Effect of an introgression from <Emphasis Type="Italic">Aegilops cylindrica</Emphasis> host on manifestation of productivity traits in winter common wheat F<Subscript>2</Subscript> plants

The effect of introgression of a chromosome 1D segment from Aegilops cylindrica to winter common wheat on productivity traits in F₂ plants was studied using storage protein loci as genetic markers. An allele of the gliadin-coding Gli-D1 locus served as a marker of the introgression. Using of two- and three-locus interaction models, it was shown that the introgression tagged with Gli-D1 affected the manifestation of productivity traits (productive tillering, grain weight per plant and grain number per plant) through interaction with other marker storage protein loci: Glu-B1, Glu-D1, and Gli-B2.Translated from Genetika, Vol. 40, No. 12, 2004, pp. 1662–1667.Original Russian Text Copyright © 2004 by Kozub, I. Sozinov, A. Sozinov.     

Development and QTL assessment of Triticum aestivum–Aegilops tauschii introgression lines

A set of 84 bread wheat lines, each containing a single homozygous introgression of the Aegilops tauschii genome was produced in the ‘Chinese Spring’ background via backcrossing of the D-genome chromosome substitution lines ‘Chinese Spring’/Sears’s ‘Synthetic 6x’ with the recurrent parent and subsequent selfing. The development of the lines was accompanied by microsatellite marker assisted selection. With the exception of three telomeric regions at chromosomes 1DL, 4DL and 7DS, and a region of less than 24 cM on the chromosome arm 3DL, the genome of Ae. tauschii is fully represented in these lines. The newly developed lines were used for the discovery of morphological and agronomical quantitative trait loci (QTLs) from the wild species. Fifty-two introgression lines were grown in the field and evaluated for six traits including flowering time, plant height, ear length, spikelet number, fertility and grain weight per ear. Seventeen significant QTLs were detected, Ae. tauschii contributed favourable alleles at nine loci influencing five traits. The whole set of 84 homozygous lines provides a tool for further testing the effects and stability of the detected QTLs and for the evaluation of new traits.     

普通野生稻中增产相关QTL的发掘

普通野生稻(Oryza Rufipogon)是重要的遗传资源,发掘其优良等位基因将对水稻遗传改良产生重要影响。文章从以珍汕97为轮回亲本,普通野生稻为供体的BC2F1群体中选择一个与珍汕97表型明显不同的单株BC2F1-15,经过连续自交获得回交重组自交系BC2F5群体。均匀分布于12条染色体的126个多态性SSR(Simplesequence repeats)标记基因型分析,发现BC2F1-15单株在30%的标记位点为杂合基因型;利用该群体共检测到4个抽穗期、3个株高、4个每穗颖花数、2个千粒重和1个单株产量QTL。在第7染色体RM481-RM2区间,检测到抽穗期、每穗颖花数和产量QTL,野生稻等位基因表现增效作用;其他3个每穗颖花数QTL位点,野生稻等位基因也均具有增效作用。结果表明野生稻携带有增产相关的等位基因,这些有利等位基因无疑是水稻遗传改良可资利用的新资源。     

Simultaneous improvement and genetic dissection of grain yield and its related traits in a backbone parent of hybrid rice (Oryza sativa L.) using selective introgression

Three populations with a total of 125 BC2F3:4 introgression lines (ILs) selected for high yields from three BC2F2 populations were used for genetic dissection of rice yield and its related traits. The progeny testing in replicated phenotyping across two environments and genotyping with 140 polymorphic simple sequence repeat markers allowed the identification of 21 promising ILs that had significantly higher yields than the recurrent parent Shuhui527 (SH527). A total of 94 quantitative trait loci (QTL) were identified using the selective introgression method based on Chi-squared (χ ²) and multi-locus probability tests and the RSTEP-LRT method based on stepwise regression. These QTL were mostly mapped to 12 clusters on seven rice chromosomes. Several important properties of the QTL affecting grain yield (GY) and its related traits were revealed. The first one was the presence of strong and frequent non-random associations between or among QTL that affect low-heritability traits (GY and spikelet number per panicle, SN) in the ILs with high trait values. Second, beneficial alleles at 88.9 % GY and 75 % SN QTL for increased productivity were from the donors, suggesting that direct phenotypic selection for high yield in our introgression breeding program was a powerful way to transfer beneficial alleles at many loci from the donors into SH527. Third, most QTL were in clusters with large effects on multiple traits, which should be the focal points in further investigations and marker-assisted selection in rice. The majority of the QTL identified were expressed only in one of the environments, suggesting that differential expression of QTL in different environments is the primary genetic basis of genotype × environment interaction. Finally, a large variation in both the direction and magnitude of QTL effects was detected for different donor alleles at seven QTL in the same genetic background and environments. This finding suggests the possible presence of functional diversity among the donor alleles at these loci. The promising ILs and QTL identified provide valuable materials and genetic information for further improving the yield potential of SH527, which is a backbone restorer of hybrid rice in China.     

Identification of QTL for growth- and grain yield-related traits in rice across nine locations of Asia

Rice double-haploid (DH) lines of an indica and japonica cross were grown at nine different locations across four countries in Asia. Genotype-by-environment (G x E) interaction analysis for 11 growth- and grain yield-related traits in nine locations was estimated by AMMI analysis. Maximum G x E interaction was exhibited for fertility percentage number of spikelets and grain yield. Plant height was least affected by environment, and the AMMI model explained a total of 76.2% of the interaction effect. Mean environment was computed by averaging the nine environments and subsequently analyzed with other environments to map quantitative trait loci (QTL). QTL controlling the 11 traits were detected by interval analysis using mapmaker/qtl. A threshold LOD of >/=3.20 was used to identify significant QTL. A total of 126 QTL were identified for the 11 traits across nine locations. Thirty-four QTL common in more than one environment were identified on ten chromosomes. A maximum of 44 QTL were detected for panicle length, and the maximum number of common QTL were detected for days to heading detected. A single locus for plant height (RZ730-RG810) had QTL common in all ten environments, confirming AMMI results that QTL for plant height were affected the least by environment, indicating the stability of the trait. Two QTL were detected for grain yield and 19 for thousand-grain weight in all DH lines. The number of QTL per trait per location ranged from zero to four. Clustering of the QTL for different traits at the same marker intervals was observed for plant height, panicle number, panicle length and spikelet number suggesting that pleiotropism and or tight linkage of different traits could be the possible reason for the congruence of several QTL. The many QTL detected by the same marker interval across environments indicate that QTL for most traits are stable and not essentially affected by environmental factors.     

Allele characterization of storage protein loci in the Greek spring wheat cultivars

Genotypes at the storage protein loci Glu-A1, Glu-B1, Glu-D1, Gli-A1, Gli-B1, Gli-D1, Gli-A3 were identified in a group of Greek spring common wheat varieties. These varieties served as the parental forms for producing dihaploid lines. Heterogeneous varieties were revealed.     

Genetic mapping of QTLs for sugar-related traits in a RIL population of Sorghum bicolor L. Moench

The productivity of sorghum is mainly determined by quantitative traits such as grain yield and stem sugar-related characteristics. Substantial crop improvement has been achieved by breeding in the last decades. Today, genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement. We have investigated QTL associated with the sugar components (Brix, glucose, sucrose, and total sugar content) and sugar-related agronomic traits (flowering date, plant height, stem diameter, tiller number per plant, fresh panicle weight, and estimated juice weight) in four different environments (two locations) using a population of 188 recombinant inbred lines (RILs) from a cross between grain (M71) and sweet sorghum (SS79). A genetic map with 157 AFLP, SSR, and EST-SSR markers was constructed, and several QTLs were detected using composite interval mapping (CIM). Further, additive × additive interaction and QTL × environmental interaction were estimated. CIM identified more than five additive QTLs in most traits explaining a range of 6.0–26.1% of the phenotypic variation. A total of 24 digenic epistatic locus pairs were identified in seven traits, supporting the hypothesis that QTL analysis without considering epistasis can result in biased estimates. QTLs showing multiple effects were identified, where the major QTL on SBI-06 was significantly associated with most of the traits, i.e., flowering date, plant height, Brix, sucrose, and sugar content. Four out of ten traits studied showed a significant QTL × environmental interaction. Our results are an important step toward marker-assisted selection for sugar-related traits and biofuel yield in sorghum.     

Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.)

Development of high-yielding wheat varieties with good end-use quality has always been a major concern for wheat breeders. To genetically dissect quantitative trait loci (QTLs) for yield-related traits such as grain yield, plant height, maturity, lodging, test weight and thousand-grain weight, and for quality traits such as grain and flour protein content, gluten strength as evaluated by mixograph and SDS sedimentation volume, an F₁-derived doubled haploid (DH) population of 185 individuals was developed from a cross between a Canadian wheat variety “AC Karma” and a breeding line 87E03-S2B1. A genetic map was constructed based on 167 marker loci, consisting of 160 microsatellite loci, three HMW glutenin subunit loci: Glu-A1, Glu-B1 and Glu-D1, and four STS-PCR markers. Data for investigated traits were collected from three to four environments in Manitoba, Canada. QTL analyses were performed using composite interval mapping. A total of 50 QTLs were detected, 24 for agronomic traits and 26 for quality-related traits. Many QTLs for correlated traits were mapped in the same genomic regions forming QTL clusters. The largest QTL clusters, consisting of up to nine QTLs, were found on chromosomes 1D and 4D. HMW glutenin subunits at Glu-1 loci had the largest effect on breadmaking quality; however, other genomic regions also contributed genetically to breadmaking quality. QTLs detected in the present study are compared with other QTL analyses in wheat.     

Mapping of quantitative trait loci associated with protein expression variation in barley grains

Barley (Hordeum vulgare) is an important cereal crop grown for both the feed and malting industries. Hence, there is great interest to gain deeper insight into the determinants of grain nutritional quality in order to improve the assessment of new traits. Two-dimensional gel electrophoresis was employed for the characterization of the grain proteome of doubled-haploid introgression lines (IL) representing a wild barley genome (Hordeum spontaneum Hs213) within a modern cultivar background (H. vulgare cv. Brenda). Proteome maps were subjected to differential cluster analysis and revealed ILs with similar or different protein expression patterns compared to the Brenda parent. A total of 51 quantitative trait loci for protein expression (pQTL) were detected, and proteins underlying these pQTL were further examined by mass spectrometry. Identification was successful for 49 of the segregating spots and functional annotation of proteins revealed that most proteins are involved in metabolism and disease/defence-related processes. Among those, multigene families of glyceraldehyde-3-phosphate dehydrogenases, heat shock proteins, peroxidases, and serpins were identified. Overall, eight pQTL signals were discovered in two independently grown sets of plants. The mapped spots included protein disulfide isomerase, α-amylase inhibitor BDAI, NADP malic enzyme, adenosine kinase and peroxidase BP1. Specific marker information of proteins involved in developmental events and protein storage as well as in disease- and defence-related processes now allows for targeted breeding approaches to improve the grain quality in barley.     

大豆小区产量及其相关性状QTL间的上位性和环境互作效应

以晋豆23栽培大豆(Glycine max)为母本、灰布支黑豆(ZDD2315,半野生大豆)为父本衍生出447个RIL群体,通过构建SSR遗传图谱及利用混合线性模型分析方法,对2年大豆小区产量及主要植物学性状进行QTL定位,并作加性效应、加性×加性上位互作效应及环境互作效应分析。结果显示,共检测到12个与小区产量、单株粒重、单株茎重、单株粒茎比、有效分枝、主茎节数、株高和结荚高度相关的QTL,分别位于A1、A2、H_1、I、J_2和M连锁群上。其中小区产量、株高、单株粒重、有效分枝和主茎节数均表现为遗传正效应,即增加其性状的等位基因来源于母本晋豆23。同时,检测到11对影响小区产量、单株粒重、单株茎重、株高和结荚高度的加性×加性上位互作效应及环境互作效应的QTL,发现22个QTL与环境存在互作。实验结果表明,上位效应和QE互作效应对大豆小区产量及主要农艺性状的遗传影响很大。进行大豆分子标记辅助育种时,既要考虑效应起主要作用的QTL,又要注重上位性QTL,这样有利于性状的稳定表达和遗传。     

PAY1 improves plant architecture and enhances grain yield in rice

Plant architecture, a complex of the important agronomic traits that determine grain yield, is a primary target of artificial selection of rice domestication and improvement. Some important genes affecting plant architecture and grain yield have been isolated and characterized in recent decades; however, their underlying mechanism remains to be elucidated. Here, we report genetic identification and functional analysis of the PLANT ARCHITECTURE AND YIELD 1 (PAY1) gene in rice, which affects plant architecture and grain yield in rice. Transgenic plants over‐expressing PAY1 had twice the number of grains per panicle and consequently produced nearly 38% more grain yield per plant than control plants. Mechanistically, PAY1 could improve plant architecture via affecting polar auxin transport activity and altering endogenous indole‐3‐acetic acid distribution. Furthermore, introgression of PAY1 into elite rice cultivars, using marker‐assisted background selection, dramatically increased grain yield compared with the recipient parents. Overall, these results demonstrated that PAY1 could be a new beneficial genetic resource for shaping ideal plant architecture and breeding high‐yielding rice varieties.     

In an elite cross of maize a major quantitative trait locus controls one-fourth of the genetic variation for grain yield

Quantitative trait loci (QTLs) for grain yield, dry matter content and test weight were identified in an F₂ segregating population derived from a single cross between two elite maize lines (B73 and A7) and testcrossed to two genetically divergent in breds. Most of the QTLs inferred were consistent across locations, indicating that the expression of the genes influencing the traits under investigation was largely independent of the environment. By using two different tester lines we found that QTLs exhibited by one tester may not necessarily be detected with the second one. Only loci with larger effects were consistent across testers, suggesting that interaction with tester alleles may contribute to the identification of QTLs in a specific fashion. Analysis across both testers revealed four significant QTLs for grain yield that explained more than 35% of the phenotypic variation and showed an overall phenotypic effect of more than 2t/ha. The major QTL for grain yield, located in the proximity of the Nucleolus Organiser Region, accounted for 24.5% of the phenotypic variation for grain yield and showed an average effect of allele substitution of approximately 1 t/ha. Marker-assisted introgression of the superior A7 allele at this locus in the B73 genetic background will not differ from qualitative trait introgression and will eventually lead to new lines having superior testcross performance.     

Quantitative trait loci for leaf chlorophyll fluorescence parameters, chlorophyll and carotenoid contents in relation to biomass and yield in bread wheat and their chromosome deletion bin assignments

Relatively little is known of the genetic control of chlorophyll fluorescence (CF) and pigment traits important in determining efficiency of photosynthesis in wheat and its association with biomass productivity. A doubled haploid population of 94 lines from the wheat cross Chinese Spring × SQ1 was trialled under optimum glasshouse conditions for 4 years to identify quantitative trait loci (QTL) for CF traits including, for the first time in wheat, JIP-test parameters per excited cross section (CS_m): ABS/CS_m, DI_o/CS_m, TR_o/CS_m, RC/CS_m and ET_o/CS_m, key parameters determining efficiency of the photosynthetic apparatus, as well as chlorophyll and carotenoid contents to establish associations with biomass and grain yield. The existing genetic map was extended to 920 loci by adding Diversity Arrays Technology markers. Markers and selected genes for photosynthetic light reactions, pigment metabolism and biomass accumulation were located to chromosome deletion bins. Across all CF traits and years, 116 QTL for CF were located on all chromosomes except 7B, and 39 QTL were identified for pigments on the majority of chromosomes, excluding 1A, 2A, 4A, 3B, 5B, 1D, 2D, 5D, 6D and 7D. Thirty QTL for plant productivity traits were mapped on chromosomes 3A, 5A, 6A, 7A, 1B, 2B, 4B, 6B, 7B, 3D and 4D. A region on chromosome 6B was identified where 14 QTL for CF parameters coincided with QTL for chlorophyll content and grain weight per ear. Thirty-five QTL regions were coincident with candidate genes. The environment was shown to dominate in determining expression of genes for those traits.     

General combining ability of most yield-related traits had a genetic basis different from their corresponding traits per se in a set of maize introgression lines

Evaluation of combining ability is a crucial process in hybrid breeding, and dissection of the genetic basis of combining ability will facilitate hybrid breeding. In this study, molecular markers significantly associated with general combining ability (GCA) of seven yield-related traits and the traits per se were detected in a set of maize introgression lines (ILs) under three environments. Totally 25 and 31 significant loci for GCA and the traits per se were commonly detected under multiple environments, respectively. Correlation analysis and comparison among these significant loci revealed that the genetic basis of GCA of these yield-related traits was generally different from that of the traits per se except for the trait of ear row number. In addition, GCA of the ILs was positively and significantly correlated to the total relative effects of significant GCA loci in the ILs in general, implying that the GCA loci identified in this study would be useful in molecular breeding. Correlation analysis also showed that the GCA of yield per plant was strongly correlated to the GCA of kernel number per row, ear length and 100-kernel-weight, thus these traits were more important in genetic improvement for GCA. Results in this study would provide useful information for hybrid breeding in maize.     

Variation at storage protein loci in winter common wheat cultivars of the central forest-steppe of Ukraine

Genotypes at the gliadin loci Gli-A1, Gli-B1, Gli-D1 and the high-molecular-weight glutenin subunit loci Glu-A1, Glu-B1, Glu-D1 were identified in 77 winter common wheat cultivars developed in the Central Forest Steppe of Ukraine in different periods of time. The highest level of variation was observed at the Gli-A1 locus. Predominant alleles (one or two per locus) were revealed. The comparison of allele frequencies in groups of cultivars developed in different periods of time (before 1996 and in 1996–2007) has demonstrated appearance of new alleles and change of frequencies of existing alleles at the storage protein loci. The high frequency of cultivars with the wheat-rye 1BL/1RS translocation was detected (about 40%). The wheat rye 1AL/1RS translocation was identified in six cultivars developed in the last decade. Four gliadin alleles, Gli-A1w (a marker for the 1AL/1RS translocation), Gli-A1x, Gli-A1y and Gli-B1x, were proposed for cataloging. The article is published in the original.     

Genetic dissection of photosynthetic efficiency traits for enhancing seed yield in chickpea

Understanding the genetic basis of photosynthetic efficiency (PE) contributing to enhanced seed yield per plant (SYP) is vital for genomics‐assisted crop improvement of chickpea. The current study employed an integrated genomic strategy involving photosynthesis pathway gene‐based association mapping, genome‐wide association study, quantitative trait loci (QTL) mapping, and expression profiling. This identified 16 potential single nucleotide polymorphism loci linked to major QTLs underlying 16 candidate genes significantly associated with PE and SYP traits in chickpea. The allelic variants were tightly linked to positively interacting QTLs regulating both enhanced PE and SYP traits as exemplified by a chlorophyll A‐B binding protein‐coding gene. The leaf tissue‐specific pronounced up‐regulated expression of 16 associated genes in germplasm accessions and homozygous individuals of mapping population was evident. Such combinatorial genomic strategy coupled with gene haplotype‐specific association and in silico protein–protein interaction study delineated natural alleles and superior haplotypes from a chlorophyll A‐B binding (CAB) protein‐coding gene and its interacting gene, Timing of CAB Expression 1 (TOC1), which appear to be most promising candidates in modulating chickpea PE and SYP traits. These functionally pertinent molecular signatures identified have efficacy to drive marker‐assisted selection for developing PE‐enriched cultivars with high seed yield in chickpea.     

DNA polymorphisms and haplotype patterns of transcription factors involved in barley endosperm development are associated with key agronomic traits

Background  

Association mapping is receiving considerable attention in plant genetics for its potential to fine map quantitative trait loci (QTL), validate candidate genes, and identify alleles of interest. In the present study association mapping in barley (Hordeum vulgare L.) is investigated by associating DNA polymorphisms with variation in grain quality traits, plant height, and flowering time to gain further understanding of gene functions involved in the control of these traits. We focused on the four loci BLZ1, BLZ2, BPBF and HvGAMYB that play a role in the regulation of B-hordein expression, the major fraction of the barley storage protein. The association was tested in a collection of 224 spring barley accessions using a two-stage mixed model approach.     

利用水稻重组自交系群体对一些重要农艺性状进行基因定位和互作分析

对水稻（OryzasativaL．）籼（indica）、粳（Japonica）交（窄叶青8号×京系17）通过一粒传获得了一个自交9代的重组自交系（RIL）群体,该群体含有107个稳定纯合的株系,通过构建分子连锁图谱,对水稻播抽期、株高、每穗颖花数、每穗实粒数、200粒重和结实率进行数量性状基因座位（QTL）分析,定位了影响播抽期的2个QTLs、株高的2个QTLs、每穗颖花数的2个QTLs和每穗实粒数的1个QTL。其中,控制播抽期的1个QTL即qHD－8为主效基因,控制株高的1个QTL即qPH－1为主效基因,其余为微效基因。同时分析了影响水稻生产力的数量性状基因座位间的互作。结果表明,影响播抽期、株高、每穗颖花数、每穗实粒数和结实率的互适型互作共有24个,对性状有6．2％～10．9％的贡献率。     

Genetic mapping of QTLs affecting productivity and plant architecture in a full-sib cross from non-inbred parents in Cassava (<Emphasis Type="Italic">Manihot esculenta</Emphasis> Crantz)

An attempt was made to identify quantitative trait loci (QTLs) for several productivity and plant architecture traits in a full-sib progeny of 144 individuals from two non-inbred parents in cassava. A molecular linkage map of this cross constructed previously with over 250 markers was the source of molecular markers. The progeny were grown under field conditions at two locations (Palmira and Quilichao) in Colombia and evaluated in 2 years (1998 and 1999) for architecture and productivity traits. Architecture traits evaluated were plant height (PH), branching height (BH), branching levels (BL), branching index (BI), stem portion with leaves (SPL) and leaf area index (LAI). Productivity traits were those related to total dry matter production and distribution, namely fresh root yield (FRY), fresh shoot yield (FSY), harvest index (HI) and the number of storage roots (NR). Phenotypic evaluation of the traits in this population revealed continuous variation for all traits. Broad-sense heritability estimates, ranged from 36% (for NR) to 94% (for BH). Several significant phenotypic correlations were observed between architecture and productivity traits. Primary QTLs, using the single-QTL model, and secondary QTLs, by a primary QTL interaction model, were detected by interval mapping. A total of 30 primary QTLs and 84 secondary QTLs were detected. We identified 35% of detected QTLs in two or more trials, the other QTLs were environment-specific. These results underscore the significant genotype × environment interactions found for most of the traits. Several genomic segments affecting multiple traits were identified and were in agreement with correlation among traits. All QTLs identified for FRY were found associated with either component traits of productivity or architecture traits. This study suggests that QTLs for plant architecture can be used to improve productivity. However an exhaustive search and analysis of QTLs controlling architecture is required before marker-assisted selection (MAS) for increasing productivity can be initiated.Communicated by H. C. Becker     

QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai × Yu8679

A set of 142 winter wheat recombinant inbred lines (RILs) deriving from the cross Heshangmai x Yu8679 were tried in four ecological environments during the seasons 2006 and 2007. Nine agronomic traits comprising mean grain filling rate (GFR(mean)), maximum grain filling rate (GFR(max)), grain filling duration (GFD), grain number per ear (GNE), grain weight per ear (GWE), flowering time (FT), maturation time (MT), plant height (PHT) and thousand grain weight (TGW) were evaluated in Beijing (2006 and 2007), Chengdu (2007) and Hefei (2007). A genetic map comprising 173 SSR markers and two EST markers was generated. Based on the genetic map and phenotypic data, quantitative trait loci (QTL) were mapped for these agronomic traits. A total of 99 putative QTLs were identified for the nine traits over four environments except GFD, PHT and MT, measured in two environments (BJ07 and CD07), respectively. Of the QTL detected, 17 for GFR(mean), 16 for GFR(max), 21 for TGW and 10 for GWE involving the chromosomes 1A, 1B, 2A, 2D, 3A, 3B, 3D, 4A, 4D, 5A, 5B, 6D and 7D were identified. Moreover, 13 genomic regions showing pleiotropic effects were detected in chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4B, 4D, 5B, 6D and 7D; these QTL revealing pleiotropic effects may be informative for a better understanding of the genetic basis of grain filling rate and other yield-related traits, and represent potential targets for multi-trait marker aided selection in wheat.