Multiple cross mapping (MCM) markedly improves the localization of a QTL for ethanol-induced activation

This study examines the use of multiple cross mapping (MCM) to reduce the interval for an ethanol response QTL on mouse chromosome 1. The phenotype is the acute locomotor response to a 1.5-g/kg i.p. dose of ethanol. The MCM panel consisted of the six unique intercrosses that can be obtained from the C57BL/6J (B6), DBA/2J (D2), BALB/cJ (C) and LP/J (LP) inbred mouse strains (N ≥ 600/cross). Ethanol response QTL were detected only with the B6xD2 and B6xC intercrosses. For both crosses, the D2 and C alleles were dominant and decreased ethanol response. The QTL information was used to develop an algorithm for sorting and editing the chromosome 1 Mit microsatellite marker set ( http://www.jax.org ) . This process yielded a cluster of markers between 82 and 85 cM (MGI). Evidence that the QTL was localized in or near this interval was obtained by the analysis of a sample ( n  = 550) of advanced cross heterogenous stock animals. In addition, it was observed that one of the BXD recombinant inbred strains (BXD-32) had a recombination in the interval of interest which produced the expected change in behavior. Overall, the data obtained suggest that the information available within existing genetic maps coupled with MCM data can be used to reduce the QTL interval. In addition, the MCM data set can be used to interrogate gene expression data to estimate which polymorphisms within the interval of interest are relevant to the QTL.     

Detection of grain protein content QTLs across environments in tetraploid wheats

Grain protein content (GPC) is an important quality factor in both durum and bread wheats. GPC is considered to be a polygenic trait influenced by environmental factors and management practice. The objectives of this study were both to compare the quantitative trait loci (QTL) for GPC in a population of 65 recombinant inbred lines of tetraploid wheats evaluated in three locations for several years (eight data sets), and to investigate the genetic relationship among GPC and grain yield. QTLs were determined based on the Messapia × dicoccoides linkage map which covers 217 linked loci on the 14 chromosomes with 42 additional loci as yet unassigned to linkage groups. The map extends to 1352 cM; the average distance between adjacent markers was 6.3 cM. Seven QTLs for GPC, located on the chromosome arms 4BS, 5AL, 6AS (two loci), 6BS, 7AS and 7BS, were detected that were significant in at least one environment at P<0.001 or in at least two environments at P<0.01. One QTL was significant in all but one environment, two were significant in four or five environments, and four were significant in two out of eight environments. Six out of seven protein content QTLs had pleiotropic effects or were associated to QTLs for grain yield and explained the negative correlation among GPC and yield components. The present results support the concept that studies conducted in a single environment are likely to underestimate the number of QTLs that can influence a trait and that the phenotypic data for a quantitative trait should be collected over a range of locations to identify putative QTLs and determine their phenotypic effects.     

Toward positional cloning of Vgt1, a QTL controlling the transition from the vegetative to the reproductive phase in maize

Vgt1 (Vegetative to generative transition 1) is a quantitative trait locus (QTL) for flowering time in maize (Zea mays L.). Vgt1 was initially mapped in a ca. 5-cM interval on chromosome bin 8.05, using a set of near-isogenic lines (NILs) in the genetic background of the late dent line N28, with the earliness allele introgressed from the early variety Gaspé Flint. A new large mapping population was produced by crossing N28 and one early NIL with a ca. 6-cM long Gaspé Flint introgression at the Vgt1 region. Using PCR-based assays at markers flanking Vgt1, 69 segmental NILs homozygous for independent crossovers near the QTL were developed. When the NILs were tested in replicated field trials for days to pollen shed (DPS) and plant node number (ND), the QTL followed a Mendelian segregation. Using bulk segregant analysis and AFLP profiling, 17 AFLP markers linked to the QTL region were identified. Statistical analysis indicated a substantial coincidence of the effects of Vgt1 on both DPS and ND. Vgt1 was mapped at ca. 0.3 cM from an AFLP marker. As compared to DPS, the higher heritability of ND allowed for a more accurate assessment of the effects of Vgt1. The feasibility of the positional cloning of Vgt1 is discussed.     

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.     

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     

Fine linkage mapping enables dissection of closely linked quantitative trait loci for seed dormancy and heading in rice

Two quantitative trait loci (QTLs) for seed dormancy (tentatively designated Sdr1) and heading date (Hd8) have been mapped to approximately the same region on chromosome 3 by interval mapping of backcross inbred lines derived from crosses between the rice cultivars Nipponbare (japonica) and Kasalath (indica). To clarify whether Sdr1 and Hd8 could be dissected genetically, we carried out fine-scale mapping with an advanced backcross progeny. We selected a BC₄F₁ plant, in which a small chromosomal region including Sdr1 and Hd8, on the short arm of chromosome 3, remained heterozygous, whereas all the other chromosomal regions were homozygous for Nipponbare. Days-to-heading and seed germination rate in the BC₄F₂ plants showed continuous variation. Ten BC₄F₂ plants with recombination in the vicinity of Sdr1 and Hd8 were selected on the basis of the genotypes of the restriction fragment length polymorphism (RFLP) markers flanking both QTLs. Genotypes of those plants for Sdr1 and Hd8 were determined by advanced progeny testing of BC₄F₄ families. Sdr1 was mapped between the RFLP markers R10942 and C2045, and co-segregated with C1488. Hd8 was also mapped between C12534S and R10942. Six recombination events were detected between Sdr1 and Hd8. These results clearly demonstrate that Sdr1 and Hd8 were tightly linked. Nearly isogenic lines for Sdr1 and Hd8 were selected by marker-assisted selection.Communicated by D. Mackill     

Detection of QTLs for Stagonospora glume blotch resistance in Swiss winter wheat

Stagonospora nodorum is the causal agent of the Stagonospora glume blotch disease in hexaploid wheat. The Swiss winter bread wheat cv. 'Arina' has a highly effective, durable and quantitative glume blotch resistance. We studied 240 single seed descent (SSD)-derived lines of an 'Arina × Forno' F_5:7 population to identify and map quantitative trait loci (QTLs) for glume blotch resistance under natural infestation. Using composite interval mapping (CIM) and LOD>4.5, we detected two chromosomal regions on chromosome arms 3BS and 4BL which were specifically associated with glume blotch resistance. These identified QTLs were designated QSng.sfr-3BS and QSng.sfr-4BL, respectively. QSng.sfr-3BS peaked at the locus Xgwm389 in the telomeric region of the short arm of chromosome 3B and explained 31.2% of the observed phenotypic variance for the resistance within the population. The responsible QSng.sfr-3BS allele originated from the resistant parent 'Arina'. The QTL QSng.sfr-4BL (19.1%) mapped to chromosome arm 4BL ('Forno' allele) very close to two known genes, TaMlo and a catalase (Cat). Both QTL alleles combined could enhance the resistance level by about 50%. Additionally, they showed significant epistatic effects (4.4%). We found PCR-based microsatellite markers closely linked to QSng.sfr-3BS (gwm389) and QSng.sfr-4BL (gwm251) which make marker-assisted selection (MAS) for Stagonospora glume blotch resistance feasible. We also found one resistance QTL, QSng.sfr-5BL, on the long arm of chromosome 5B which overlapped with QTLs for plant height as well as heading time.Communicated by H. C. Becker     

Molecular marker dissection of rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) plant architecture under temperate and tropical climates

Rice (Oryza sativa L.) plants develop vertically with shoot elongation and horizontally with tillering. The purpose of this study was to identify and characterize genomic regions influencing the rice plant architecture by quantitative trait locus (QTL) analysis for the component traits: culm length (CL), panicle length (PnL), panicle number (PnN) and tiller number (TN). For this QTL analysis, 191 recombinant inbred lines (F₇) derived from a cross of Milyang 23 (M23) and Akihikari (AK) were grown in 1995, 1996 and 1997 (May–Oct) in Joetsu, Japan (temperate climate), and in the 2000 dry season (Jan–Apr), the 2000 wet season (Jun–Oct) and the 2001 dry season in Los Baños, The Philippines (tropical climate). Results showed that rice plant architecture was influenced by 19 genomic regions categorized into five groups. In Group I, two regions (on chrs. 6 and 11) affected shoot elongation (CL and PnL) and tillering (PnN and TN) in opposite directions more significantly in Los Baños than in Joetsu. In Group II, two regions (chrs. 3 and 12) affected shoot elongation, whereas in Group III, five regions [chrs. 1 (two), 2, 3 and 9] affected only culm length (CL). Expressions of four regions of Group III were influenced by either tropical or temperate environments. In Group IV, seven regions (chrs. 1, 2, 4, 5, 6, 8 and 9) controlled panicle development (PnN or PnL), and in Group V, three regions (chrs. 1, 2 and 3) regulated tillering (PnN or TN). Characterizing these 19 genomic regions provided a detailed analysis of rice plant architecture with emphasis on the multiple effect and environmental responsive regions.Communicated by D. Mackill     

Precise mapping of a locus affecting grain protein content in durum wheat

Grain protein content (GPC) is an important factor in pasta and breadmaking quality, and in human nutrition. It is also an important trait for wheat growers because premium prices are frequently paid for wheat with high GPC. A promising source for alleles to increase GPC was detected on chromosome 6B of Triticum turgidum var. dicoccoides accession FA-15-3 (DIC). Two previous quantitative trait locus (QTL) studies found that the positive effect of DIC-6B was associated to a single locus located between the centromere and the Nor-B2 locus on the short arm of chromosome 6B. Microsatellite markers Xgwm508 and Xgwm193 flanking the QTL region were used in this study to develop 20 new homozygous recombinant substitution lines (RSLs) with crossovers between these markers. These 20 RSLs, plus nine RSLs developed in previous studies were characterized with four new RFLP markers located within this chromosome segment. Grain protein content was determined in three field experiments organized as randomized complete block designs with ten replications each. The QTL peaks for protein content were located in the central region of a 2.7-cM interval between RFLP markers Xcdo365 and Xucw67 in the three experiments. Statistical analyses showed that almost all lines could be classified unequivocally within low- and high- protein groups, facilitating the mapping of this trait as a single Mendelian locus designated Gpc-6B1. The Gpc-6B1 locus was mapped 1.5-cM proximal to Xcdo365 and 1.2-cM distal to Xucw67. These new markers can be used to reduce the size of the DIC chromosome segment selected in marker-assisted selection programs. Markers Nor-B2 and Xucw66 flanking the previous two markers can be used to select against the DIC segment and reduce the linkage drag during the transfer of Gpc-6B1 into commercial bread and pasta wheat varieties. The precise mapping of the high GPC gene, the high frequency of recombinants recovered in the targeted region, and the recent development of a tetraploid BAC library including the Gpc-6B1 DIC allele are the first steps towards the map-based cloning of this gene.Communicated by J. Dvorak     

Efficient construction of high-density linkage map and its application to QTL analysis in barley

Using a High Efficiency Genome Scanning (HEGS) system and recombinant inbred (RI) lines derived from the cross of Russia 6 and H.E.S. 4, a high-density genetic map was constructed in barley. The resulting 1,595.7-cM map encompassed 1,172 loci distributed on the seven linkage groups comprising 1,134 AFLP, 34 SSR, three STS and vrs1 (kernel row type) loci. Including PCR reactions, gel electrophoresis and data processing, 6 months of work by a single person was sufficient for the whole mapping procedure under a reasonable cost. To make an appraisal of the resolution of genetic analysis for the 95 RI lines based on the constructed linkage map, we measured three agronomic traits: plant height, spike exsertion length and 1,000-kernel weight, and the analyzed quantitative trait loci (QTLs) associated with these traits. The results were compared on the number of detected QTLs and their effects between a high-density map and a skeleton map constructed by selected AFLP and anchor markers. The composite interval mapping on the high-density map detected more QTLs than the other analyses. Closely linked markers with QTLs on the high-density map could be powerful tools for marker-assisted selection in barley breeding programs and further genetic analyses including an advanced backcross analysis or a map-based cloning of QTL. Electronic Supplementary Material Supplementary material is available in the online version of this article at Communicated by J.S. Heslop-Harrison