Molecular tagging of a major QTL for fiber strength in Upland cotton and its marker-assisted selection

Fiber is a basic raw material in the textile industry. The changes in spinning technology have in common the requirement of unique and often greater cotton fiber quality, especially strength, for processing. We used a Gossypium anomalum introgression line, 7235, characterized by good fiber quality properties, to identify molecular markers linked to fiber-strength QTLs. By the use of F(2) and F(3) populations derived from a cross between 7235 and TM-1, a genetic standard of Upland cotton, nine molecular markers, three SSRs and six RAPDs, were identified to be linked to two QTLs for fiber strength. One was a major QTL, QTL(FS1), detected both in Nanjing and Hainan, China, and the Texas College Station, USA. It was found to be associated with eight markers and explained more than 30% of the phenotypic variation. QTL(FS1) was mapped to chromosome 10. The major QTL in 7235 was identified to be transferred from an Acala 3080 cotton. The marker-assisted selection revealed that DNA markers linked to this QTL could be used in increasing the fiber strength of commercial cultivars.     

The Negative Correlation between Fiber Color and Quality Traits Revealed by QTL Analysis

Naturally existing colored cotton was far from perfection due to having genetic factors for lower yield, poor fiber quality and monotonous color. These factors posed a challenge to colored cotton breeding and innovation. To identify novel quantitative trait loci (QTL) for fiber color along with understanding of correlation between fiber color and quality in colored cotton, a RIL and two F₂ populations were generated from crosses among Zong128 (Brown fiber cotton) and two white fiber cotton lines which were then analyzed in four environments. Two stable and major QTLs (qLC-7-1, qFC-7-1) for fiber lint and fuzz color were detected accounting for 16.01%-59.85% of the phenotypic variation across multiple generations and environments. Meanwhile, some minor QTLs were also identified on chromosomes 5, 14, 21 and 24 providing low phenotypic variation (<5%) from only F2 populations, not from the RILs population. Especially, a multiple-effect locus for fiber color and quality has been detected between flanking markers NAU1043 and NAU3654 on chromosome 7 (A genome) over multiple environments. Of which, qLC-7-1, qFC-7-1 were responsible for positive effects and improved fiber color in offsprings. Meanwhile, the QTLs (qFL-7-1, qFU-7-1, qFF-7-1, qFE-7-1, and qFS-7-1) for fiber quality had negative effects and explained 2.19%-8.78% of the phenotypic variation. This multiple-effect locus for fiber color and quality may reveal the negative correlation between the two types of above traits, so paving the way towards cotton genetic improvement.     

分子标记辅助聚合两个棉纤维高强主效QTLs的选择效果

利用长江流域推广品种泗棉3号和优异纤维种质系7235为育种亲本,配置了系统育种和修饰回交聚合育种两套群体。基于来自7235的2个高强纤维主效QTL的分子标记,在上述育种群体中进行了分子标记辅助选择效率研究。高强纤维主效QTLfs1是利用(7235×TM1)F2分离群体,通过集团混合分离法检测到的,它可解释纤维强度表型变异的30%以上。高强纤维主效QTLfs2最初是利用(HS42710×TM1)F2分离群体检测到的,它可解释纤维强度表型变异的12.5%以上。进一步的研究表明,该QTL也位于7235优质系中,但与QTLfs1非等位。2套育种分离群体的2个高强纤维主效QTL的分子标记辅助选择效果表明:QTLfs1在不同环境条件下均稳定表达,它对不同遗传背景的育种群体均有显著的选择效果。尽管QTLfs2的选择效果低于QTLfs1,它在高世代育种群体中也表现较高的选择效率。利用分子标记辅助选择具有一定遗传距离的QTLfs1区间,其纤维强度的选择效率将大大增强。通过分子标记对位于不同连锁群上的2个QTL聚合选择,其中选单株的纤维强度显著提高。研究结果为利用分子标记辅助聚合优质QTL提供了成功实例。     

Construction of a comprehensive PCR-based marker linkage map and QTL mapping for fiber quality traits in upland cotton (Gossypium hirsutum L.)

To facilitate marker assisted selection, there is an urgent need to construct a saturated genetic map of upland cotton (Gossypium hirsutum L.). Four types of markers including SSR, SRAP, morphological marker, and intron targeted intron–exon splice junction (IT-ISJ) marker were used to construct a linkage map with 270 F_2:7 recombinant inbred lines derived from an upland cotton cross (T586 × Yumian 1). A total of 7,508 SSR, 740 IT-ISJ and 384 SRAP primer pairs/combinations were used to screen for polymorphism between the two mapping parents, and the average polymorphisms of three types of molecular markers represented 6.8, 6.6 and 7.0%, respectively. The polymorphic primer pairs/combinations and morphological markers were used to genotype 270 recombinant inbred lines, and a map including 604 loci (509 SSR, 58 IT-ISJ, 29 SRAP and 8 morphological loci) and 60 linkage groups was constructed. The map spanned 3,140.9 cM with an average interval of 5.2 cM between two markers, approximately accounting for 70.6% of the cotton genome. Fifty-four of 60 linkage groups were ordered into 26 chromosomes. Multiple QTL mapping was used to identify QTL for fiber quality traits in five environments, and thirteen QTL were detected. These QTL included four for fiber length (FL), two for fiber strength (FS), two for fiber fineness (FF), three for fiber length uniformity (FU), and two for fiber elongation (FE), respectively. Each QTL explained between 7.4 and 43.1% of phenotypic variance. Five out of thirteen QTL (FL1 and FU1 on chromosome 6, FL2, FU2 and FF1 on chromosome7) were detected in five environments, and they explained more than 20% of the phenotypic variance. Eleven QTL were distributed on A genome, while the other two on D genome.     

Verification of QTL for Grain Starch Content and Its Genetic Correlation with Oil Content Using Two Connected RIL Populations in High-Oil Maize

Grain oil content is negatively correlated with starch content in maize in general. In this study, 282 and 263 recombinant inbred lines (RIL) developed from two crosses between one high-oil maize inbred and two normal dent maize inbreds were evaluated for grain starch content and its correlation with oil content under four environments. Single-trait QTL for starch content in single-population and joint-population analysis, and multiple-trait QTL for both starch and oil content were detected, and compared with the result obtained in the two related F_2∶3 populations. Totally, 20 single-population QTL for grain starch content were detected. No QTL was simultaneously detected across all ten cases. QTL at bins 5.03 and 9.03 were all detected in both populations and in 4 and 5 cases, respectively. Only 2 of the 16 joint-population QTL had significant effects in both populations. Three single-population QTL and 8 joint-population QTL at bins 1.03, 1.04–1.05, 3.05, 8.04–8.05, 9.03, and 9.05 could be considered as fine-mapped. Common QTL across F_2∶3 and RIL generations were observed at bins 5.04, 8.04 and 8.05 in population 1 (Pop.1), and at bin 5.03 in population 2 (Pop.2). QTL at bins 3.02–3.03, 3.05, 8.04–8.05 and 9.03 should be focused in high-starch maize breeding. In multiple-trait QTL analysis, 17 starch-oil QTL were detected, 10 in Pop.1 and 7 in Pop.2. And 22 single-trait QTL failed to show significance in multiple-trait analysis, 13 QTL for starch content and 9 QTL for oil content. However, QTL at bins 1.03, 6.03–6.04 and 8.03–8.04 might increase grain starch content and/or grain oil content without reduction in another trait. Further research should be conducted to validate the effect of these QTL in the simultaneous improvement of grain starch and oil content in maize.     

QTL mapping for fiber quality traits across multiple generations and environments in upland cotton

Identification of quantitative trait loci (QTL) for fiber quality traits that are stable across multiple generations and environments could facilitate marker-assisted selection for improving cotton strains. In the present study, F₂, F_2:3, and recombinant inbred lines (RILs, F _6:8 ) populations derived from an upland cotton (Gossypium hirsutum L.) cross between strain 0-153, which has excellent fiber quality, and strain sGK9708, a commercial transgenic cultivar, were constructed for QTL tagging of fiber quality. We used 5,742 simple sequence repeat primer pairs to screen for polymorphisms between the two parent strains. Linkage maps of F₂ and RILs were constructed, containing 155 and 190 loci and with a total map distance of 959.4 centimorgans (cM) and 700.9?cM, respectively. We screened fiber quality QTL across multiple generations and environments through composite interval mapping of fiber quality data. Specifically, we studied F₂ and F_2:3 family lines from Anyang (Henan Province) in 2003 and 2004 and RILs in Anyang in 2007 and Anyang, Quzhou (Hebei Province), and Linqing (Shandong Province) in 2008. We identified 50 QTL for fiber quality: 10 for fiber strength, 10 for fiber length, 10 for micronaire, eight for fiber uniformity, and 12 for fiber elongation. Nine of these fiber quality QTL were identified in F₂, F_2:3 and RILs simultaneously. Two QTL for fiber strength on chromosomes C7 and C25 were detected in all three generations and all four environments and explained 16.67?C27.86% and 9.43?C21.36% of the phenotypic variation, respectively. These stable QTL for fiber quality traits could be used for marker assisted selection.     

A new interspecific, <Emphasis Type="Italic">Gossypium hirsutum</Emphasis> × <Emphasis Type="Italic">G. barbadense,</Emphasis> RIL population: towards a unified consensus linkage map of tetraploid cotton

We report the development of a new interspecific cotton recombinant inbred line (RIL) population of 140 lines deriving from an interspecific cross between Gossypium hirsutum (Gh) and G. barbadense (Gb), using the same two parents that have served for the construction of a BC₁ map and for the marker-assisted backcross selection program underway at CIRAD. Two marker systems, microsatellites and AFLPs, were used. An important feature of the RIL population was its marked segregation distortion with a genome-wide bias to Gh alleles (parental genome ratio is 71/29). The RIL map displays an excellent colinearity with the BC₁ map, although it is severely contracted in terms of map size. Existence of 255 loci in common (between 6 and 14 per chromosome) allowed the integration of the two data sets. A consensus BC₁–RIL map based upon 215 individuals (75 BC1 + 140 RIL) was built. It consisted of 1,745 loci, spanned 3,637 cM, intermediate between the sizes of the two component maps, and constituted a solid framework to cross align cotton maps using common markers. The new RIL population will be further exploited for fiber property QTL mapping and eQTL mapping. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Genetic mapping and quantitative trait locus analysis of fiber quality traits using a three-parent composite population in upland cotton (Gossypium hirsutum L.)

Composite cross populations (CP) developed from three or more cultivars/lines are frequently used to improve agronomic and economic traits in crop cultivar development programs. Employing CP in linkage map construction and quantitative trait locus (QTL) mapping may increase the marker density of upland cotton (Gossypium hirsutum L.) genetic maps, exploit more adequate gene resources and facilitate marker-assisted selection (MAS). To construct a relatively high-density map and identify QTL associated with fiber quality traits in upland cotton, three elite upland cultivars/lines, Yumian 1, CRI 35 and 7,235, were used to obtain the segregating population, Yumian 1/CRI 35//Yumian 1/7,235. A genetic map containing 978 simple sequence repeat (SSR) loci and 69 linkage groups was constructed; the map spanned 4,184.4 cM, covering approximately 94.1% of the entire tetraploid cotton genome. A total of 63 QTL were detected, explaining 8.1–55.8% of the total phenotypic variance: 11 QTL for fiber elongation, 16 QTL for fiber length, 9 QTL for fiber micronaire reading, 10 QTL for fiber strength and 17 QTL for fiber length uniformity. The genetic map and QTL detected for fiber quality traits are promising for further breeding programs of upland cotton with improved fiber quality.     

Fine-mapping qFS07.1 controlling fiber strength in upland cotton (<Emphasis Type="Italic">Gossypium hirsutum</Emphasis> L.)

Key message

qFS07.1 controlling fiber strength was fine-mapped to a 62.6-kb region containing four annotated genes. RT-qPCR and sequence of candidate genes identified an LRR RLK gene as the most likely candidate.

Abstract

Fiber strength is an important component of cotton fiber quality and is associated with other properties, such as fiber maturity, fineness, and length. Stable QTL qFS07.1, controlling fiber strength, had been identified on chromosome 7 in an upland cotton recombinant inbred line (RIL) population from a cross (CCRI35?×?Yumian1) described in our previous studies. To fine-map qFS07.1, an F₂ population with 2484 individual plants from a cross between recombinant line RIL014 and CCRI35 was established. A total of 1518 SSR primer pairs, including 1062, designed from chromosome 1 of the Gossypium raimondii genome and 456 from chromosome 1 of the G. arboreum genome (corresponding to the QTL region) were used to fine-map qFS07.1, and qFS07.1 was mapped into a 62.6-kb genome region which contained four annotated genes on chromosome A07 of G. hirsutum. RT-qPCR and comparative analysis of candidate genes revealed a leucine-rich repeat protein kinase (LRR RLK) family protein to be a promising candidate gene for qFS07.1. Fine mapping and identification of the candidate gene for qFS07.1 will play a vital role in marker-assisted selection (MAS) and the study of mechanism of cotton fiber development.

     

Detection and integration of quantitative trait loci for grain yield components and oil content in two connected recombinant inbred line populations of high-oil maize

Improvement in grain yield is an important objective in high-oil maize breeding. In this study, one high-oil maize inbred was crossed with two normal maize inbreds to produce two connected recombinant inbred line (RIL) populations with 282 and 263 F_7:8 families, respectively. The field experiments were conducted under four environments, and eight grain yield components and grain oil content were evaluated. Two genetic linkage maps were constructed using 216 and 208 polymorphic SSR markers. Quantitative trait loci (QTL) were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL in both populations. A total of 199 QTL were detected, 122 in population 1 and 87 in population 2. Seven, 11 and 19 QTL showed consistency across five environments, across two RIL populations and with respective F_2:3 generations, respectively. 183 QTL were integrated in 28 meta-QTL (mQTL). QTL with contributions over 15% were consistently detected in 3–4 cases and integrated in mQTL. Each mQTL included 3–19 QTL related to 1–4 traits, reflecting remarkable QTL co-location for grain yield components and oil content. Further research and marker-assisted selection (MAS) should be concentrated on 37 consistent QTL and four genetic regions of mQTL with more than 10 QTL at bins 3.04–3.05, 7.02, 8.04–8.05 and 9.04–9.05. Near-isogenic lines for 100-grain-weight QTL at bin 7.02–7.03, for ear-length QTL at bin 7.02–7.03 and for rows-per-ear QTL at bin 3.08 are now in construction using MAS. Co-located candidate genes could facilitate the identification of candidate genes for grain yield in maize.     

Mapping Fusarium wilt race 1 resistance genes in cotton by inheritance,QTL and sequencing composition

Knowledge of the inheritance of disease resistance and genomic regions housing resistance (R) genes is essential to prevent expanding pathogen threats such as Fusarium wilt [Fusarium oxysporum f.sp. vasinfectum (FOV) Atk. Sny & Hans] in cotton (Gossypium spp.). We conducted a comprehensive study combining conventional inheritance, genetic and quantitative trait loci (QTL) mapping, QTL marker-sequence composition, and genome sequencing to examine the distribution, structure and organization of disease R genes to race 1 of FOV in the cotton genome. Molecular markers were applied to F₂ and recombinant inbred line (RIL) interspecific mapping populations from the crosses Pima-S7 (G. barbadense L.) × ‘Acala NemX’ (G. hirsutum L.) and Upland TM-1 (G. hirsutum) × Pima 3-79 (G. barbadense), respectively. Three greenhouse tests and one field test were used to obtain sequential estimates of severity index (DSI) of leaves, and vascular stem and root staining (VRS). A single resistance gene model was observed for the F₂ population based on inheritance of phenotypes. However, additional inheritance analyses and QTL mapping indicated gene interactions and inheritance from nine cotton chromosomes, with major QTLs detected on five chromosomes [Fov1-C06, Fov1-C08, (Fov1-C11 ₁ and Fov1-C11 ₂₎ , Fov1-C16 and Fov1-C19 loci], explaining 8–31% of the DSI or VRS variation. The Fov1-C16 QTL locus identified in the F₂ and in the RIL populations had a significant role in conferring FOV race 1 resistance in different cotton backgrounds. Identified molecular markers may have important potential for breeding effective FOV race 1 resistance into elite cultivars by marker-assisted selection. Reconciliation between genetic and physical mapping of gene annotations from marker-DNA and new DNA sequences of BAC clones tagged with the resistance-associated QTLs revealed defenses genes induced upon pathogen infection and gene regions rich in disease-response elements, respectively. These offer candidate gene targets for Fusarium wilt resistance response in cotton and other host plants.     

陆地棉优质纤维渐渗系中外源遗传组分的鉴定与分析

鲁原343是一个渐渗了海岛棉优质纤维基因的陆地棉种质,对其渐渗的优质纤维片段进行鉴定,对利用优质纤维渐渗系改良陆地棉品种的纤维品质具有重要意义。本研究以综合性状优良的转基因抗虫棉鲁棉研22号与鲁原343杂交构建作图群体,利用317对SSR引物对鲁原343和鲁棉研22号进行多态性分析,有24对引物表现多态。利用这些引物进一步和TM-1、优质纤维渐渗片段的供体Ash imoun i作比较,初步鉴定出10个SSR位点与海岛棉渐渗有关。利用这些标记分析(鲁棉研22×鲁原343)F2群体的标记基因型和纤维品质性状的关系,6个标记与纤维品质显著相关,涉及到4条染色体。其中与伸长率相关的标记BNL2986(R2=5.87%)和与长度、细度相关的标记NAU751(R2=6.62%,6.01%)同位于16号染色体的连锁群LG1上,标记间距离为17.7 cM;与纤维成熟度相关的标记BNL3590(R2=8.62%)和与成熟度、伸长率相关的标记BNL3971(R2=15.0%,9.79%)位于2号染色体的连锁群LG3上,标记间距离为4.5 cM;与纤维强度相关的标记BNL3279(R2=8.12%)和与细度相关的标记BNL827(R2=13.94%)分别位于LGD02和25号染色体上。     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.     

Genetic linkage maps of two interspecific grape crosses (Vitis spp.) used to localize quantitative trait loci for downy mildew resistance

Two populations (Pop) segregating quantitatively for resistance to downy mildew (DM), caused by Plasmopara viticola, were used to construct genetic maps and to carry out quantitative trait locus (QTL) analysis. Pop1 comprised of 174 F₁ individuals from a cross of ‘Moscato Bianco’, a susceptible Vitis vinifera cultivar, and a resistant individual of Vitis riparia. Pop2 consisted of 94 progeny from a cross of two interspecific hybrids, ‘VRH3082 1-42’ and ‘SK77 5/3’, with resistance traits inherited from Vitis rotundifolia and Vitis amurensis, respectively. Resistance of progeny was measured in field and greenhouse conditions by visual evaluation of disease symptoms on leaves. Linkage maps of 1037.2 and 651 cM were built essentially with simple sequence repeat markers and were enriched with gene-derived single-strand conformational polymorphism and single-nucleotide polymorphism markers. Simple interval mapping and Kruskall–Wallis analysis detected a stable QTL involved in field resistance to DM on linkage group (LG) 7 of the Pop1 integrated map co-localized with a putative Caffeoyl-CoA O-methyltransferase-derived marker. Additional QTLs were detected on LGs 8, 12 and 17. We were able to identify genetic factors correlated with resistance to P. viticola with lower statistical significance on LGs 1, 6 and 7 of the Pop2 map. Finally, no common QTLs were found between the two crosses analyzed. A search of the grapevine genome sequence revealed either homologues to non-host-, host- or defense-signalling genes within the QTL intervals. These positional candidate genes may provide new information about chromosomal regions hosting phenotypic loci.     

QTL identification of grain protein concentration and its genetic correlation with starch concentration and grain weight using two populations in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

Protein is one of the three main storage chemical components in maize grains, and is negatively correlated with starch concentration (SC). Our objective was to analyse the influence of genetic backgrounds on QTL detection for protein concentration (PC) and to reveal the molecular genetic associations between PC and both SC and grain weight (GWP). Two hundred and eighty-four (Pop1) and 265 (Pop2) F_2:3 families were developed from two crosses between one high-oil maize inbred GY220 and two normal maize inbreds 8984 and 8622 respectively, and were genotyped with 185 and 173 pairs of SSR markers. PC, SC and GWP were evaluated under two environments. Composite interval mapping (CIM) and multiple interval mapping (MIM) methods were used to detect single-trait QTL for PC, and multiple-trait QTL for PC with both SC and GWP. No common QTL were shared between the two populations for their four and one PC QTL. Common QTL with opposite signs of effects for PC and SC/GWP were detected on three marker intervals at bins 6.07–6.08, 8.03 and 8.03–8.04. Multiple-traits QTL mapping showed that tightly-linked QTL, pleiotropic QTL and QTL having effects with opposite directions for PC and SC/GWP were all observed in Pop1, while all QTL reflected opposite effects in Pop2.     

Inheritance of long staple fiber quality traits of Gossypium barbadense in G. hirsutum background using CSILs

Gossypium hirsutum is a high yield cotton species that exhibits only moderate performance in fiber qualities. A promising but challenging approach to improving its phenotypes is interspecific introgression, the transfer of valuable traits or genes from the germplasm of another species such as G. barbadense, an important cultivated extra long staple cotton species. One set of chromosome segment introgression lines (CSILs) was developed, where TM-1, the genetic standard in G. hirsutum, was used as the recipient parent and the long staple cotton G. barbadense Hai7124 was used as the donor parent by molecular marker-assisted selection (MAS) in BC₅S_1–4 and BC₄S_1–3 generations. After four rounds of MAS, the CSIL population was comprised of 174 lines containing 298 introgressed segments, of which 86 (49.4%) lines had single introgressed segments. The total introgressed segment length covered 2,948.7 cM with an average length of 16.7 cM and represented 83.3% of tetraploid cotton genome. The CSILs were highly varied in major fiber qualities. By integrated analysis of data collected in four environments, a total of 43 additive quantitative trait loci (QTL) and six epistatic QTL associated with fiber qualities were detected by QTL IciMapping 3.0 and multi-QTL joint analysis. Six stable QTL were detected in various environments. The CSILs developed and the analyses presented here will enhance the understanding of the genetics of fiber qualities in long staple G. barbadense and facilitate further molecular breeding to improve fiber quality in Upland cotton.     

Dissection and fine mapping of a major QTL for preharvest sprouting resistance in white wheat Rio Blanco

Preharvest sprouting (PHS) is a major constraint to white wheat production. Previously, we mapped quantitative trait loci (QTL) for PHS resistance in white wheat by using a recombinant inbred line (RIL) population derived from the cross Rio Blanco/NW97S186. One QTL, QPhs.pseru-3A, showed a major effect on PHS resistance, and three simple sequence repeat (SSR) markers were mapped in the QTL region. To determine the flanking markers for the QTL and narrow down the QTL to a smaller chromosome region, we developed a new fine mapping population of 1,874 secondary segregating F₂ plants by selfing an F6 RIL (RIL25) that was heterozygous in the three SSR marker loci. Segregation of PHS resistance in the population fitted monogenic inheritance. An additive effect of the QTL played a major role on PHS resistance, but a dominant effect was also observed. Fifty-six recombinants among the three SSR markers were identified in the population and selfed to produce homozygous recombinants or QTL near-isogenic lines (NIL). PHS evaluation of the recombinants delineated the QTL in the region close to Xbarc57 flanked by Xbarc321 and Xbarc12. To saturate the QTL region, 11 amplified fragment length polymorphism (AFLP) markers were mapped in the QTL region with 7 AFLP co-segregated with Xbarc57 by using the NIL population. Dissection of the QTL as a Mendelian factor and saturation of the QTL region with additional markers created a solid foundation for positional cloning of the major QTL.     

QTL mapping for resistance to root-knot nematodes in the M-120 RNR Upland cotton line (Gossypium hirsutum L.) of the Auburn 623 RNR source

Root-knot nematodes Meloidogyne incognita (Kofoid and White) can cause severe yield loss in cotton (Gossypium hirsutum L.). The objectives of this study were to determine the inheritance and genomic location of genes conferring root-knot nematode resistance in M-120 RNR, a highly resistant G. hirsutum line with the Auburn 623 RNR source of resistance. Utilizing two interspecific F₂ populations developed from the same M-120 RNR by Gossypium barbadense (cv. Pima S-6) cross, genome-wide scanning with RFLP markers revealed a marker on Chromosome 7 and two on Chromosome 11 showing significant association with the resistant phenotype. The association was confirmed using SSR markers with the detection of a minor and a major dominant QTL on Chromosome 7 and 11, respectively. Combined across the two populations, the major QTL on Chromosome 11 Mi-C11 had a LOD score of 19.21 (9.69 and 9.61 for Pop1 and Pop2, respectively) and accounted for 63.7% (52.6 and 65.56% for Pop1 and Pop2, respectively) of the total phenotypic variation. The minor QTL locus on Chromosome 7 Mi ₁ -C07 had a LOD score of 3.48 and accounted for 7.7% of the total phenotypic variation in the combined dataset but was detected in only one population. The allele from the M-120 RNR parent contributed to increased resistance in the Mi-C11 locus, but surprisingly, the Pima S-6 allele contributed to increased resistance in the Mi-C07 locus. The M-120 RNR allele in the Mi-C11 locus, derived from the Auburn 623 RNR, is likely to have originated from the Clevewilt 6 cultivar. Results from this study indicated that the SSR marker CIR316 may replace the laborious greenhouse screening in breeding programs to identify genotypes resistant to M. incognita.     

Identification of QTL regions and SSR markers associated with resistance to reniform nematode in <Emphasis Type="Italic">Gossypium barbadense</Emphasis> L. accession GB713

The identification of molecular markers that are closely linked to gene(s) in Gossypium barbadense L. accession GB713 that confer a high level of resistance to reniform nematode (RN), Rotylenchulus reniformis Linford & Oliveira, would be very useful in cotton breeding programs. Our objectives were to determine the inheritance of RN resistance in the accession GB713, to identify SSR markers linked with RN resistance QTLs, and to map these linked markers to specific chromosomes. We grew and scored plants for RN reproduction in the P₁, P₂, F₁, F₂, BC₁P₁, and BC₁P₂ generations from the cross of GB713 × Acala Nem-X. The generation means analysis using the six generations indicated that one or more genes were involved in the RN resistance of GB713. The interspecific F₂ population of 300 plants was genotyped with SSR molecular markers that covered most of the chromosomes of Upland cotton (G. hirsutum L.). Results showed two QTLs on chromosome 21 and one QTL on chromosome 18. One QTL on chromosome 21 was at map position 168.6 (LOD 28.0) flanked by SSR markers, BNL 1551_162 and GH 132_199 at positions 154.2 and 177.3, respectively. A second QTL on chromosome 21 was at map position 182.7 (LOD 24.6) flanked by SSR markers BNL 4011_155 and BNL 3279_106 at positions 180.6 and 184.5, respectively. Our chromosome 21 map had 61 SSR markers covering 219 cM. One QTL with smaller genetic effects was localized to chromosome 18 at map position 39.6 (LOD 4.0) and flanked by SSR markers BNL 1721_178 and BNL 569_131 at positions 27.6 and 42.9, respectively. The two QTLs on chromosome 21 had significant additive and dominance effects, which were about equal for each QTL. The QTL on chromosome 18 showed larger additive than dominance effects. Following the precedent set by the naming of the G. longicalyx Hutchinson & Lee and G. aridum [(Rose & Standley) Skovsted] sources of resistance, we suggest the usage of Ren ^barb1 and Ren ^barb2 to designate these QTLs on chromosome 21 and Ren ^barb3 on chromosome 18.