Fine Mapping of the Body Fat QTL on Human Chromosome 1q43

IntroductionEvidence for linkage and association of obesity-related quantitative traits to chromosome 1q43 has been reported in the Quebec Family Study (QFS) and in populations of Caribbean Hispanic ancestries yet no specific candidate locus has been replicated to date.MethodsUsing a set of 1,902 single nucleotide polymorphisms (SNPs) genotyped in 525 African American (AA) and 391 European American (EA) women enrolled in the NIEHS uterine fibroid study (NIEHS-UFS), we generated a fine association map for the body mass index (BMI) across a 2.3 megabase-long interval delimited by RGS7 (regulator of G-protein signaling 7) and PLD5 (Phospholipase D, member 5). Multivariable-adjusted linear regression models were fitted to the data to evaluate the association in race-stratified analyses and meta-analysis.ResultsThe strongest associations were observed in a recessive genetic model and peaked in the 3’ end of RGS7 at intronic rs261802 variant in the AA group (p = 1.0 x 10⁻⁴) and in meta-analysis of AA and EA samples (p = 9.0 x 10⁻⁵). In the EA group, moderate associations peaked at rs6429264 (p = 2.0 x 10⁻³) in the 2 Kb upstream sequence of RGS7. In the reference populations for the European ancestry in the 1,000 genomes project, rs6429264 occurs in strong linkage disequilibrium (D’ = 0.94) with rs1341467, the strongest candidate SNP for total body fat in QFS that failed genotyping in the present study. Additionally we report moderate associations at the 3’ end of PLD5 in meta-analysis (3.2 x 10⁻⁴ ≤ p ≤ 5.8 x 10⁻⁴).ConclusionWe report replication data suggesting that RGS7, a gene abundantly expressed in the brain, might be a putative body fat QTL on human chromosome 1q43. Future genetic and functional studies are required to substantiate our observations and to potentially link them to the neurobehavioral phenotypes associated with the RGS7 region.     

Data-Driven Reversible Jump for QTL Mapping

We propose a birth–death–merge data-driven reversible jump (DDRJ) for multiple-QTL mapping where the phenotypic trait is modeled as a linear function of the additive and dominance effects of the unknown QTL genotypes. We compare the performance of the proposed methodology, usual reversible jump (RJ) and multiple-interval mapping (MIM), using simulated and real data sets. Compared with RJ, DDRJ shows a better performance to estimate the number of QTLs and their locations on the genome mainly when the QTLs effect is moderate, basically as a result of better mixing for transdimensional moves. The inclusion of a merge step of consecutive QTLs in DDRJ is efficient, under tested conditions, to avoid the split of true QTL’s effects between false QTLs and, consequently, selection of the wrong model. DDRJ is also more precise to estimate the QTLs location than MIM in which the number of QTLs need to be specified in advance. As DDRJ is more efficient to identify and characterize QTLs with smaller effect, this method also appears to be useful and brings contributions to identifying single-nucleotide polymorphisms (SNPs) that usually have a small effect on phenotype.     

Mapping QTL for agronomic traits in breeding populations

Detection of quantitative trait loci (QTL) in breeding populations offers the advantage that these QTL are of direct relevance for the improvement of crops via knowledge-based breeding. As phenotypic data are routinely generated in breeding programs and the costs for genotyping are constantly decreasing, it is tempting to exploit this information to unravel the genetic architecture underlying important agronomic traits in crops. This review characterizes the germplasm from breeding populations available for QTL detection, provides a classification of the different QTL mapping approaches that are available, and highlights important considerations concerning study design and biometrical models suitable for QTL analysis.     

水稻籽粒锌含量的QTL 定位

锌元素的营养失衡已成为影响人类健康的最重要因素之一, 籽粒锌含量的QTL(quantitative trait loci)定位对研究富锌水稻的遗传育种具有重要的意义。以水稻(Oryza sativa L.)亲本奉新红米和明恢100杂交的145个株系的F2群体为实验材料, 利用92个SSR(simple sequence repeat)标记对水稻籽粒锌含量进行了QTL定位, 共检测到3个QTLs , 分别定位于第3、6和11染色体上, 对表型变异的贡献率分别为4.97%、12.75%和7.74%。其中位于第3染色体上的分子标记RM186和RM168之间的QZN3对表型变异的贡献率最大, 其增效等位基因来自亲本明恢100, 表现为部分显性。3个QTLs 的联合贡献率为25.46%, 具有基因累加效应。该研究结果有利于深入理解水稻锌含量的遗传基础, 为锌含量的QTL精细定位、基因克隆和分子标记辅助选择提供依据。     

作物QTL定位常用作图群体

作物大多重要农艺性状是数量性状,受多基因控制,基因之间及基因与环境之间都会发生互作,这为研究带来了很大的不便。因此,好的QTL作图群体,是研究QTL间的互作、QTL与环境的互作、QTL定位以及基因克隆的最根本保障。随着分子标记技术的发展,QTL定位的作图群体也在不断的发展并逐渐满足研究者对于QTL的精细定位及基因克隆等研究的进一步要求。文章主要综述了作物QTL定位常用作图群体的构建及优缺点。     

水稻籽粒锌含量的QTL定位

锌元素的营养失衡已成为影响人类健康的最重要因素之一,籽粒锌含量的QTL（quantitative trait loci）定位对研究富锌水稻的遗传育种具有重要的意义。以水稻（Oryzasativa L．）亲本奉新红米和明恢100杂交的145个株系的F2群体为实验材料,利用92个SSR（simple sequence repeat）标记对水稻籽粒锌含量进行了QTL定位,共检测到3个QTLs,分别定位于第3、6和11染色体上,对表型变异的贡献率分别为4．97％、12．75％和7．74％。其中位于第3染色体上的分子标记RM186和RM168之间的QZN3对表型变异的贡献率最大,其增效等位基因来自亲本明恢100,表现为部分显性。3个QTLs的联合贡献率为25．46％。具有基因累加效应。该研究结果有利于深入理解水稻锌含量的遗传基础,为锌含量的QTL精细定位、基因克隆和分子标记辅助选择提供依据。     

小麦籽粒品质性状的QTL分析

利用小麦中国春(母本)和兰考大粒(父本)F2群体构建了169个标记的分子遗传图谱,将F2∶3家系分别种植于3个环境中,利用基于完备区间混合模型的单环境作图模型和多环境作图模型对小麦籽粒容重、硬度、蛋白含量和结合水含量性状进行了QTL分析。结果显示:(1)两种作图模型下,检测到容重的6个共同QTL(QTW-6B-6、QTW-7B-6、QTW-7B-9、QTW-5D-2、QTW-6D-1、QTW-6D-4),单环境模型下遗传贡献率为1.99%~6.57%,多环境模型下遗传贡献率为3.66%~20.07%,其中QM TW-7B-9、QM TW-6D-1和QM TW-6D-4在多环境模型中表现为主效QTL。(2)检测到硬度的3个共同QTL(QHD-4A-5、QHD-7A-1和QHD-7B-9),单环境模型下的遗传贡献率为6.00%~6.95%,多环境模型中遗传贡献率为5.43%~9.64%。(3)检测到蛋白含量1个共同QTL(QPR-6D-1),单环境模型下的遗传贡献率为5.39%,多环境模型中遗传贡献率为10.06%,表现为主效QTL。(4)检测到籽粒结合水含量1个共同QTL(QMO-1B-4),单环境模型下的遗传贡献率为39.20%,多环境模型下的遗传贡献率为75.01%,均表现为主效QTL。(5)1B染色体上存在同时控制籽粒容重、硬度、蛋白和结合水含量的QTL,说明1B染色体对小麦品质的影响可能很大。研究表明,小麦容重、硬度、蛋白含量、结合水含量的遗传主要受加性效应控制。该研究初步定位的一些重要QTL可为进一步精细定位、基因挖掘和育种早代品质性状分子标记辅助选择提供依据。     

作物耐旱性QTL定位和分析的思路

干旱是非生物胁迫中对作物生长和产量影响最严重的胁迫之一.作物的耐旱性受数量性状位点(QTL)的控制,存在复杂的基因/QTL互作和与环境的互作.对作物耐旱相关性状QTL进行定位和分析是耐旱研究的重点之一.本文通过对目前研究中涉及到的作物耐旱性特点、耐旱QTL分析的技术路线与新方法,表型鉴定以及耐旱性QTL互作分析等方面进行了比较系统的阐述,旨在为作物耐旱性QTL定位及未来的分子标记辅助选择提供有益的借鉴.     

Mapping of QTL for downy mildew resistance in maize

Quantitative trait loci (QTLs) of maize involved in mediating resistance to Peronosclerospora sorghi, the causative agent of sorghum downy mildew (SDM), were detected in a population of recombinant inbred lines (RILs) derived from the Zea mays L. cross between resistant (G62) and susceptible (G58) inbred lines. Field tests of 94 RILs were conducted over two growing seasons using artificial inoculation. Heritability of the disease reaction was high (around 70%). The mapping population of the RILs was also scored for restriction fragment length polymorphic (RFLP) markers. One hundred and six polymorphic RFLP markers were assigned to ten chromosomes covering 1648 cM. Three QTLs were detected that significantly affected resistance to SDM combined across seasons. Two of these mapped quite close together on chromosome 1, while the third one was on chromosome 9. The percentage of phenotypic variance explained by each QTL ranged from 12.4% to 23.8%. Collectively, the three QTLs identified in this study explained 53.6% of the phenotypic variation in susceptibility to the infection. The three resistant QTLs appeared to have additive effects. Increased susceptibility was contributed by the alleles of the susceptible parent. The detection of more than one QTL supports the hypothesis that several qualitative and quantitative genes control resistance to P. sorghi.     

一个基于熵的精细定位数量性状位点的指数

针对数量性状位点的精细定位,本文采用群体的极端样本,利用稠密的标记位点,通过比较标记的熵和条件熵,给出了一个基于熵的指数。该指数是标记基因和性状位点间连锁不平衡系数的函数,它不依赖于标记基因的频率。该指数对应我们之前提出的数量性状位点精细定位的哈迪-温伯格不平衡(HWD)指数,但在精细定位数量性状位点时,本文提出的指数的效能要高于哈迪-温伯格不平衡(HWD)指数。通过计算机模拟,文章调查了不同遗传参数下该指数的性质。模拟结果表明该指数用作精细定位是有效的。     

植物QTL定位方法的研究进展

本文系统地介绍了QTL定位的单一标记分析法、区间作图法以及复合区间作图法、混合显性模型的分析方法,概述了一些主要定位方法的分析原理、存在的主要优缺点。单一标记分析法可以采用方差分析、回归分析或似然比检验的方法分析。区间作图法和复合区间作图法是基于两个相邻标记的QTL定位方法,可采用回归分析或最大似然法分析。复合区间作图法在模型中包括了与其他QTL连锁的标记,可以提高作图的精度和效率。混合线性模型的QTL定位方法可以包括复杂的遗传效应及QTL与环境的互作效应,具有更广阔的应用前景。 Abstract:QTL mapping methods are reviewed for single-marker mapping,interval mapping,composite interval mapping,and mixed-model based method.Statistical approaches along with their properties are discussed for the mapping methods.ANOVA,regression method and likelihood ratio test can be applied in single-marker mapping.Interval mapping and composite interval mapping can be conducted,based on two interval markers,by regression method and maximum likelihood method.Since markers linked with other QTLs are include in the model,composite interval mapping is more precision and powerful.Mapping QTL by mixed-model approaches is more applicable when complicated QTL effects as well as QTL by environment interaction are analyzed.     

Mapping QTL for water regime in spring bread wheat

For the first time, the authors assessed and mapped the chromosome QTLs (Quantitative Trait Loci) for the manifestation of morpho-physiological and agronomic indices of plant water status and related quantitative traits, such as plant height, weight, and dry matter content in spring bread wheat (Triticum aestivum L.). Following the study of ten agronomic traits, 13 QTLs were mapped on linkage groups 1A, 1B, 2B, 2D, 4A, 5A, 5B, 5D, 6A, and 6D. Some of the identified QTLs concurrently determined several traits. The physiological components of water status were shown to correlate with quantitative traits in wheat plants, such as plant height, weight, and dry matter content, and the correlation coefficients were calculated for all traits under study. Water retention capacity after 3 h correlated with water retention capacity after 24 h (r _xy = 0.47). The correlations were also established between water retention capacity after 3 h and plant height at booting stage (r _xy = 0.29) and between water retention capacity after 3 h and plant dry weight (r _xy = 0.33). Statistical calculations supported generally observed negative correlation (up to ?1) between leaf water and dry matter contents, as well as between the root indices of variance in the mapping population of wheat lines. The results obtained in the present study will promote future efforts to fine-map the genes residing within the identified QTLs, to eventually clone these genes in order to establish the physiological mechanisms for maintaining water homeostasis in higher plant cells and to accomplish the practical implementation of marker-assisted assessment of water status in wheat plants studied on the basis of morpho-physiological and economical indices.     

Mapping yield-associated QTL in globe artichoke

Globe artichoke (Cynara cardunculus var. scolymus), whose immature inflorescences (capitula) are consumed as a vegetable all over the world, contributes significantly to the agricultural economy of the Mediterranean basin. Here, we describe a QTL (quantitative trait loci) analysis aimed at elucidating the mode of inheritance of seven main and first-order capitulum traits. Mapping was carried out in an F₁ population obtained by crossing a globe artichoke with a cultivated cardoon (C. cardunculus var. altilis). A total of 100 QTL associated with the seven capitulum traits were mapped to 23 chromosomal regions, scattered over 12 of the 17 linkage groups. Among these, 73 were expressed in both growing seasons, while the others were only detected in one season. Up to nine QTL per trait were identified, and major QTL, responsible for some 20 % of the phenotypic variation, were detected for capitulum length, diameter, shape index and fresh weight. The QTL for correlated traits frequently co-localized, most likely due to pleiotropy. This study represents the first report on yield traits QTL in globe artichoke. The QTL identified, along with linked markers, particularly those located in four hot-spot QTL regions are of practical interest for crop improvement based on marker-assisted breeding.     

水稻抽穗期QTL定位及候选基因分析

水稻(Oryza sativa)抽穗期是决定产量和品质的重要性状,在育种、制种及引种驯化过程中发挥重要作用。将热研2号(O. sativa subsp. japonica cv.‘Nekken2’)和华占(O. sativa subsp. indica cv.‘HZ’)杂交获得F₁代,经连续多代自交得到120个重组自交系(RILs)群体。在常规水肥管理条件下,对120个RILs株系的抽穗时间进行统计分析。利用已构建好的高密度遗传图谱,对水稻抽穗期相关性状进行QTL定位分析,结果共检测到11个QTLs,分别位于第1、3、4、5、6、8和12号染色体上,其中1个LOD值高达5.75。通过分析QTLs区间内的候选基因,筛选出可能影响两亲本抽穗期的相关基因,并利用实时定量PCR进行基因表达量分析,发现LOC＿Os03g03070、LOC＿Os03g50310、LOC＿Os03g55389、LOC＿Os04g55510、LOC＿Os08g07740和LOC＿Os08g01670共6个基因在双亲间的表达量差异显著,其中LOC＿Os03g50310在Nekken2中的表达量比H...     

小麦旗叶早衰性状的QTL定位

为小麦旗叶早衰性状的精细定位和基因克隆奠定基础,该试验以普通小麦(Triticum aestivum L.)‘宁春4号’和‘宁春27号’杂交得到的128个F10代RIL群体为研究材料,利用307对多态性SSR标记对小麦旗叶早衰性状进行了QTL定位,并通过构建整合图谱的方法进行了标记加密。结果表明,共检测到1个控制旗叶早衰性状的加性QTL,位于2A染色体长臂的gwm526和gwm382标记区间内,可解释49.88%的表型变异。经遗传图谱整合后发现,gwm526和gwm382标记之间存在124个SNP标记。     

小麦早衰及其相关生理性状的QTL分析

利用RIL群体及其分子标记遗传图谱,对小麦早衰指标和与早衰相关的6个生理性状进行了QTL定位分析。小麦早衰指标中,检测到2个籽柆饱满度的加性QTL,分别位于3A和3B染色体,可解释表型变异的9.62%和18.30%。生理性状中,共检测到可溶性蛋白含量、SOD活性和POD活性3个性状的5个加性QTL,涉及2A、2B、2D、4A和6B等5条染色体,可解释表型变异的8.1%~49.56%。这些QTL间不存在连锁关系。     

豌豆遗传图谱构建及QTL定位研究进展

豌豆的许多性状是多基因控制的数量性状,QTL定位就是以分子标记技术为工具、以遗传连锁图谱为基础、利用分子标记与QTL之间的连锁关系确定控制数量性状的基因在基因组中的位置.本文对QTL定位原理、方法进行了简单介绍;对豌豆遗传图谱构建及主要性状,如产量、品质、抗病性等QTL定位、遗传效应分析等方面的研究进行综述;对目前基于QTL豌豆分子标记育种存在的问题、应用前景进行了探讨.     

Mapping QTL controlling maize deep-seeding tolerance-related traits and confirmation of a major QTL for mesocotyl length

Deep-seeding tolerant seeds can emerge from deep soil where the moisture is suitable for seed germination. Breeding deep-seeding tolerant cultivars is becoming increasingly important in arid and semi-arid regions. To dissect the quantitative trait loci (QTL) controlling deep-seeding tolerance traits, we selected a tolerant maize inbred line 3681-4 and crossed it with the elite inbred line-X178 to generate an F₂ population and the derivative F_2:3 families. A molecular linkage map composed of 179 molecular markers was constructed, and 25 QTL were detected including 10 QTL for sowing at 10 cm depth and 15 QTL for sowing at 20 cm depth. The QTL analysis results confirmed that deep-seeding tolerance was mainly caused by mesocotyl elongation and also revealed considerable overlap among QTL for different traits. To confirm a major QTL on chromosome 10 for mesocotyl length measured at 20 cm depth, we selected and self-pollinated a BC₃F₂ plant that was heterozygous at the markers around the target QTL and homozygous at other QTL to generate a BC₃F₃ population. We found that this QTL explained more phenotypic variance in the BC₃F₃ population than that in the F₂ population, which laid the foundation for fine mapping and NIL (near-isogenic line) construction.     

Mapping QTL for Omega-3 Content in Hybrid Saline Tilapia

Tilapia is one of most important foodfish species. The low omega-3 to omega-6 fatty acid ratio in freshwater tilapia meat is disadvantageous for human health. Increasing omega-3 content is an important task in breeding to increase the nutritional value of tilapia. However, conventional breeding to increase omega-3 content is difficult and slow. To accelerate the increase of omega-3 through marker-assisted selection (MAS), we conducted QTL mapping for fatty acid contents and profiles in a F₂ family of saline tilapia generated by crossing red tilapia and Mozambique tilapia. The total omega-3 content in F₂ hybrid tilapia was 2.5 ± 1.0 mg/g, higher than that (2.00 mg/g) in freshwater tilapia. Genotyping by sequencing (GBS) technology was used to discover and genotype SNP markers, and microsatellites were also genotyped. We constructed a linkage map with 784 markers (151 microsatellites and 633 SNPs). The linkage map was 2076.7 cM long and consisted of 22 linkage groups. Significant and suggestive QTL for total lipid content were mapped on six linkage groups (LG3, -4, -6, -8, -13, and -15) and explained 5.8–8.3% of the phenotypic variance. QTL for omega-3 fatty acids were located on four LGs (LG11, -18, -19, and -20) and explained 5.0 to 7.5% of the phenotypic variance. Our data suggest that the total lipid and omega-3 fatty acid content were determined by multiple genes in tilapia. The markers flanking the QTL for omega-3 fatty acids can be used in MAS to accelerate the genetic improvements of these traits in salt-tolerant tilapia.