Identification of candidate genes for early-maturity traits by combining BSA-seq and QTL mapping in upland cotton(Gossypium hirsutum L.)

Cotton breeding for the development of early-maturing varieties is an effective way to improve multiple cropping indexes and alleviate the conflict between grains and cotton in the cultivated fields in China.In the present study,we aimed to identify upland cotton quantitative trait loci(QTLs)and candidate genes related to early-maturity traits,including whole growth period(WGP),flowering timing(FT),node of the first fruiting branch(NFFB),height of the node of the first fruiting branch(HNFFB),and plant height(PH).An early-maturing variety,CCRI50,and a latematuring variety,Guoxinmian 11,were crossed to obtain biparental populations.These populations were used to map QTLs for the early-maturity traits for two years(2020 and 2021).With BSA-seq analysis based on the data of population 2020,the candidate regions related to early maturity were found to be located on chromosome D03.We then developed 22 polymorphic insertions or deletions(InDel)markers to further narrow down the candidate regions,resulting in the detection of five and four QTLs in the 2020 and 2021 populations,respectively.According to the results of QTL mapping,two candidate regions(InDel_G286-InDel_G144 and InDel_G24-InDel_G43)were detected.In these regions,three genes(GH_D03G0451,GH_D03G0649,and GH_D03G1180)have nonsynonymous mutations in their exons and one gene(GH_D03G0450)has SNP variations in the upstream sequence between CCRI50 and Guoxinmian 11.These four genes also showed dominant expression in the floral organs.The expression levels of GH_D03G0451,GH_D03G0649 and GH_D03G1180 were significantly higher in CCRI50 than in Guoxinmian 11 during the bud differentiation stages,while GH_D03G0450 showed the opposite trend.Further functional verification of GH_D03G0451 indicated that the GH_D03G0451-silenced plants showed a delay in the flowering time.The results suggest that these are the candidate genes for cotton early maturity,and they may be used for breeding early-maturity cotton varieties.

青稞分蘖角度的QTL定位

分蘖角度是青稞株型的主要构成因素,在提高青稞产量与抗倒伏性中发挥着极为重要的作用。为解析青稞分蘖角度的遗传机制,本研究以青稞品种‘达章紫’(株型松散)和‘昆仑10号’(株型紧凑)为亲本构建的RIL群体为材料,基于高密度遗传图谱,在多环境中进行青稞分蘖角度的QTL定位,并利用RIL群体衍生的剩余杂合系,对鉴定到的主效QTLqTA7H-1进行精细定位。在青稞7条染色体上共检测到9个控制分蘖角度的QTL,解释表型变异为6.41%~33.57%,其中,qTA3H-1和qTA7H-1为多环境共检测的主效QTL,平均加性效应分别为5.42°(增效)和-3.87°(减效);在减效QTL qTA7H-1初定位区间筛选到4个剩余杂合体,自交衍生F8:9近等基因系,在置信区间内加密设计14对分子标记对RHL群体极端单株进行检测,利用获得的5种交换类型单株,将qTA7H-1进一步界定在PC08(32,252,397)与PA10(41,790,765)约9.54Mb的物理区间内。本研究初步揭示调控青稞分蘖角度的遗传因子,为开展分蘖角度性状的遗传改良与分子设计育种奠定了基础。

Multi-environment BSA-seq using large F3 populations is able to achieve reliable QTL mapping with high power and resolution: An experimental demonstration in rice

Bulked-segregant analysis by deep sequencing(BSA-seq) is a widely used method for mapping QTL(quantitative trait loci) due to its simplicity, speed, cost-effectiveness, and efficiency. However, the ability of BSA-seq to detect QTL is often limited by inappropriate experimental designs, as evidenced by numerous practical studies. Most BSA-seq studies have utilized small to medium-sized populations, with F2populations being the most common choice. Nevertheless, theoretical studies have shown that using a large population with an appropriate pool size can significantly enhance the power and resolution of QTL detection in BSA-seq, with F_(3)populations offering notable advantages over F2populations. To provide an experimental demonstration, we tested the power of BSA-seq to identify QTL controlling days from sowing to heading(DTH) in a 7200-plant rice F_(3)population in two environments, with a pool size of approximately 500. Each experiment identified 34 QTL, an order of magnitude greater than reported in most BSA-seq experiments, of which 23 were detected in both experiments, with 17 of these located near41 previously reported QTL and eight cloned genes known to control DTH in rice. These results indicate that QTL mapping by BSA-seq in large F_(3)populations and multi-environment experiments can achieve high power, resolution, and reliability.

Consensus linkage map construction and QTL mapping for eight yield-related traits in wheat using the BAAFS Wheat 90K SNP array

Identifying stable quantitative trait loci(QTLs)for yield-related traits across populations and environments is crucial for wheat breeding and genetic studies.Consensus maps also play important roles in wheat genetic and genomic research.In the present study,a wheat consensus map was constructed using a doubled haploid(DH)population derived from Jinghua 1×Xiaobaidongmai(JX),an F_(2)population derived from L43×Shanxibaimai(LS)and the BAAFS Wheat 90K SNP array single nucleotide polymorphism(SNP)array.A total of 44,503 SNP markers were mapped on the constructed consensus map,and they covered 5,437.92 cM across 21 chromosomes.The consensus map showed high collinearity with the individual maps and the wheat reference genome IWGSC RefSeq v2.1.Phenotypic data on eight yield-related traits were collected in the JX population,as well as the F_(2:3)and F_(2:4)populations of LS,in six,two and two environments,respectively,and those data were used for QTL analysis.Inclusive composite interval mapping(ICIM)identified 32 environmentally stable QTLs for the eight yield-related traits.Among them,four QTLs(QPH.baafs-4B,QKNS.baafs-4B,QTGW.baafs-4B,and QSL.baafs-5A.3)were detected across mapping populations and environments,and nine stable QTLs(qKL.baafs-1D,QPH.baafs-2B,QKNS.baafs-3D,QSL.baafs-3D,QKW.baafs-4B,QPH.baafs-5D,QPH.baafs-6A.1,QSL.baafs-6A,and QSL.baafs-6D)are likely to be new.The physical region of 17.25–44.91 Mb on chromosome 4B was associated with six yield-related traits,so it is an important region for wheat yield.The physical region around the dwarfing gene Rht24 contained QTLs for kernel length(KL),kernel width(KW),spike length(SL),and thousand-grain weight(TGW),which are either from a pleiotropic effect of Rht24 or closely linked loci.For the stable QTLs,254 promising candidate genes were identified.Among them,TraesCS5A03G1264300,TraesCS1B03G0624000 and TraesCS6A03G0697000 are particularly noteworthy since their homologous genes have similar functions for the corresponding traits.The constructed consensus map and the identified QTLs along with their candidate genes will facilitate the genetic dissection of wheat yield-related traits and accelerate the development of wheat cultivars with desirable plant morphology and high yield.

Combining QTL Mapping and Multi-Omics Identify Candidate Genes for Nutritional Quality Traits during Grain Filling Stage in Maize

The nutritional composition and overall quality of maize kernels are largely determined by the key chemical com-ponents:protein,oil,and starch.Nevertheless,the genetic basis underlying these nutritional quality traits during grainfilling remains poorly understood.In this study,the concentrations of protein,oil,and starch were studied in 204 recombinant inbred lines resulting from a cross between DH1M and T877 at four different stages post-pollination.All the traits exhibited considerable phenotypic variation.During the grain-filling stage,the levels of protein and starch content generally increased,whereas oil content decreased,with significant changes observed between 30 and 40 days after pollination.Quantitative trait locus(QTL)mapping was conducted and a total of 32 QTLs,comprising 14,12,and 6 QTLs for grain protein,oil,and starch content were detected,respectively.Few QTLs were consistently detectable across different time points.By integrating QTL analysis,glo-bal gene expression profiling,and comparative genomics,we identified 157,86,and 54 differentially expressed genes harboring nonsynonymous substitutions between the parental lines for grain protein,oil,and starch con-tent,respectively.Subsequent gene function annotation prioritized 15 candidate genes potentially involved in reg-ulating grain quality traits,including those encoding transcription factors(NAC,MADS-box,bZIP,and MYB),cell wall invertase,cellulose-synthase-like protein,cell division cycle protein,trehalase,auxin-responsive factor,and phloem protein 2-A13.Our study offers significant insights into the genetic architecture of maize kernel nutritional quality and identifies promising QTLs and candidate genes,which are crucial for the genetic enhance-ment of these traits in maize breeding programs.

First identification of two co-existing genome-wide significant sex quantitative trait loci(QTL) in red tilapia using integrative QTL mapping

Red tilapia(Oreochromis spp.)is one of the most popular fish in China due to its bright red appearance,fast growth rate,and strong adaptability.Understanding the sex determination mechanisms is of vital importance for the selection of all-male lines to increase aquacultural production of red tilapia.In this research,the genetic architecture for sex from four mapping populations(n=1090)of red tilapia was analyzed by quantitative trait loci(QTL)-seq,linkage-based QTL mapping,and linkage disequilibrium(LD)-based genome-wide association studies.Two genome-wide significant QTL intervals associated with sex were identified on ChrLG1(22.4-23.9 Mb)and ChrLG23(32.0-35.9 Mb),respectively.The QTL on ChrLG1 was detected in family 1(FAM1),FAM2,and FAM4,and the other QTL on ChrLG23 was detected in FAM3 and FAM4.Four microsatellite markers located within the QTL were successfully developed for marker-assisted selection.Interestingly,three(Ipp,sox14,and amh)of the 12 candidate genes located near or on the two QTL intervals were abundantly expressed in males,while the remaining genes were more highly expressed in females.Seven genes(scly,ube3a,Ipp,gpr17,oca2,cog4,and atp10a)were significantly differentially expressed between the male and female groups.Furthermore,LD block analysis suggested that a cluster of genes on ChrLG23 may participate in regulating sex development in red tilapia.Our study provides important information on the genetic architecture of sex in red tilapia and should facilitate further exploration of sex determination mechanisms in this species.

Quantitative Trait Loci(QTL)Mapping and Marker Analysis of Fatty Acids in Peanut

Peanut,with high oil content,has been a major oil and food crop globally.The compositions of the fatty acids are the common factors in determining the oil quality.In the present study,an F2 segregated population with 140 individuals derived from the cross of Weihua8(a cultivar)and 12L49(a line with high oleic acid concentration)was used to construct a genetic map and conduct QTL mapping analysis.A total of 103 polymorphic SSR primers were utilized for genotyping the RILs and finally generating the SSR loci.Within the 103 SSR loci,a genetic linkage map,covering a total length of 3592.35 cM of the whole peanut genome,was constructed.Based on the genetic map,sixteen QTLs located on nine linkage groups related to peanut fatty acids were finally identified.Among them,four QTLs were detected associated with various traits simultaneously,which showed genetic stability in relation to fatty acids of peanut.Except for the QTLs for oleic acid,linoleic acid,and linolenic acid,three novel QTLs for arachidic acid and behenic acid were also detected.These QTLs might be helpful for further fine mapping analysis and marker-assisted selection of fatty acids in peanut.

Mapping of Quantitative Trait Loci （QTLs） Controlling Cherry and Green Bean Characters in the Robusta Coffee （Coffea canephora Pierre）

In coffee breeding practice, two quantitative traits, namely cherry and green bean characters are the important phenotypic selection index. The synchronous of cherry maturation, size, weight and shape of green bean are desirable traits for the future breeding. In order to increase the breeding efficiency, a set of quantitative trait loci （QTLs） analysis controlling these traits was carried out. The QTL analysis was performanced in cross pollinated population of Coffea canephora using single nucleotide polymorphisms （SNPs） and simple sequence repeats （SSRs） markers. Totally 12 QTLs determined desirable cherry and green bean traits were identified on 9 linkage groups （LG）, where these QTLs mapped forming clusters in 11 different chromosomal regions. The desirable traits which can be detected by their QTLs are synchronous of cherry maturation （LG B and LG G）, cherry size （LG A, LG F and LG G）, bean shape （LG B, LG D and LG J）, bean weight （LG H）, bean size （LG A and LG E） and cherry-bean size （LG K） The gene action of these QTLs was dominance or an interaction of alleles （epistasis between alleles at the studied locus） effect. The yielded linkage map and the detected QTL can provide a tool for further genetic analysis of two traits and be potential for maker-assisted selection in C. canephora breeding.

QTL Mapping of Yield and Yield Components for Elite Hybrid Derived-RILs in Upland Cotton

A population of 180 recombinant inbred lines （RILs） was developed by single seed descended from the cross of high yield Upland cotton （Gossypium hirsutum L.） varieties Zhongmiansuo12 （ZMSI2） and 8891, the two parents of Xiangzamian2 （XZM2）. A genetic linkage map consisting of 132 loci and covering 865.20 cM was constructed using the RIL population chiefly with SSR markers. Yield and yield components were investigated for RILs in three environments in China. The purpose of the present research was to analyze the relationship between yield and its components and to map QTL for yield and yield components in cotton. QTL were tagged with data sets from single environment （separate analysis） and a set of data from means of the three environments （joint analysis）. A total of 34 QTL for yield and yield components were independently detected in three environments, whereas fifteen QTL were found in joint analysis. Notably, a stable lint percentage QTL qLP-A10-1 was detected both in joint analysis and in two environments of separate analysis, which might be of special value for marker-assisted selection. The QTL detected in the present study provide new information on improving yield and yield components. Results of path analysis showed that bolls/plant had the largest contribution to lint yield, which is consistent with the mid-parent heterosis value in F1. Accordingly, in cotton breeding, bolls/plant can be considered first and other yield components measured as a whole to implement variety enhancement and hybrid selection of cotton.

Identification of Quantitative Trait Loci (QTLs) Affecting Yield and Fiber Properties in Chromosome 16 in Cotton Using Substitution Line

Gossypium hirsutum L. and G. barbadense L. are the two cultivated tetraploid species of cotton. The first is characterized by a high yield and wide adaptation, and the second by its super fiber property. Substitution line in which a pair of intact chromosomes of TM_1 ( G. hirsutum ) were replaced by a pair of homozygous chromosomes of 3_79 ( G. barbadense ) is an excellent material for genetic research and molecular tagging. In this study, substitution line 16 (Sub 16) was used to evaluate the performance of the 16th chromosome in G. barbadense in TM_1 background. The genetic analysis using the major gene plus polygene mixed inheritance model in F 2∶3 family revealed that there might exist 2 QTLs respectively for boll size, lint percentage, lint index, fiber length and the first fruit branch node, 1 QTL for fiber elongation and flowering date, and no QTL for seed index, fiber strength and Micronaire in chromosome 16. However, 9 QTLs (LOD (logarithm of odds)≥3.0) controlling 6 quantitative traits were significantly identified in linkage group of chromosome 16 constructed in (TM_1×3_79) F 2by interval mapping. Among them, 1 QTL for boll size, fiber length, flowering date and fiber elongation could explain 15.2%, 19.7%, 12.1%, and 11.7% phenotypic variance respectively, 2 QTLs for lint index could explain 11.6% and 41.9%, and 3 QTLs for lint percentage could explain 8.7%, 9.6% and 29.2% phenotypic variance respectively. One unlinked SSR marker was associated with one QTL respectively for boll size and flowering date and they could explain 1.60% and 4.63% phenotypic variance. The traits associated significantly with chromosome 16 from Sub 16 were boll weight, lint percentage, lint index, fiber length, fiber elongation and flowering days.

QTL Mapping and Q×E Interactions of Grain Cooking and Nutrient Qualities in Rice Under Upland and Lowland Environments

Grain cooking and nutrient qualities are the most important components of rice （Oryza sativa L.） quality. A doubled haploid （DH） population from a cross between two japonica cultivars was used to examine the phenotypic values and potential QTLs for the quality traits. The cooking and nutrient quality traits, including the amylose content （AC）, the gel consistency （CJC）, the gelatinization temperature （GT）, and the protein content （PC）, in rice grown under upland and lowland environments were evaluated. Significant differences for AC, GC, GT, and PC between upland and lowland environments were detected. The phenotypic values of all four traits were higher under upland environment than lowland environment. The value of PC under upland environment was significantly higher （by 37.9%） than that under lowland environment. This suggests that upland cultivation had large effect on both cooking and nutrient qualifies. A total of seven QTLs and twelve pairs of QTLs were detected to have significant additive and epistatic effects for the four traits. Significant Q x E interaction effects of two QTLs and two pairs of QTLs were also discovered. The general contribution of additive QTLs ranged from 1.91% to 19.77%. The Q × E interactions of QTLs QGt3 and QAc6 accounted for 8.99% and 47.86% of the phenotypic variation, respectively, whereas those of the 2 pairs of epistatic QTLs, QAc6-QAcllb and QAc8-QAc9, accounted for 32.54% and 11.82%, respectively. Five QTLs QGt6b, QGt8, QGt11, QGcl, and QPc2, which had relatively high general contribution and no Q x E interactions, were selected to facilitate the upland rice grain quality breeding.

Interval Mapping of Quantitative Trait Loci Underlying Triploid Endosperm Traits Using F_3 Seeds

A statistical method for mapping quantitative trait loci （QTLs） underlying endosperm traits is proposed. The method is based on a genetic model containing both the direct effects and maternal effects of an endosperm QTL and on an experimental design termed two-stage hierarchical design, in which the trait information is obtained from F3 endosperms and molecular marker information is obtained from F2 plants and F3 embryos （plants）. Results of computer simulations indicate that the method can efficiently map endosperm QTLs and precisely estimate both the direct and maternal effects of endosperm QTLs when the sample size is sufficiently large.

Mapping of QTLs Related to Grain Weight Using Chromosome Single Segment Substitution Lines in Rice

Grain weight, one of the major factors determining rice yield, is a typical quantitative trait control ed by multiple genes. With Guangluai 4 as recipient and Nipponbare as donor, a population of 119 chromosome single segment substitution lines had been developed. Correlation analysis between grain weight and grain shape by SPSS revealed that 1 000-grain weight shared extremely significant posi-tive correlation with grain length and length-width ratio, but no significant correlation with grain width and thickness. The QTL analysis of grain weight was carried out using one-way analysis of variance and Dunnett＇s test. Nineteen stable QTLs re-sponsible for grain weight were identified over two years. Al 19 QTLs were identi-fied on al chromosomes except for chromosome 10 and 12 at a significance level of P≤0.001. Among them, 10 QTLs had a positive effect and were derived from the Nipponbare al ele, the additive effect of these QTLs ranged from 0.49 to 2.74 g, and the contributions of the additive effects ranged from 2.00% to 11.05%. Another 9 QTLs had a negative effect and were al derived from Guangluai 4 al ele, the ad-ditive effect of these QTLs ranged from 0.60 to 2.35 g, and the contributions of the additive effects ranged from 2.40% to 9.84%. The results provide a basis for the fine mapping and gene cloning of novel locus associated with rice grain weight.

QTLs Mapping for Salinity Tolerance at Seedling Stage or Rice(Oryza sativa L.) Using Chromosome Segment Substitution Lines

In this study, a population of chromosome segment substitution lines （CSSLs） derived from the cross between 9311 （indica） and Nipponbare （japonica） was employed to map the quantitative trait loci （QTLs） for salt tolerance under the salt stress simulated with 0.5% NaCI, using survival rate as the index. The data were analyzed by QTL IciMapping v3.1, and the results showed that one QTL （QSsr3） related to salt tolerance was located in the vicinity of the marker RM1350 on chromosome 3, into a genetic interval of 113.2-132.8 cM, with a contribution rate of 17.75%. The additive effect was 10.9, indicating that the QTL derived from the parent Nipponbare improved the salt tolerance of rice at seedling stage. This study will provide a theoretical basis for the selection of salt tolerant rice germplasm.

An Entropy-based Index for Fine-scale Mapping of QTL

By comparing the entropy and conditional entropy in a marker, an entropy-based index for fine-scale linkage-disequilibrium gene mapping is presented using high-density marker maps in extreme samples for quantitative trait. The entropy-based index is the function of LD between the marker and the traitlocus and does not depend on marker allele frequencies across the loci. It is parallel to Hardy-Weinberg disequilibrium （HWD） measure for QTL fine mapping, but its power of fine mapping QTL is higher than that of HWD measure. Through simulations, the fine mapping performance of this entropy-based index is investigated extensively under various genetic parameters. The results show that the indices presented here are both robust and powerful.

Mapping QTLs Associated with Sheath Blight Resistance Using Chromosome Segment Substitution Lines of Rice(Oryza sativa L.)

In this study, a population of 119 chromosome segment substitution lines （CSSLs） derived from backcross between indica 9311 and japonica Nipponbare was employed to map quantitative trait loci （QTL） associated with sheath blight resis-tance in rice with toothpick inoculation method. A total of three sheath blight resis-tance-associated QTLs （qsb8-1, qsb8-2 and qsb8-3） were identified, which were lo-cated on adjacent molecular markers RM3262, RM5485 and RM3496 of chromo-some 8; the genetic interval was 81.7cM-91.7cM, 91.7cM-108.1cM and 108.1cM-119.6cM, respectively. The additive effect of qsb8-2 was negative, indicating that sheath blight resistance of susceptible parent harboring qsb8-2 fragment was en-hanced; additive effects of qsb8-1 and qsb8-3 were positive, indicating that sheath blight resistance of susceptible parent harboring qsb8-1 and qsb8-3 fragments was reduced.

利用QTL-Seq结合分子标记定位粳稻垩白粒率控制位点qChalk8

[目的]垩白是影响稻米外观品质的重要性状。本研究旨在利用QTL-Seq和分子标记作图定位粳稻垩白粒率调控相关的QTL。[方法]利用高垩白粒率粳稻材料拉木加和低垩白粒率粳稻品种水晶3号构建F_(2)分离群体,将两份独立的F_(2)群体分别种植于河南原阳和海南三亚,两个群体单株垩白粒率考种后分别选取极端个体混池进行QTL-Seq分析,然后使用分子标记作图对稳定的QTL进行验证。[结果]两个F_(2)群体的QTL-Seq分析发现8号染色体存在一个较为稳定的QTL位点qChalk8。进一步通过分子标记作图将该QTL定位于17.6-18.5Mb,该QTL位点的LOD值为7.08,表型贡献率为15.9%。[结论]利用QTL-Seq和分子标记作图定位了粳稻垩白粒率相关QTL-qChalk8,为粳稻垩白调控基因进一步的精细定位和基因克隆奠定了基础。

谷子籽粒类黄酮含量和粒色的QTL定位

谷子(Setaria italica L.)是我国北方地区重要的粮食作物,籽粒营养丰富,且富含多种类黄酮物质,对生长发育和品质形成发挥着重要作用。目前谷子籽粒类黄酮合成及粒色形成相关调控机制研究较少。分析谷子类黄酮含量及粒色性状相关的QTL,为类黄酮合成关键基因的精细定位、克隆及功能研究奠定基础,同时,也为揭示谷子类黄酮合成及代谢机制和培育富含类黄酮谷子品种提供技术支撑。本研究以红粒色高类黄酮品种金苗红酒谷和黄粒色低类黄酮品种豫谷28为亲本构建的包含150个家系的重组自交系(RIL)群体为试验材料,在谷子成熟期对籽粒粒色和类黄酮含量相关性状进行分析。同时,采用复合区间作图法(composite interval mapping,CIM)对粒色和类黄酮含量进行QTL定位与分析,并对QTL置信区间内的候选基因进行预测。相关性分析表明,类黄酮含量与粒色呈显著正相关。共定位到4个与类黄酮含量相关和11个与粒色相关的QTL,分别位于1号、2号、5号、6号、7号、8号和9号染色体上,单个QTL的表型贡献率为2.01%~29.25%,6个为主效QTL,其中,qSC1-2和qFLA1-1、qSC7-1和qFLA7-1、qSC9-3和qFLA9-1为2个性状下共同定位到的QTL。通过基因预测与功能注释,筛选出QTL置信区间内5个与类黄酮物质合成及代谢相关的候选基因,表明类黄酮物质的合成、代谢及利用相关基因极有可能控制了这些基因的表达。15个QTL分别聚集于7条染色体上,基于基因功能注释,共筛选了5个与谷子类黄酮合成及代谢相关的候选基因,表明不同QTL位点参与到了共同遗传机制,并可通过分子标记辅助选择进行类黄酮合成及代谢等有利基因的聚合育种。

柞蚕高密度遗传图谱构建及体色性状QTL初步解析

为构建柞蚕高密度遗传图谱并对体色性状进行QTL初步解析,采用Super-GBS技术对115个柞蚕样品(2个亲本、3个F_(1)代个体、110个BC_(1)M个体)开展测序及基因分型,并利用区间作图法对体色性状进行QTL定位分析及候选基因发掘。结果得到柞蚕首张遗传图谱,全长4059.163 cM,平均遗传距离为1.17 cM,共有3466个标记分配到48个连锁群上;QTL定位分析共得到11个与体色性状相关的位点,分布在4个连锁群上,单个LOD范围1.92~16.86,其中在连锁群LG8与LG41上共获得9个QTL;在候选区间内进行基因挖掘,共得到11个候选基因。得到的候选基因为柞蚕体色性状调控机制研究提供了线索,助力柞蚕生物育种研究的开展。

栽培花生籽仁面积和周长性状的QTL定位分析

籽仁面积和周长是影响花生籽仁大小和外观的重要性状。本研究以‘鲁花11号’ב06B16’构建的重组自交系(recombinant inbred line,RIL)群体为试验材料,对花生籽仁面积和籽仁周长在4个环境进行性状考察及QTL定位分析。基于表型数据和高密度遗传图谱信息,在A04和B06染色体上定位到15个与籽仁面积和籽仁周长性状相关的QTL,其中8个与籽仁面积相关,7个与籽仁周长相关。控制籽仁面积和周长的主效位点qSAB06.1d和qSPB06a在多个不同环境均能检测到,表型贡献率为9.52%~33.78%,其增效等位基因均来自鲁花11号,共定位在B06染色体138.53~140.76 Mb区域内。对主效位点qSAB06.1d/qSPB06a进行功能注释,鉴定到3个编码转运蛋白、1个编码ABA受体PYL和1个编码钙调磷酸酶的基因,它们可能是调控花生籽仁面积和周长的候选基因。本研究将为花生产量和外观性状的精细定位和遗传改良奠定理论基础。