scholarly journals Utilization of STMS markers to verify admixture in clonal progenies of Acacia mapping populations and relabelling using assignment tests

2016 ◽  
Vol 61 (No. 5) ◽  
pp. 200-209
Author(s):  
Asif MJ ◽  
Ariffin MAT ◽  
Yit HM ◽  
M. Wong ◽  
Abdullah MZ
2019 ◽  
Vol 7 (6) ◽  
pp. 809-818 ◽  
Author(s):  
Wenjing Hu ◽  
Xinyao He ◽  
Susanne Dreisigacker ◽  
Carolina P. Sansaloni ◽  
Philomin Juliana ◽  
...  

Rice ◽  
2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Chaopu Zhang ◽  
Zhiyang Yuan ◽  
Yuntong Wang ◽  
Wenqiang Sun ◽  
Xinxin Tang ◽  
...  

Genes ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 604
Author(s):  
Paolo Vitale ◽  
Fabio Fania ◽  
Salvatore Esposito ◽  
Ivano Pecorella ◽  
Nicola Pecchioni ◽  
...  

Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F2 and F2-derived F3 families) and late (F6 and F7, recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F2 and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F2 mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging.


Genetics ◽  
2000 ◽  
Vol 155 (3) ◽  
pp. 1369-1378 ◽  
Author(s):  
Grant A Walling ◽  
Peter M Visscher ◽  
Leif Andersson ◽  
Max F Rothschild ◽  
Lizhen Wang ◽  
...  

Abstract For many species several similar QTL mapping populations have been produced and analyzed independently. Joint analysis of such data could be used to increase power to detect QTL and evaluate population differences. In this study, data were collated on almost 3000 pigs from seven different F2 crosses between Western commercial breeds and either the European wild boar or the Chinese Meishan breed. Genotypes were available for 31 markers on chromosome 4 (on average 8.3 markers per population). Data from three traits common to all populations (birth weight, mean backfat depth at slaughter or end of test, and growth rate from birth to slaughter or end of test) were analyzed for individual populations and jointly. A QTL influencing birth weight was detected in one individual population and in the combined data, with no significant interaction of the QTL effect with population. A QTL affecting backfat that had a significantly greater effect in wild boar than in Meishan crosses was detected. Some evidence for a QTL affecting growth rate was detected in all populations, with no significant differences between populations. This study is the largest F2 QTL analysis achieved in a livestock species and demonstrates the potential of joint analysis.


2010 ◽  
Vol 90 (1) ◽  
pp. 49-60 ◽  
Author(s):  
Z I Talukder ◽  
E Anderson ◽  
P N Miklas ◽  
M W Blair ◽  
J Osorno ◽  
...  

Common bean (Phaseolus vulgaris L.) is an important source of dietary protein and minerals worldwide. Genes conditioning variability for mineral contents are not clearly understood. Our ultimate goal is to identify genes conditioning genetic variation for Zn and Fe content. To establish mapping populations for this objective, we tested mineral content of 29 common bean genotypes. Chemical analyses revealed significant genetic variability for seed Zn and Fe contents among the genotypes. Genetic diversity was evaluated with 49 primer pairs, of which 23 were simple sequence repeats (SSR), 16 were developed from tentative consensus (TC) sequences, and 10 were generated from common bean NBS-LRR gene sequences. The discriminatory ability of molecular markers for identifying allelic variation among genotypes was estimated by polymorphism information content (PIC) and the genetic diversity was measured from genetic similarities between genotypes. Primers developed from NBS-LRR gene sequences were highly polymorphic in both PIC values and number of alleles (0.82 and 5.3), followed by SSRs (0.56 and 3.0), and markers developed from TC (0.39 and 2.0). genetic similarity values between genotypes ranged from 14.0 (JaloEEP558 and DOR364) to 91.4 (MIB152 and MIB465). Cluster analysis clearly discriminated the genotypes into Mesoamerican and Andean gene pools. Common bean genotypes were selected to include in crossing to enhance seed Zn and Fe content based on genetic diversity and seed mineral contents of the genotypes. Key words: Common bean, genetic diversity, mineral nutrients, breeding


1970 ◽  
Vol 2 (1) ◽  
pp. 72-89
Author(s):  
Umesh R Rosyara ◽  
Bal K Joshi

DNA-based molecular markers have been extensively utilized for mapping of genes and quantitative trait loci (QTL) of interest based on linkage analysis in mapping populations. This is in contrast to human genetics that use of linkage disequilibrium (LD)-based mapping for fine mapping of QTLs using single nucleotide polymorphisms. LD based association mapping (AM) has promise to be used in plants. Possible use of such approach may be for fine mapping of genes / QTLs, identifying favorable alleles for marker aided selection and cross validation of results from linkage mapping for precise location of genes / QTLs of interest. In the present review, we discuss different mapping populations, approaches, prospects and limitations of using association mapping in plant breeding populations. This is expected to create awareness in plant breeders in use of AM in crop improvement activities.Key words: Association mapping; plant breeding; DNA marker; quantitative trait lociDOI: http://dx.doi.org/10.3126/njb.v2i1.5686  Nepal Journal of Biotechnology Jan.2012, Vol.2(1): 72-89


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