Inheritance of Soybean Aphid Resistance in PI 567541B and PI 567598B

Crop Science ◽  
2008 ◽  
Vol 48 (5) ◽  
pp. 1759-1763 ◽  
Author(s):  
Clarice Mensah ◽  
Christina DiFonzo ◽  
Dechun Wang
Author(s):  
S J Bhusal ◽  
R L Koch ◽  
A J Lorenz

Abstract Soybean aphid (Aphis glycines Matsumura (Hemiptera: Aphididae)) has been a major pest of soybean in North America since its detection in this continent in 2000 and subsequent spread. Although several aphid resistance genes have been identified, at least four soybean aphid biotypes have been discovered, with three of them being virulent on soybean cultivars with certain soybean aphid resistance genes. These biotypes are known to vary across years and locations, but information on their variation within single fields is limited. An investigation was conducted to study the variation of soybean aphid biotypes within single townships and fields in Minnesota. Screening of 28 soybean aphid isolates collected from seven soybean fields (six soybean fields in Cairo and Wellington Townships of Renville County, MN and one field in Wilmar Township of Kandiyohi County, MN) revealed the existence of multiple known biotypes of soybean aphid within single fields of soybean. We found up to three biotypes of soybean aphid in a single field. Two biotypes were found in five fields while only one field had only a single biotype. Three isolates presented reactions on a panel of resistant and susceptible indicator lines that were different from known biotypes. These results highlight the importance of characterizing soybean aphid biotypes in small geographical areas and utilizing generated knowledge to develop soybean cultivars pyramided with multiple resistance genes. The outcome will be decreased use of insecticides, thereby improving economic and environmental sustainability of soybean production.


Crop Science ◽  
2007 ◽  
Vol 47 (1) ◽  
pp. 463-463
Author(s):  
Curtis B. Hill ◽  
Yan Li ◽  
Glen L. Hartman

2014 ◽  
Vol 127 (5) ◽  
pp. 1251-1259 ◽  
Author(s):  
Ki-Seung Kim ◽  
Anitha Chirumamilla ◽  
Curtis B. Hill ◽  
Glen L. Hartman ◽  
Brian W. Diers

2008 ◽  
Vol 117 (6) ◽  
pp. 955-962 ◽  
Author(s):  
M. A. Rouf Mian ◽  
Sung-Taeg Kang ◽  
Scott E. Beil ◽  
Ronald B. Hammond

Crop Science ◽  
2014 ◽  
Vol 54 (5) ◽  
pp. 2093-2098 ◽  
Author(s):  
Siddhi J. Bhusal ◽  
Guo-Liang Jiang ◽  
Louis S. Hesler ◽  
James H. Orf

2011 ◽  
Vol 124 (1) ◽  
pp. 13-22 ◽  
Author(s):  
Tae-Hwan Jun ◽  
M. A. Rouf Mian ◽  
Andrew P. Michel

Crop Science ◽  
2017 ◽  
Vol 57 (6) ◽  
pp. 3035-3042
Author(s):  
Russell A. Ward ◽  
Ki-Seung Kim ◽  
Brian W. Diers

2008 ◽  
Vol 118 (3) ◽  
pp. 473-482 ◽  
Author(s):  
Guorong Zhang ◽  
Cuihua Gu ◽  
Dechun Wang

2006 ◽  
Vol 19 (1) ◽  
pp. 25-34 ◽  
Author(s):  
Yan Li ◽  
Curtis B. Hill ◽  
Shawn R. Carlson ◽  
Brian W. Diers ◽  
Glen L. Hartman

Genome ◽  
2007 ◽  
Vol 50 (12) ◽  
pp. 1104-1111 ◽  
Author(s):  
Charles Y. Chen ◽  
Cuihua Gu ◽  
Clarice Mensah ◽  
Randall L. Nelson ◽  
Dechun Wang

The soybean aphid ( Aphis glycines Matsumura) has become a major pest of soybean in North America since 2000. Seven aphid resistance sources, PI 71506, Dowling, Jackson, PI 567541B, PI 567598B, PI 567543C, and PI 567597C, have been identified. Knowledge of genetic relationships among these sources and their ancestral parents will help breeders develop new cultivars with different resistance genes. The objective of this research was to examine the genetic relationships among these resistance sources. Sixty-one lines were tested with 86 simple sequence repeat (SSR) markers from 20 linkage groups. Non-hierarchical (VARCLUS) and hierarchical (Ward’s) clustering and multidimensional scaling (MDS) were used to determine relationships among the 61 lines. Two hundred and sixty-two alleles of the 86 SSR loci were detected with a mean polymorphism information content of 0.36. The 61 lines were grouped into 4 clusters by both clustering methods and the MDS results consistently corresponded to the assigned clusters. The 7 resistance sources were clustered into 3 different groups corresponding to their geographical origins and known pedigree information, indicating genetic differences among these sources. The largest variation was found among individuals within different clusters by analysis of molecular variance.


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