Relationship between QTLs for preharvest sprouting and alpha-amylase activity in rye grain

Preharvest sprouting (PHS) and high alpha-amylase activity (AA) negatively affect quality of rye grain. The objective of this study was to reveal genetic relationship between PHS and AA by developing a consensus map of QTLs controlling each trait. A method of composite interval mapping (CIM) was used to search for QTLs within the 541 × Ot1-3 and DS2 × RXL10 F₂ mapping populations representing wide variation range of both traits. Sixteen QTLs for AA were detected on chromosomes 1R (3), 2R (2), 3R (2), 4R (3), 5R (3), 6R (2) and 7R (1). Their distribution was not random showing a tendency of QTL location in distal regions of chromosomes. Nine QTLs for AA located on chromosome arms 1RS, 2RL, 3RS, 4RL, 5RS, 5RL, 6RS, 6RL and 7RS coincided with QTLs for PHS. Seven QTLs for AA independent from PHS were detected on chromosome arms 1RL (2), 2RS, 3RL, 4RS, 4RL and 5RL. Four QTLs for PHS not associated with those for AA were identified on chromosomes 1RL, 2RL, 5RL and 7RL. Partial overlapping of the genetic systems controlling AA and PHS suggests that alpha-amylase found in sound grain of rye could be produced through at least three independent mechanisms i.e. PHS at its initial stage, late maturity alpha-amylase (LMA) and/or retained pericarp alpha-amylase (RPAA). Six QTLs co-located on both maps were found on chromosome arms 1RS, 2RS, 5RS, 5RL, 6RS and 6RL. Valuable features of line Ot1-3 i.e. resistance to preharvest sprouting and low alpha-amylase production in ripening grain can be attributed to seven major QTLs from chromosomes 1RL, 2RL, 5RL (2), 6RL and 7R (2). This set of QTLs, identified in line Ot1-3, might be useful in breeding sprouting resistant cultivars of rye.     

利用粳稻染色体片段置换系群体检测水稻抗亚铁毒胁迫有关性状QTL

潜育性水稻田广泛分布于中国、斯里兰卡、印度、印度尼西亚、塞拉里昂、利比亚、尼日利亚、哥伦比亚和菲律宾等国,其中我国南方稻区就有近700万公顷低产潜育性水稻田。该类水稻田还原性强,矿质营养失调,尤以Fe^2 过量积累,对水稻生长发育产生不良的逆境胁迫作用。培育抗亚铁毒的水稻品种是简便、经济有效地提高稻谷产量的重要途径之一。该文利用由粳稻品种Asominori与籼稻品种IR24杂交衍生的Asominori染色体片段置换系(Chromosome Segment Substitution Lines,CSSLs)群体为材料,检测与抗亚铁毒胁迫有关性状QTL。共检测到与抗亚铁毒胁迫有关性状QTL14个,各QTL的LOD值为2．72～6．63。其中检测到与抗亚铁毒胁迫直接有关的性状叶片棕色斑点指数QTL3个,分别位于第3、9、11染色体C515～XNpb279、R2638～C1263和G1465～C950之间,对应的贡献率分别为16．45％、11．16％和28．02％;与其他已发表的定位结果比较发现,位于第三染色体C515～XNpb279间控制叶片棕色斑点指数的QTL与水稻功能图谱上控制叶绿素含量的QTL的位置一致;表明在亚铁毒胁迫条件下,水稻在其叶片表面出现棕色斑点,叶片衰老,产生一些叶绿素降解物或衍生物,以提高叶片细胞对亚铁等重金属毒害的耐受力。另外,在第11染色体G1465～C950之间检测到了控制叶片棕色斑点指数、茎干重和根干重QTL1个,为主效QTL。在第6染色体XNpb386～XNpb342之间检测到控制茎干重、株高、根长和根干重QTL1个,是否与水稻抗亚铁毒有关需要进一步研究。本研究旨在通过定位与抗亚铁毒有关的QTL,借助与之紧密连锁的分子标记有效地聚合这些QTL,培育出抗亚铁毒性强的水稻新种质材料。     

云南软米直链淀粉含量的遗传分析与基因定位

以低直链淀粉( 软米)品种毫木细与高直链淀粉品种桂朝2号杂交F2代分离群体为试验材料,研究水稻低直链淀粉含量的遗传规律和基因定位。结果表明,软米品种毫木细直链淀粉含量受一个隐性主效基因/QTL控制,该基因位点（QTL）与糯性基因(wx)为非等位。除主效QTL外,可能还有微效基因的作用。用SSR标记检测到该主效基因/QTL位于11号染色体上RM224附近,LOD值为15.4,可解释的表型变异率为32%。     

Quantitative trait loci controlling resistance to cadmium rhizotoxicity in two recombinant inbred populations of Arabidopsis thaliana are partially shared by those for hydrogen peroxide resistance

To understand mechanisms of cadmium (Cd) tolerance variation associated with root elongation in Arabidopsis thaliana , quantitative trait loci (QTLs) and epistasis were analyzed using relative root length (RRL: % of the root length in +Cd to −Cd) as a tolerant index. Using the composite interval mapping method, three major QTLs ( P < 0.05) were detected on chromosomes 2, 4 and 5 in the recombinant inbred population derived from a cross between Landsberg erecta (L er −0) and Columbia (Col-4). The highest logarithm of odds (LOD) of 5.6 was detected with the QTL on chromosome 5 (QTL5), which is linked to the genetic marker CDPK9 and explained about 26% of the Cd tolerance variation. There was no significant difference in Cd-translocation ratio from roots to shoots between tolerant and sensitive recombinant inbreed lines (RILs), while greater accumulations of reactive oxygen species were observed in the roots of sensitive RILs. This suggested that accumulation of ROS would explain Cd tolerance variation of the L er /Col RILs, which is mainly controlled by the QTL on chromosome 5. The QTL5 in L er /Col population was also detected as one of the major QTLs controlling tolerances to hydrogen peroxide and to copper, which is another ROS generating rhizotoxic metal. The same chromosomal position was detected as a common major QTL for Cd and hydrogen peroxide tolerances in a different recombinant inbreed (RI) population derived from a cross of Col- gl1 and Kashmir (Kas-1). These data, along with a multitraits QTL analysis in both sets of RILs, suggest that peroxide damage depends on the genotype at a major Cd-tolerant locus on the upper part of chromosome 5.     

QTLs for resistance to preharvest sprouting in rye (<Emphasis Type="Italic">Secale cereale</Emphasis> L.)

Grain quality of rye is often negatively affected by sprouting - a complex trait with a poorly understood genetic background and strong interaction with weather conditions. The aim of this report was to detect the main quantitative trait loci (QTLs) underlying preharvest sprouting resistance in rye, measured as a percentage of sprouted kernels after spraying spikes with water for 7 days. Simple and composite interval mapping, carried out in 3 environments on 94 F3 and F4 families of the cross between sprouting-susceptible (541) and sprouting-resistant (Ot1-3) inbred lines, revealed 5 QTLs located on chromosome arms 1RL, 2RL, 5RL, 6RL and 7RL. The significance of these QTLs was additionally proved by disruptive selection carried out on 5000 F2 plants of the 541 x Ot1-3 cross and continued to the F5 generation of recombinant inbred lines (RIL), which strongly affected allele frequencies at linked marker loci. Resistance to preharvest sprouting showed dominant inheritance except for QPhs.uas-7R.1 (recessive) and QPhs.uas-1R.1 (additive). Results of the present study suggest that introgression of 4-5 QTLs, identified in line Ot1-3, should substantially reduce sprouting risk in rye varieties.     

The genetic contribution to heart rate and heart rate variability in quiescent mice

Recent studies have suggested a genetic component to heart rate (HR) and HR variability (HRV). However, a systematic examination of the genetic contribution to the variation in HR and HRV has not been performed. This study investigated the genetic contribution to HR and HRV using a wide range of inbred and recombinant inbred (RI) mouse strains. Electrocardiogram data were recorded from 30 strains of inbred mice and 29 RI strains. Significant differences in mean HR and total power (TP) HRV were identified between inbred strains and RI strains. Multiple significant differences within the strain sets in mean low-frequency (LF) and high-frequency (HF) power were also found. No statistically significant concordance was found between strain distribution patterns for HR and HRV phenotypes. Genomewide interval mapping identified a significant quantitative trait locus (QTL) for HR [LOD (likelihood of the odds) score = 3.763] on chromosome 6 [peak at 53.69 megabases (Mb); designated HR 1 (Hr1)]. Suggestive QTLs for TP were found on chromosomes 2, 4, 5, 6, and 14. A suggestive QTL for LF was found on chromosome 16; for HF, we found one significant QTL on chromosome 5 (LOD score = 3.107) [peak at 53.56 Mb; designated HRV-high-frequency 1 (Hrvhf1)] and three suggestive QTLs on chromosomes 2, 11 and 15. In conclusion, the results demonstrate a strong genetic component in the regulation of resting HR and HRV evidenced by the significant differences between strains. A lack of correlation between HR and HRV phenotypes in some inbred strains suggests that different sets of genes control the phenotypes. Furthermore, QTLs were found that will provide important insight to the genetic regulation of HR and HRV at rest.     

Detection of quantitative trait loci on chromosome 5R of rye (Secale cereale L.)

 Progenies of an F₂ mapping population were analyzed for quantitative traits to detect QTLs by using marker information from F₂ plants for chromosome 5R. The mapping population was segregating for the major dwarfing gene Ddw1 and the gene Hp1 for hairy peduncle. The only QTL determining plant height was located between HP1 and Ddw1 on the distal part of chromosome 5RL. At the same position a QTL for peduncle length was found, and this trait was closely related to plant height (r=0.895). Since Hp1 and Ddw1 are dominant marker loci, no dominance effect could be estimated. The QTLs for spike length and the number of florets were located near the centromere on 5RL. These two traits were correlated with r=0.824 and showed partial dominance, but these traits were not correlated to plant height and peduncle length. Homoeologous relationships between the QTLs mapped for the first time in rye and those mapped in other Triticeae members are discussed. Received: 8 June 1998 / Accepted: 8 October 1998     

Genetic analysis of tongue size and taste papillae number and size in recombinant inbred strains of mice

Quantitative trait loci (QTLs) analysis has been used to examine natural variation of phenotypes in the mouse somatosensory cortex, hippocampus, cerebellum, and amygdala. QTL analysis has also been utilized to map and identify genes underlying anatomical features such as muscle, organ, and body weights. However, this methodology has not been previously applied to identification of anatomical structures related to gustatory phenotypes. In this study, we used QTL analysis to map and characterize genes underlying tongue size, papillae number, and papillae area. In a set of 43 BXD recombinant inbred (RI) mice (n = 111) and 2 parental strains (C57BL/6J and DBA/2J; n = 7), we measured tongue length, width, and weight. In a subset of 23 BXD RI mice and the parental mice, we measured filiform and fungiform papillae number and fungiform papillae area. Using QTL linkage analysis (through WebQTL), we detected 2 significant and noninteracting QTLs influencing tongue length on chromosomes 5 and 7. We also found a significant QTL on chromosome 19 underlying fungiform papillae area and a suggestive QTL on chromosome 2 linked to fungiform papillae number. From these QTLs, we identified a number of candidate genes within the QTL intervals that include SRY-box containing gene, nebulin-related anchoring protein, and actin-binding LIM protein 1. This study is an important first step in identifying genetic factors underlying tongue size, papillae size, and papillae number using QTL analysis.     

Genetic determinants of obesity-related lipid traits

In our ongoing effort to identify genes influencing the biological pathways that underlie the metabolic disturbances associated with obesity, we performed genome-wide scanning in 2,209 individuals distributed over 507 Caucasian families to localize quantitative trait loci (QTLs), which affect variation of plasma lipids. Pedigree-based analysis using a quantitative trait variance component linkage method that localized a QTL on chromosome 7q35-q36, which linked to variation in levels of plasma triglyceride [TG, logarithm of odds (LOD) score = 3.7] and was suggestive of linkage to LDL-cholesterol (LDL-C, LOD = 2.2). Covariates of the TG linkage included waist circumference, fasting insulin, and insulin:glucose, but not body mass index or hip circumference. Plasma HDL-cholesterol (HDL-C) levels were suggestively linked to a second QTL on chromosome 12p12.3 (LOD = 2.6). Five other QTLs with lower LOD scores were identified for plasma levels of LDL-C, HDL-C, and total cholesterol. These newly identified loci likely harbor genetic elements that influence traits underlying lipid adversities associated with obesity.     

Mapping genetic loci that regulate lipid levels in a NZB/B1NJxRF/J intercross and a combined intercross involving NZB/B1NJ, RF/J, MRL/MpJ, and SJL/J mouse strains

The NZB/B1NJ (NZB) mouse strain exhibits high cholesterol and HDL levels in blood compared with several other strains of mice. To study the genetic regulation of blood lipid levels, we performed a genome-wide linkage analysis in 542 chow-fed F2 female mice from an NZBxRF/J (RF) intercross and in a combined data set that included NZBxRF and MRL/MpJxSJL/J intercrosses. In the NZBxRF F2 mice, the cholesterol and HDL concentrations were influenced by quantitative trait loci (QTL) on chromosome (Chr) 5 [logarithm of odds (LOD) 17-19; D5Mit10] that was in the region identified earlier in crosses involving NZB mice, but two QTLs on Chr 12 (LOD 4.7; D12Mit182) and Chr 19 (LOD 5.7; D19Mit1) were specific to the NZBxRF intercross. Triglyceride levels were affected by two novel QTLs at D12Mit182 (LOD 8.7) and D15Mit13 (LOD 3.5). The combined-cross linkage analysis (1,054 mice, 231 markers) 1) identified four shared QTLs (Chrs 5, 7, 14, and 17) that were not detected in one of the parental crosses and 2) improved the resolution of two shared QTLs. In summary, we report additional loci regulating lipid levels in NZB mice that had not been identified earlier in crosses involving the NZB strain of mice. The identification of shared loci from multiple crosses increases confidence toward finding the QTL gene.     

Genetic mapping of gray leaf spot (GLS) resistance genes in maize

Bulked segregant analysis was used to identify amplified fragment length polymorphism markers (AFLPs) linked to quantitative trait loci (QTLs) involved in the resistance to gray leaf spot (GLS) in maize. By using ten AFLP primer combinations 11 polymorphic markers were identified and converted to sequence- specific PCR markers. Five of the 11 converted AFLPs were linked to three GLS resistance QTLs. The markers were mapped to maize chromosomes 1, 3 and 5 using existing linkage maps of two commercially available recombinant inbred-line populations. Converted restriction fragment length polymorphism markers and microsatellite markers were used to obtain a more-precise localization for the detected QTLs. The QTL on chromosome 1 was localized in bin 1.05/06 and had a LOD score of 21. A variance of 37% was explained by the QTL. Two peaks were visible on chromosome 5, one was localized in bin 5.03/04 and the other in bin 5.05/06. Both peaks had a LOD score of 5, and 11% of the variance was explained by the QTLs. A variance of 8–10% was explained by the QTL on chromosome 3 (bin 3.04). The consistency of the QTLs was tested across two F₂ populations planted in consecutive years. Received: 10.10.00 / Accepted: 26.01.01     

Genomic architecture of alpha-amylase activity in mature rye grain relative to that of preharvest sprouting

Bi-directional selective genotyping (BSG) carried out on two opposite groups of F₉(541 × Ot1-3) recombinant inbred lines (RILs) with extremely low and extremely high alpha-amylase activities in mature (dry) grain of rye, followed by molecular mapping, revealed a complex system of selection-responsive loci. Three classes of loci controlling alpha-amylase activity were discerned, including four major AAD loci on chromosomes 3R (three loci) and 6RL (one locus) responding to both directions of the disruptive selection, 20 AAR loci on chromosomes 2RL (three loci), 3R (three loci), 4RS (two loci), 5RL (three loci), 6R (two loci) and 7R (seven loci) responding to selection for low alpha-amylase activity and 17 AAE loci on chromosomes 1RL (seven loci), 2RS (two loci), 3R (two loci), 5R (two loci) and 6RL (four loci) affected by selection for high alpha-amylase activity. The majority of the discerned AA loci also showed responsiveness to selection for preharvest sprouting (PHS). Two AAD loci on chromosome arm 3RL coincided with PHSD loci. The AAD locus on chromosome arm 3RS was independent from PHS, whereas that on chromosome 6RL belonged to the PHSR class. AAR-PHSR loci were found on chromosomes 4RS (one locus) and 5R (two loci) and AAE-PHSE loci were identified on chromosomes 1RL (one locus) and 5RL (one locus). Some PHSD loci represented the AAE (chromosomes 1RL, 3RS and 3RL) or AAR classes (chromosome 5RL). AAR and AAE loci not related to PHS were found on chromosomes 1RL, 2R, 3RS, 4R, 6RL and 7RL. On the other hand, several PHS loci (1RL, 3RS, 5RL, 6RS and 7RS) had no effect on alpha-amylase activity. Allele originating from the parental line 541 mapped in six AA loci on chromosomes 2R (two loci), 5R (three loci) and 7R (one locus) exerted opposite effects on PHS and alpha-amylase activity. Differences between the AA and PHS systems of loci may explain the weak correlation between these two traits observed among recombinant inbred lines. Strategies for the breeding of sprouting-resistant varieties with low alpha-amylase and high PHS resistance are discussed.     

Mapping quantitative trait loci associated with leaf and stem pubescence in cotton

Leaf pubescence in cotton have a potential for insect pest management. Varying degrees of leaf trichome density in Gossypium species and cultivars have been associated to a series of five genes, referred to as t(1)-t(5). We used two segregating interspecific G. hirsutum x G. barbadense backcross populations developed in our laboratory to assess qualitatively and quantitatively leaf and stem pubescence. QTL analyses were performed using simple and composite interval mapping. Based on both types of measurements and under both types of QTL analyses, nine QTLs met permutation-based thresholds. The nine QTLs mapped to four different chromosome regions. Highest LOD values corresponded to the QTLs detected on c6 (four colocalized QTLs) and on D03 (two QTLs) for which the higher pubescence in the progeny derived from the pubescent G. hirsutum parent alleles. Conversely, on c17 (one QTL) and A01 (two QTLs), the G. hirsutum parental alleles affected negatively pubescence. These results combined with another published study confirm (1) the location in a center region of chromosome 6 of the t(1) locus as a major locus/gene determining leaf pubescence, and (2) additional genes located on seven additional chromosomes have been shown to impart trichome density either positively or negatively. The existence of a high density of PCR-based loci in most of the regions identified as harboring leaf pubescence QTLs, particularly that on chromosome 6, will facilitate future efforts for map-based cloning.     

QTL analysis of bread-making quality in wheat using a doubled haploid population

A set of 187 doubled haploid lines derived from the cross between cvs. Courtot and Chinese Spring was explored for QTLs for three bread-making quality tests: hardness, protein content and strength of the dough (W of alveograph). The scores of the parental lines were quite different except for protein content, and the population showed a wide range of variation. About 350 molecular and biochemical markers were used to establish the genetic map, and technological criteria were evaluated in 1 to 3 years. QTL detection was performed by the ”marker regression” method. The most significant unlinked markers were used in the model as covariates, and the results were tested by bootstrap resampling. For hardness, we confirmed a previously tagged major QTL on chromosome 5DS, and two additional minor QTLs were found on chromosome 1A and 6D, respectively. For protein content two main QTLs were identified on chromosomes 1B and 6A, respectively. For W, three consistent QTLs were detected: two at the same location as those for hardness, on chromosomes 1A and 5D; the third one on chromosome 3B. Therefore, it appeared that except for the Glu-1A locus, storage protein loci were not clearly involved in the genetic control of the criteria studied in the present work. Despite the reasonable size of the population no QTL with interactive effects could be substantially established as measured. All computations were carried out using home-made programmes in Splus language, and these are available upon request. Received: 16 May 1999 / Accepted: 15 October 1999     

Genetic dissection of root growth in rice (Oryza sativa L.). II: mapping quantitative trait loci using molecular markers

Drought is a major abiotic stress of upland rice, and good root growth has been associated with drought avoidance. We report on the genetic mapping of root growth traits in an F₂ population derived from two drought-resistant rice varieties, ‘Bala’ and ‘Azucena’. Restriction fragment length polymorphism (RFLP) between the parents was 32%, and a molecular map with 71 marker loci and 17 linkage groups covering 1280 cM was produced. Quantitative trait loci (QTLs) for eight root growth characteristics were mapped using phenotype data obtained in a hydroponic screen previously described in a companion paper. Using a significance threshold of LOD 2.4, we observed one QTL for maximum root length after 28 days growth on chromosome 11. It had a LOD score of 6.9, explained nearly 30% of the variation and appeared to be largely additive in effect. QTLs for maximum root length after 3, 7, 14 and 21 days of growth were also revealed. Some root-length QTLs, including that on chromosome 11, varied greatly with developmental stage. One QTL for root volume and two QTLs for adventitious root thickness were detected. No QTLs were detected for the length of cells in the mature (fully expanded) zone of adventitious root tips. The results obtained are discussed in the context of previous reports on mapping root growth parameters in rice.     

Mapping QTLs for root morphology of a rice population adapted to rainfed lowland conditions

In the rainfed lowlands, rice ( Oryza sativa L.) develops roots under anaerobic soil conditions with ponded water, prior to exposure to water stress and aerobic soil conditions that arise later in the season. Constitutive root system development in anaerobic soil conditions has been reported to have a positive effect on subsequent expression of adaptive root traits and water extraction during progressive water stress in aerobic soil conditions. We examined quantitative trait loci (QTLs) for constitutive root morphology traits using a mapping population derived from a cross between two rice lines which were well-adapted to rainfed lowland conditions. The effects of phenotyping environment and genetic background on QTLs identification were examined by comparing the experimental data with published results from four other populations. One hundred and eighty-four recombinant inbred lines (RILs) from a lowland indica cross (IR58821/IR52561) were grown under anaerobic conditions in two experiments. Seven traits, categorized into three groups (shoot biomass, deep root morphology, root thickness) were measured during the tillering stage. Though parental lines showed consistent differences in shoot biomass and root morphology traits across the two seasons, genotype-by-environment interaction (GxE) and QTL-by-environment interaction were significant among the progeny. Two, twelve, and eight QTLs for shoot biomass, deep root morphology, and root thickness, respectively, were identified, with LOD scores ranging from 2.0 to 12.8. Phenotypic variation explained by a single QTL ranged from 6% to 30%. Only two QTLs for deep root morphology, in RG256-RG151 in chromosome 2 and in PC75M3-PC11M4 in chromosome 4, were identified in both experiments. Comparison of positions of QTLs across five mapping populations (the current population plus populations from four other studies) revealed that these two QTLs for deep root morphology were only identified in populations that were phenotyped under anaerobic conditions. Fourteen and nine chromosome regions overlapped across different populations as putative QTLs for deep root morphology and root thickness, respectively. PC41M2-PC173M5 in chromosome 2 was identified as an interval that had QTLs for deep root morphology in four mapping populations. The PC75M3-PC11M4 interval in chromosome 4 was identified as a QTL for root thickness in three mapping populations with phenotypic variation explained by a single QTL consistently as large as 20-30%. Three QTLs for deep root morphology were found only in japonica/indica populations but not in IR58821/IR52561. The results identifying chromosome regions that had putative QTLs for deep root morphology and root thickness over different mapping populations indicate potential for marker-assisted selection for these traits.     

Mapping of quantitative trait loci for fire blight resistance in the apple cultivars 'Florina' and 'Nova Easygro'

Fire blight is a devastating bacterial disease of rosaceous plants. Its damage to apple production is a major concern, since no existing control option has proven to be completely effective. Some commercial apple varieties, such as 'Florina' and 'Nova Easygro', exhibit a consistent level of resistance to fire blight. In this study, we used an F1 progeny of 'Florina'?× 'Nova Easygro' to build parental genetic maps and identify quantitative trait loci (QTLs) related to fire blight resistance. Linkage maps were constructed using a set of microsatellites and enriched with amplified fragment length polymorphism (AFLP) markers. In parallel, progeny plants were artificially inoculated with Erwinia amylovora strain CFBP 1430 in a quarantine glasshouse. Shoot length measured 7?days after inoculation (DAI) and lesion length measured 7 and 14 DAI were used to calculate the lesion length as a percentage of the shoot length (PLL1 and PLL2, respectively). Percent lesion length data were log10-transformed (log10(PLL)) and used to perform the Kruskal-Wallis test, interval mapping (IM), and multiple QTL mapping (MQM). Two significant fire blight resistance QTLs were detected in 'Florina'. One QTL was mapped on linkage group 10 by IM and MQM; it explained 17.9% and 15.3% of the phenotypic variation by MQM with log10(PLL1) and log10(PLL2) data, respectively. A second QTL was identified on linkage group 5 by MQM with log10(PLL2) data; it explained 10.1% of the phenotypic variation. Genotyping the plants of 'Florina' pedigree with the microsatellites flanking the QTLs showed that the QTLs on linkage groups 5 and 10 were inherited from 'Jonathan' and 'Starking' (a 'Red Delicious' sport mutation), respectively. Other putative QTLs (defined as QTLs with LOD scores above the chromosomal threshold and below the genome-wide threshold) were detected by IM on linkage groups 5 and 9 of 'Nova Easygro'.     

Genetic loci affecting body weight and fatness in a C57BL/6J × PWK/PhJ mouse intercross

To determine the genetic variation that contributes to body composition in the mouse, we interbred a wild-derived strain (PWK/PhJ; PWK) with a common laboratory strain (C57BL/6J; B6). The parental, F₁, and F₂ mice were phenotyped at 18 weeks old for body weight and composition using dual-energy X-ray absorptiometry (DEXA). A total of 479 (244 male and 235 female) F₂ mice were genotyped for 117 polymorphic markers spanning the autosomes. Twenty-eight suggestive or significant linkages for four traits (body weight, adjusted lean and fat weight, and percent fat) were detected. Of these, three QTLs were novel: one on the proximal portion of Chr 5 for body weight (Bwq8; LOD = 4.7), one on Chr 3 for lean weight (Bwtq13; LOD = 3.6), and one on Chr 11 for percent fat (Adip19; LOD = 5.8). The remaining QTLs overlapped previously identified linkages, e.g., Adip5 on Chr 9. One QTL was sex-specific (present in males only) and seven were sex-biased (more prominent in one sex than the other). Most alleles that increased body weight were contributed by the B6 strain, and most alleles that increased percent fat were contributed by the PWK strain. Eight pairs of interacting loci were identified, none of which exactly overlapped the main-effect QTLs. Many of the QTLs found in the B6 × PWK cross map to the location of previously reported linkages, suggesting that some QTLs are common to many strains (consensus QTLs), but three new QTLs appear to be particular to the PWK strain. The location and type of QTLs detected in this new cross will assist in future efforts to identify the genetic variation that determines the ratio of lean to fat weight as well as body size in mice.     

Mapping QTLs associated with drought avoidance in upland rice

The identification of molecular markers linked to genes controlling drought resistance factors in rice is a necessary step to improve breeding efficiency for this complex trait. QTLs controlling drought avoidance mechanisms were analyzed in a doubled-haploid population of rice. Three trials with different drought stress intensities were carried out in two sites. Leaf rolling, leaf drying, relative water content of leaves and relative growth rate under water stress were measured on 105 doubled haploid lines in two trials and on a sub-sample of 85 lines in the third one. Using composite interval mapping with a LOD threshold of 2.5, the total number of QTLs detected in all trials combined was 11 for leaf rolling, 10 for leaf drying, 11 for relative water content and 10 for relative growth rate under stress. Some of these QTLs were common across traits. Among the eleven possible QTLs for leaf rolling, three QTLs (on chromosomes 1, 5 and 9) were common across the three trials and four additional QTLs (on chromosomes 3, 4 and 9) were common across two trials. One QTL on chromosome 4 for leaf drying and one QTL on chromosome 1 for relative water content were common across two trials while no common QTL was identified for relative growth rate under stress. Some of the QTLs detected for leaf rolling, leaf drying and relative water content mapped in the same places as QTLs controlling root morphology, which were identified in a previous study involving the same population. Some QTL identified here were also located similarly with other QTLs for leaf rolling as reported from other populations. This study may help to chose the best segments for introgression into rice varieties and improvement of their drought resistance.     

Multiple QTLs influence variation in paraoxonase 1 activity in Mexican Americans

Paraoxonase 1 (PON1), a high-density-lipoprotein-associated enzyme known to protect against cellular damage from toxic agents, may also have antioxidant properties. Although the importance of the influence of the PON1 structural locus on chromosome 7q21-22 for variation in the concentration and activity of the enzyme is well-documented, the contribution of other loci is poorly understood. Based on the recent observations of at least one additional quantitative trait locus (QTL) for PON1 activity in pedigreed baboons, we conducted a whole-genome linkage screen for QTLs other than the PON1 structural locus that may influence PON1 activity in humans. We measured PON1 activity in frozen serum for 1,406 individuals in more than 40 extended pedigrees from the San Antonio Family Heart Study (SAFHS). We used a maximum-likelihood-based variance decomposition approach implemented in SOLAR to test for QTLs that may influence PON1 activity. In addition to a QTL for which we detected the strongest, significant evidence (LOD = 31.41) at or near the PON1 structural locus on chromosome 7q21-22, we also localized at least one additional significant QTL on chromosome 12 (LOD = 3.56). Furthermore, we detected suggestive evidence for two more PON-related QTLs on chromosomes 17 and 19. We have provided evidence that other genes, in addition to the well-known ones on chromosome 7, play a role in influencing normal variation in PON1 activity.