Parentage analysis of natural citrus hybrid ‘Zhelong Zhoupigan’ based on nuclear and chloroplast SSR markers

2015 ◽  
Vol 186 ◽  
pp. 24-30 ◽  
Author(s):  
Hang Li ◽  
Xiaoming Yang ◽  
Lianshu Zhu ◽  
Hualin Yi ◽  
Lijun Chai ◽  
...  
Keyword(s):  
Ssr Markers ◽  
Parentage Analysis ◽  
Chloroplast Ssr

scholarly journals Parentage Analysis in Pear Cultivars Characterized by SSR Markers

2003 ◽  
Vol 72 (3) ◽  
pp. 182-189 ◽  
Author(s):  
Tetsuya Kimura ◽  
Yutaka Sawamura ◽  
Kazuo Kotobuki ◽  
Nagao Matsuta ◽  
Tateki Hayashi ◽  
...  
Keyword(s):  
Ssr Markers ◽  
Parentage Analysis

scholarly journals Genetic Relationships between Cultivated and Wild Olive Trees (Olea Europaea L. Var. Europaea and Var. Sylvestris) Based on Nuclear and Chloroplast SSR Markers

2010 ◽  
Vol 01 (02) ◽  
pp. 95-103 ◽  
Author(s):  
Hedia Hannachi ◽  
Catherine Breton ◽  
Monji Msallem ◽  
Salem Ben El Hadj ◽  
Mohamed El Gazzah ◽  
...  
Keyword(s):  
Ssr Markers ◽  
Olea Europaea ◽  
Genetic Relationships ◽  
Olea Europaea L ◽  
Wild Olive ◽  
Olive Trees ◽  
Chloroplast Ssr ◽  
Olea Europaéa

Genetic diversity and phylogeny of Japanese sake-brewing rice as revealed by AFLP and nuclear and chloroplast SSR markers

2004 ◽  
Vol 109 (8) ◽  
pp. 1586-1596 ◽  
Author(s):  
Z. Hashimoto ◽  
N. Mori ◽  
M. Kawamura ◽  
T. Ishii ◽  
S. Yoshida ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Ssr Markers ◽  
Chloroplast Ssr

scholarly journals Parentage Analysis in Japanese Peaches using SSR Markers

2003 ◽  
Vol 53 (1) ◽  
pp. 35-40 ◽  
Author(s):  
Toshiya Yamamoto ◽  
Kouhei Mochida ◽  
Tsuyoshi Imai ◽  
Takashi Haji ◽  
Hideaki Yaegaki ◽  
...  
Keyword(s):  
Ssr Markers ◽  
Parentage Analysis

Genetic structure of gall oak (Quercus infectoria) characterized by nuclear and chloroplast SSR markers

2017 ◽  
Vol 13 (3) ◽  
Author(s):  
Negar Mohammad-Panah ◽  
Naghi Shabanian ◽  
Ali Khadivi ◽  
Mohammad-Shafie Rahmani ◽  
Arezoo Emami
Keyword(s):  
Genetic Structure ◽  
Ssr Markers ◽  
Chloroplast Ssr ◽  
Quercus Infectoria

Genetic variation in wild Prunus L. subgen. Cerasus germplasm from Iran characterized by nuclear and chloroplast SSR markers

Trees ◽  
2013 ◽  
Vol 28 (2) ◽  
pp. 471-485 ◽  
Author(s):  
Abdollah Khadivi-Khub ◽  
Zabihollah Zamani ◽  
Reza Fattahi ◽  
Ana Wünsch
Keyword(s):  
Genetic Variation ◽  
Ssr Markers ◽  
Chloroplast Ssr

scholarly journals Genetic Diversity, Population Structure, Parentage Analysis, and Construction of Core Collections in the French Apple Germplasm Based on SSR Markers

2016 ◽  
Vol 34 (4) ◽  
pp. 827-844 ◽  
Author(s):  
Ludivine Lassois ◽  
Caroline Denancé ◽  
Elisa Ravon ◽  
Arnaud Guyader ◽  
Rémi Guisnel ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Ssr Markers ◽  
Parentage Analysis ◽  
Core Collections

scholarly journals Distance-based exclusion method for parentage analysis using microsatellites (SSR) markers

2021 ◽  
Author(s):  
Gil-Muñoz Francisco ◽  
Abrahamsson Sara ◽  
García-Gil M Rosario
Keyword(s):  
Ssr Markers ◽  
Parentage Analysis ◽  
Resolving Power ◽  
Genotyping Errors ◽  
Distance Ratio ◽  
Real Dataset ◽  
Error Calculation ◽  
Biological Meaning ◽  
Exclusion Method

AbstractGenotyping mistakes represent a challenge in parental assignment where even small errors can lead to significant amounts of unassigned siblings. Different parental assignment algorithms have been designed to approach this problem. The Exclusion method is the most applied for its reliability and biological meaning. However, the resolving power of this method is the lowest for data containing genotyping errors. We introduce a new distance-based approach which we coin as Distance-Based Exclusion (DBE). The DBE method calculates the distance between the offspring haplotype and haplotype of each of the potential fathers. The father with the lowest distance is then assigned as candidate father according to a distance ratio (α). We have tested the Exclusion and DBE methods using a real dataset of 1230 offsprings subdivided into families of 25 individuals. Each family had six potential fathers and one known mother. Compared with the Exclusion method, the DBE method is able to solve 4.7% more individuals (64.4% Exclusion vs 69.1% DBE) using the most restrictive α tested without errors. DBE method can also be used together with the Exclusion method for error calculation and to further solve unassigned individuals. Using a two-step approach, we were able to assign 98.1% of the offsprings with a total predicted error of 4.7%. Considering the results obtained, we propose the use of the DBE method in combination with the Exclusion method for parental assignment.

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