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      Genome-Wide SNP Linkage Mapping and QTL Analysis for Fiber Quality and Yield Traits in the Upland Cotton Recombinant Inbred Lines Population

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          Abstract

          It is of significance to discover genes related to fiber quality and yield traits and tightly linked markers for marker-assisted selection (MAS) in cotton breeding. In this study, 188 F 8 recombinant inbred lines (RILs), derived from a intraspecific cross between HS46 and MARCABUCAG8US-1-88 were genotyped by the cotton 63K single nucleotide polymorphism (SNP) assay. Field trials were conducted in Sanya, Hainan Province, during the 2014–2015 cropping seasons under standard conditions. Results revealed significant differences ( P < 0.05) among RILs, environments and replications for fiber quality and yield traits. Broad-sense heritabilities of all traits including fiber length, fiber uniformity, micronaire, fiber elongation, fiber strength, boll weight, and lint percentage ranged from 0.26 to 0.66. A 1784.28 cM (centimorgans) linkage map, harboring 2618 polymorphic SNP markers, was constructed, which had 0.68 cM per marker density. Seventy-one quantitative trait locus (QTLs) for fiber quality and yield traits were detected on 21 chromosomes, explaining 4.70∼32.28% phenotypic variance, in which 16 were identified as stable QTLs across two environments. Meanwhile, 12 certain regions were investigated to be involved in the control of one (hotspot) or more (cluster) traits, mainly focused on Chr05, Chr09, Chr10, Chr14, Chr19, and Chr20. Nineteen pairs of epistatic QTLs (e-QTLs) were identified, of which two pairs involved in two additive QTLs. These additive QTLs, e-QTLs, and QTL clusters were tightly linked to SNP markers, which may serve as target regions for map-based cloning, gene discovery, and MAS in cotton breeding.

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          A modified algorithm for the improvement of composite interval mapping.

          Composite interval mapping (CIM) is the most commonly used method for mapping quantitative trait loci (QTL) with populations derived from biparental crosses. However, the algorithm implemented in the popular QTL Cartographer software may not completely ensure all its advantageous properties. In addition, different background marker selection methods may give very different mapping results, and the nature of the preferred method is not clear. A modified algorithm called inclusive composite interval mapping (ICIM) is proposed in this article. In ICIM, marker selection is conducted only once through stepwise regression by considering all marker information simultaneously, and the phenotypic values are then adjusted by all markers retained in the regression equation except the two markers flanking the current mapping interval. The adjusted phenotypic values are finally used in interval mapping (IM). The modified algorithm has a simpler form than that used in CIM, but a faster convergence speed. ICIM retains all advantages of CIM over IM and avoids the possible increase of sampling variance and the complicated background marker selection process in CIM. Extensive simulations using two genomes and various genetic models indicated that ICIM has increased detection power, a reduced false detection rate, and less biased estimates of QTL effects.
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            A rapid method for extraction of cotton (Gossypium spp.) genomic DNA suitable for RFLP or PCR analysis

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              Advances in molecular marker techniques and their applications in plant sciences.

              Detection and analysis of genetic variation can help us to understand the molecular basis of various biological phenomena in plants. Since the entire plant kingdom cannot be covered under sequencing projects, molecular markers and their correlation to phenotypes provide us with requisite landmarks for elucidation of genetic variation. Genetic or DNA based marker techniques such as RFLP (restriction fragment length polymorphism), RAPD (random amplified polymorphic DNA), SSR (simple sequence repeats) and AFLP (amplified fragment length polymorphism) are routinely being used in ecological, evolutionary, taxonomical, phylogenic and genetic studies of plant sciences. These techniques are well established and their advantages as well as limitations have been realized. In recent years, a new class of advanced techniques has emerged, primarily derived from combination of earlier basic techniques. Advanced marker techniques tend to amalgamate advantageous features of several basic techniques. The newer methods also incorporate modifications in the methodology of basic techniques to increase the sensitivity and resolution to detect genetic discontinuity and distinctiveness. The advanced marker techniques also utilize newer class of DNA elements such as retrotransposons, mitochondrial and chloroplast based microsatellites, thereby revealing genetic variation through increased genome coverage. Techniques such as RAPD and AFLP are also being applied to cDNA-based templates to study patterns of gene expression and uncover the genetic basis of biological responses. The review details account of techniques used in identification of markers and their applicability in plant sciences.
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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
                08 September 2016
                2016
                : 7
                : 1356
                Affiliations
                [1] 1Department of Agronomy, Zhejiang University Hangzhou, China
                [2] 2Department of Biotechnology and Genetic Engineering, Kohat University of Science and Technology Kohat, Pakistan
                Author notes

                Edited by: Xiaowu Wang, Biotechnology Research Institute – Chinese Academy of Agricultural Sciences, China

                Reviewed by: Zhongyun Piao, Shenyang Agricultural University, China; Youlu Yuan, Institute of Cotton Research – Chinese Academy of Agricultural Sciences, China

                *Correspondence: Shuijin Zhu, shjzhu@ 123456zju.edu.cn

                This article was submitted to Plant Genetics and Genomics, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2016.01356
                5014859
                27660632
                b9443815-078a-48b8-9b6c-44cbdf5a043e
                Copyright © 2016 Li, Dong, Zhao, Li, Li, Yu, Mei, Daud, He, Chen and Zhu.

                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) or licensor 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
                : 06 May 2016
                : 25 August 2016
                Page count
                Figures: 7, Tables: 6, Equations: 0, References: 66, Pages: 16, Words: 0
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                upland cotton,cotton 63k snp array,linkage analysis,molecular marker,qtls
                Plant science & Botany
                upland cotton, cotton 63k snp array, linkage analysis, molecular marker, qtls

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