RFLP linkage analysis and mapping genes controlling the fatty acid profile of <Emphasis Type="Italic">Brassica juncea</Emphasis> using reciprocal DH populations

An RFLP linkage map, comprising 300 linked and 16 unlinked loci, was constructed using reciprocal DH populations of Brassica juncea. The linked loci were organized into 18 linkage groups and seven unlinked segments, covering a total map distance of 1,564 cM. The A and B genomes were identified. The chi(2) test showed that 96.1% of the common intervals in the two populations differed non-significantly for recombination fractions, thus strongly suggesting the absence of sex-based differences for recombination fractions in B. juncea. Two QTLs, E(1a) and E(1b), significantly affected erucic acid content, and individually explained 53.7% and 32.1%, respectively, and collectively 85.8% of the phenotypic variation in the population. The QTLs E(1a) and E(1b) showed epistasis, and the full model including epistasis explained nearly all of the phenotypic variation in the population. The QTLs E(1a) and E(1b) were also associated with contents of oleic, linoleic and linolenic acids. Three additional QTLs (LN(2), LN(3) and LN(4)) significantly influenced linolenic acid content. The QTL LN(2) accounted for 35.4% of the phenotypic variation in the population. Epistatic interactions were observed between the QTLs E1a and LN(2). The stability of the detected QTLs across years and locations, and breeding strategies for improving the fatty acid profile of B. juncea, are discussed.     

利用双单倍体群体剖析水稻产量及其相关性状的遗传基础

主效QTL、上位性效应和它们与环境的互作(QE)都是数量性状的重要遗传因素。利用籼粳交珍汕97／武育粳2号F1植株上的花药进行组织培养得到的190个双单倍体群体和179个微卫星标记,通过两年两重复田间试验,采用混合线性模型方法分析了9个控制水稻产量及其相关性状的遗传效应,得到57个主效QTL,41对上位性互作,8对QTL与环境的互作和7对上位性效应与环境的互作。单个主效QTL解释这些性状1．3％～25．8％的表型方差。各性状QTL的累积表型贡献率达11．5％～66．8％。大多数性状之间具有显著的表型相关性,相关性较高的性状之间常具有较多共同或紧密连锁的QTL。结果表明,基因的多效性或紧密连锁可能是性状相关的重要遗传基础。     

Molecular mapping of seed aliphatic glucosinolates in Brassica juncea.

An RFLP genomic map with 316 loci was used to study the inheritance of aliphatic glucosinolates in Brassica juncea using doubled-haploid (DH) populations developed from a cross between RLM-514, an agronomically superior non-canola quality B. juncea (high erucic acid and high glucosinolates), and an agronomically poor canola quality B. juncea breeding line. Two QTLs (GSL-A2a and GSL-A2b) associated with 3-butenyl were consistent across years and locations, and explained 75% of the phenotypic variance in the population. Three QTLs (GSL-A2a, GSL-F, GSL-B3) affected 2-propenyl and explained 78% of the phenotypic variance in the population. For total aliphatic glucosinolates, five QTLs explained 30% to 45% of the total phenotypic variance in the population in different environments. Several QTLs (GSL-A7 and GSL-A3) were highly inconsistent in different environments. Major QTLs (GSL-A2a and GSL-A2b) associated with individual glucosinolates were non-significant for total aliphatic glucosinolates. A marker-assisted selection strategy based on QTLs associated with individual glucosinolates rather than total aliphatic glucosinolates is proposed for B. juncea.     

不同生长环境下水稻最上节间长度QTL定位研究

利用由98 个家系组成的 Nipponbare/Kasalath//Nipponbare 回交重组自交系(backcross inbred lines, BIL)作图群体(BC1F12和BC1F13)和复合区间作图方法(CIM), 在3种不同的生长环境下对水稻最上节间长度进行了 QTL 分析。结果表明, 3种不同的生长环境共检测到 13 个 QTL , 分布于第 1, 2, 3, 5, 6, 8, 10, 11 染色体上, 解释性状变异的 3.97%～15.21%。其中qUIL-6在3种不同生长环境中均检测到, qUIL-1a, qUIL-3a, qUIL-3b和 qUIL-10a 等4个位点在两种不同生长环境中均被检测到, 说明这些 QTL 位点受环境影响较小, 表达较为稳定。     

应用中国和欧洲油菜建立的双二倍体群体对3个重要农艺性状的QTL定位以及与环境的互作分析

以中国的高油分自交系“高油”和欧洲高含油量品种“Sollux”的F1产生的282个株系组成的双二倍体(DH)群体为材料,在125个SSR标记座位构建的连锁图谱基础上,根据在中国和欧洲四个不同环境下的表型鉴定结果,采用混合线性模型基础上的QTL分析软件,对油菜3个重要农艺性状:株高,开花期和成熟期进行了数量性状基因座位(QTL)的联合定位分析,估测了这些QTL的加性、上位性以及与环境的互作效应。结果表明各性状均受多个加性、加加上位以及与环境互作的QTL控制。株高受多个QTL影响(12个位点具有加性或兼有环境互作效应,5个位点具有互作效应),以加性效应为主,加性效应总和可解释定位群体表型变异的75%左右,并多兼有上位性效应。12个主效QTL中,9个是“高油”等位基因相对“Sollux”有降低株高的作用,大多数加性×环境互作QTL的有效等位基因具有环境选择特异性。7个ae基因座位中,5个“高油”等位基因在杭州种植环境下,除一例外所有在德国环境下的互作基因座中,“Sollux”等位基因起着增加株高的作用,加加上位性主效总和为加性主效总和的三分之一。7个控制花期和8个控制成熟期的主效QTL中,分别有6个和5个是来自“高油”的等位基因相对“Sollux”具有提前开花和成熟的效应,这些QTL的效应总和占到性状表型变异的60%左右。5个位于第2和第12连锁群中的2个大效应QTL可能和已多次报导的VFN1和VFN3基因相近或相同。开花期和成熟期两性状均检测到显著的ae互作效应,双亲等位基因的效应在各环境下呈离散分布。位于14和19连锁群上的两个主效株高QTL同时也是控制开花期和油分含量的基因位点,因而利用这两个位点进行标记辅助筛选时要考虑到对油分含量的影响。控制成熟期的8个主效QTL中有3个同时也是控制开花期的基因座位,证实了开花期和成熟期高度正相关的遗传基础,两个生育性状均表现有较弱的QTL间加加上位互作,但以主效QTL的作用为主。     

Mapping quantitative trait loci controlling seed dormancy and heading date in rice, Oryza sativa L., using backcross inbred lines

 To detect quantitative trait loci (QTLs) controlling seed dormancy, 98 BC₁F₅ lines (backcross inbred lines) derived from a backcross of Nipponbare (japonica)/Kasalath (indica)//Nipponbare were analyzed genetically. We used 245 RFLP markers to construct a framework linkage map. Five putative QTLs affecting seed dormancy were detected on chromosomes 3, 5, 7 (two regions) and 8, respectively. Phenotypic variations explained by each QTL ranged from 6.7% to 22.5% and the five putative QTLs explained about 48% of the total phenotypic variation in the BC₁F₅ lines. Except for those of the QTLs on chromosome 8, the Nipponbare alleles increased the germination rate. Five putative QTLs controlling heading date were detected on chromosomes 2, 3, 4, 6 and 7, respectively. The phenotypic variation explained by each QTL for heading date ranged from 5.7% to 23.4% and the five putative QTLs explained about 52% of the total phenotypic variation. The Nipponbare alleles increased the number of days to heading, except for those of two QTLs on chromosomes 2 and 3. The map location of a putative QTL for heading date coincided with that of a major QTL for seed dormancy on chromosome 3, although two major heading-date QTLs did not coincide with any seed dormancy QTLs detected in this study. Received: 10 October 1997 / Accepted: 12 January 1998     

A genetic analysis of seed and berry weight in grapevine.

Fruit size and seedlessness are highly relevant traits in many fruit crop species, and both are primary targets of breeding programs for table grapes. In this work we performed a quantitative genetic analysis of size and seedlessness in an F1 segregating population derived from the cross between a classical seeded (Vitis vinifera L. 'Dominga') and a newly bred seedless ('Autumn Seedless') cultivar. Fruit size was scored as berry weight (BW), and for seedlessness we considered both seed fresh weight (SFW) and the number of seeds and seed traces (SN) per berry. Quantitative trait loci (QTL) analysis of BW detected 3 QTLs affecting this trait and accounting for up to 67% of the total phenotypic variance. QTL analysis for seedlessness detected 3 QTLs affecting SN (explaining up to 35% of total variance) and 6 affecting SFW (explaining up to 90% of total variance). Among them, a major effect QTL explained almost half of the phenotypic variation for SFW. Comparative analysis of QTLs for these traits reduced the number of grapevine genomic regions involved, one of them being a major effect QTL for seedlessness. Association analyses showed that microsatellite locus VMC7F2, closely linked to this QTL, is a useful marker for selection of seedlessnes.     

Dynamic Quantitative Trait Locus Analysis of Seed Vigor at Three Maturity Stages in Rice

Seed vigor is an important characteristic of seed quality. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential, germination rate, germination index and time for 50% of germination, at 4 (early), 5 (middle) and 6 weeks (late) after heading in two years. A total of 24 additive and 9 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program respectively in 2012; while 32 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The additive, epistatic and QTL × development interaction effects regulated the dry maturity developmental process to improve seed vigor in rice. The phenotypic variation explained by each additive, epistatic QTL and QTL × development interaction ranged from 5.86 to 40.67%, 4.64 to 11.28% and 0.01 to 1.17%, respectively. The QTLs were rarely co-localized among the different maturity stages; more QTLs were expressed at the early maturity stage followed by the late and middle stages. Twenty additive QTLs were stably expressed in two years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of these stably expressed additive QTLs with those previously identified, the regions of QTL for seed vigor are likely to coincide with QTL for grain size, low temperature germinability and seed dormancy; while 5 additive QTL might represent novel genes. Using four selected RILs, three cross combinations of seed vigor for the development of RIL populations were predicted; 19 elite alleles could be pyramided by each combination.     

Identification of quantitative trait loci (QTL) for oil and protein contents and their relationships with other seed quality traits in Brassica juncea

A detailed RFLP-genomic map was used to study the genetics of oil, seed and meal protein and sum of oil and seed/meal protein contents in a recombinant doubled-haploid population developed by crossing black- and yellow-seeded Brassica juncea lines. Two yellow seed color genes (SC-B4, SC-A6) and one QTL for erucic acid content (E_1b) showed pleiotropic effect for oil, protein and sum of oil and seed/meal protein contents. Six (O-A1, O-A6, O-A9, O-B3, O-B4, O-B5) and five (SP-A1, SP-A9, SP-B4, SP-B6, SP-C) QTLs were significant for oil and seed protein contents, respectively. Tight linkage of three of these QTLs (SP-A1, SP-A9, SP-B4, O-A1, O-A9, O-B4), with opposite effects, poses challenge to the plant breeders for simultaneous improvement of negatively correlated (r = −0.7**) oil and seed protein contents. However, one QTL for oil content (O-B3) and two for seed protein content (SP-B6, SP-C) were found to be unlinked, which offer the possibility for simultaneous improvement of these two traits. QTLs significant for meal protein (MP-A1, MP-A6, MP-A9, MP-B5, MP-B6) were significant at least for oil, seed protein or sum of oil and seed/meal protein contents (T-A6, T-A7, T-B4, T-B5). Sum of oil and seed protein contents and sum of oil and meal protein contents had a perfect correlation, as well as same epistatic interactions and QTLs with similar additive effect. This indicates that protein in seed or meal has practically the same meaning for breeding purposes. Epistatic interactions were significant for the quality traits, and their linkage reflected association among the traits.     

玉米开花期相关性状的QTL分析

利用玉米强优势组合(Mo17×黄早四)自交衍生的191个F_2单株构建了由SSR和AFLP标记组成的分子连锁图谱,用F2进一步自交产生的184个F_(2:3)家系调查散粉期、吐丝期和开花-吐丝间隔期(ASI)的表型值,采用基于混合线性模型的复合区间作图法和相应的作图软件QTLmapper/V2.0,在两个生长环境下定位了与散粉期、吐丝期和ASI相关的QTL数目分别为13、7和5个,检测到3对控制散粉期、17对控制吐丝期和5对控制ASI的上位性效应位点;同时发现了与环境存在显著互作的3个散粉期、3个吐丝期和2个ASI单位点标记区域以及1对散粉期、3对吐丝期和2对ASI上位性效应区域.对玉米散粉期、吐丝期和ASI遗传基础中遗传因素相对作用大小分析表明,加性效应、部分显性效应和上位性效应是玉米开花期相关性状的重要遗传基础.     

小麦株高性状的QTL分析

自20世纪60年代农林10号矮秆基因被用于小麦育种以来,矮化育种成为世界范围内势不可挡的趋势,矮秆基因研究被越来越多的育种专家重视,先后鉴定出20余个矮秆基因,并应用其中6,7个基因,培育了大批丰产潜力大的半矮秆品种,应用矮秆冬小麦吕系DN3338（♀）和F390（♂）杂交得到的F2：3群体,研究小麦株高的遗传基础,以控制株高的数量性状基因座进行定位,利用240个F2：3家系,构建了含215个微卫星标记,覆盖3600cM,由21个连锁群组成的遗传 连锁图谱,并对该群体进行了4个环境（2年：2000年和2001年,2点：北京和石家庄）3重复的田间种植;采用区间作图法,对该群体的株高性状进行了QTL分析。结果表明：7个影响株高的QTL分别位于染色体1B,4B(2个）,6A（2个）,6D和7A上,每个QTL能解释5．2％－50．1％的表型变异,每个环境条件下检测出的所有QTL能解释64．8％－75％,的表型变异,除了7A上的QTL外,其他6个降低株高的QTL均来自ND3338,其效应介于0．94cm-9.33cm之间,且其中的4个在所有的环境下都能被检测出来,具有较高的稳定性,在4BS的Xgwm113标记附近有一主效QTL,其在不同的环境下能降低株高7．91cm-9.33cm,解释27．8％－36．2％,的表型变异,有着同农林10号中Rht-Blb相近的效应;同时在4BS上还发现一个和地点互作的QTL,该QTL在石家庄的两年试验中均被检测到,且有较大的效应值（80cm和7.6cm),因此,认为大部分的QTL能在所有的环境中检测到,这些QTO可以被用于品种改良和分子标记辅助选择育种。     

Identification of quantitative trait loci controlling heading date in rice using a high-density linkage map

 Quantitative trait locus (QTL) analysis has been carried out to identify genes conferring heading date in rice. One hundred and eighty six F₂ plants derived from a cross between a japonica variety, Nipponbare, and an indica variety, Kasalath, were used as a segregating population for QTL mapping and more than 850 markers were employed to identify QTLs. Scan-analysis revealed the existence of two QTLs with large effects, Hd-1 and Hd-2, one in the middle of chromosome 6 and one at the end of chromosome 7, respectively. For both loci, the Kasalath alleles reduced days-to-heading. In addition, three QTLs with minor effects, Hd-3, Hd-4 and Hd-5, were found to be located on chromosomes 6, 7 and 8 based on a secondary scan analysis which was carried out by removing the phenotypic effects of Hd-1 and Hd-2. For the three secondary loci, the Nipponbare alleles reduced days-to-heading. The five QTLs explained 84% of the total phenotypic variation in the F₂ population based on a multiple-QTL model. The presence of a digenic interaction between Hd-1 and Hd-2 was clearly suggested. Received: 18 March 1997 / Accepted: 24 June 1997     

Identification of QTLs with Additive,Epistatic, and QTL × Seed Maturity Interaction Effects for Seed Vigor in Rice

Seed maturity is a critical process of seed vigor establishment. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential (GP), germination rate (GR), germination index (GI), and time for 50 % of germination (T₅₀), at 4, 5, and 6 weeks after heading in 2 years. Significant differences of seed vigor were observed among two parents and RIL population; the heritability of four traits was more than 90 % at three maturity stages. A total of 19 additive and 2 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program, respectively, in 2012, while 16 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The phenotypic variation explained by each additive, epistatic QTL, and QTL × seed maturity interaction ranged from 9.19 to 22.94 %, 7.23 to 7.75 %, and 0.05 to 0.63 %, respectively. Ten additive QTLs were stably expressed in 2 years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of ten stably expressed additive QTLs with those previously identified, they might be true QTLs for seed vigor; the regions of QTLs for seed vigor are likely to coincide with QTLs for seed dormancy, seed reserve mobilization, low-temperature germinability, and seedling growth. Using four selected RILs, three cross-combinations were predicted to improve seed vigor; 9 to 10 elite alleles could be pyramided by each combination. The selected RILs and the identified QTLs might be applicable for the improvement of seed vigor by marker-assisted selection (MAS) in rice.     

水稻耐储藏特性三年动态鉴定与QTL分析

种子耐储藏特性是粮食作物的特殊农艺性状之一, 耐储藏性能对种子生产和种质资源保存有重要意义。以粳型超级稻龙稻5 (LD5)和高产籼稻中优早8 (ZYZ8)杂交衍生的重组自交系(RILs)群体(共180个株系)为实验材料, 自然高温高湿条件下放置1年、2年和3年后, 对不同储藏时段种子发芽率进行比较, 并利用223个分子标记的遗传图谱进行动态QTL鉴定。结果表明, 不同储藏时段龙稻5的发芽率均显著低于中优早8, 株系间耐储性存在较大差异; 不同储藏时段发芽率显著相关, 相邻存储时段发芽率关系紧密。共检测到17个耐储性相关的QTLs, 3个老化时段分别检测到5、4和3个, 检测到5个动态条件QTLs, 单一QTL解释5.60%-32.76%的表型变异, 加性效应在-16.78%-16.95%范围内。主效QTL簇qSSC2、qSSC6、qSSC7和qSSC8能调控不同储藏时段的发芽率, qSSC6具有明显降低发芽率的效应。共检测到26对上位性互作位点, 主效QTL qSS1和qSS4参与上位性互作, 这表明上位性互作是调控耐储藏性状的重要遗传组成。研究结果为水稻(Oryza sativa)耐储性相关QTL的精细定位奠定基础, 同时丰富了耐储性分子标记辅助选择育种的基因资源。     

水稻耐储藏特性三年动态鉴定与QTL分析

种子耐储藏特性是粮食作物的特殊农艺性状之一, 耐储藏性能对种子生产和种质资源保存有重要意义。以粳型超级稻龙稻5 (LD5)和高产籼稻中优早8 (ZYZ8)杂交衍生的重组自交系(RILs)群体(共180个株系)为实验材料, 自然高温高湿条件下放置1年、2年和3年后, 对不同储藏时段种子发芽率进行比较, 并利用223个分子标记的遗传图谱进行动态QTL鉴定。结果表明, 不同储藏时段龙稻5的发芽率均显著低于中优早8, 株系间耐储性存在较大差异; 不同储藏时段发芽率显著相关, 相邻存储时段发芽率关系紧密。共检测到17个耐储性相关的QTLs, 3个老化时段分别检测到5、4和3个, 检测到5个动态条件QTLs, 单一QTL解释5.60%-32.76%的表型变异, 加性效应在-16.78%-16.95%范围内。主效QTL簇qSSC2、qSSC6、qSSC7和qSSC8能调控不同储藏时段的发芽率, qSSC6具有明显降低发芽率的效应。共检测到26对上位性互作位点, 主效QTL qSS1和qSS4参与上位性互作, 这表明上位性互作是调控耐储藏性状的重要遗传组成。研究结果为水稻(Oryza sativa)耐储性相关QTL的精细定位奠定基础, 同时丰富了耐储性分子标记辅助选择育种的基因资源。     

Detection of quantitative trait loci for body weight at 10 weeks from Philippine wild mice

A genome-wide scan for quantitative trait loci (QTLs) controlling body weight at 10 weeks after birth was carried out in a population of 387 intersubspecific backcross mice derived from a cross between C57BL/6J inbred mice (Mus musculus domesticus) and wild mice (M. m. castaneus) captured in the Philippines, in order to discover novel QTLs from the wild mice that have about 60% lower body weight than C57BL/6J. By interval mapping, we detected four QTLs: a highly significant QTL on Chromosome (Chr) 2, which was common in both sexes; two significant QTLs on Chr 13, one male-specific and the other female-specific; and a suggestive male-specific QTL on X Chr. By composite interval mapping, we confirmed the presence of the three QTLs on Chrs 2 and 13, but not of the male-specific X-linked QTL. The composite interval mapping analysis newly identified three QTLs: a significant male-specific QTL on Chr 11 and two highly significant female-specific QTLs on Chrs 9 and X. Individual QTLs explained 3.8–11.6% of the phenotypic variance, and all the QTL alleles derived from the wild mice decreased body weight. A two-way analysis of variance revealed a significant epistatic interaction between the Chr 2 QTL and the background marker locus D12Mit4 on Chr 12 only in males. The interaction effect unexpectedly increased body weight. The chromosomal region containing the Chr 2 QTL did not coincide with those of growth or fatness QTLs mapped in previous studies. These results suggest that a population of wild mice may play an important role as new sources of valuable QTLs. Received: 14 January 2000 / Accepted: 14 April 2000     

不同发育时期小麦粒重性状QTL的动态分析

利用6044×01-35构建的重组自交系(RIL)群体为试验材料,对小麦粒重性状进行发育动态QTL分析。结果表明,在小麦花后子粒灌浆的7个不同时期,两个试验点共检测到16个与粒重性状相关的QTL。其中开花后20d检测到的单穗粒重QTL位于2A染色体上,解释率达12%,遗传效应超过10;两环境下控制千粒重QTL在7个时期均被检测到。花后的各个时期均能在Xgwm448-Xgpw7399标记区间定位到千粒重QTL。其中花后10d检测到1个千粒重QTL,位于2A染色体的Xgwm448-Xgpw7399标记区间,解释较大的表型变异,达到18%。Qtl8、Qtl13和Qtl14均定位在Xgwm448-Xgpw7399标记区间的同一位置,共同解释11%的表型变异。花后20d和花后25d均检测到1个QTL,位于2A染色体的Xgwm372-Xgwm95标记区间的不同位点,均能解释4%的表型变异。花后40d检测到1个QTL,位于1D染色体的Xwmc93-Xgpw2224标记区间,解释1%的表型变异。从连锁群的位置上看,控制千粒重的QTL主要集中在2A染色体的Xgwm448-Xgpw7399标记区间,这是一个控制千粒重QTL的富集区域,以期进行精细定位和图位克隆。     

水稻穗部性状的QTL与环境互作分析

分别在两年收集珍汕97／明恢63的重组自交系群体的表现数据,运用混合线性模型的QTL定位方法,联合分析穗部5个性状的QTLs7及QTL与环境互作关系。每穗颖花数、每穗实粒数、结实率、穗长和穗着密度分别检测到10、3、6、8和7个QTLs分别解释各性状变异的29．13％、19．2％、29．46％、26．39％和35．76％。对于同一性状,高值亲本和低值亲本中均存在增效和减效QTL。相关性状QTL的位置表现相同或相似,高值亲本和低值亲本中均存在增效和减效QTL。相关性状QTL的位置表现相同或相似,成族分布。1个穗长QTL,2个每穗颖花数QTL3,3个结实率QTLs表现与环境显著互作,QTL与环境互作效应的贡献率比相应的QTL贡献率略大。遗传力稍高的每穗实粒数和穗着粒密度的DQTL与环境不互作。     

Quantitative trait loci for body weight in the intercross between SM/J and A/J mice.

We performed a genome-wide quantitative trait locus (QTL) analysis of body weight at 10 weeks of age in a population of 321 intercross offspring from SM/J and A/J mice, progenitor strains of SMXA recombinant inbred strains. Interval mapping revealed two significant QTLs, Bwq3 (body weight QTL3) and Bwq4, on Chromosomes (Chrs) 8 and 18 respectively, and five suggestive QTLs on Chrs 2, 6, 7, 15 and 19. Bwq3 and Bwq4 explained 6% of the phenotypic variance. The SM/J alleles at both QTLs increased body weight, though the SM/J mouse was smaller than the A/J mouse. On the other hand, four of the five suggestive QTLs detected had male-specific effects on body weight and the remainder was female-specific. These suggestive QTLs explained 5-6% of the phenotypic variance and all the SM/J alleles decreased body weight.     

Quantitative trait loci mapping of yield and related traits using a high-density genetic map of maize

Improving grain yield is the ultimate goal of the maize-breeding programs. In this study, analyses of conditional and unconditional quantitative trait locus (QTL) and epistatic interactions were used to elucidate the genetic architecture of yield and its related traits. A total of 15 traits of a recombinant inbred line population, including yield per plant (YPP), seven ear-related traits, and seven kernel-related traits, were measured in six different environments. Based on the genetic linkage map constructed using 2091 bins as markers, 56 main-effect QTLs for these traits were identified. These QTLs were distributed across eight genomic regions (bin 1.06, bin 4.02/4.05/4.08, bin 5.04, bin 7.04, bin 8.08, and bin 9.04), within the marker intervals of 85.45–6260.66 kb, and the phenotypic variance explained ranging from 5.69 to 11.56 %. One gene (GRMZM2G168229) encoding SBP-box domain protein was located in the small interval of qKRN4-3 and may be involved in patterning of kernel row number. Seventeen conditional QTLs identified for YPP were conditioned on its related traits and explained 6.18–23.15 % of the phenotypic variance. Conditional mapping analysis revealed that qYPP4-1, qYPP6-1, and qYPP8-1 are partially influenced by YPP-related traits at the individual QTL level. Digenic epistatic analysis identified 12 digenic interactions involving 22 loci across the whole genome. In addition, conditional digenic epistatic analysis identified 14 digenic interactions involving 21 loci. This study provides valuable information for understanding the genetic relationship between YPP and related traits and constitutes the first step toward the cloning of the relevant genes.