通过对水稻萌发耐淹性进行QTL定位和稳定位点的聚合效应分析,可以为萌发耐淹性基因的精细定位及后续分子辅助育种奠定基础。本研究利用一个包含144份家系的强萌发耐淹性粳型杂草稻WR-4与籼稻品种广百香占的F2:3定位群体,基于1K m GPS SN...通过对水稻萌发耐淹性进行QTL定位和稳定位点的聚合效应分析,可以为萌发耐淹性基因的精细定位及后续分子辅助育种奠定基础。本研究利用一个包含144份家系的强萌发耐淹性粳型杂草稻WR-4与籼稻品种广百香占的F2:3定位群体,基于1K m GPS SNP芯片构建了一个包含825个Bin标记的高密度遗传图谱,利用完备区间作图法共检测到10个萌发耐淹性QTL,分布于水稻第3、4、7、8、9和10染色体上,LOD值介于3.6~21.3之间,可解释3.0%~21.1%的表型变异。其中,具有较高LOD值和贡献率的2个主效QTL(q GS4-1和q GS7-1)能够被重复检测到,是后续基因克隆的候选位点。根据Bin标记分型结果将不同子代在两个稳定QTL区间内分为WR型和广百香占型,在F2:3群体中进行聚合效应分析,发现聚合增效等位基因数量越多的家系,其淹水条件下的胚芽鞘越长,这些携带多个耐性QTL的株系可为分子育种培育耐低氧萌发水稻新品种提供亲本资源。展开更多
The seed storage materials accumulate during seed development,and are essential for seed germination and seedling establishment.Here we employed two bi-parental populations of an F2:3 population developed from a cross...The seed storage materials accumulate during seed development,and are essential for seed germination and seedling establishment.Here we employed two bi-parental populations of an F2:3 population developed from a cross of improved 220(I220,small seeds with low starch)and PH4CV(large seeds with high starch),as well as recombinant-inbred lines(RILs)of X178(high starch)and its improved introgression line I178(low starch),to identify the genes that control seed storage materials.We identified a total of 12 QTLs for starch,protein and oil,which explained 3.44-10.79%of the phenotypic variances.Among them,qSTA2-1 identified in F2:3 and qSTA2-2 identified in the RILs partially overlapped at an interval of 7.314-9.554 Mb,and they explained 3.44-10.21%of the starch content variation,so they were selected for further study.Fine mapping of qSTA2-2 with the backcrossed populations of ^(I220)/PH4CV in each generation narrowed it down to a 199.7 kb interval that contains 14 open reading frames(ORFs).Transcriptomic analysis of developing seeds from the near-isogenic lines(NILs)of ^(I220)/PH4CV(BC_(5)F_(2))showed that only 11 ORFs were expressed in 20 days after pollination(DAP)seeds.Five of them were upregulated and six of them were downregulated in NIL^(I220),and the differentially expressed genes(DEGs)between NIL^(I220) and NIL^(PH4CV) were enriched in starch metabolism,hormone signal transduction and glycosaminoglycan degradation.Of the eleven NIL^(I220) differential expressed ORFs,ORF4(Zm00001d002260)and ORF5(Zm00001d002261)carry 75%protein sequence similarity,both encodes an glycolate oxidase,were the possible candidates of qSTA2-2.Further analysis and validation indicated that mutation of the qSTA2-2 locus resulted in the dysfunction of ABA accumulation,the embryo/endosperm ratio and the starch and hormone levels.展开更多
Grain weight is one of the key components of wheat(Triticum aestivum L.)yield.Genetic manipulation of grain weight is an efficient approach for improving yield potential in breeding programs.A recombinant inbred line(...Grain weight is one of the key components of wheat(Triticum aestivum L.)yield.Genetic manipulation of grain weight is an efficient approach for improving yield potential in breeding programs.A recombinant inbred line(RIL)population derived from a cross between W7268 and Chuanyu 12(CY12)was employed to detect quantitative trait loci(QTLs)for thousand-grain weight(TGW),grain length(GL),grain width(GW),and the ratio of grain length to width(GLW)in six environments.Seven major QTLs,QGl.cib-2D,QGw.cib-2D,QGw.cib-3B,QGw.cib-4B.1,QGlw.cib-2D.1,QTgw.cib-2D.1 and QTgw.cib-3B.1,were consistently identified in at least four environments and the best linear unbiased estimation(BLUE)datasets,and they explained 2.61 to 34.85%of the phenotypic variance.Significant interactions were detected between the two major TGW QTLs and three major GW loci.In addition,QTgw.cib-3B.1 and QGw.cib-3B were co-located,and the improved TGW at this locus was contributed by GW.Unlike other loci,QTgw.cib-3B.1/QGw.cib-3B had no effect on grain number per spike(GNS).They were further validated in advanced lines using Kompetitive Allele Specific PCR(KASP)markers,and a comparison analysis indicated that QTgw.cib-3B.1/QGw.cib-3B is likely a novel locus.Six haplotypes were identified in the region of this QTL and their distribution frequencies varied between the landraces and cultivars.According to gene annotation,spatial expression patterns,ortholog analysis and sequence variation,the candidate gene of QTgw.cib-3B.1/QGw.cib-3B was predicted.Collectively,the major QTLs and KASP markers reported here provide valuable information for elucidating the genetic architecture of grain weight and for molecular marker-assisted breeding in grain yield improvement.展开更多
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 ...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.展开更多
基金supported by grants from the STI 2030-Major Projects,China(2022ZD040190101,2022ZD040190502)the National Natural Science Foundation of China(32072130,32272162 and 31701437)+1 种基金the Project of Sanya Yazhou Bay Science and Technology City,China(SCKJ-JYRC-2023-64)the 2115 Talent Development Program of China Agricultural University,and the China Agriculture Research System(CARS-02-13)。
文摘The seed storage materials accumulate during seed development,and are essential for seed germination and seedling establishment.Here we employed two bi-parental populations of an F2:3 population developed from a cross of improved 220(I220,small seeds with low starch)and PH4CV(large seeds with high starch),as well as recombinant-inbred lines(RILs)of X178(high starch)and its improved introgression line I178(low starch),to identify the genes that control seed storage materials.We identified a total of 12 QTLs for starch,protein and oil,which explained 3.44-10.79%of the phenotypic variances.Among them,qSTA2-1 identified in F2:3 and qSTA2-2 identified in the RILs partially overlapped at an interval of 7.314-9.554 Mb,and they explained 3.44-10.21%of the starch content variation,so they were selected for further study.Fine mapping of qSTA2-2 with the backcrossed populations of ^(I220)/PH4CV in each generation narrowed it down to a 199.7 kb interval that contains 14 open reading frames(ORFs).Transcriptomic analysis of developing seeds from the near-isogenic lines(NILs)of ^(I220)/PH4CV(BC_(5)F_(2))showed that only 11 ORFs were expressed in 20 days after pollination(DAP)seeds.Five of them were upregulated and six of them were downregulated in NIL^(I220),and the differentially expressed genes(DEGs)between NIL^(I220) and NIL^(PH4CV) were enriched in starch metabolism,hormone signal transduction and glycosaminoglycan degradation.Of the eleven NIL^(I220) differential expressed ORFs,ORF4(Zm00001d002260)and ORF5(Zm00001d002261)carry 75%protein sequence similarity,both encodes an glycolate oxidase,were the possible candidates of qSTA2-2.Further analysis and validation indicated that mutation of the qSTA2-2 locus resulted in the dysfunction of ABA accumulation,the embryo/endosperm ratio and the starch and hormone levels.
基金supported by the Major Program of National Agricultural Science and Technology of China(NK20220607)the West Light Foundation of the Chinese Academy of Sciences(2022XBZG_XBQNXZ_A_001)the Sichuan Science and Technology Program,China(2022ZDZX0014)。
文摘Grain weight is one of the key components of wheat(Triticum aestivum L.)yield.Genetic manipulation of grain weight is an efficient approach for improving yield potential in breeding programs.A recombinant inbred line(RIL)population derived from a cross between W7268 and Chuanyu 12(CY12)was employed to detect quantitative trait loci(QTLs)for thousand-grain weight(TGW),grain length(GL),grain width(GW),and the ratio of grain length to width(GLW)in six environments.Seven major QTLs,QGl.cib-2D,QGw.cib-2D,QGw.cib-3B,QGw.cib-4B.1,QGlw.cib-2D.1,QTgw.cib-2D.1 and QTgw.cib-3B.1,were consistently identified in at least four environments and the best linear unbiased estimation(BLUE)datasets,and they explained 2.61 to 34.85%of the phenotypic variance.Significant interactions were detected between the two major TGW QTLs and three major GW loci.In addition,QTgw.cib-3B.1 and QGw.cib-3B were co-located,and the improved TGW at this locus was contributed by GW.Unlike other loci,QTgw.cib-3B.1/QGw.cib-3B had no effect on grain number per spike(GNS).They were further validated in advanced lines using Kompetitive Allele Specific PCR(KASP)markers,and a comparison analysis indicated that QTgw.cib-3B.1/QGw.cib-3B is likely a novel locus.Six haplotypes were identified in the region of this QTL and their distribution frequencies varied between the landraces and cultivars.According to gene annotation,spatial expression patterns,ortholog analysis and sequence variation,the candidate gene of QTgw.cib-3B.1/QGw.cib-3B was predicted.Collectively,the major QTLs and KASP markers reported here provide valuable information for elucidating the genetic architecture of grain weight and for molecular marker-assisted breeding in grain yield improvement.
基金supported by Natural Science Foundation of Fujian Province (CN) (2020I0009, 2022J01596)Cooperation Project on University Industry-Education-Research of Fujian Provincial Science and Technology Plan (CN) (2022N5011)+1 种基金Lancang-Mekong Cooperation Special Fund (2017-2020)International Sci-Tech Cooperation and Communication Program of Fujian Agriculture and Forestry University (KXGH17014)。
文摘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.
