利用两种方法构建的近等基因系对水稻两个多效区段遗传效应进行评价

水稻每穗颖花数是水稻产量的重要构成因子之一。适当的抽穗期和株高对水稻高产是非常必要的。依据珍汕97和HR5衍生的重组自交系初步定位的结果, 利用高世代回交的方法构建了第7染色体同时控制抽穗期、株高和每穗颖花数的靶区段近等基因系(BC4F2); 利用基于重组自交系群体的杂合区段自交的方法构建了第8染色体同时控制抽穗期、株高和每穗颖花数的靶区段近等基因系, 并利用两个近等基因系对这两个多效区段的遗传效应进行了准确的评价。两个近等基因系的QTL分析结果表明, 3个性状都是由一个QTL或紧密连锁的QTL控制, 而且加性效应和显性效应的方向均相同; 同时3个性状在各自的近等基因系中呈现典型的双峰分布或不连续分布,这些结果暗示3个性状可能是一因多效的结果。文章还对抽穗期和株高与水稻产量的关系、3个性状显著正相关在育种中的应用及两种构建近等基因系方法的优缺点也进行了讨论。     

Identification and fine mapping of quantitative trait loci for the number of vascular bundle in maize stem

Studies that investigated the genetic basis of source and sink related traits have been widely conducted. However, the vascular system that links source and sink received much less attention. When maize was domesticated from its wild ancestor, teosinte, the external morphology has changed dramatically; however, less is known for the internal anatomy changes. In this study, using a large maize‐teosinte experimental population, we performed a high‐resolution quantitative trait locus (QTL) mapping for the number of vascular bundle in the uppermost internode of maize stem. The results showed that vascular bundle number is dominated by a large number of small‐effect QTLs, in which a total of 16 QTLs that jointly accounts for 52.2% of phenotypic variation were detected, with no single QTL explaining more than 6% of variation. Different from QTLs for typical domestication traits, QTLs for vascular bundle number might not be under directional selection following domestication. Using Near Isogenic Lines (NILs) developed from heterogeneous inbred family (HIF), we further validated the effect of one QTL qVb9‐2 on chromosome 9 and fine mapped the QTL to a 1.8‐Mb physical region. This study provides important insights for the genetic architecture of vascular bundle number in maize stem and sets basis for cloning of qVb9‐2.     

Genetic analysis of vertical root pulling resistance (VRPR) in maize using two genetic populations

Root traits are important in improving nutrient and water use efficiency. Vertical root pulling resistance (VRPR) has been shown to be closely related to root system characteristics in maize (Zea mays L.). In the present study, two genetic populations derived from the same parents, one containing 218 recombinant inbred lines (RILs) and the other containing 187 advanced backcross BC₄F₃ lines, were genotyped using 184 SSR markers and evaluated for VRPR, grain yield (GY), stover yield (SY), and nitrogen uptake (N_up) under field conditions over 2 years. Our aims were (1) to locate QTLs associated with VRPR, SY, GY, and N_up, (2) to determine whether QTL detection is consistent between the BC₄F₃ and RIL populations, and (3) to identify backcross lines harboring favorable VRPR QTLs for use in future breeding programs. Using composite interval mapping (CIM), 12 and 17 QTLs were detected in BC₄F₃ and RIL populations, respectively. An important QTL region in bin 6.02 within the interval umc1006-umc1257 was found to control VRPR, SY, and N_up in both populations. These favorable alleles were contributed by the large-rooted parent Ye478. A significant positive correlation was detected between VRPR, SY, and N_up, but not between VRPR and GY. Backcross lines harboring VRPR QTLs could be useful germplasm for developing near isogenic lines (NILs) and for map-based cloning of genes controlling root growth.     

Comparison of a set of allelic QTL-NILs for chromosome 4 of tomato: Deductions about natural variation and implications for germplasm utilization

Quantitative Trait Locus (QTL) allelic variation was studied by analyzing near-isogenic lines (NILs) carrying homologous introgressions on chromosome 4 from three green-fruited wild tomato species. The NILs affect agronomic (yield, brix, fruit weight) and fruit (fruit shape, color, epidermal reticulation) traits in a similar manner. However, significant differences were detected in the magnitudes of the effects, the dominance deviations and epistatic interactions, indicating that those species carry different alleles for the QTL. As the QTL did not show any interaction across environments, gene-tic backgrounds or other QTLs, it can be used to introduce novel genetic variation into a broad range of cultivars. Analysis of new recombinant NILs showed that fruit traits are controlled by several linked genetic loci, whereas multiple genetic loci control the agronomic traits within the original introgression. The hypothesis that QTLs may be composed of multiple linked genes can not be rejected prior to implement projects for QTL isolation and cloning. Loci involved in color enhancement could not be related to any known gene involved in the carotenoid biosynthesis pathway, therefore it is hypothesized that the function of those loci must be related to the genetic regulation of the carotenoid biosynthetic pathway. Received: 14 April 2000 / Accepted: 12 May 2000     

Meta-analysis of quantitative trait loci for grain yield and component traits under reproductive-stage drought stress in an upland rice population

A recombinant inbred population developed from a cross between high-yielding lowland rice (Oryza sativa L.) subspecies indica cv. IR64 and upland tropical rice subspecies japonica cv. Cabacu was used to identify quantitative trait loci (QTLs) for grain yield (GY) and component traits under reproductive-stage drought stress. One hundred fifty-four lines were grown in field trials in Indonesia under aerobic conditions by giving surface irrigation to field capacity every 4 days. Water stress was imposed for a period of 15 days during pre-flowering by withholding irrigation at 65 days after seeding. Leaf rolling was scored at the end of the stress period and eight agronomic traits were evaluated after recovery. The population was also evaluated for root pulling force, and a total of 201 single nucleotide polymorphism markers were used to construct the molecular genetic linkage map and QTL mapping. A QTL for GY under drought stress was identified in a region close to the sd1 locus on chromosome 1. QTL meta-analysis across diverse populations showed that this QTL was conserved across genetic backgrounds and co-localized with QTLs for leaf rolling and osmotic adjustment (OA). A QTL for percent seed set and grains per panicle under drought stress was identified on chromosome 8 in the same region as a QTL for OA previously identified in three different populations.     

Identification of growth processes involved in QTLs for tomato fruit size and composition

Many quantitative trait loci (QTLs) for quality traits havebeen located on the tomato genetic map, but introgression offavourable wild alleles into large fruited species is hamperedby co-localizations of QTLs with antagonist effects. The aimof this study was to assess the growth processes controlledby the main QTLs for fruit size and composition. Four nearlyisogenic lines (NILs) derived from an intraspecific cross betweena tasty cherry tomato (Cervil) and a normal-tasting large fruittomato (Levovil) were studied. The lines carried one (L2, L4,and L9) or five (Lx) introgressions from Cervil on chromosomes1, 2, 4, and 9. QTLs for fruit size could be mainly associatedwith cell division processes in L2 and L9, whereas cell expansionwas rather homogeneous among the genotypes, except Cervil forwhich the low expansion rate was attributed to low cell plasticity.The link between endoreduplication and fruit size remained unclear,as cell or fruit sizes were positively correlated with the cellDNA content, but not with the endoreduplication factor. QTLsfor fruit composition reflected differences in water accumulationrather than in sugar accumulation, except in L9 for which theup-regulation of sucrose unloading and hexose transport and/orstarch synthesis was suggested. This may explain the increasedamount of carbon allocated to cell structures in L9, which couldbe related to a QTL for fruit texture. In Lx, these effectswere attenuated, except on fruit size and cell division. Finally,the region on top of chromosome 9 may control size and compositionattributes in tomato, by a combination of QTL effects on celldivision, cell wall synthesis, and carbon import and metabolism. Key words: Cell division and expansion, endoreduplication, fruit quality, near isogenic line, osmotic regulation, quantitative trait locus, Solanum lycopersicum, starch, sugar and acid contents Received 22 July 2008; Revised 17 October 2008 Accepted 20 October 2008     

Fine mapping of three quantitative trait loci for late blight resistance in tomato using near isogenic lines (NILs) and sub-NILs

An earlier study identified quantitative trait loci (QTLs) lb4, lb5b, and lb11b for quantitative resistance to Phytophthora infestans (late blight) in a backcross population derived from crossing susceptible cultivated tomato (Lycopersicon esculentum) with resistant L. hirsutum. The QTLs were located in intervals spanning 28–47 cM. Subsequently, near-isogenic lines (NILs) were developed for lb4, lb5b, and lb11b by marker-assisted backcrossing to L. esculentum. Sub-NILs containing overlapping L. hirsutum segments across each QTL region were selected and used to validate the QTL effects, fine-map QTLs, and evaluate potential linkage drag between resistance QTLs and QTLs for horticultural traits. The NILs and sub-NILs were evaluated for disease resistance and eight horticultural traits at three field locations. Resistance QTLs were detected in all three sets of NIL lines, confirming the BC₁ mapping results. Lb4 mapped near TG609, and between TG182 and CT194, on chromosome 4, a 6.9-cM interval; lb5b mapped to an 8.8-cM interval between TG69a and TG413 on chromosome 5, with the most likely position near TG23; and lb11b mapped to a 15.1-cM interval on chromosome 11 between TG194 and TG400, with the peak centered between CT182 and TG147. Most QTLs for horticultural traits were identified in intervals adjacent to those containing the late blight resistance QTLs. Fine mapping of these QTLs permits the use of marker-assisted selection for the precise introgression of L. hirsutum segments containing late blight resistance alleles separately from those containing deleterious alleles at horticulturally important QTLs.Electronic Supplementary Material Supplementary material is available in the online version of this article at Communicated by D.B. Neale     

A intervarietal genetic map and QTL analysis for yield traits in wheat

A new genetic linkage map was constructed based on recombinant inbred lines (RILs) derived from the cross between the Chinese winter wheat (Triticum aestivum L.) varieties, Chuang 35050 and Shannong 483 (ChSh). The map included 381 loci on all the wheat chromosomes, which were composed of 167 SSR, 94 EST-SSR, 76 ISSR, 26 SRAP, 15 TRAP, and 3 Glu loci. This map covered 3636.7 cM with 1327.7 cM (36.5%), 1485.5 cM (40.9%), and 823.5 cM (22.6%) for A, B, and D genome, respectively, and contained 13 linkage gaps. Using the RILs and the map, we detected 46 putative QTLs on 12 chromosomes for grain yield (GY) per m², thousand-kernel weight (TKW), spike number (SN) per m², kernel number per spike (KNS), sterile spikelet number per spike (SSS), fertile spikelet number per spike (FSS), and total spikelet number per spike (TSS) in four environments. Each QTL explained 4.42–70.25% phenotypic variation. Four QTL cluster regions were detected on chromosomes 1D, 2A, 6B, and 7D. The most important QTL cluster was located on chromosome 7D near the markers of Xwmc31, Xgdm67, and Xgwm428, in which 8 QTLs for TKW, SN, SSS and FSS were observed with very high contributions (27.53–67.63%).     

Influence of dent corn genetic backgrounds on QTL detection for plant-height traits and their relationships in high-oil maize

QTL mapping for plant-height traits has not been hitherto reported in high-oil maize. A high-oil maize inbred ‘GY220’ was crossed with two dent maize inbreds (‘8984’ and ‘8622’) to generate two connected F_2:3 populations. Four plant-height traits were evaluated in 284 and 265 F_2:3 families. Single-trait QTL mapping and multiple-trait joint QTL mapping was used to detect QTLs for the traits and the genetic relationship between plant height (PH) and two other plant-height traits. A total of 28 QTLs and 12 pairs of digenic interactions among detected QTLs for four traits were detected in the two F_2:3 families. Only one marker was shared between the two populations. Joint analysis of PH with ear height (EH) and PH with top height (TH) detected 32 additional QTLs. Our results showed that QTL detection for PH was dependent on the genetic background of dent corn inbreds. Multiple-trait joint QTL analysis could increase the number of detected QTLs.     

QTL mapping for yield and photosynthetic related traits under different water regimes in wheat

The improvement for drought tolerance requires understanding of the genetic control of wheat (Triticum aestivum L.) reaction to drought. In this study, a set of 131 recombinant inbred lines of wheat were investigated under well-watered (WW) and drought stress (DS) environments across 2 years to map quantitative trait loci (QTLs) for yield and physiological traits. A total of 225 QTLs were detected, including 32 non-environment-specific loci that were significant in both DS and WW, one drought-specific locus and two watering-specific loci. Three consistently-expressed QTLs (QTkw-3A.2, QTss-1A, and QScn-7A.1) were identified in at least three environments and the QTkw-1D.1 was significant in DS across the 2 years. By unconditional and conditional QTL analysis, spike number per plant and kernel number per spike were more important than thousand-kernel weight for grain yield (GY) at the given genetic background. Meta-analysis identified 67 meta-QTLs that contained QTLs for at least two traits. High frequency co-location of QTLs was found among either the spike-related traits or the six physiological traits. Four photosynthesis traits (CHL, LWUE, P _N, and C _i) were co-located with GY and/or yield components on various MQTLs. The results provided QTLs that warrant further study for drought tolerance breeding and are helpful for understanding the genetic basis of drought tolerance and the genetic contribution of yield components to GY at individual QTL level in wheat.