A transgressive segregation factor (RKN2) in Gossypium barbadense for nematode resistance clusters with gene rkn1 in G. hirsutum

Host plant resistance is an important strategy for managing root-knot nematode (Meloidogyne incognita) in cotton (Gossypium L.). Here we report evidence for enhanced resistance in interspecific crosses resulting from transgressive segregation of clustered gene loci. Recently, a major gene, rkn1, on chromosome 11 for resistance to M. incognita in cv. Acala NemX was identified using an intraspecific G. hirsutum cross with susceptible cv. Acala SJ-2. Using interspecific crosses of Acala NemX × susceptible G. barbadense cv. Pima S-7, F₁, F₂, F_2:3, backcross, and testcross Acala NemX × F₁ (Pima S-7 × SJ-2), parental entries and populations were inoculated in greenhouse tests with M. incognita. Genetic analyses based on nematode-induced root galling and nematode egg production on roots, and molecular marker analysis of the segregating interspecific populations revealed that gene rkn1 interacted with a gene (designated as RKN2) in susceptible Pima S-7 to produce a highly resistant phenotype. RKN2 did not confer resistance in Pima S-7, but when combined with rkn1 (genotype Aa or aa), high levels of resistance were produced in the F₁ and segregating F₂, F₃, and BC₁F₁ populations. One SSR marker MUCS088 was identified tightly linked to RKN2 within 4.4 cM in a NemX × F₁ (Pima S-7 × SJ-2) testcross population. Using mapped SSR markers and interspecific segregating populations, MUCS088 linked to the transgressive gene from the susceptible parent and was located in the vicinity of rkn1 on chromosome 11. Diverse genome analyses among A and D genome diploid and tetraploid cottons revealed that marker MUCS088 (165 and 167 bp) is derived from G. arboreum, A₂ diploid genome. These results demonstrated that a highly susceptible parent contributed to nematode resistance via transgressive segregation. Derived highly resistant lines can be used as improved resistance sources in cotton breeding, and MUCS088 can be used to monitor RKN2 introgression in diverse populations. The close genomic location of the transgressive resistance determinants provides an important model system for studying transgressive segregation and epistasis in plants.     

SSR markers closely associated with genes for resistance to root-knot nematode on chromosomes 11 and 14 of Upland cotton

Molecular markers closely linked to genes that confer a high level of resistance to root-knot nematode (RKN) [Meloidogyne incognita (Kofoid & White) Chitwood] in cotton (Gossypium hirsutum L.) germplasm derived from Auburn 623 RNR would greatly facilitate cotton breeding programs. Our objectives were to identify simple sequence repeat (SSR) markers linked to RKN resistance quantitative trait loci (QTL) and map these markers to specific chromosomes. We developed three recombinant inbred line (RIL) populations by single seed descent from the crosses of RKN-resistant parents M-240 RNR (M240), developed from the Auburn 623 RNR source, moderately resistant Clevewilt 6 (CLW6), one of the parents of Auburn 623 RNR, and susceptible parent Stoneville 213 (ST213). These crosses were CLW6 × ST213, M240 × CLW6, and M240 × ST213. RILs from these populations were grown under greenhouse conditions, inoculated with RKN eggs, scored for root gall index, eggs plant⁻¹, and eggs g⁻¹ root. Plants were also genotyped with SSR markers. Results indicated that a minimum of two major genes were involved in the RKN resistance of M240. One gene was localized to chromosome 11 and linked to the marker CIR 316-201. This CIR 316-201 allele was also present in CLW6 but not in Mexico Wild (MW) (PI593649), both of which are parents of Auburn 623 RNR. A second RKN resistance gene was localized to the short arm of chromosome 14 and was linked to the SSR markers BNL3545-118 and BNL3661-185. These two marker alleles were not present in CLW6 but were present in MW. Our data also suggest that the chromosome 11 resistance QTL primarily affects root galling while the QTL on chromosome 14 mediates reduced RKN egg production. The SSRs identified in this study should be useful to select plants with high levels of RKN resistance in segregating populations derived from Auburn 623 RNR.     

Phenotypic Expression of rkn1-Mediated Meloidogyne incognita Resistance in Gossypium hirsutum Populations

The root-knot nematode Meloidogyne incognita is a damaging pest of cotton (Gossypium hirsutum) worldwide. A major gene (rkn1) conferring resistance to M. incognita was previously identified on linkage group A03 in G. hirsutum cv. Acala NemX. To determine the patterns of segregation and phenotypic expression of rkn1, F₁, F₂, F_2:3, BC₁F₁ and F_2:7 recombinant inbred lines (RIL) from intraspecific crosses between Acala NemX and a closely related susceptible cultivar Acala SJ-2 were inoculated in greenhouse tests with M. incognita race 3. The resistance phenotype was determined by the extent of nematode-induced root galling and nematode egg production on roots. Suppression of root galling and egg production was highly correlated among individuals in all tests. Root galling and egg production on heterozygous plants did not differ from the susceptible parent phenotype 125 d or more after inoculation, but were slightly suppressed with shorter screening (60 d), indicating that rkn1 behaved as a recessive gene or an incompletely recessive gene, depending on the screening condition. In the RIL, rkn1 segregated in an expected 1 resistant: 1 susceptible ratio for a major resistance gene. However, within the resistant class, 21 out of 34 RIL were more resistant than the resistant parent Acala NemX, indicating transgressive segregation. These results suggest that rkn1-based resistance in G. hirsutum can be enhanced in progenies of crosses with susceptible genotypes. Allelism tests and molecular genetic analysis are needed to determine the relationship of rkn1 to other M. incognita resistance sources in cotton.     

Identification of QTLs for arsenic accumulation in maize (Zea mays L.) using a RIL population

The Arsenic (As) concentration in different tissues of maize was analyzed using a set of RIL populations derived from an elite hybrid, Nongda108. The results showed that the trend of As concentration in the four measured tissues was leaves>stems>bracts>kernels. Eleven QTLs for As concentration were detected in the four tissues. Three QTLs for As concentration in leaves were mapped on chromosomes 1, 5, and 8, respectively. For As concentration in the bracts, two QTLs were identified, with 9.61% and 10.03% phenotypic variance. For As concentration in the stems, three QTLs were detected with 8.24%, 14.86%, and 15.23% phenotypic variance. Three QTLs were identified for kernels on chromosomes 3, 5, and 7, respectively, with 10.73%, 8.52%, and 9.10% phenotypic variance. Only one common chromosomal region between SSR marker bnlg1811 and umc1243 was detected for QTLs qLAV1 and qSAC1. The results implied that the As accumulation in different tissues in maize was controlled by different molecular mechanism. The study demonstrated that maize could be a useful plant for phytoremediation of As-contaminated paddy soil, and the QTLs will be useful for selecting inbred lines and hybrids with low As concentration in their kernels.     

Genetic mapping of seed shape in three populations of recombinant inbred lines of soybean (Glycine max L. Merr.)

Round soybean seeds are sought-after for food-type soybean. Also the genetic control of seed geometry is of scientific interest. The objectives of this study were to estimate heritability and map quantitative trait loci (QTLs) responsible for seed shape traits. Three densely mapped recombinant inbred populations each with 192 segregants were used, Minsoy × Archer, Minsoy × Noir1, and Noir1 × Archer. A two rep two location experiment was conducted in Los Andes, Chile, and East Lansing, MI, USA. Seed height (SH), width (SW), length (SL), and seed volume (SV) as width × height × length were measured to determine seed shape. Heritability was estimated by variance component analysis. A total of 19 significant QTLs (LOD ≥ 3.7) in ten linkage groups (LG) were detected for all the traits. Only one QTL was stable across populations and environments and six were stable in at least two populations in both environments. The amount of phenotypic variation explained by a single QTL varied from 7.5% for SH, to 18.5% for SW and at least 30% of the genetic variation for the traits is controlled by four QTL or less. All traits were highly correlated with each other in all populations with values ranging from 0.5 to 0.9, except for SL and SW that were not significantly correlated or had a low correlation in all populations. Narrow sense heritabilities for all traits ranged from 0.42 to 0.88. We note that LG u9, u11, and u14 are hot points of the genome for QTLs for various traits. The number and genomic distribution of the QTLs confirms the complex genetic control of seed shape. Transgressive segregation was observed for all traits suggesting that careful selection of parents with similar phenotypes but different genotypes using molecular markers can result in desirable transgressive segregants.     

Improvement of Rice Biomass Yield through QTL-Based Selection

Biomass yield of rice (Oryza sativa L.) is an important breeding target, yet it is not easy to improve because the trait is complex and phenotyping is laborious. Using progeny derived from a cross between two high-yielding Japanese cultivars, we evaluated whether quantitative trait locus (QTL)-based selection can improve biomass yield. As a measure of biomass yield, we used plant weight (aboveground parts only), which included grain weight and stem and leaf weight. We measured these and related traits in recombinant inbred lines. Phenotypic values for these traits showed a continuous distribution with transgressive segregation, suggesting that selection can affect plant weight in the progeny. Four significant QTLs were mapped for plant weight, three for grain weight, and five for stem and leaf weight (at α = 0.05); some of them overlapped. Multiple regression analysis showed that about 43% of the phenotypic variance of plant weight was significantly explained (P < 0.0001) by six of the QTLs. From F₂ plants derived from the same parental cross as the recombinant inbred lines, we divergently selected lines that carried alleles with positive or negative additive effects at these QTLs, and performed successive selfing. In the resulting F₆ lines and parents, plant weight significantly differed among the genotypes (at α = 0.05). These results demonstrate that QTL-based selection is effective in improving rice biomass yield.     

不同发育时期小麦粒重性状QTL的动态分析

利用6044×01-35构建的重组自交系(RIL)群体为试验材料,对小麦粒重性状进行发育动态QTL分析。结果表明,在小麦花后子粒灌浆的7个不同时期,两个试验点共检测到16个与粒重性状相关的QTL。其中开花后20d检测到的单穗粒重QTL位于2A染色体上,解释率达12%,遗传效应超过10;两环境下控制千粒重QTL在7个时期均被检测到。花后的各个时期均能在Xgwm448-Xgpw7399标记区间定位到千粒重QTL。其中花后10d检测到1个千粒重QTL,位于2A染色体的Xgwm448-Xgpw7399标记区间,解释较大的表型变异,达到18%。Qtl8、Qtl13和Qtl14均定位在Xgwm448-Xgpw7399标记区间的同一位置,共同解释11%的表型变异。花后20d和花后25d均检测到1个QTL,位于2A染色体的Xgwm372-Xgwm95标记区间的不同位点,均能解释4%的表型变异。花后40d检测到1个QTL,位于1D染色体的Xwmc93-Xgpw2224标记区间,解释1%的表型变异。从连锁群的位置上看,控制千粒重的QTL主要集中在2A染色体的Xgwm448-Xgpw7399标记区间,这是一个控制千粒重QTL的富集区域,以期进行精细定位和图位克隆。     

Mapping of quantitative trait loci for salt tolerance at the seedling stage in rice

Salt tolerance was evaluated at the young seedling stage of rice (Oryza sativa L.) using recombinant inbred lines (MG RILs) from a cross between Milyang 23 (japonica/indica) and Gihobyeo (japonica). 22 of 164 MG RILs were classified as tolerant with visual scores of 3.5-5.0 in 0.7% NaCl. Interval mapping of QTLs related to salt tolerance was conducted on the basis of the visual scores at the young seedling stage. Two QTLs, qST1 and qST3, conferring salt tolerance, were detected on chromosome 1 and 3, respectively, and the total phenotypic variance explained by the two QTLs was 36.9% in the MG RIL population. qST1 was the major QTL explaining 27.8% of the total phenotypic variation. qST1 was flanked by Est12-RZ569A, and qST3 was flanked by RG179-RZ596. The detection of new QTLs associated with salt tolerance will provide important information for the functional analysis of rice salt tolerance.     

Mapping and quantitative trait loci analysis of verticillium wilt resistance genes in cotton

Verticillium wilt is one of the most serious constraints to cotton production in almost all of the cotton-growing countries. In this study, ＂XinLuZaol＂ （XLZl）, a susceptible cultivar Gossypium hirsutum L. and ＂Hai7124＂ （H7124）, a resistant line G. barbadense, and their F2：3 families were used to map and study the disease index induced by verticillium wilt. A total of 430 SSR loci were mapped into 41 linkage groups; the map spanned 3 745.9 cM and the average distance between adjacent loci was 8.71 cM. Four and five quantitative trait loci （QTLs） were detected based on the disease index investigated on July 22 and August 24 in 2004, respectively. These nine QTLs explained 10.63-28.83% of the phenotypic variance, six of them were located on the D sub-genome. Two QTLs located in the same marker intervals may partly explain the significant correlation of the two traits. QTLs explaining large phenotypic variation were identified in this study, which may be quite useful in cotton anti-disease breeding.     

A QTL analysis of sunflower partial resistance to downy mildew ( Plasmopara halstedii) and black stem ( Phoma macdonaldii) by the use of recombinant inbred lines (RILs)

Partial resistance to downy mildew (Plasmopara halstedii) and to black stem (Phoma macdonaldii) in sunflower were investigated under natural field infection and a controlled growth chamber respectively. Genetic control for resistance to the diseases was determined in recombinant inbred lines (RILs) and their two parents, ’PAC-2’ and ’RHA-266.’ The experiments were undertaken in a randomized complete block design with two replications, in a field severely infected by downy mildew and in a controlled growth chamber with plants inoculated with an agressive French isolate of P. macdonaldii. Each replication consisted of three rows, 4.6-m long, giving 48 plants per RIL or parent in the field and 15 plants in the growth chamber. Genetic variability was observed among the RILs for resistance to both diseases. When 10% of the selected RILs were compared with the mean of the two parents genetic gain was significant for partial resistance to the diseases. Four putative QTLs for resistance to downy mildew on linkage groups 1, 9 and 17 were detected using composite interval mapping. The QTLs explained 54.9% of the total phenotypic variance. Major QTLs (dmr1–1 and dmr1–2) for resistance were found on linkage group 1 with up to 31% of the phenotypic variability explained by two peaks. QTL analysis of resistance to black stem showed seven QTLs on linkage groups 3, 6, 8, 9, 11, 15 and 17. The detected QTLs together explain 92% of the phenotypic variation of the trait. Crosses between RILs contrasted for their resistance to downy mildew and black stem, and exhibiting molecular polymorphism in detected QTLs, will be made in order to focus more-precisely on the genomic region of interest. Received: 28 February 2001 / Accepted: 14 June 2001     

Identification and introgression of QTLs implicated in resistance to sorghum downy mildew (Peronosclerospora sorghi (Weston and Uppal) C. G. Shaw) in maize through marker-assisted selection

Sorghum downy mildew caused by Peronosclerospora sorghi is a major disease of maize and resistance is under the control of polygenes which necessitated identification of quantitative-trait loci (QTLs) for initiating marker-assisted introgression of resistant QTLs in elite susceptible inbred lines. In the present study, QTLs for sorghum downy mildew (SDM) resistance in maize were identified based on cosegregation with linked simple sequence repeats in 185 F₂ progeny from a cross between susceptible (CM500-19) and resistant (MAI105) parents. F₃ families were screened in the National Sorghum Downy Mildew Screening Nursery during 2010 and 2011. High heritability was observed for the disease reaction. The final map generated using 87 SSR markers had 10 linkage groups, spanning a length of 1210.3 cM. Although, we used only 87 SSR markers for mapping, the per cent of genome within 20 cM to the nearest marker was 88.5. Three putative QTLs for SDM resistance were located on chromosomes 3 (bin 3.01), 6 (bin 6.01) and 2 (bin 2.02) using composite interval mapping. The locus on chromosome 3 had a major effect and explained up to 12.6% of the phenotypic variation. The other two QTLs on chromosomes 6 and 2 had minor effects with phenotypic variation of 7.1 and 2%. The three QTLs appeared to have additive effects on resistance. The QTLs on chromosomes 3 and 6 were successfully used in the marker-assisted selection programme for introgression of resistance to SDM in eight susceptible maize lines.     

Quantitative trait loci analysis of fiber quality traits using a random-mated recombinant inbred population in Upland cotton (Gossypium hirsutum L.)

Background

Upland cotton (Gossypium hirsutum L.) accounts for about 95% of world cotton production. Improving Upland cotton cultivars has been the focus of world-wide cotton breeding programs. Negative correlation between yield and fiber quality is an obstacle for cotton improvement. Random-mating provides a potential methodology to break this correlation. The suite of fiber quality traits that affect the yarn quality includes the length, strength, maturity, fineness, elongation, uniformity and color. Identification of stable fiber quantitative trait loci (QTL) in Upland cotton is essential in order to improve cotton cultivars with superior quality using marker-assisted selection (MAS) strategy.

Results

Using 11 diverse Upland cotton cultivars as parents, a random-mated recombinant inbred (RI) population consisting of 550 RI lines was developed after 6 cycles of random-mating and 6 generations of self-pollination. The 550 RILs were planted in triplicates for two years in Mississippi State, MS, USA to obtain fiber quality data. After screening 15538 simple sequence repeat (SSR) markers, 2132 were polymorphic among the 11 parents. One thousand five hundred eighty-two markers covering 83% of cotton genome were used to genotype 275 RILs (Set 1). The marker-trait associations were analyzed using the software program TASSEL. At p < 0.01, 131 fiber QTLs and 37 QTL clusters were identified. These QTLs were responsible for the combined phenotypic variance ranging from 62.3% for short fiber content to 82.8% for elongation. The other 275 RILs (Set 2) were analyzed using a subset of 270 SSR markers, and the QTLs were confirmed. Two major QTL clusters were observed on chromosomes 7 and 16. Comparison of these 131 QTLs with the previously published QTLs indicated that 77 were identified before, and 54 appeared novel.

Conclusions

The 11 parents used in this study represent a diverse genetic pool of the US cultivated cotton, and 10 of them were elite commercial cultivars. The fiber QTLs, especially QTL clusters reported herein can be readily implemented in a cotton breeding program to improve fiber quality via MAS strategy. The consensus QTL regions warrant further investigation to better understand the genetics and molecular mechanisms underlying fiber development.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-397) contains supplementary material, which is available to authorized users.     

水稻对叶瘟和穗瘟部分抗性的遗传分析

在一个水稻籼籼交重组自交系群体中,选用由感病株系构成的2个亚群体和2个不同的稻瘟病菌小种,进行了水稻对叶瘟部分抗性的QTL定位,还选用由感病而且抽穗期相近的株系构成的亚群体和另一个病菌小种,进行了水稻对穗瘟部分抗性的QTL定位,将病叶面积百分比(DLA)、病斑大小(LS)和病斑数(LN)作为对叶瘟部分抗性的性状,将病斑长度(LL)和孢子量(CA)作为对穗瘟部分抗性的性状。所构建的图谱包含168个标记。应用QTLMapper 1．01b,共检测到11个表现主效应的QTL和28对双因子互作,有3个表现主效应的QTL参与对同一性状的互作。QTL的主效应对单一性状的贡献率为4．7％～38．8％,而上位性效应对单一性状的贡献率为16．0％～51．7％,QTL的主效应对大多数性状的贡献率小于互作效应,表明互作效应对于部分抗性的重要作用。对穗瘟部分抗性的两个性状LL和CA,所检测到QTL总效应的贡献率分别达到70．6％和82．6％,表明由排除了主效抗病基因的感病株系组成的亚群体适合于进行部分抗性QTL定位。     

QTL mapping of seed-quality traits in sunflower recombinant inbred lines under different water regimes.

The objectives of the present research were to determine the effects of water stress on seed-quality traits and to map QTLs controlling the studied traits under two different water treatments in a population of sunflower recombinant inbred lines (RILs). Two experiments were conducted in greenhouse and field conditions, each with well-watered and water-stressed treatments. The experiments consisted of a split-plot design (water treatment and RIL) with three blocks. Analyses of variance showed significant variation among genotypes, and a water treatment x genotype interaction was also observed for most of the traits. Two to 15 QTLs were found, depending on trait and growth conditions, and the percentage of phenotypic variance explained by the QTLs ranged from 5% to 31%. Several QTLs for oil content overlapped with QTLs for palmitic and stearic acid contents in all four conditions. An overlapping region on linkage group 3 (QTLs 2.OC.3.1 and 4.SA.3.1) was linked to an SSR marker (ORS657). A principal component analysis was performed on four fatty acid traits. Two principal components, P1 and P2, were used for QTL analysis. This method improved the ability to identify chromosomal regions affecting the fatty acids. We also detected the principal-component QTLs that did not overlap with the fatty acid QTLs. The results highlight genomic regions of interest in marker-based breeding programmes for increasing oil content in sunflower.     

Identification of QTLs with Additive,Epistatic, and QTL × Seed Maturity Interaction Effects for Seed Vigor in Rice

Seed maturity is a critical process of seed vigor establishment. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential (GP), germination rate (GR), germination index (GI), and time for 50 % of germination (T₅₀), at 4, 5, and 6 weeks after heading in 2 years. Significant differences of seed vigor were observed among two parents and RIL population; the heritability of four traits was more than 90 % at three maturity stages. A total of 19 additive and 2 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program, respectively, in 2012, while 16 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The phenotypic variation explained by each additive, epistatic QTL, and QTL × seed maturity interaction ranged from 9.19 to 22.94 %, 7.23 to 7.75 %, and 0.05 to 0.63 %, respectively. Ten additive QTLs were stably expressed in 2 years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of ten stably expressed additive QTLs with those previously identified, they might be true QTLs for seed vigor; the regions of QTLs for seed vigor are likely to coincide with QTLs for seed dormancy, seed reserve mobilization, low-temperature germinability, and seedling growth. Using four selected RILs, three cross-combinations were predicted to improve seed vigor; 9 to 10 elite alleles could be pyramided by each combination. The selected RILs and the identified QTLs might be applicable for the improvement of seed vigor by marker-assisted selection (MAS) in rice.     

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.     

Both epistatic and additive effects of QTLs are involved in polygenic induced resistance to disease: a case study,the interaction pepper — Phytophthora capsici Leonian

To study the resistance of pepper to Phytophthora capsici, we analyzed 94 doubled-haploid (DH) lines derived from the intraspecific F₁ hybrid obtained from a cross between Perennial, an Indian pungent resistant line, and Yolo Wonder, an American bell-pepper susceptible line, with 119 DNA markers. Four different criteria were used to evaluate the resistance, corresponding to different steps or mechanisms of the host-pathogen interaction: root-rot index, receptivity, inducibility and stability. Three distinct ANOVA models between DNA marker genotypes and the four disease criteria identified 13 genomic regions, distributed across several linkage groups or unlinked markers, affecting the resistance of pepper to P. capsici. Some QTLs were criterion specific, whereas others affect several criteria, so that the four resistance criteria were controlled by different combinations of QTLs. The QTLs were very different in their quantitative effect (R² values), including major QTLs which explained 41–55% of the phenotypic variance, intermediate QTLs with additive or/and epistatic action (17–28% of the variance explained) and minor QTLs. Favourable alleles of some minor QTLs were carried in the susceptible parent. The total phenotypic variation accounted for by QTLs reached up to 90% for receptivity, with an important part due to epistasis effects between QTLs (with or without additive effects). The relative impact of resistance QTLs in disease response is discussed.     

Small RNA and degradome deep sequencing reveals important roles of microRNAs in cotton (Gossypium hirsutum L.) response to root-knot nematode Meloidogyne incognita infection

Investigation of cotton response to nematode infection will allow us to better understand the cotton immune defense mechanism and design a better biotechnological approach for efficiently managing pest nematodes in cotton. In this study, we firstly treated cotton by root knot nematode (RKN, Meloidogyne incognita) infections, then we employed the high throughput deep sequencing technology to sequence and genome-widely identify all miRNAs in cotton; finally, we analyzed the functions of these miRNAs in cotton response to RKN infections. A total of 266 miRNAs, including 193 known and 73 novel miRNAs, were identified by deep sequencing technology, which belong to 67 conserved and 66 novel miRNA families, respectively. A majority of identified miRNA families only contain one miRNA; however, miR482 family contains 14 members and some others contain 2–13 members. Certain miRNAs were specifically expressed in RKN-infected cotton roots and others were completely inhibited by RKN infection. A total of 50 miRNAs were differentially expressed after RKN infection, in which 28 miRNAs were up-regulated and 22 were inhibited by RKN treatment. Based on degradome sequencing, 87 gene targets were identified to be targeted by 57 miRNAs. These miRNA-targeted genes are involved in the interaction of cotton plants and nematode infection. Based on GO (gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis, 466 genes from all 636 miRNA targets were mapped to 6340 GO terms, 181 genes from 228 targets of differentially expressed miRNAs were mapped to 1588 GO terms. The GO terms were then categorized into the three main GO classes: biological processes, cellular components, and molecular functions. The targets of differentially expressed miRNAs were enriched in 43 GO terms, including 22 biological processes, 10 cellular components, and 11 molecular functions (p < 0.05). Many identified processes were associated with organism responses to the environmental stresses, including regulation of nematode larval development, response to nematode, and response to flooding. Our results will enhance the study and application of developing new cotton cultivars for nematode resistance.     

Divergent expression of cytokinin biosynthesis,signaling and catabolism genes underlying differences in feeding sites induced by cyst and root‐knot nematodes

Cyst and root‐knot nematodes are obligate parasites of economic importance with a remarkable ability to reprogram root cells into unique metabolically active feeding sites. Previous studies have suggested a role for cytokinin in feeding site formation induced by these two types of nematodes, but the mechanistic details have not yet been described. Using Arabidopsis as a host plant species, we conducted a comparative analysis of cytokinin genes in response to the beet cyst nematode (BCN), Heterodera schachtii, and the root‐knot nematode (RKN), Meloidogyne incognita. We identified distinct differences in the expression of cytokinin biosynthesis, catabolism and signaling genes in response to infection by BCN and RKN, suggesting differential manipulation of the cytokinin pathway by these two nematode species. Furthermore, we evaluated Arabidopsis histidine kinase receptor mutant lines ahk2/3, ahk2/4 and ahk3/4 in response to RKN infection. Similar to our previous studies with BCN, these lines were significantly less susceptible to RKN without compromising nematode penetration, suggesting a requirement of cytokinin signaling in RKN feeding site formation. Moreover, an analysis of ahk double mutants using CycB1;1:GUS/ahk introgressed lines revealed contrasting differences in the cytokinin receptors mediating cell cycle activation in feeding sites induced by BCN and RKN.