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Plant Genetics and Molecular Biology

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Attention for Chapter 50: Trait Mapping Approaches Through Association Analysis in Plants
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Chapter title
Trait Mapping Approaches Through Association Analysis in Plants
Chapter number 50
Book title
Plant Genetics and Molecular Biology
Published in
Advances in biochemical engineering biotechnology, January 2018
DOI 10.1007/10_2017_50
Pubmed ID
Book ISBNs
978-3-31-991312-4, 978-3-31-991313-1
Authors

M. Saba Rahim, Himanshu Sharma, Afsana Parveen, Joy K. Roy

Abstract

Previously, association mapping (AM) methodology was used to unravel genetic complications in animal science by measuring the complex traits for candidate and non-candidate genes. Nowadays, this statistical approach is widely used to clarify the complexity in plant breeding program-based genome-wide breeding strategies, marker development, and diversity analysis. This chapter is particularly focused on methodologies with limitations and provides an overview of AM models and software used up to now. Association or linkage disequilibrium mapping has become a very popular method for discovering candidate and non-candidate genes and confirmation of quantitative trait loci (QTL) on various parts of the genome and in marker-assisted selection for breeding. Previously, various QTL investigations were carried out for different plants exclusively by linkage mapping. To help to understand the basics of modern molecular genetic techniques, in this chapter we summarize previous studies done on different crops. AM offers high-resolution power when there is large genotypic diversity and low linkage disequilibrium (LD) for the germplasm being investigated. The benefits of AM, compared with traditional QTL mapping, include a relatively detailed mapping resolution and a far less time-consuming approach since no mapping populations need to be generated. The advancements in genotyping and computational techniques have encouraged the use of AM. AM provides a fascinating approach for genetic investigation of QTLs, due to its resolution and the possibility to study the various genomic areas at the same time without construction of mapping populations. In this chapter we also discuss the advantages and disadvantages of AM, especially in the dicotyledonous crops Fabaceae and Solanaceae, with various genome-size reproductive strategies (clonal vs. sexual), and statistical models. The main objective of this chapter is to highlight the uses of association genetics in major and minor crop species that have trouble being analyzed for dissection of complex traits by identification of the factor responsible for controlling the effect of trait. Graphical Abstract.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 21%
Student > Ph. D. Student 3 13%
Other 2 8%
Student > Doctoral Student 2 8%
Student > Master 2 8%
Other 2 8%
Unknown 8 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 38%
Biochemistry, Genetics and Molecular Biology 3 13%
Unspecified 1 4%
Arts and Humanities 1 4%
Engineering 1 4%
Other 0 0%
Unknown 9 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 March 2018.
All research outputs
#18,590,133
of 23,026,672 outputs
Outputs from Advances in biochemical engineering biotechnology
#148
of 226 outputs
Outputs of similar age
#330,575
of 442,363 outputs
Outputs of similar age from Advances in biochemical engineering biotechnology
#5
of 7 outputs
Altmetric has tracked 23,026,672 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 226 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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