Adaptation of tree growth to elevated CO2: quantitative trait loci for biomass in Populus

* Information on the genetic variation of plant response to elevated CO(2) (e[CO(2)]) is needed to understand plant adaptation and to pinpoint likely evolutionary response to future high atmospheric CO(2) concentrations. * Here, quantitative trait loci (QTL) for above- and below-ground tree growth were determined in a pedigree - an F(2) hybrid of poplar (Populus trichocarpa and Populus deltoides), following season-long exposure to either current day ambient CO(2) (a[CO(2)]) or e[CO(2)] at 600 microl l(-1), and genotype by environment interactions investigated. * In the F(2) generation, both above- and below-ground growth showed a significant increase in e[CO(2)]. Three areas of the genome on linkage groups I, IX and XII were identified as important in determining above-ground growth response to e[CO(2)], while an additional three areas of the genome on linkage groups IV, XVI and XIX appeared important in determining root growth response to e[CO(2)]. * These results quantify and identify genetic variation in response to e[CO(2)] and provide an insight into genomic response to the changing environment.     

甘蓝型油菜遗传图谱的构建及单株产量构成因素的QTL分析

采用常规品系04-1139与高产多角果品系05-1054构建的F2代群体为作图群体, 运用SSR(Simple sequence repeat)和SRAP(Sequence-related amplified polymorphism)构建分子标记遗传图谱并对甘蓝型油菜单株产量构成因素进行QTL分析。遗传图谱包含200个分子标记, 分布于19个连锁群上, 总长度1 700.23 cM, 标记间的平均距离8.50 cM。采用复合区间作图法(Composite interval mapping, CIM)对单株产量构成因素(单株有效角果数、每果粒数和千粒重)进行QTL分析, 共检测到12个QTL: 其中单株有效角果数4个QTL, 分别解释表型变异为35.64%、12.96%、28.71%和34.02%; 每果粒数获得5个QTL, 分别解释表型变异为8.41%、7.87%、24.37%、8.57%和14.31%; 千粒重获得３个QTL, 分别解释表型变异为2.33%、1.81%和1.86%。结果表明: 同一性状的等位基因增效作用可以同时来自高值亲本和低值亲本; 文章中与主效QTL连锁的标记可用于油菜产量性状的分子标记辅助选择和聚合育种。     

RiceQTLPro: an integrated database for quantitative trait loci marker mapping in rice plant

The National Agricultural Biotechnology Information Center (NABIC) in South Korea reconstructed a RiceQTLPro database for gene positional analysis and structure prediction of the chromosomes. This database is an integrated web-based system providing information about quantitative trait loci (QTL) markers in rice plant. The RiceQTLPro has the three main features namely, (1) QTL markers list, (2) searching of markers using keyword, and (3) searching of marker position on the rice chromosomes. This updated database provides 112 QTL markers information with 817 polymorphic markers on each of the 12 chromosomes in rice.

Availability

The database is available for free at http://nabic.rda.go.kr/gere/rice/geneticMap/     

数量性状基因座位及其在家禽中的定位

近年来随着现代分子生物学的发展 ,一些高效的分子遗传标记将各种畜禽的遗传图谱研究推向深入。为高密度、覆盖面广的连锁图谱的构建及QTL的定位奠定了基础。有关QTL的基本理论、QTL定位的步骤、QTL的检测方法以及家禽中定位的QTL已经展开了深入的研究 ,但目前QTL定位中存在诸多问题的问题     

A new approach for mapping quantitative trait loci using complete genetic marker linkage maps

A new approach based on nonlinear regression for the mapping of quantitative trait loci (QTLs) using complete genetic marker linkage maps is advanced in this paper. We call the approach joint mapping as it makes comprehensive use of the information from every marker locus on a chromosome. With this approach, both the detection of the existence of QTLs and the estimation of their positions, with corresponding confidence intervals, and effects can be realized simultaneously. This approach is widely applicable because only moments are used. It is simple and can save considerable computer time. It is especially useful when there are multiple QTLs and/or interactions between them on a chromosome.     

Age-dependent quantitative trait loci affecting growth traits in Scottish Blackface sheep

To dissect age-dependent quantitative trait loci (QTL) associated with growth and to examine changes in QTL effects over time, the Gompertz growth model was fitted to longitudinal live weight data on 788 Scottish Blackface lambs from nine half-sib families. QTL were mapped for model parameters and weekly live weights and growth rates using microsatellite markers on chromosomes 1, 2, 3, 5, 14, 18, 20 and 21. QTL significance (using α = 0.05 chromosome-wide significance thresholds, unless otherwise stated) varied with age, and those for growth rate occurred earlier than equivalent QTL for live weight. A chromosome 20 QTL for growth rate was significant from 4 to 9 weeks (maximum significance at 6 weeks) and for maximum growth rate. For live weight, this QTL was significant from 8 to 16 weeks (maximum significance at 12 weeks). A nominally significant chromosome 14 QTL was detected for growth rates from birth to week 2 in the same families and location as an 8-week weight QTL. In addition, at the same position on chromosome 14, a QTL was significant for growth rate for 17–28 weeks (maximum significance at 24 weeks). A chromosome 3 QTL was significant for weights at early ages (birth to week 4) and a growth rate QTL on chromosome 18 was significant from 8 to 12 weeks. Fitting growth curves allowed the combination of information from multiple measurements into a few biologically meaningful variables, and the detection of growth QTL that were not observed from analyses of raw weight data. These QTL describe distinct parts of an animal's growth curve trajectory, possibly enabling manipulation of this trajectory.     

Identifying regions of the wheat genome controlling seed development by mapping expression quantitative trait loci

Statistical methods established for the genetic analysis of quantitative traits can be applied to gene expression data. Quantitative trait locus (QTL) analysis can associate the expression of genes or groups of genes with particular genomic regions, and thereby identify regions regulating gene expression. A segregating population of 41 doubled haploid (DH) lines from the hard red spring wheat cross RL4452 x 'AC Domain' was used to map expression level polymorphisms. This population had previously been mapped with microsatellites, and includes a full QTL analysis for agronomic and seed quality traits. Expression analysis on mRNA from developing seed grown in two field locations was conducted on 39 of the 41 DH lines using the Affymetrix GeneChip Wheat Genome Array. Analysis of the hybridization intensity identified 1484 Affymetrix probe sets in the first location and 10,280 probe sets in the second location, where the hybridization intensity varied significantly between genotypes of the population. A common set of 1455 probe sets differing in intensity between genotypes in both locations was used for mapping, and 542 QTLs were identified that each mapped to a single chromosome interval, illustrating that major gene expression QTLs could be found in wheat. Genomic regions corresponding to multiple gene expression QTLs were identified. Comparison of expression mapping data with physical mapping of wheat expressed sequence tag (EST) sequences using rice synteny, as well as logarithm of odds (LOD) score analysis, showed that both cis- and trans-acting expression QTLs were present. Chromosomes 1D and 4B may contain significant trans-regulatory regions in this population.     

Linkage disequilibrium fine mapping of quantitative trait loci: A simulation study

Recently, the use of linkage disequilibrium (LD) to locate genes which affect quantitative traits (QTL) has received an increasing interest, but the plausibility of fine mapping using linkage disequilibrium techniques for QTL has not been well studied. The main objectives of this work were to (1) measure the extent and pattern of LD between a putative QTL and nearby markers in finite populations and (2) investigate the usefulness of LD in fine mapping QTL in simulated populations using a dense map of multiallelic or biallelic marker loci. The test of association between a marker and QTL and the power of the test were calculated based on single-marker regression analysis. The results show the presence of substantial linkage disequilibrium with closely linked marker loci after 100 to 200 generations of random mating. Although the power to test the association with a frequent QTL of large effect was satisfactory, the power was low for the QTL with a small effect and/or low frequency. More powerful, multi-locus methods may be required to map low frequent QTL with small genetic effects, as well as combining both linkage and linkage disequilibrium information. The results also showed that multiallelic markers are more useful than biallelic markers to detect linkage disequilibrium and association at an equal distance.     

Constructing a new integrated genetic linkage map and mapping quantitative trait loci for vegetative mycelium growth rate in Lentinula edodes

The most saturated linkage map for Lentinula edodes to date was constructed based on a monokaryotic population of 146 single spore isolates (SSIs) using sequence-related amplified polymorphism (SRAP), target region amplification polymorphism (TRAP), insertion–deletion (InDel) markers, and the mating-type loci. Five hundred and twenty-four markers were located on 13 linkage groups (LGs). The map spanned a total length of 1006.1 cM, with an average marker spacing of 2.0 cM. Quantitative trait loci (QTLs) mapping was utilized to uncover the loci regulating and controlling the vegetative mycelium growth rate on various synthetic media, and complex medium for commercial cultivation of L. edodes. Two and 13 putative QTLs, identified respectively in the monokaryotic population and two testcross dikaryotic populations, were mapped on seven different LGs. Several vegetative mycelium growth rate-related QTLs uncovered here were clustered on LG4 (Qmgr1, Qdgr1, Qdgr2 and Qdgr9) and LG6 (Qdgr3, Qdgr4 and Qdgr5), implying the presence of main genomic areas responsible for growth rate regulation and control. The QTL hotspot region on LG4 was found to be in close proximity to the region containing the mating-type A (MAT-A) locus. Moreover, Qdgr2 on LG4 was detected on different media, contributing 8.07 %–23.71 % of the phenotypic variation. The present study provides essential information for QTL mapping and marker-assisted selection (MAS) in L. edodes.     

Fifteen years of quantitative trait loci studies in fish: challenges and future directions

Understanding the genetic basis of phenotypic variation is a major challenge in biology. Here, we systematically evaluate 146 quantitative trait loci (QTL) studies on teleost fish over the last 15 years to investigate (i) temporal trends and (ii) factors affecting QTL detection and fine‐mapping. The number of fish QTL studies per year increased over the review period and identified a cumulative number of 3632 putative QTLs. Most studies used linkage‐based mapping approaches and were conducted on nonmodel species with limited genomic resources. A gradual and moderate increase in the size of the mapping population and a sharp increase in marker density from 2011 onwards were observed; however, the number of QTLs and variance explained by QTLs changed only minimally over the review period. Based on these findings, we discuss the causative factors and outline how larger sample sizes, phenomics, comparative genomics, epigenetics and software development could improve both the quantity and quality of QTLs in future genotype–phenotype studies. Given that the technical limitations on DNA sequencing have mostly been overcome in recent years, a renewed focus on these and other study design factors will likely lead to significant improvements in QTL studies in the future.     

Identification of quantitative trait loci influencing foliar concentrations of terpenes and formylated phloroglucinol compounds in Eucalyptus nitens

Leaves of eucalypt species contain a variety of plant secondary metabolites, including terpenoids and formylated phloroglucinol compounds (FPCs). Both terpene and FPC concentrations are quantitative traits that can show large variation within a population and have been shown to be heritable. The molecular genetic basis of this variation is currently unknown. Progeny from a field trial of a three-generation mapping pedigree of Eucalyptus nitens were assayed for terpenes and FPCs. Quantitative trait loci (QTL) analyses were conducted using a map constructed from 296 markers to locate regions of the genome influencing foliar concentrations of these plant secondary compounds. A large number of significant QTL for 14 traits were located across nine linkage groups, with significant clustering of QTL on linkage groups 7, 8 and 9. As expected, QTL for biosynthetically related compounds commonly colocated, but QTL for unrelated monterpenes and FPCs also mapped closely together. Colocation of these QTL with mapped candidate genes from the various biosynthetic pathways, and subsequent use of these genes in association mapping, will assist in determining the causes of variation in plant secondary metabolites in eucalypts.     

Genetic mapping of quantitative trait loci for aseasonal reproduction in sheep

The productivity and economic prosperity of sheep farming could benefit greatly from more effective methods of selection for year-round lambing. Identification of QTL for aseasonal reproduction in sheep could lead to more accurate selection and faster genetic improvement. One hundred and twenty microsatellite markers were genotyped on 159 backcross ewes from a Dorset × East Friesian crossbred pedigree. Interval mapping was undertaken to map the QTL underlying several traits describing aseasonal reproduction including the number of oestrous cycles, maximum level of progesterone prior to breeding, pregnancy status determined by progesterone level, pregnancy status determined by ultrasound, lambing status and number of lambs born. Seven chromosomes (1, 3, 12, 17, 19, 20 and 24) were identified to harbour putative QTL for one or more component traits used to describe aseasonal reproduction. Ovine chromosomes 12, 17, 19 and 24 harbour QTL significant at the 5% chromosome-wide level, chromosomes 3 and 20 harbour QTL that exceeded the threshold at the 1% chromosome-wide level, while the QTL identified on chromosome 1 exceeded the 1% experiment-wide significance level. These results are a first step towards understanding the genetic mechanism of this complex trait and show that variation in aseasonal reproduction is associated with multiple chromosomal regions.     

Functional mapping of growth and development

Understanding how an organism develops into a fully functioning adult from a mass of undifferentiated cells may reveal different strategies that allow the organism to survive under limiting conditions. Here, we review an analytical model for characterizing quantitative trait loci (QTLs) that underlie variation in growth trajectories and developmental timing. This model, called functional mapping, incorporates fundamental principles behind biological processes or networks that are bridged with mathematical functions into a statistical mapping framework. Functional mapping estimates parameters that determine the shape and function of a particular biological process, thus providing a flexible platform to test biologically meaningful hypotheses regarding the complex relationships between gene action and development.     

Analysis of quantitative trait loci underlying the traits related to chlorophyll content of the flag leaf in rice

A population of 117 doubled haploid (DH) lines derived from the cross of Zhaiyeqing 8 (indica)× Jingxi 17 (japonica) was employed to map quantitative trait loci (QTL) underlying four physiological traits related to chlorophyll contents of the flag leaf. There were significantly positive correlations among chlorophyll a, chlorophyll b and chlorophyll a + b content. Chlorophyll a/b ratio was significantly negatively correlated with chlorophyll b content. These four traits were normally distributed with transgressive segregation, suggesting that they were controlled by multiple minor genes. A total of 11 QTLs were detected for the four traits and they lay on six chromosomes. Each of them explained 9.2%–19.6% of the phenotypic variations, respectively. Of these, two QTLs controlling chlorophyll a content were mapped on chromosomes 2 and 5; four QTLs underlying chlorophyll b content were mapped on chromosomes 2, 3, 5 and 9; three QTLs underlying chlorophyll a + b amount were mapped on chromosomes 3, 5 and 9; two QTLs underlying chlorophyll a/b ratio were mapped on chromosomes 6 and 11. The intrinsic relationship among the four traits and the practical implication in rice breeding are discussed. __________ Translated from Journal of Wuhan University (Science Edition), 2006, 52(6): 751–756 [译自: 武汉大学学报(理学版)]     

Confirmation of quantitative trait loci affecting fatness in chickens

In this report we describe the analysis of an advanced intercross line (AIL) to confirm the quantitative trait locus (QTL) regions found for fatness traits in a previous study. QTL analysis was performed on chromosomes 1, 3, 4, 15, 18, and 27. The AIL was created by random intercrossing in each generation from generation 2 (G₂) onwards until generation 9 (G₉) was reached. QTL for abdominal fat weight (AFW) and/or percentage abdominal fat (AF%) on chromosomes 1, 3 and 27 were confirmed in the G₉ population. In addition, evidence for QTL for body weight at the age of 5 (BW5) and 7 (BW7) weeks and for the percentage of intramuscular fat (IF%) were found on chromosomes 1, 3, 15, and 27. Significant evidence for QTL was detected on chromosome 1 for BW5 and BW7. Suggestive evidence was found on chromosome 1 for AFW, AF% and IF%, on chromosome 15 for BW5, and on chromosome 27 for AF% and IF%. Furthermore, evidence on the chromosome-wise level was found on chromosome 3 for AFW, AF%, and BW7 and on chromosome 27 for BW5. For chromosomes 4 and 18, test statistics did not exceed the significance threshold.     

Mapping of quantitative trait loci affecting behaviour in swine

Behavioural indices in vertebrates are under genetic control at least to some extent. In spite of significant behavioural problems in farm animals, information on the genetic background of behaviour is sparse. The aim of this study was to map QTL for behavioural indices in swine under healthy conditions and after infection with Sarcocystis miescheriana , as behaviour can be significantly influenced by disease . This well-described parasite model subsequently leads to acute (day 14 p.i.), subclinical (day 28 p.i.) and chronic disease (day 42 p.i.), allowing the study and comparison of the behaviour of pigs under four different states of health or disease. The study was based on a well-described Pietrain/Meishan F₂ family that has recently allowed the detection of QTL for disease resistance. We have mapped six genome-wide significant and 24 chromosome-wide significant QTL for six behavioural indices in swine. Six of these QTL (i.e. 20% of total QTL) showed effects on behavioural traits of the healthy pigs (day 0). Some of them (QTL on SSC11 and 18) lost influence on behavioural activities during disease, while the effects of others (QTL on SSC5, SSC8) partly remained during the whole experiment, although with different effects on the distinct behavioural indices. The disease model has been of high relevance to detect effects of gene loci on behavioural indices. Considering the importance of segregating alleles and environmental conditions that allow the identification of the phenotype, we conclude that there are indeed QTL with interesting effects on behavioural indices in swine.     

Analysis of quantitative trait loci underlying the traits related to chlorophyll content of the flag leaf in rice

A population of 117 doubled haploid (DH) lines derived from the cross of Zhaiyeqing 8 (indica) x Jingxi 17 (japonica) was employed to map quantitative trait loci (QTL) underlying four physiological traits related to chlorophyll contents of the flag leaf. There were significantly positive correlations among chlorophyll a, chlorophyll b and chlorophyll a+ b content. Chlorophyll a/b ratio was significantly negatively correlated with chlorophyll b content. These four traits were normally distributed with transgressive segregation, suggesting that they were controlled by multiple minor genes. A total of 11 QTLs were detected for the four traits and they lay on six chromosomes. Each of them explained 9.2%-19.6% of the phenotypic variations, respectively. Of these, two QTLs controlling chlorophyll a content were mapped on chromosomes 2 and 5; four QTLs underlying chlorophyll b content were mapped on chromosomes 2, 3, 5 and 9; three QTLs underlying chlorophyll a+b amount were mapped on chromosomes 3, 5 and 9; two QTLs under-lying chlorophyll a/b ratio were mapped on chromosomes 6 and 1 1. The intrinsic relationship among the four traits and the practical implication in rice breeding are discussed.     

Quantitative trait loci associated with leaf and neck blast resistance in recombinant inbred line population of rice (Oryza sativa).

Blast is an economically important disease of rice. To map genes controlling blast resistance, recombinant inbred lines (RIL) were developed from Khao Dawk Mali 105, an aromatic, blast-susceptible cultivar and the blast resistance donor, CT 9993-5-10-M (CT). A linkage map encompassing 2112 cM was constructed from 141 RILs using 90 restriction fragment length polymorphisms (RFLPs) and 31 simple sequence repeats (SSR). Virulent isolates of blast fungus were identified by screening differential host sets against 87 single-spore isolates collected from the north and northeast of Thailand. Fifteen virulent blast isolates were selected for leaf blast screening. Neck blast was evaluated both under natural conditions and controlled inoculations. Quantitative trait loci (QTLs) for broad resistance spectrum (BRS) to leaf blast were located on chromosomes 7 and 9. In particular, the QTL(ch9) was mapped near the Pi5(t) locus. The QTL(ch7) was located close to a previously mapped partial resistance QTL. Both loci showed significant allelic interaction. Genotypes having CT alleles at both QTL(ch7) and QTL(ch9) were the most resistant. Two neck-blast QTLs were mapped on chromosomes 5 and 6. The inconsistent map locations between the leaf and neck blast QTLs indicate the complexity of fixing both leaf and neck blast resistance. The coincidence of BRS and field resistance QTLs on chromosome 7 supports the idea that BRS may reflect the broad resistance spectrum to leaf blast in rice. These findings laid the foundation for the development of a marker-assisted scheme for improving Khoa Dawk Mali 105 and the majority of aromatic Thai rice varieties that are susceptible to blast.     

Sequential sampling in determining linkage between marker loci and quantitative trait loci

Summary As compared to classical, fixed sample size techniques, simulation studies showed that a proposed sequential sampling procedure can provide a substantial decrease (up to 50%, in some cases) in the mean sample size required for the detection of linkage between marker loci and quantitative trait loci. Sequential sampling with truncation set at the required sample size for the non-sequential test, produced a modest further decrease in mean sample size, accompanied by a modest increase in error probabilities. Sequential sampling with observations taken in groups produced a noticeable increase in mean sample size, with a considerable decrease in error probabilities, as compared to straightforward sequential sampling. It is concluded that sequential sampling has a particularly useful application to experiments aimed at investigating the genetics of differences between lines or strains that differ in some single outstanding trait.