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1.
The objective of this investigation was to map QTL controlling oil, protein, and starch concentrations in maize grain and to evaluate their genetic effects. The mapping population included 298 F2:3 family lines containing Beijing high-oil (BHO) maize germplasm. F2 individuals were genotyped with 183 SSR markers to construct a genetic linkage map, which spanned 1,605.7 cM, with an average interval of 8.77 cM. Oil, protein, and starch concentrations in grain among F2:3 families were measured by near-infrared (NIR) analyzer. Using QTL Cartographer, we mapped six QTL associated with oil in grain, six associated with protein, and five associated with starch concentrations. The proportion of phenotypic variation explained by single QTL ranged from 4.34 to 13.13% for oil, from 5.19 to 6.66% for protein, and from 4.14 to 7.85% for starch concentrations. QTL for oil, protein, or starch concentrations were often detected in identical intervals and the direction of their effects were consistent with the sign of their phenotypic correlation. They were considered as common QTL for chemical compositions in maize grain. In this study, we identified three QTL for oil in grain, two QTL for protein, and three QTL for starch concentrations, which were on identical or similar chromosomal locations to those previously mapped with Illinois high-oil (IHO) maize germplasm. These suggests that more diverse germplasm should be necessary to detect additional QTL and to discover more favorable alleles for chemical composition of maize grain.  相似文献   

2.
In maize, high grain moisture (GM) at harvest causes problems in harvesting, threshing, artificial drying, storage, transportation and processing. Understanding the genetic basis of GM will be useful for breeding low‐GM varieties. A quantitative genetics approach was used to identify quantitative trait loci (QTL) related to GM at harvest in field‐grown maize. The GM of a double haploid population consisting of 240 lines derived from Xianyu335 was evaluated in three planting seasons and a high‐density genetic linkage map covering 1546.4 cM was constructed. The broad‐sense heritability of GM at harvest was 71.0%. Using composite interval mapping, six QTL for GM at harvest were identified on five chromosomes (Chr). Two QTL located on Chr1, qgm1‐1 and qgm1‐2, explained 5.0% and 10.8% of the phenotypic variation in GM at harvest, respectively. The QTL qgm2, qgm3, qgm4 and qgm5 accounted for 3.3%, 8.3%, 5.4% and 11.0% of the mean phenotypic variation, respectively. Because of their consistent detection over multiple planting seasons, the detected QTL appear to be robust and reliable for the breeding of low‐GM varieties.  相似文献   

3.
Cellulose is one of the main chemical component of bast fibre in jute. However, quantitative trait loci (QTL) for bast fibre cellulose content remains elusive. In this study, we identified 846 new SSR markers from 70,792 unigenes in the NCBI and validated them in a panel of 24 diverse jute accessions. Of 846 SSRs, 748 (88.41%) were successfully amplified, and 585 (69.14%) showed polymorphisms, implying that these are high‐quality SSRs. Furthermore, 585 SSRs along with 5,074 polymorphic SLAF (specific locus amplified fragment) and 173 InDel markers were used to reconstruct a high‐dense linkage map in a recombinant inbred population with 104 F8 lines. Totally, 835 markers were successfully mapped to a whole length of 604.5 cM with a mean distance of 2.84 cM between adjacent markers. Furthermore, five QTLs for bast fibre cellulose were identified. One major QTL (qBFC1‐1) was stable in 2 years and explained average phenotypic variance with 14.34%. These results may be useful for developing enhanced bast fibre quality in white jute through marker‐assisted selection (MAS) breeding.  相似文献   

4.
Botrytis grey mould (BGM) caused by Botrytis cinerea Pers. ex. Fr. is the second most important foliar disease of chickpea (Cicer arietinum L.) after ascochyta blight. An intraspecific linkage map of chickpea consisting of 144 markers assigned on 11 linkage groups was constructed from recombinant inbred lines (RILs) of a cross that involved a moderately resistant kabuli cultivar ICCV 2 and a highly susceptible desi cultivar JG 62. The length of the map obtained was 442.8 cM with an average interval length of 3.3 cM. Three quantitative trait loci (QTL) which together accounted for 43.6% of the variation for BGM resistance were identified and mapped on two linkage groups. QTL1 explained about 12.8% of the phenotypic variation for BGM resistance and was mapped on LG 6A. It was found tightly linked to markers SA14 and TS71rts36r at a LOD score of 3.7. QTL2 and QTL3 accounted for 9.5 and 48% of the phenotypic variation for BGM resistance, respectively, and were mapped on LG 3. QTL 2 was identified at LOD 2.7 and flanked by markers TA25 and TA144, positioned at 1 cM away from marker TA25. QTL3 was a strong QTL detected at LOD 17.7 and was flanked by TA159 at 12 cM distance on one side and TA118 at 4 cM distance on the other side. This is the first report on mapping of QTL for BGM resistance in chickpea. After proper validation, these QTL will be useful in marker-assisted pyramiding of BGM resistance in chickpea.  相似文献   

5.
A genetic map was constructed with 353 sequence-related amplified polymorphism and 34 simple sequence repeat markers in oilseed rape (Brassica napus L.). The map consists of 19 linkage groups and covers 1,868 cM of the rapeseed genome. A recombinant doubled haploid (DH) population consisting of 150 lines segregating for oil content and other agronomic traits was produced using standard microspore culture techniques. The DH lines were phenotyped for days to flowering, oil content in the seed, and seed yield at three locations for 3 years, generating nine environments. Data from each of the environments were analyzed separately to detect quantitative trait loci (QTL) for these three phenotypic traits. For oil content, 27 QTL were identified on 14 linkage groups; individual QTL for oil content explained 4.20–30.20% of the total phenotypic variance. For seed yield, 18 QTL on 11 linkage groups were identified, and the phenotypic variance for seed yield, as explained by a single locus, ranged from 4.61 to 24.44%. Twenty-two QTL were also detected for days to flowering, and individual loci explained 4.41–48.28% of the total phenotypic variance.  相似文献   

6.
A partial resistance to maize mosaic virus (MMV) and maize stripe virus (MStV) was mapped in a RILs population derived from a cross between lines MP705 (resistant) and B73 (susceptible). A genetic map constructed from 131 SSR markers spanned 1399 cM with an average distance of 9.6 cM. A total of 10 QTL were detected for resistance to MMV and MStV, using composite interval mapping. A major QTL explaining 34–41% of the phenotypic variance for early resistance to MMV was detected on chromosome 1. Another major QTL explaining up to 30% of the phenotypic variation for all traits of resistance to MStV was detected in the centromeric region of chromosome 3 (3.05 bin). After adding supplementary SSR markers, this region was found to correspond well to the one where a QTL of resistance to MStV already was located in a previous mapping study using an F2 population derived from a cross between Rev81 and B73. These results suggested that these QTL of resistance to MStV detected on chromosome 3 could be allelic in maize genome.  相似文献   

7.
Improving maize starch content is of great importance for both forage and grain yield. In this study, 13 starch degradability traits were analysed including percentage of the seedling area, floury endosperm, hard endosperm of total grain area, percentage of the floury endosperm surface and vitreousness ratio surface hard: floury endosperm surface, etc. We mapped quantitative trait loci (QTL) in a biparental population of 309 doubled haploid lines based on field phenotyping at two locations. A genetic linkage map was constructed using 168 SSR (simple sequence repeat) markers, which covered 1508 cM of the maize genome, with an average distance of 9.0 cM. Close phenotypic and genotypic correlations were found for all traits, and were all statistically significant (p = 0.01) at two locations. Major QTL for more than two traits were detected, especially in two regions in bins 4.05–4.06 and 7.04–7.05, associated with 13 and 9 traits, respectively. This study contributes to marker‐assisted breeding and also to fine mapping candidate genes associated with maize starch degradability.  相似文献   

8.
玉米产量性状“一致性QTL”分析   总被引：3，自引：0，他引：3  
在构建含221个玉米产量性状QTL整合图谱的基础上,采用元分析方法,当LOD值≥4.0时,在第2染色体上确定了1个控制粒重和穗数的“一致性QTL”,介于标记Sdg107和Isu2117b之间,间距30.99 cM;同样,在第3和第4染色体上发掘了2个控制穗数和粒重的“一致性QTL”,分别由标记ucsd72d和IDP37...  相似文献   

9.
Despite the well-recognized importance of grain yield in high-oil maize (Zea mays L.) breeding and production, few studies have reported the application of QTL mapping of such traits. An inbred line of high-oil maize designated ‘GY220’ was crossed with two dent maize inbred lines to generate two connected F2:3 populations with 284 and 265 F2:3 families. Our main objective was to evaluate the influence of genetic background on QTL detection of grain yield traits through comparisons between the F2:3 populations. The field experiments were conducted during the spring in Luoyang and summer in Xuchang, Henan, China. Two genetic linkage maps were constructed with a genetic distance of 2111.7 and 2298.5 cM using 185 and 173 polymorphic SSR markers, respectively. In total, 18 and 15 QTL were detected for six grain yield traits in the two populations. Only one common QTL marker was shared between the two populations. A QTL cluster associated with five traits was identified at bin 1.05–1.06, including the shared QTL for 100GW, which demonstrated the largest effect (16.7%). Among the detected QTL, 12 digenic interactions were identified. Our results reflect the substantial influence of dent maize genetic background on QTL detection of grain yield traits.  相似文献   

10.
Association analysis studies can be used to test for associations between molecular markers and quantitative trait loci (QTL). In this study, a genome-wide scan was performed using 150 simple sequence repeat (SSR) markers to identify QTL associated with seed protein content in soybean. The initial mapping population consisted of two subpopulations of 48 germplasm accessions each, with high or low protein levels based on data from the USDA’s Germplasm Resources Information Network website. Intrachromosomal LD extended up to 50 cM with r 2 > 0.1 and 10 cM with r 2 > 0.2 across the accessions. An association map consisting of 150 markers was constructed on the basis of differences in allele frequency distributions between the two subpopulations. Eleven putative QTL were identified on the basis of highly significant markers. Nine of these are in regions where protein QTL have been mapped, but the genomic regions containing Satt431 on LG J and Satt551 on LG M have not been reported in previous linkage mapping studies. Furthermore, these new putative protein QTL do not map near any QTL known to affect maturity. Since biased population structure was known to exist in the original association analysis population, association analyses were also conducted on two similar but independent confirmation populations. Satt431 and Satt551 were also significant in those analyses. These results suggest that our association analysis approach could be a useful alternative to linkage mapping for the identification of unreported regions of the soybean genome containing putative QTL.  相似文献   

11.
H. J. Zheng    A. Z. Wu    C. C. Zheng    Y. F. Wang    R. Cai    X. F. Shen    R. R. Xu    P. Liu    L. J. Kong    S. T. Dong 《Plant Breeding》2009,128(1):54-62
A maize genetic linkage map derived from 115 simple sequence repeat (SSR) markers was constructed from an F2 population. The F2 was generated from a cross between a stay-green inbred line (Q319) and a normal inbred line (Mo17). The map resolved 10 linkage groups and spanned 1431.0 cM in length with an average genetic distance of 12.44 cM between two neighbouring loci. A total of 14 quantitative trait loci (QTL) were detected for stay-green traits at different postflowering time intervals and identified by composite interval mapping. The respective QTL contribution to phenotypic variance ranged from 5.40% to 11.49%, with trait synergistic action from Q319. Moreover, maize stay-green traits were closely correlated to grain yield. Additional QTL analyses indicated that multiple intervals of stay-green QTL overlapped with yield QTL.  相似文献   

12.
Sugarcane mosaic virus (SCMV) is one of devastating pathogens in maize (Zea mays L.), and causes serious yield loss in susceptible cultivars. An effective solution to control the virus is utilizing resistant genes to improve the resistance of susceptible materials, whereas the basic work is to analyze the genetic basis of resistance. In this study, maize inbred lines Huangzao4 (resistant) and Mo17 (susceptible) were used to establish an F9 immortal recombinant inbred line (RIL) population containing 239 RILs. Based on this segregation population, a genetic map was constructed with 100 simple sequence repeat (SSR) markers selected from 370 markers, and it covers 1421.5 cM of genetic distance on ten chromosomes, with an average interval length of 14.2 cM. Analysis of the genetic map and resistance by mapping software indicated that a major quantitative trait locus (QTL) was between bin6.00 and bin6.01 on chromosome 6, linked with marker Bnlg1600 (0.1 cM of interval). This QTL could account for 50.0% of phenotypic variation, and could decrease 27.9% of disease index.  相似文献   

13.
Quantitative trait loci (QTL) analysis was conducted to identify QTL for seed yield and color retention following processing of a recombinant inbred line (RIL) black bean population. A population of 96 RILs were derived from the cross of black bean cultivars ‘Jaguar’ and 115M and evaluated in replicated trials at one location over 4 years (2004–2007) in Michigan. A 119-point genetic map constructed using simple sequence repeat (SSR), sequence related amplified polymorphism (SRAP), target region amplified polymorphism (TRAP) and phenotypic markers spanned fifteen linkage groups (LG) or 460 cM of the bean genome. Fourteen QTL for yield and color retention in four environments were identified by composite interval mapping on six linkage groups. A major QTL SY10.2J115 for seed yield was identified on LG B10 with additional QTL on B3, B5, and B11. Color retention following processing was associated with loci on B1, B3, B5, B8, and B11. 115M possessed positive alleles for yield, but negative alleles for color retention. Some QTL for yield and color retention co-localized with regions identified in previous studies while others, particularly for color retention, were unique. Additional QTL for agronomic and canning quality traits were detected and individual contributions to future black bean breeding are discussed.  相似文献   

14.
Pod dehiscence (PD) prior to harvest results in serious yield loss in soybean. Two linkage maps with simple sequence repeat (SSR) markers were independently constructed using recombinant inbred lines (RILs) developed from Keunolkong (pod-dehiscent) × Sinpaldalkong (pod-indehiscent) and Keunolkong × Iksan 10 (pod-indehiscent). These soybean RIL populations were used to identify quantitative trait loci (QTLs) conditioning resistance to PD. While a single major QTL on linkage group (LG) J explained 46% of phenotypic variation in PD in the Keunolkong × Sinpaldalkong population with four minor QTLs, three minor QTLs were identified in the Keunolkong × Iksan 10 population. Although these two populations share the pod dehiscent parent, no common QTL has been identified. In addition, epistatic interactions among three marker loci partially explained phenotypic variation in PD in both populations. The result of this study indicates that different breeding strategies will be required for PD depending on genetic background.  相似文献   

15.
Grain size is a main component of rice appearance quality. In this study, we performed the SSR mapping of quantitative trait loci (QTLs) controlling grain size (grain length and breadth) and shape (length/breadth ratio) using an F2 population of a cross between two Iranian cultivars, Domsephid and Gerdeh, comprising of 192 individuals. A linkage map with 88 markers was constructed, which covered 1367.9 cM of the rice genome with an average distance of 18 cM between markers. Interval mapping procedure was used to identify the QTLs controlling three grain traits, and QTLs detected were further confirmed using composite interval mapping. A total of 11 intervals carrying 18 QTLs for three traits were identifed, that included five QTLs for grain length, seven QTLs for grain breadth, and six QTLs for grain shape. A major QTL for grain length was detected on chromosome 3, that explained 19.3% of the phenotypic variation. Two major QTLs for grain breadth were mapped on chromosomes 3 and 8, which explained 34.1% and 20% of the phenotypic variation, respectively. Another two major QTLs were identified for grain shape on chromosomes 3 and 8, which accounted for 27.1% and 20.5% of the phenotypic variance, respectively. The two QTLs that were mapped for grain shape coincided with the major QTLs detected for grain length and grain breadth. Intrestingly, gs2 QTL specific to grain shape was detected on chromosome 2 that explained 15% of the phenotypic variation.  相似文献   

16.
Seed protein content at the harvest stage is the sum of protein accumulation during seed filling. The aim of our investigation was to identify loci underlying the filling rate of seed protein at different developmental stages. To this end, we used 143 recombinant inbred lines (RILs) derived from the cross of soybean cultivars ‘Charleston’ and ‘Dongnong 594’ and composite interval mapping with a mixed genetic model. The genotype × environment interactions of the quantitative trait loci (QTL) were also evaluated. Thirty-nine unconditional QTL underlying the filling rate of seed protein at five developmental stages were mapped onto 14 linkage groups. The proportion of phenotypic variation explained by these QTL ranged from 4.88 to 26.05%. Thirty-eight conditional QTL underlying the filling rate of seed protein were mapped onto 16 linkage groups. The proportion of phenotypic variation explained by these QTL ranged from 1.87 to 31.34%. The numbers and types of QTL and their genetic effects on the filling rate of seed protein were different at each developmental stage. A G × E interaction effect was observed for some QTL.  相似文献   

17.
Ascochyta blight (AB) caused by Ascochyta rabiei, is globally the most important foliar disease that limits the productivity of chickpea (Cicer arietinum L.). An intraspecific linkage map of cultivated chickpea was constructed using an F2 population derived from a cross between an AB susceptible parent ICC 4991 (Pb 7) and an AB resistant parent ICCV 04516. The resultant map consisted of 82 simple sequence repeat (SSR) markers and 2 expressed sequence tag (EST) markers covering 10 linkage groups, spanning a distance of 724.4 cM with an average marker density of 1 marker per 8.6 cM. Three quantitative trait loci (QTLs) were identified that contributed to resistance to an Indian isolate of AB, based on the seedling and adult plant reaction. QTL1 was mapped to LG3 linked to marker TR58 and explained 18.6% of the phenotypic variance (R 2) for AB resistance at the adult plant stage. QTL2 and QTL3 were both mapped to LG4 close to four SSR markers and accounted for 7.7% and 9.3%, respectively, of the total phenotypic variance for AB resistance at seedling stage. The SSR markers which flanked the AB QTLs were validated in a half-sib population derived from the same resistant parent ICCV 04516. Markers TA146 and TR20, linked to QTL2 were shown to be significantly associated with AB resistance at the seedling stage in this half-sib population. The markers linked to these QTLs can be utilized in marker-assisted breeding for AB resistance in chickpea.  相似文献   

18.
A diversity arrays technology (DArT) map was constructed to identify quantitative trait loci (QTL) affecting seed colour, hairy leaf, seedling anthocyanin, leaf chlorosis and days to flowering in Brassica rapa using a F2 population from a cross between two parents with contrasting traits. Two genes with dominant epistatic interaction were responsible for seed colour. One major dominant gene controls the hairy leaf trait. Seedling anthocyanin was controlled by a major single dominant gene. The parents did not exhibit leaf chlorosis; however, 32% F2 plants showed leaf chlorosis in the population. A distorted segregation was observed for days to flowering in the F2 population. A linkage map was constructed with 376 DArT markers distributed over 12 linkage groups covering 579.7 cM. The DArT markers were assigned on different chromosomes of B. rapa using B. rapa genome sequences and DArT consensus map of B. napus. Two QTL (RSC1‐2 and RSC12‐56) located on chromosome A8 and chromosome A9 were identified for seed colour, which explained 19.4% and 18.2% of the phenotypic variation, respectively. The seed colour marker located in the ortholog to Arabidopsis thaliana Transparent Testa2 (AtTT2). Two QTL RLH6‐0 and RLH9‐16 were identified for hairy leaf, which explained 31.6% and 20.7% phenotypic variation, respectively. A single QTL (RSAn‐12‐157) on chromosome A7, which explained 12.8% of phenotypic variation was detected for seedling anthocyanin. The seedling anthocyanin marker is found within the A. thaliana Transparent Testa12 (AtTT12) ortholog. A QTL (RLC6‐04) for leaf chlorosis was identified, which explained 55.3% of phenotypic variation. QTL for hairy leaf and leaf chlorosis were located 0–4 cM apart on the same chromosome A1. A single QTL (RDF‐10‐0) for days to flowering was identified, which explained 21.4% phenotypic variation.  相似文献   

19.
Summary The aim of this investigation was to map quantitative trait loci (QTL) associated with grain yield and yield components in maize and to analyze the role of epistasis in controlling these traits. An F2:3 population from an elite hybrid (Zong3 × 87-1) was used to evaluate grain yield and yield components in two locations (Wuhan and Xiangfan, China) using a randomized complete-block design. The mapping population included 266 F2:3 family lines. A genetic linkage map containing 150 simple sequence repeats and 24 restriction fragment length polymorphism markers was constructed, spanning a total of 2531.6 cM with an average interval of 14.5 cM. A logarithm-of-odds threshold of 2.8 was used as the criterion to confirm the presence of one QTL after 1000 permutations. Twenty-nine QTL were detected for four yield traits, with 11 of them detected simultaneously in both locations. Single QTL contribution to phenotypic variations ranged from 3.7% to 16.8%. Additive, partial dominance, dominance, and overdominance effects were all identified for investigated traits. A greater proportion of overdominance effects was always observed for traits that exhibited higher levels of heterosis. At the P ≤ 0.005 level with 1000 random permutations, 175 and 315 significant digenic interactions were detected in two locations for four yield traits using all possible locus pairs of molecular markers. Twenty-four significant digenic interactions were simultaneously detected for four yield traits at both locations. All three possible digenic interaction types were observed for investigated traits. Each of the interactions accounted for only a small proportion of the phenotypic variation, with an average of 4.0% for single interaction. Most interactions (74.9%) occurred among marker loci, in which significant effects were not detected by single-locus analysis. Some QTL (52.2%) detected by single-locus analysis were involved in epistatic interactions. These results demonstrate that digenic interactions at the two-locus level might play an important role in the genetic basis of maize heterosis.  相似文献   

20.
The identification of quantitative trait loci (QTL) across different environments is a prerequisite for marker‐assisted selection (MAS) in crop improvement programmes. CottonSNP63k Illumina infinium array was used for genotyping 178 inter‐specific recombinant inbred lines and the parents, and identified 1,667 homozygous polymorphic markers between the parents. Of these, 1,430 markers were used for the construction of linkage map after removing 237 redundant markers. The genetic map spans a total genetic length of 3,149.8 cM with an average marker interval size of 2.2 cM. The phenotypic data from five environments were analysed separately using inclusive composite interval mapping which identified a total of 56 QTL explaining phenotypic variances (PVE) in the range of 8.18%–28.91%. There were 11 and 24 major QTL found for fibre quality and yield components, respectively. A total of 64 QTL were identified through Multi‐Environment Trials analysis, of which 34 recorded QTL × Environment interactions.  相似文献   

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