100-seed weight is a very complicated quantitative trait of yield. The study of gene mapping for yield trait in soybean is very important for application. However, the mapping result of 100-seed weight was dispersed, ...100-seed weight is a very complicated quantitative trait of yield. The study of gene mapping for yield trait in soybean is very important for application. However, the mapping result of 100-seed weight was dispersed, the public map should be chosen which was suitable for the published results integrated, and to improve yield. In this research, an integrated map of 100-seed weight QTLs in soybean had been established with soymap2 published in 2004 as a reference map. QTLs of 100-seed weight in soybean were collected in recent 20 yr. With the software BioMercator 2.1, QTLs from their own maps were projected to the reference map. From published papers, 65 QTLs of 100-seed weight were collected and 53 QTLs were integrated, including 17 reductive effect QTLs and 36 additive effect QTLs. 12 clusters of QTLs were found in the integrated map. A method of meta-analysis was used to narrow down the confidence interval, and 6 additive QTLs and 6 reductive QTLs and their corresponding markers were obtained respectively. The minimum confidence interval （C.I.） was shrunk to 1.52 cM. These results would lay the foundation for marker-assisted selection and mapping QTL precisely, as well as QTL gene cloning in soybean.展开更多
1000-grain weight （ TGW） is one ot the three component traits ot the grain yiela in rice （Oryza sativa L）. This study was conducted to validate and fine-map qTGWl. 1, a minor QTL for TGW which was previously locat...1000-grain weight （ TGW） is one ot the three component traits ot the grain yiela in rice （Oryza sativa L）. This study was conducted to validate and fine-map qTGWl. 1, a minor QTL for TGW which was previously located in a 3.7-Mb region on the long arm of rice chromosome 1. Five sets of near isogenic lines （NILs） were developed from two BC2F4 populations of the indica rice cross Zhenshan 973/Milyang 46 The NIL sets consisted of two homozygous genotypic groups differing in the regions RM11448-RM11522, RM11448-RM11549, RM1232-RM11615, RM11543-RM11554 and RM11569-RM11621, respectively. Four traits, including TGW, grain length, grain width and heading date, were measured. Phenotypic difference between the two genotypic groups in each NIL population was analyzed using SAS procedure GLM. Significant QTL effects were detected on TGW with the Zhenshan 97 allele increasing grain weight by 0.12 g to 0.14 g and explaining 8.30% to 15.19% of the phenotypic variance. Significant effects were also observed for grain length and width, whereas no significant effect was found for heading date. Based on comparison among the five NILs on the segregating regions and the results of QTL analysis, qTGWl. 1 was delimited to a 376.9-kb region flanked by DNA markers Wn28382 and RMl1554. Our results indicate that the effects of minor QTLs could be steadily detected in a highly isogenic background and suggest that such QTLs could be utilized in the breeding of high-yielding rice varieties.展开更多
In order to clarify the impact posed by wheat powdery mildew （Blumeria graminis f. sp. tritici） on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, ...In order to clarify the impact posed by wheat powdery mildew （Blumeria graminis f. sp. tritici） on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009-2010, 2010-2011 and 2011-2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index （DI）, as well as area under disease progress curve （AUDPC） were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point （CP） of growth stages （GS） and AUDPC in the three growing seasons, respectively. The CPs for estimating 1 000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS l 0.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011-2012 season were significant different from these for 2009-2010 and 2010-2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1 000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred.展开更多
supported by a grant from the National High-Tech R＆D Program of China （2014AA10A603, 2014AA10A604）;a grant from the Youth Foundation in Sichuan, China （2011JTD0022）;the special fund for China Agricultural Researc...supported by a grant from the National High-Tech R＆D Program of China （2014AA10A603, 2014AA10A604）;a grant from the Youth Foundation in Sichuan, China （2011JTD0022）;the special fund for China Agricultural Research System （CARS-01-08）;the Provincial Specialized Funds for Innovation Ability Promotion in Sichuan, China （2013GXJS005）展开更多
基金supported by the Chinese Transgenic Specific Technology Programs (2009ZX08009-013B)
文摘100-seed weight is a very complicated quantitative trait of yield. The study of gene mapping for yield trait in soybean is very important for application. However, the mapping result of 100-seed weight was dispersed, the public map should be chosen which was suitable for the published results integrated, and to improve yield. In this research, an integrated map of 100-seed weight QTLs in soybean had been established with soymap2 published in 2004 as a reference map. QTLs of 100-seed weight in soybean were collected in recent 20 yr. With the software BioMercator 2.1, QTLs from their own maps were projected to the reference map. From published papers, 65 QTLs of 100-seed weight were collected and 53 QTLs were integrated, including 17 reductive effect QTLs and 36 additive effect QTLs. 12 clusters of QTLs were found in the integrated map. A method of meta-analysis was used to narrow down the confidence interval, and 6 additive QTLs and 6 reductive QTLs and their corresponding markers were obtained respectively. The minimum confidence interval （C.I.） was shrunk to 1.52 cM. These results would lay the foundation for marker-assisted selection and mapping QTL precisely, as well as QTL gene cloning in soybean.
基金supported by the National Science Foundation of China (Grant No. 31221004)a research grant of the China National Rice Research Institute (Grant No. 2012RG002-3)
文摘1000-grain weight （ TGW） is one ot the three component traits ot the grain yiela in rice （Oryza sativa L）. This study was conducted to validate and fine-map qTGWl. 1, a minor QTL for TGW which was previously located in a 3.7-Mb region on the long arm of rice chromosome 1. Five sets of near isogenic lines （NILs） were developed from two BC2F4 populations of the indica rice cross Zhenshan 973/Milyang 46 The NIL sets consisted of two homozygous genotypic groups differing in the regions RM11448-RM11522, RM11448-RM11549, RM1232-RM11615, RM11543-RM11554 and RM11569-RM11621, respectively. Four traits, including TGW, grain length, grain width and heading date, were measured. Phenotypic difference between the two genotypic groups in each NIL population was analyzed using SAS procedure GLM. Significant QTL effects were detected on TGW with the Zhenshan 97 allele increasing grain weight by 0.12 g to 0.14 g and explaining 8.30% to 15.19% of the phenotypic variance. Significant effects were also observed for grain length and width, whereas no significant effect was found for heading date. Based on comparison among the five NILs on the segregating regions and the results of QTL analysis, qTGWl. 1 was delimited to a 376.9-kb region flanked by DNA markers Wn28382 and RMl1554. Our results indicate that the effects of minor QTLs could be steadily detected in a highly isogenic background and suggest that such QTLs could be utilized in the breeding of high-yielding rice varieties.
基金financially supported by the National Basic Research Program of China(2010CB951503)the Special Fund for Agro-Scientific Research in the Public Interest,China(201303016)the National Key Technologies R&D Program of China(2012BAD19B04)
文摘In order to clarify the impact posed by wheat powdery mildew （Blumeria graminis f. sp. tritici） on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009-2010, 2010-2011 and 2011-2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index （DI）, as well as area under disease progress curve （AUDPC） were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point （CP） of growth stages （GS） and AUDPC in the three growing seasons, respectively. The CPs for estimating 1 000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS l 0.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011-2012 season were significant different from these for 2009-2010 and 2010-2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1 000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred.
基金supported by a grant from the National High-Tech R&D Program of China (2014AA10A603, 2014AA10A604)a grant from the Youth Foundation in Sichuan, China (2011JTD0022)+1 种基金the special fund for China Agricultural Research System (CARS-01-08)the Provincial Specialized Funds for Innovation Ability Promotion in Sichuan, China (2013GXJS005)
文摘supported by a grant from the National High-Tech R＆D Program of China （2014AA10A603, 2014AA10A604）;a grant from the Youth Foundation in Sichuan, China （2011JTD0022）;the special fund for China Agricultural Research System （CARS-01-08）;the Provincial Specialized Funds for Innovation Ability Promotion in Sichuan, China （2013GXJS005）
