton.

RESULTS

To finely map this major QTL, the F2 population with 6975 individuals was established from a cross between Yumian 1 and a recombinant inbred line (RIL118) selected from a recombinant inbred line population (T586 × Yumian 1). The QTL was mapped to a 0.28-cM interval between markers HAU2119 and SWU2302. The QTL explained 54.7 % (LOD = 222.3), 40.5 % (LOD = 145.0), 50.0 % (LOD = 194.3) and 30.1 % (LOD = 100.4) of phenotypic variation with additive effects of 2.78, -0.43, 2.92 and 1.90 units for fiber length, micronaire, strength and uniformity, respectively. The QTL region corresponded to a 2.7-Mb interval on chromosome 10 in the G. raimondii genome sequence and a 5.3-Mb interval on chromosome A06 in G. hirsutum. The fiber of Yumian 1 was much longer than that of RIL118 from 3 DPA to 7 DPA. RNA-Seq of ovules at 0 DPA and fibers at 5 DPA from Yumian 1 and RIL118 showed four genes in the QTL region of the G. raimondii genome to be extremely differentially expressed. RT-PCR analysis showed three genes in the QTL region of the G. hirsutum genome to behave similarly.

CONCLUSIONS

This study mapped a major QTL influencing four fiber quality traits to a 0.28-cM interval and identified three candidate genes by RNA-Seq and RT-PCR analysis. Integration of fine mapping and RNA-Seq is a powerful strategy to uncover candidates for QTL in large genomes.

Genetic analysis of Verticillium wilt resistance in a backcross inbred line population and a meta-analysis of quantitative trait loci for disease resistance in cotton

Background

Verticillium wilt (VW) and Fusarium wilt (FW), caused by the soil-borne fungi Verticillium dahliae and Fusarium oxysporum f. sp. vasinfectum, respectively, are two most destructive diseases in cotton production worldwide. Root-knot nematodes (Meloidogyne incognita, RKN) and reniform nematodes (Rotylenchulus reniformis, RN) cause the highest yield loss in the U.S. Planting disease resistant cultivars is the most cost effective control method. Numerous studies have reported mapping of quantitative trait loci (QTLs) for disease resistance in cotton; however, very few reliable QTLs were identified for use in genomic research and breeding.

Results

This study first performed a 4-year replicated test of a backcross inbred line (BIL) population for VW resistance, and 10 resistance QTLs were mapped based on a 2895 cM linkage map with 392 SSR markers. The 10 VW QTLs were then placed to a consensus linkage map with other 182 VW QTLs, 75 RKN QTLs, 27 FW QTLs, and 7 RN QTLs reported from 32 publications. A meta-analysis of QTLs identified 28 QTL clusters including 13, 8 and 3 QTL hotspots for resistance to VW, RKN and FW, respectively. The number of QTLs and QTL clusters on chromosomes especially in the A-subgenome was significantly correlated with the number of nucleotide-binding site (NBS) genes, and the distribution of QTLs between homeologous A- and D- subgenome chromosomes was also significantly correlated.

Conclusions

Ten VW resistance QTL identified in a 4-year replicated study have added useful information to the understanding of the genetic basis of VW resistance in cotton. Twenty-eight disease resistance QTL clusters and 24 hotspots identified from a total of 306 QTLs and linked SSR markers provide important information for marker-assisted selection and high resolution mapping of resistance QTLs and genes. The non-overlapping of most resistance QTL hotspots for different diseases indicates that their resistances are controlled by different genes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1682-2) contains supplementary material, which is available to authorized users.

Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations

KEY MESSAGE

A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.

Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations

KEY MESSAGE

A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.

Genetic mapping of the nulliplex-branch gene (gb_nb1) in cotton using next-generation sequencing

Using bulked segregant analysis based on next-generation sequencing, the recessive nulliplex-branch gene was mapped between two SNP markers ~600 kb apart. In a "nulliplex-branch" cotton mutant, most of the flowers arise directly from leaf axils on the main shoot, which usually does not have a fruiting branch. A nulliplex-branch is a useful trait by which to study cotton architecture; however, the genetic basis of this mutant has remained elusive. In this study, bulked segregant analysis combined with next-generation sequencing technology was used to finely map the underlying genes that result in a nulliplex-branch plant. The nulliplex-branch Pima cotton variety, Xinhai-18, was crossed with the normal branch upland cotton line, TM-1, resulting in an F2 population. The nulliplex-branch trait was found to be controlled by the recessive gene gb_nb1. Allelic single-nucleotide polymorphisms (SNPs) were discovered by reduced-representation sequencing between the parents, and their profiles were also characterized in the nulliplex-branch and normal branch bulks constructed using the F2 plants. A candidate ~9.0 Mb-long region comprising 42 SNP markers was found to be associated with gb_nb1, which helped localize it at the ~600-kb interval on Chr 16 by segregation analysis in the F2 population. The closely linked markers with gb_nb1 developed in this study will facilitate the marker-assisted selection of the nulliplex-branch trait, and the fine map constructed will accelerate map-based cloning of gb_nb1.

A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations

KEY MESSAGE

Based on 1075 and 1059 QTL from intraspecific Upland and interspecific Upland × Pima populations, respectively, the identification of QTL clusters and hotspots provides a useful resource for cotton breeding. Mapping of quantitative trait loci (QTL) is a pre-requisite of marker-assisted selection for crop yield and quality. Recent meta-analysis of QTL in tetraploid cotton (Gossypium spp.) has identified regions of the genome with high concentrations of QTL for various traits called clusters and specific trait QTL called hotspots or meta-QTL (mQTL). However, the meta-analysis included all population types of Gossypium mixing both intraspecific G. hirsutum and interspecific G. hirsutum × G. barbadense populations. This study used 1,075 QTL from 58 publications on intraspecific G. hirsutum and 1,059 QTL from 30 publications on G. hirsutum × G. barbadense populations to perform a comprehensive comparative analysis of QTL clusters and hotspots between the two populations for yield, fiber and seed quality, and biotic and abiotic stress tolerance. QTL hotspots were further analyzed for mQTL within the hotspots using Biomercator V3 software. The ratio of QTL between the two population types was proportional yet differences in hotspot type and placement were observed between the two population types. However, on some chromosomes QTL clusters and hotspots were similar between the two populations. This shows that there are some universal QTL regions in the cultivated tetraploid cotton which remain consistent and some regions which differ between population types. This study for the first time elucidates the similarities and differences in QTL clusters and hotspots between intraspecific and interspecific populations, providing an important resource to cotton breeding programs in marker-assisted selection .

Re-evaluation of the inheritance for root-knot nematode resistance in the Upland cotton germplasm line M-120 RNR revealed two epistatic QTLs conferring resistance

We report a second major QTL for root-knot nematode resistance in the highly resistant Upland cotton line M-120RNR and show epistasis between two resistant QTLs with different mechanisms conferring resistance. In an earlier study, we identified a major QTL on Chromosome 11 associated with resistance to root-knot nematode in the M-120 RNR Upland cotton line (Gossypium hirsutum L.) of the Auburn 623 RNR source. Herein, we re-evaluated the genetics of the resistance to root-knot nematode in the M-120 RNR × Pima S-6 population by linkage mapping using recently published SSR markers. The QTL analysis detected two regions significantly associated with the resistance phenotype. In addition to the QTL previously identified on Chromosome 11 (qMi-C11), a major QTL was identified on Chromosome 14 (qMi-C14). The resistance locus on qMi-C11 originated from the Clevewilt parent, while the qMi-C14 locus originated from the other resistant parent, Mexico Wild Jack Jones. The qMi-C14 locus had logarithms of odds score of 17 and accounted for 45 % of the total phenotype variation in egg production. It was also associated with galling index, but the percent variation explained was only 6 %, suggesting that the qMi-C11 locus had a much stronger effect on root gall suppression than egg production, while the qMi-C14 locus had a stronger effect on egg production than galling. The results also suggest that the transgressive segregation observed in the development of Auburn 623 RNR was due to the pyramiding of at least two main effect QTLs as well as an additive-by-additive epistatic effects between the two resistant loci. The SSRs markers tightly linked to the qMi-C11 and qMi-C14 loci will greatly facilitate the improvement of RKN resistance in cotton via marker-assisted breeding.

A comprehensive meta QTL analysis for fiber quality, yield, yield related and morphological traits, drought tolerance, and disease resistance in tetraploid cotton

BACKGROUND

The study of quantitative trait loci (QTL) in cotton (Gossypium spp.) is focused on traits of agricultural significance. Previous studies have identified a plethora of QTL attributed to fiber quality, disease and pest resistance, branch number, seed quality and yield and yield related traits, drought tolerance, and morphological traits. However, results among these studies differed due to the use of different genetic populations, markers and marker densities, and testing environments. Since two previous meta-QTL analyses were performed on fiber traits, a number of papers on QTL mapping of fiber quality, yield traits, morphological traits, and disease resistance have been published. To obtain a better insight into the genome-wide distribution of QTL and to identify consistent QTL for marker assisted breeding in cotton, an updated comparative QTL analysis is needed.

RESULTS

In this study, a total of 1,223 QTL from 42 different QTL studies in Gossypium were surveyed and mapped using Biomercator V3 based on the Gossypium consensus map from the Cotton Marker Database. A meta-analysis was first performed using manual inference and confirmed by Biomercator V3 to identify possible QTL clusters and hotspots. QTL clusters are composed of QTL of various traits which are concentrated in a specific region on a chromosome, whereas hotspots are composed of only one trait type. QTL were not evenly distributed along the cotton genome and were concentrated in specific regions on each chromosome. QTL hotspots for fiber quality traits were found in the same regions as the clusters, indicating that clusters may also form hotspots.

CONCLUSIONS

Putative QTL clusters were identified via meta-analysis and will be useful for breeding programs and future studies involving Gossypium QTL. The presence of QTL clusters and hotspots indicates consensus regions across cultivated tetraploid Gossypium species, environments, and populations which contain large numbers of QTL, and in some cases multiple QTL associated with the same trait termed a hotspot. This study combines two previous meta-analysis studies and adds all other currently available QTL studies, making it the most comprehensive meta-analysis study in cotton to date.

QTL analysis for transgressive resistance to root-knot nematode in interspecific cotton (Gossypium spp.) progeny derived from susceptible parents

The southern root-knot nematode (RKN, Meloidogyne incognita) is a major soil-inhabiting plant parasite that causes significant yield losses in cotton (Gossypium spp.). Progeny from crosses between cotton genotypes susceptible to RKN produced segregants in subsequent populations which were highly resistant to this parasite. A recombinant inbred line (RIL) population of 138 lines developed from a cross between Upland cotton TM-1 (G. hirsutum L.) and Pima 3–79 (G. barbadense L.), both susceptible to RKN, was used to identify quantitative trait loci (QTLs) determining responses to RKN in greenhouse infection assays with simple sequence repeat (SSR) markers. Compared to both parents, 53.6% and 52.1% of RILs showed less (P<0.05) root-galling index (GI) and had lower (P<0.05) nematode egg production (eggs per gram root, EGR). Highly resistant lines (transgressive segregants) were identified in this RIL population for GI and/or EGR in two greenhouse experiments. QTLs were identified using the single-marker analysis nonparametric mapping Kruskal-Wallis test. Four major QTLs located on chromosomes 3, 4, 11, and 17 were identified to account for 8.0 to 12.3% of the phenotypic variance (R²) in root-galling. Two major QTLs accounting for 9.7% and 10.6% of EGR variance were identified on chromosomes 14 and 23 (P<0.005), respectively. In addition, 19 putative QTLs (P<0.05) accounted for 4.5–7.7% of phenotypic variance (R²) in GI, and 15 QTLs accounted for 4.2–7.3% of phenotypic variance in EGR. In lines with alleles positive for resistance contributed by both parents in combinations of two to four QTLs, dramatic reductions of >50% in both GI and EGR were observed. The transgressive segregants with epistatic effects derived from susceptible parents indicate that high levels of nematode resistance in cotton may be attained by pyramiding positive alleles using a QTL mapping approach.