水稻籽粒淀粉分支酶活性的遗传分析

用由247个株系组成的珍汕97B/密阳46重组自交系群体及其含207个分子标记的连锁图谱,在2002年和2003年分别测定亲本和重组自交系群体开花后10 d和20 d籽粒的淀粉分支酶的活性,检测到3个控制开花后10 d Q酶活性的主效应QTL(qnantitative trait loci),联合贡献率为10%,其中qQ10-6与环境发生显著的互作;分别检测到5对和2对染色体区间对开花后10 d、20 d Q酶活性的影响具有加性×加性上位性作用,其中开花后10 d的3对染色体区间具有显著的上位性×环境互作效应.由此可见,水稻籽粒Q酶活性相关基因的表达,受到环境因子的极大影响.     

From QTLs for enzyme activity to candidate genes in maize

In order to facilitate the search for genes underlying QTLs (Quantitative Trait Loci), the activities of key enzymes of the carbohydrate metabolism in maize, and the concentration of their substrates or products were used as quantitative traits. For each of the chosen enzyme, i.e. ADPglucose pyrophosphorylase, sucrose-phosphate-synthase and invertases, the corresponding cDNA was available. Since biochemical traits are more closely related to gene expression than agronomic traits, co-locations could be expected between an enzyme structural gene and a QTL for its enzyme activity, and/or the corresponding product or substrate content. This approach was applied using recombinant inbred lines on leaves at 3- or 4-leaf stage, under control and water stress conditions and on grain, at maturity. Several QTLs were detected for each trait, particularly for two enzyme activities measured in mature leaves. Apparent co-locations between QTL for activity and structural locus were observed for sucrose-phosphate-synthase (chromosome 8) and acid-soluble invertase (chromosome 2 and 5). Leaf acid-soluble (vacuolar) invertase provided an interesting case since QTL, on chromosome 5, explaining 17% of variability was apparently co-located with the Ivr2 gene encoding a vacuolar invertase protein which was strongly water-stress inducible. Similarly, in grain, an amylose QTL co-located with the Sh2 gene of ADPglucose pyrophosphorylase. The reliability of this candidate was further tested through the examination of Sh2 DNA polymorphism in 46 genetically unrelated lines. A correlation was obtained between this polymorphism and kernel starch content, which further validated Sh2 as a candidate. Some improvements or alternatives to this strategy are briefly discussed.      

RFLP mapping of quantitative trait loci controlling abscisic acid concentration in leaves of drought-stressed maize (Zea mays L.)

 Abscisic acid (ABA) concentration in leaves of drought-stressed plants is a quantitatively inherited trait. In order to identify quantitative trait loci (QTLs) controlling leaf ABA concentration (L-ABA) in maize, leaf samples were collected from 80 F_3:4 families of the cross Os420 (high L-ABA)×IABO78 (low L-ABA) tested under drought conditions in field trials conducted over 2 years. In each year, leaf samples were collected at stem elongation and near anthesis. The genetic map obtained with 106 restriction fragment length polymorphism (RFLP) loci covered 1370 cM, which represented approximately 85% of the UMC maize map. Sixteen different QTLs with a LOD>2.0 were revealed in at least one sampling. Across samplings, only four QTLs significantly influenced L-ABA, accounting for 66% of the phenotypic variation and 76% of the genetic variation among families. At these QTLs, the alleles which increased L-ABA were contributed by Os420. The two most important QTLs were mapped on chromosome 2 near csu133 and csu109a. The effects associated with the QTL near csu133 were more pronounced near anthesis. The support intervals of the four primary QTLs for L-ABA did not overlap the presumed map position of mutants impaired in ABA biosynthesis. Received: 27 January 1998 / Accepted: 22 April 1998     

GBS-SNP and SSR based genetic mapping and QTL analysis for drought tolerance in upland cotton

A recombinant inbred line mapping population of intra-species upland cotton was generated from a cross between the drought-tolerant female parent (AS2) and the susceptible male parent (MCU13). A linkage map was constructed deploying 1,116 GBS-based SNPs and public domain-based 782 SSRs spanning a total genetic distance of 28,083.03 cM with an average chromosomal span length of 1,080.12 cM with inter-marker distance of 10.19 cM.A total of 19 quantitative trait loci (QTLs) were identified in nine chromosomes for field drought tolerance traits. Chromosomes 3 and 8 harbored important drought tolerant QTLs for chlorophyll stability index trait while for relative water content trait, three QTLs on chromosome 8 and one QTL each on chromosome 4, 12 were identified. One QTL on each chromosome 8, 5, and 7, and two QTLs on chromosome 15 linking to proline content were identified. For the nitrate reductase activity trait, two QTLs were identified on chromosome 3 and one on each chromosome 8, 13, and 26. To complement our QTL study, a meta-analysis was conducted along with the public domain database and resulted in a consensus map for chromosome 8. Under field drought stress, chromosome 8 harbored a drought tolerance QTL hotspot with two in-house QTLs for chlorophyll stability index (qCSI01, qCSI02) and three public domain QTLs (qLP.FDT_1, qLP.FDT_2, qCC.ST_3). Identified QTL hotspot on chromosome 8 could play a crucial role in exploring abiotic stress-associated genes/alleles for drought trait improvement.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-01041-y.     

玉米籽粒淀粉含量遗传基础与调控机制*

玉米是世界上种植面积最大、总产量最高的粮食作物,其籽粒重量的70%来自于淀粉。淀粉不仅是人类及其他动物的主要能量来源,同时也是化工等行业的重要原料。利用拟南芥、水稻等模式植物,淀粉合成相关基因克隆与功能研究已取得较多进展。近年来,随着玉米淀粉含量相关遗传学研究的深入开展,通过数量性状位点(quantitative trait locus mapping,QTL)定位、全基因组关联分析(genome-wide association study, GWAS)及各种组学分析方法,发现了较多新的与淀粉含量相关的遗传位点及候选基因,但是尚缺乏归纳总结。综述了玉米籽粒淀粉合成与调控研究进展,对玉米籽粒淀粉含量相关的QTL和基因进行汇总和分析,通过构建一致性物理图谱,提炼玉米籽粒淀粉含量遗传定位热点区间,这为进一步解析玉米籽粒淀粉合成与代谢相关基因的功能提供参考,并为分子标记辅助育种提供遗传资源。     

QTLs for grain dry milling properties, composition and vitreousness in maize recombinant inbred lines

Vitreousness and kernel hardness are important properties for maize processing and end-product quality. In order to examine the genetic basis of these traits, a recombinant inbred line population resulting from a cross between a flint line (F-2) and a semident line (Io) was used to search for vitreousness and kernel composition QTLs. Vitreousness was measured by image processing from a kernel section, while NIR spectroscopy was used to estimate starch, protein, cellulose, lipid and semolina yield. In addition, thousand-grain weight and grain weight per ear were measured. The MQTL method was used to map the QTLs for the different traits. An additional program allowed for the detection of interaction QTLs between markers. The total number of main-effect and interaction QTLs was similar. The QTLs were not evenly distributed but tended to cluster. Such clusters, mixing main-effect and interaction QTLs, were observed at six positions : on chromosomes 1, 2, 3, 6, 8 and 9. Two of them, on chromosomes 6 and 9, concerned both QTLs for kernel-weight traits and QTLs for kernel-composition traits (protein and cellulose). Technological-trait QTLs (vitreousness or semolina yield) were located less than 16 cM from a protein-content QTL on chromosome 2, and were co-located with lipid- and starch-content QTLs on chromosome 8. The co-location of a vitreousness and a semolina-yield QTL at the telomeric end of the chromosome 2 (Bin 2.02) is likely to be meaningful since measurement of these related traits, made by completely different methods (NIRS vs image processing), yielded very close QTLs. A similar location was previously reported independently for a kernel-friability QTL. Comparing the map location of the numerous loci for known-function genes it was shown that three zein loci were closely linked to QTLs for vitreousness on chromosome 3, for semolina yield and starch on chromosome 4, and for protein, cellulose and grain weight on chromosome 9. Some other candidate genes linked to starch precursor metabolism were also suggested on chromosomes 6 and 8. Received: 27 April 2000 / Accepted: 3 July 2000     

Natural variation for carbohydrate content in Arabidopsis. Interaction with complex traits dissected by quantitative genetics

Besides being a metabolic fuel, carbohydrates play important roles in plant growth and development, in stress responses, and as signal molecules. We exploited natural variation in Arabidopsis (Arabidopsis thaliana) to decipher the genetic architecture determining carbohydrate content. A quantitative trait locus (QTL) approach in the Bay-0 x Shahdara progeny grown in two contrasting nitrogen environments led to the identification of 39 QTLs for starch, glucose, fructose, and sucrose contents representing at least 14 distinct polymorphic loci. A major QTL for fructose content (FR3.4) and a QTL for starch content (ST3.4) were confirmed in heterogeneous inbred families. Several genes associated with carbon (C) metabolism colocalize with the identified QTL. QTLs for senescence-related traits, and for flowering time, water status, and nitrogen-related traits, previously detected with the same genetic material, colocalize with C-related QTLs. These colocalizations reflect the complex interactions of C metabolism with other physiological processes. QTL fine-mapping and cloning could thus lead soon to the identification of genes potentially involved in the control of different connected physiological processes.     

Genetic dissection of starch paste viscosity characteristics in waxy maize revealed by high-density SNPs in a recombinant inbred line population

Starch paste viscosity properties are widely used as important indicators for quality estimation in waxy maize. To elucidate the genetic basis of paste viscosity characteristics of waxy maize, seven parameters from the rapid visco analyzer (RVA) profile were analyzed for quantitative trait loci (QTLs) in this study, using a recombinant inbred line population derived from a cross between the inbred lines Tongxi5 and Hengbai522. A high-density linkage map was constructed using 2703 bin markers, covering 1876.20 cM of the whole genome with an average genetic distance of 0.73 cM between adjacent bin markers. Seventy-two QTLs were detected for RVA parameters across 3 years, of which 17 could be identified in 2 years, and 6 identified in all 3 years. Eight QTL clusters were observed to be co-associated with two or more RVA parameters. Three major QTLs, qPV4-1, qTV4-1, and qFV5-2, which explained over 10% of the phenotypic variation, were stably mapped to the chromosomes 4 or 5 in all years. Based on functional annotations, two genes were considered as potential candidate genes for the identified major QTLs. The QTLs and candidate genes identified in this study will be useful for further understanding of the genetic architecture of starch paste viscosity characteristics in waxy maize, and may facilitate molecular breeding for grain quality improvement in breeding programs, and simultaneously provide a basis for cloning of the genes underlying these QTLs.     

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

The identification of quantitative trait loci (QTLs) affecting agronomically important traits enable to understand their underlying genetic mechanisms and genetic basis of their complex interactions. The aim of the present study was to detect QTLs for 12 agronomic traits related to staygreen, plant early development, grain yield and its components, and some growth characters by analyzing replicated phenotypic datasets from three crop seasons, using the population of 168 F₇ RILs of the cross 296B × IS18551. In addition, we report mapping of a subset of genic-microsatellite markers. A linkage map was constructed with 152 marker loci comprising 149 microsatellites (100 genomic- and 49 genic-microsatellites) and three morphological markers. QTL analysis was performed by using MQM approach. Forty-nine QTLs were detected, across environments or in individual environments, with 1–9 QTLs for each trait. Individual QTL accounted for 5.2–50.4% of phenotypic variance. Several genomic regions affected multiple traits, suggesting the phenomenon of pleiotropy or tight linkage. Stable QTLs were identified for studied traits across different environments, and genetic backgrounds by comparing the QTLs in the study with previously reported QTLs in sorghum. Of the 49 mapped genic-markers, 18 were detected associating either closely or exactly as the QTL positions of agronomic traits. EST marker Dsenhsbm19, coding for a key regulator (EIL-1) of ethylene biosynthesis, was identified co-located with the QTLs for plant early development and staygreen trait, a probable candidate gene for these traits. Similarly, such exact co-locations between EST markers and QTLs were observed in four other instances. Collectively, the QTLs/markers identified in the study are likely candidates for improving the sorghum performance through MAS and map-based gene isolations.     

玉米抗甘蔗花叶病毒基因的比较定位

收集了玉米抗甘蔗花叶病毒基因/QTL定位信息, 借助玉米遗传图谱IBM2 2005 Neighbors进行了整合。在国内外研究中, 累计报道81个抗病毒基因位点, 分布在玉米7条染色体上, 比较定位发现这些位点集中分布于第3和6染色体。采用元分析技术, 确定3个“一致性”抗病毒QTL, 其中1个位于第3染色体, 在遗传图谱IBM2 2005 Neighbors上覆盖的范围为6.44 cM; 2个位于第6染色体, 覆盖范围分别为6.16 cM和27.48 cM。借助比较基因组学策略, 在第3染色体“一致性”QTL区间内筛选出4个抗病位置候选基因。该研究结果为确定和克隆抗病主效基因提供了基础。     

Analysis of the Relationships between Growth, Photosynthesis and Carbohydrate Metabolism Using Quantitative Trait Loci (QTLs) in Young Maize Plants Subjected to Water Deprivation

One hundred to 120 maize recombinant inbred lines at the mature fourth leaf stage derived from F-2 and Io parental lines were grown in a glasshouse and were deprived of water for 9 days in order to detect pertinent markers of the physiological response to water stress which may be used for breeding. Carbohydrate metabolism QTLs were compared to photosynthesis gas exchange QTLs. The locations of these QTLs were further compared with those of morphological trait QTLs when water availability varied. The traits ranged from three enzyme activities (invertase, sucrose-P synthase, ADP glucose pyrophosphorylase) and hexose, sucrose, starch content to CO₂ uptake and stomatal conductance, water status, leaf size, root/shoot ratio, and ABA (leaf, root and xylem sap). Four main results were obtained (1) only 14 % of QTLs were common to both drought and watered treatments, confirming the existence of stress specific chromosome regions, (2) the QTLs tended to form clusters, frequently consisting of QTLs from different classes (growth, photosynthesis, water status, carbohydrate metabolism and ABA), (3) carbohydrate metabolism trait QTLs were more frequently co-located with growth trait QTLs than photosynthesis related ones, especially in control conditions, (4) one co-location was observed between the three enzyme activities implied in sucrose and starch metabolism and a corresponding structural gene, which can be considered as a candidate gene for explaining part of the variability of each enzymatic trait (invertase, sucrose-P synthase, ADPglucose pyrophosphorylase). It is concluded that, carbohydrate metabolism provides valuable traits for understanding and improving maize responses to water stress.     

Maize leaf temperature responses to drought: Thermal imaging and quantitative trait loci (QTL) mapping

Leaf temperature has been shown to vary when plants are subjected to water stress conditions. Recent advances in infrared thermography have increased the probability of recording drought tolerant responses more accurately. The aims of this study were to identify the effects of drought on leaf temperature using infrared thermography. Furthermore, the genomic regions responsible for the expression of leaf temperature variation in maize seedlings (Zea mays L.) were explored. The maize inbred lines Zong3 and 87-1 were evaluated using infrared thermography and exhibited notable differences in leaf temperature response to water stress. Correlation analysis indicated that leaf temperature response to water stress played an integral role in maize biomass accumulation. Additionally, a mapping population of 187 recombinant inbred lines (RILs) derived from a cross between Zong3 and 87-1 was constructed to identify quantitative trait loci (QTL) responsible for physiological traits associated with seedling water stress. Leaf temperature differences (LTD) and the drought tolerance index (DTI) of shoot fresh weight (SFW) and shoot dry weight (SDW) were the traits evaluated for QTL analysis in maize seedlings. A total of nine QTL were detected by composite interval mapping (CIM) for the three traits (LTD, RSFW and RSDW). Two co-locations responsible for both RSFW and RSDW were detected on chromosomes 1 and 2, respectively, which showed common signs with their trait correlations. Another co-location was detected on chromosome 9 between LTD and shoot biomass, which provided genetic evidence that leaf temperature affects biomass accumulation. Additionally, the utility of a thermography system for drought tolerance breeding in maize was discussed.     

The genetic architecture of amino acids dissection by association and linkage analysis in maize

Amino acids are both constituents of proteins, providing the essential nutrition for humans and animals, and signalling molecules regulating the growth and development of plants. Most cultivars of maize are deficient in essential amino acids such as lysine and tryptophan. Here, we measured the levels of 17 different total amino acids, and created 48 derived traits in mature kernels from a maize diversity inbred collection and three recombinant inbred line (RIL) populations. By GWAS, 247 and 281 significant loci were identified in two different environments, 5.1 and 4.4 loci for each trait, explaining 7.44% and 7.90% phenotypic variation for each locus in average, respectively. By linkage mapping, 89, 150 and 165 QTLs were identified in B73/By804, Kui3/B77 and Zong3/Yu87‐1 RIL populations, 2.0, 2.7 and 2.8 QTLs for each trait, explaining 13.6%, 16.4% and 21.4% phenotypic variation for each QTL in average, respectively. It implies that the genetic architecture of amino acids is relative simple and controlled by limited loci. About 43.2% of the loci identified by GWAS were verified by expression QTL, and 17 loci overlapped with mapped QTLs in the three RIL populations. GRMZM2G015534, GRMZM2G143008 and one QTL were further validated using molecular approaches. The amino acid biosynthetic and catabolic pathways were reconstructed on the basis of candidate genes proposed in this study. Our results provide insights into the genetic basis of amino acid biosynthesis in maize kernels and may facilitate marker‐based breeding for quality protein maize.     

BioMercator: integrating genetic maps and QTL towards discovery of candidate genes

SUMMARY: Breeding programs face the challenge of integrating information from genomics and from quantitative trait loci (QTL) analysis in order to identify genomic sequences controlling the variation of important traits. Despite the development of integrative databases, building a consensus map of genes, QTL and other loci gathered from multiple maps remains a manual and tedious task. Nevertheless, this is a critical step to reveal co-locations between genes and QTL. Another important matter is to determine whether QTL linked to same traits or related ones is detected in independent experiments and located in the same region, and represents a single locus or not. Statistical tools such as meta-analysis can be used to answer this question. BioMercator has been developed to automate map compilation and QTL meta-analysis, and to visualize co-locations between genes and QTL through a graphical interface. AVAILABILITY: Available upon request (http://moulon/~bioinfo/BioMercator/). Free of charge for academic use.     

A consensus linkage map of common carp (Cyprinus carpio L.) to compare the distribution and variation of QTLs associated with growth traits

The ability to detect and identify quantitative trait loci (QTLs) in a single population is often limited. Analyzing multiple populations in QTL analysis improves the power of detecting QTLs and provides a better understanding of their functional allelic variation and distribution. In this study, a consensus map of the common carp was constructed, based on four populations, to compare the distribution and variation of QTLs. The consensus map spans 2371.6 cM across the 42 linkage groups and comprises 257 microsatellites and 421 SNPs, with a mean marker interval of 3.7 cM/marker. Sixty-seven QTLs affecting four growth traits from the four populations were mapped to the consensus map. Only one QTL was common to three populations, and nine QTLs were detected in two populations. However, no QTL was common to all four populations. The results of the QTL comparison suggest that the QTLs are responsible for the phenotypic variability observed for these traits in a broad array of common carp germplasms. The study also reveals the different genetic performances between major and minor genes in different populations.     

Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome

Genetic architecture of flowering time in maize was addressed by synthesizing a total of 313 quantitative trait loci (QTL) available for this trait. These were analyzed first with an overview statistic that highlighted regions of key importance and then with a meta-analysis method that yielded a synthetic genetic model with 62 consensus QTL. Six of these displayed a major effect. Meta-analysis led in this case to a twofold increase in the precision in QTL position estimation, when compared to the most precise initial QTL position within the corresponding region. The 62 consensus QTL were compared first to the positions of the few flowering-time candidate genes that have been mapped in maize. We then projected rice candidate genes onto the maize genome using a synteny conservation approach based on comparative mapping between the maize genetic map and japonica rice physical map. This yielded 19 associations between maize QTL and genes involved in flowering time in rice and in Arabidopsis. Results suggest that the combination of meta-analysis within a species of interest and synteny-based projections from a related model plant can be an efficient strategy for identifying new candidate genes for trait variation.     

Mapping of Defense Response Gene Homologs and Their Association with Resistance Loci in Maize

Defense response genes in higher plant species are involved in a variety of signal transduction pathways and biochemical reactions to counterattack invading pathogens. In this study, a total of 366 non-redundant defense response gene homologs （DRHs）, including 124 unigenes/expressed sequence tags, 226 tentative consensuses, and 16 DRH contigs have been identified by mining the Maize Genetics and Genomics and The Institute for Genomic Research maize databases using 35 essential defense response genes. Of 366 DRHs, 202 are mapped to 152 loci across ten maize chromosomes via both the genetic and in silico mapping approaches. The mapped DRHs seem to cluster together rather than be evenly distributed along the maize genome. Approximately half of these DHRs are located in regions harboring either major resistance genes or quantitative trait loci （QTL）. Therefore, this comprehensive DRH linkage map will provide reference sequences to identify either positional candidate genes for resistance genes and/or QTLs or to develop makers for fine-mapping and marker-assisted selection of resistance genes and/or QTLs.     

Combined genetic and physiological analysis of a locus contributing to quantitative variation

The natural variation of many traits is controlled by multiple genes, individually referred to as quantitative trait loci (QTL), that interact with the environment to determine the ultimate phenotype of any individual. A QTL has yet to be described molecularly, in part because strategies to systematically identify them are underdeveloped and because the subtle nature of QTLs prevents the application of standard methods of gene identification. Therefore, it will be necessary to develop a systematic approach(es) for the identification of QTLs based upon the numerous positional data now being accumulated through molecular marker analyses. We have characterized a QTL by the following three-step approach: (1) identification of a QTL in complex populations, (2) isolation and genetic mapping of this QTL in near-isogenic lines, and (3) identification of a candidate gene using map position and physiological criteria. Using this approach we have characterized a plant height QTL in maize that maps to chromosome 9 near the centromere. Both map position and physiological criteria suggest the gibberillin biosynthesis gene dwarf3 as a candidate gene for this QTL.     

Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers

Huge efforts have been invested in the last two decades to dissect the genetic bases of complex traits including yields of many crop plants, through quantitative trait locus (QTL) analyses. However, almost all the studies were based on linkage maps constructed using low-throughput molecular markers, e.g. restriction fragment length polymorphisms (RFLPs) and simple sequence repeats (SSRs), thus are mostly of low density and not able to provide precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, we constructed an ultra-high density genetic map based on high quality single nucleotide polymorphisms (SNPs) from low-coverage sequences of a recombinant inbred line (RIL) population of rice, generated using new sequencing technology. The quality of the map was assessed by validating the positions of several cloned genes including GS3 and GW5/qSW5, two major QTLs for grain length and grain width respectively, and OsC1, a qualitative trait locus for pigmentation. In all the cases the loci could be precisely resolved to the bins where the genes are located, indicating high quality and accuracy of the map. The SNP map was used to perform QTL analysis for yield and three yield-component traits, number of tillers per plant, number of grains per panicle and grain weight, using data from field trials conducted over years, in comparison to QTL mapping based on RFLPs/SSRs. The SNP map detected more QTLs especially for grain weight, with precise map locations, demonstrating advantages in detecting power and resolution relative to the RFLP/SSR map. Thus this study provided an example for ultra-high density map construction using sequencing technology. Moreover, the results obtained are helpful for understanding the genetic bases of the yield traits and for fine mapping and cloning of QTLs.