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      QTL Landscape for Oil Content in Brassica juncea: Analysis in Multiple Bi-Parental Populations in High and “0” Erucic Background

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          Abstract

          Increasing oil content in oilseed mustard ( Brassica juncea) is a major breeding objective—more so, in the lines that have “0” erucic acid content (< 2% of the seed oil) as earlier studies have shown negative pleiotropic effect of erucic acid loci on the oil content, both in oilseed mustard and rapeseed. We report here QTL analysis of oil content in eight different mapping populations involving seven different parents—including a high oil content line J8 (~49%). The parental lines of the mapping populations contained wide variation in oil content and erucic acid content. The eight mapping populations were categorized into two sets—five populations with individuals segregating for erucic acid (SE populations) and the remaining three with zero erucic acid segregants (ZE populations). Meta-analysis of QTL mapped in individual SE populations identified nine significant C-QTL, with two of these merging most of the major oil QTL that colocalized with the erucic acid loci on the linkage groups A08 and B07. QTL analysis of oil content in ZE populations revealed a change in the landscape of the oil QTL compared to the SE populations, in terms of altered allelic effects and phenotypic variance explained by ZE QTL at the “common” QTL and observation of “novel” QTL in the ZE background. The important loci contributing to oil content variation, identified in the present study could be used in the breeding programmes for increasing the oil content in high erucic and “0” erucic backgrounds.

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          Most cited references41

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          Permutation tests for multiple loci affecting a quantitative character.

          The problem of detecting minor quantitative trait loci (QTL) responsible for genetic variation not explained by major QTL is of importance in the complete dissection of quantitative characters. Two extensions of the permutation-based method for estimating empirical threshold values are presented. These methods, the conditional empirical threshold (CET) and the residual empirical threshold (RET), yield critical values that can be used to construct tests for the presence of minor QTL effects while accounting for effects of known major QTL. The CET provides a completely nonparametric test through conditioning on markers linked to major QTL. It allows for general nonadditive interactions among QTL, but its practical application is restricted to regions of the genome that are unlinked to the major QTL. The RET assumes a structural model for the effect of major QTL, and a threshold is constructed using residuals from this structural model. The search space for minor QTL is unrestricted, and RET-based tests may be more powerful than the CET-based test when the structural model is approximately true.
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            The ABC's of comparative genomics in the Brassicaceae: building blocks of crucifer genomes.

            In this review we summarize recent advances in our understanding of phylogenetics, polyploidization and comparative genomics in the family Brassicaceae. These findings pave the way for a unified comparative genomic framework. We integrate several of these findings into a simple system of 24 conserved chromosomal blocks (labeled A-X). The naming, order, orientation and color-coding of these blocks are based on their positions in a proposed ancestral karyotype (n=8), rather than by their position in the reduced genome of Arabidopsis thaliana (n=5). We show how these crucifer building blocks can be rearranged to model the genome structures of A. thaliana, Arabidopsis lyrata, Capsella rubella and Brassica rapa. A framework for comparison between species is timely because several crucifer genome-sequencing projects are underway.
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              BioMercator: integrating genetic maps and QTL towards discovery of candidate genes.

              Breeding programs face the challenge of integrating information from genomics and from quantitative trait loci (QTL) analysis in order to identify genomic sequences controlling the variation of important traits. Despite the development of integrative databases, building a consensus map of genes, QTL and other loci gathered from multiple maps remains a manual and tedious task. Nevertheless, this is a critical step to reveal co-locations between genes and QTL. Another important matter is to determine whether QTL linked to same traits or related ones is detected in independent experiments and located in the same region, and represents a single locus or not. Statistical tools such as meta-analysis can be used to answer this question. BioMercator has been developed to automate map compilation and QTL meta-analysis, and to visualize co-locations between genes and QTL through a graphical interface. Available upon request (http://moulon/~bioinfo/BioMercator/). Free of charge for academic use.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                16 October 2018
                2018
                : 9
                : 1448
                Affiliations
                [1] 1Department of Genetics, University of Delhi South Campus , New Delhi, India
                [2] 2Centre for Genetic Manipulation of Crop Plants, University of Delhi South Campus , New Delhi, India
                Author notes

                Edited by: Maoteng Li, Huazhong University of Science and Technology, China

                Reviewed by: Leonardo Velasco, Instituto de Agricultura Sostenible (IAS), Spain; Harsh Raman, New South Wales Department of Primary Industries, Australia

                *Correspondence: Akshay K. Pradhan pradhancgmcp@ 123456gmail.com

                This article was submitted to Plant Breeding, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2018.01448
                6198181
                30386353
                b79daa1a-f8ed-44a4-8ee5-c596bef6d45e
                Copyright © 2018 Rout, Yadav, Yadava, Mukhopadhyay, Gupta, Pental and Pradhan.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 08 June 2018
                : 12 September 2018
                Page count
                Figures: 3, Tables: 8, Equations: 0, References: 46, Pages: 15, Words: 10222
                Funding
                Funded by: Department of Biotechnology, Ministry of Science and Technology 10.13039/501100001407
                Award ID: BT/01/COE/08/06/-II
                Award ID: BT/01/NDDB/UDSC/2016
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                brassica juncea,seed oil content,seed erucic acid content,qtl mapping,meta-analysis,pleiotropy

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