Introgression lines population was effectively used in mapping quantitative trait loci （QTLs）, identifying favorable genes, discovering hidden genetic variation, evaluating the action or interaction of QTLs in multi...Introgression lines population was effectively used in mapping quantitative trait loci （QTLs）, identifying favorable genes, discovering hidden genetic variation, evaluating the action or interaction of QTLs in multiple conditions and providing the favorable experimental materials for plant breeding and genetic research. In this study, an advanced backcross and consecutive selfing strategy was used to develop introgression lines （ILs）, which derived from an accession of Oryza rufipogon Griff. collected from Yuanjiang County, Yunnan Province of China, as the donor, and an elite indica cultivar Teqing （O. sativa L.）, as the recipient. Introgression segments from O. rufipogon were screened using 179 polymorphic simple sequence repeats （SSR） markers in the genome of each IL. Introgressed segments carried by the introgression lines population contained 120 ILs covering the whole O. rufipogon genome. The mean number of homozygous O. rufipogon segments per introgression line was about 3.88. The average length of introgressed segments was approximate 25.5 cM, and about 20.8% of these segments had sizes less than 10 cM. The genome of each IL harbored the chromosomal fragments of O. rufipogon ranging from 0.54% to 23.7%, with an overall average of 5.79%. At each locus, the ratio of substitution of O. rufipogon alleles had a range of 1.67-9.33, with an average of 5.50. A wide range of alterations in morphological and yield-related traits were also found in the introgression lines population. Using single-point analysis, a total of 37 putative QTLs for yield and yield components were detected at two sites with 7%-20% explaining the phenotypic variance. Nineteen QTLs （51.4%） were detected at both sites, and the alleles from O. rufipogon at fifteen loci （40.5%） improved the yield and yield components in the Teqing background. These O. rufipogon-O, sativa introgression lines will serve as genetic materials for identifying and using favorable genes from common wild rice.展开更多
Synthetic hexaploid wheat （SHW） represents a valuable source of new resistances to a range of biotic and abiotic stresses. A recombinant inbred line （RIL） population with 127 recombinant inbred lines derived from ...Synthetic hexaploid wheat （SHW） represents a valuable source of new resistances to a range of biotic and abiotic stresses. A recombinant inbred line （RIL） population with 127 recombinant inbred lines derived from a SHW-derived variety Chuanmai 42 crossing with a Chinese spring wheat variety Chuannong 16 was used to map QTLs for agronomic traits including grain yield, grains per square meter, thousand-kernel weight, spikes per square meter, grain number per spike, grains weight per spike, and biomass yield. The population was genotyped using 184 simple-sequence repeat （SSR） markers and 34 sequence-related amplified polymorphism （SRAP） markers. Of 76 QTLs （LOD〉2.5） identified, 42 were found to have a positive effect from Chuanmai 42. The QTL QGy.saas-4D.2 associated with grain yield on chromosome 4D was detected in four of the six environments and the combined analysis, and the mean yield, across six environments, of individuals carrying the Chuanmai 42 allele at this locus was 8.9% higher than that of those lines carrying the Chuannong 16 allele. Seven clusters of the yield-coincident QTLs were detected on 1A, 4A, 3B, 5B, 4D, and 7D.展开更多
The contribution of spike photosynthesis to grain yield(GY)has been overlooked in the accurate spectral prediction of yield.Thus,it’s essential to construct and estimate a yield-related phenotypic trait considering s...The contribution of spike photosynthesis to grain yield(GY)has been overlooked in the accurate spectral prediction of yield.Thus,it’s essential to construct and estimate a yield-related phenotypic trait considering spike photosynthesis.Based on field and spectral reflectance data from 19 wheat cultivars under two nitrogen fertilization conditions in two years,our objectives were to(i)construct a yield-related phenotypic trait(spike–leaf composite indicator,SLI)accounting for the contribution of the spike to photosynthesis,(ii)develop a novel spectral index(enhanced triangle vegetation index,ETVI3)sensitive to SLI,and(iii)establish and evaluate SLI estimation models by integrating spectral indices and machine learning algorithms.The results showed that SLI was sensitive to nitrogen fertilizer and wheat cultivar variation as well as a better predictor of yield than the leaf area index.ETVI3 maintained a strong correlation with SLI throughout the growth stage,whereas the correlations of other spectral indices with SLI were poor after spike emergence.Integrating spectral indices and machine learning algorithms improved the estimation accuracy of SLI,with the most accurate estimates of SLI showing coefficient of determination,root mean square error(RMSE),and relative RMSE values of 0.71,0.047,and 26.93%,respectively.These results provide new insights into the role of fruiting organs for the accurate spectral prediction of GY.This high-throughput SLI estimation approach can be applied for wheat yield prediction at whole growth stages and may be assisted with agronomical practices and variety selection.展开更多
Despite the great success achieved by the exploitation of heterosis in rice,the genetic basis of heterosis is still not well understood.We adopted an advanced-backcross breeding strategy to dissect the genetic basis o...Despite the great success achieved by the exploitation of heterosis in rice,the genetic basis of heterosis is still not well understood.We adopted an advanced-backcross breeding strategy to dissect the genetic basis of heterosis for yield and eight related traits.Four testcross(TC) populations with 228 testcross F1 combinations were developed by crossing57 introgression lines with four types of widely used male sterile lines using a North Carolina II mating design.Analysis of variance indicated that the effects of testcross F1 combinations and their parents were significant or highly significant for most of the traits in both years,and all interaction effects with year were significant for most of the traits.Positive midparent heterosis(HMP) was observed for most traits in the four TC populations in the two years.The relative HMPlevels for most traits varied from highly negative to highly positive.Sixty-two dominant-effect QTL were identified for HMPof the nine traits in the four TC populations in the two years.Of these,22 QTL were also identified for the performance of testcross F1.Most dominant-effect QTL could individually explain more than 10% of the phenotypic variation.Four QTL clusters were observed including the region surrounding the RM9–RM297 region on chromosome 1,the RM110–RM279–RM8–RM5699–RM452 region on chromosome 2,the RM5463 locus on chromosome 6 and the RM1146–RM147 region on chromosome 10.The identified QTL for heterosis provide valuable information for dissecting the genetic basis of heterosis.展开更多
基金Supported by the Project of Conservation and Utilization of Agricultural Wild Plants of the Ministry of Agriculture of China and a Grant from High- Tech Research and Development （863） Program of China （2006AA100101 ）, and the National Natural Science Foundation of China （30270803）. Publication of this paper is supported by the National Natural Science Foundation of China （30624808）.
文摘Introgression lines population was effectively used in mapping quantitative trait loci （QTLs）, identifying favorable genes, discovering hidden genetic variation, evaluating the action or interaction of QTLs in multiple conditions and providing the favorable experimental materials for plant breeding and genetic research. In this study, an advanced backcross and consecutive selfing strategy was used to develop introgression lines （ILs）, which derived from an accession of Oryza rufipogon Griff. collected from Yuanjiang County, Yunnan Province of China, as the donor, and an elite indica cultivar Teqing （O. sativa L.）, as the recipient. Introgression segments from O. rufipogon were screened using 179 polymorphic simple sequence repeats （SSR） markers in the genome of each IL. Introgressed segments carried by the introgression lines population contained 120 ILs covering the whole O. rufipogon genome. The mean number of homozygous O. rufipogon segments per introgression line was about 3.88. The average length of introgressed segments was approximate 25.5 cM, and about 20.8% of these segments had sizes less than 10 cM. The genome of each IL harbored the chromosomal fragments of O. rufipogon ranging from 0.54% to 23.7%, with an overall average of 5.79%. At each locus, the ratio of substitution of O. rufipogon alleles had a range of 1.67-9.33, with an average of 5.50. A wide range of alterations in morphological and yield-related traits were also found in the introgression lines population. Using single-point analysis, a total of 37 putative QTLs for yield and yield components were detected at two sites with 7%-20% explaining the phenotypic variance. Nineteen QTLs （51.4%） were detected at both sites, and the alleles from O. rufipogon at fifteen loci （40.5%） improved the yield and yield components in the Teqing background. These O. rufipogon-O, sativa introgression lines will serve as genetic materials for identifying and using favorable genes from common wild rice.
基金supported by the Sichuan Provincial Youth Foundation,China (09ZQ026-086)the earmarked fund for Modern Agro-Industry Technology Research System,China (nycytx-03)+1 种基金the National 863 Program of China (2006AA10Z1C6)the National Natural Science Foundation of China (30771338 and30871532)
文摘Synthetic hexaploid wheat （SHW） represents a valuable source of new resistances to a range of biotic and abiotic stresses. A recombinant inbred line （RIL） population with 127 recombinant inbred lines derived from a SHW-derived variety Chuanmai 42 crossing with a Chinese spring wheat variety Chuannong 16 was used to map QTLs for agronomic traits including grain yield, grains per square meter, thousand-kernel weight, spikes per square meter, grain number per spike, grains weight per spike, and biomass yield. The population was genotyped using 184 simple-sequence repeat （SSR） markers and 34 sequence-related amplified polymorphism （SRAP） markers. Of 76 QTLs （LOD〉2.5） identified, 42 were found to have a positive effect from Chuanmai 42. The QTL QGy.saas-4D.2 associated with grain yield on chromosome 4D was detected in four of the six environments and the combined analysis, and the mean yield, across six environments, of individuals carrying the Chuanmai 42 allele at this locus was 8.9% higher than that of those lines carrying the Chuannong 16 allele. Seven clusters of the yield-coincident QTLs were detected on 1A, 4A, 3B, 5B, 4D, and 7D.
基金supported by the National Natural Science Foundation of China(32371990,31971784)the Earmarked Fund for Jiangsu Agricultural Industry Technology System(JATS(2022)168,JATS(2022)468)+1 种基金the Jiangsu Provincial Cooperative Promotion Plan of Major Agricultural Technologies(2021-ZYXT-01-1)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_0783)。
文摘The contribution of spike photosynthesis to grain yield(GY)has been overlooked in the accurate spectral prediction of yield.Thus,it’s essential to construct and estimate a yield-related phenotypic trait considering spike photosynthesis.Based on field and spectral reflectance data from 19 wheat cultivars under two nitrogen fertilization conditions in two years,our objectives were to(i)construct a yield-related phenotypic trait(spike–leaf composite indicator,SLI)accounting for the contribution of the spike to photosynthesis,(ii)develop a novel spectral index(enhanced triangle vegetation index,ETVI3)sensitive to SLI,and(iii)establish and evaluate SLI estimation models by integrating spectral indices and machine learning algorithms.The results showed that SLI was sensitive to nitrogen fertilizer and wheat cultivar variation as well as a better predictor of yield than the leaf area index.ETVI3 maintained a strong correlation with SLI throughout the growth stage,whereas the correlations of other spectral indices with SLI were poor after spike emergence.Integrating spectral indices and machine learning algorithms improved the estimation accuracy of SLI,with the most accurate estimates of SLI showing coefficient of determination,root mean square error(RMSE),and relative RMSE values of 0.71,0.047,and 26.93%,respectively.These results provide new insights into the role of fruiting organs for the accurate spectral prediction of GY.This high-throughput SLI estimation approach can be applied for wheat yield prediction at whole growth stages and may be assisted with agronomical practices and variety selection.
基金funded by the National High Technology Research and Development Program of China (No.2014AA10A604)the Shenzhen Municipal Peacock Plan for introducing high-level overseas talents
文摘Despite the great success achieved by the exploitation of heterosis in rice,the genetic basis of heterosis is still not well understood.We adopted an advanced-backcross breeding strategy to dissect the genetic basis of heterosis for yield and eight related traits.Four testcross(TC) populations with 228 testcross F1 combinations were developed by crossing57 introgression lines with four types of widely used male sterile lines using a North Carolina II mating design.Analysis of variance indicated that the effects of testcross F1 combinations and their parents were significant or highly significant for most of the traits in both years,and all interaction effects with year were significant for most of the traits.Positive midparent heterosis(HMP) was observed for most traits in the four TC populations in the two years.The relative HMPlevels for most traits varied from highly negative to highly positive.Sixty-two dominant-effect QTL were identified for HMPof the nine traits in the four TC populations in the two years.Of these,22 QTL were also identified for the performance of testcross F1.Most dominant-effect QTL could individually explain more than 10% of the phenotypic variation.Four QTL clusters were observed including the region surrounding the RM9–RM297 region on chromosome 1,the RM110–RM279–RM8–RM5699–RM452 region on chromosome 2,the RM5463 locus on chromosome 6 and the RM1146–RM147 region on chromosome 10.The identified QTL for heterosis provide valuable information for dissecting the genetic basis of heterosis.
