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Jinfa Zhang - One of the best experts on this subject based on the ideXlab platform.
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a genome wide analysis of the lysophosphatidate acyltransferase lpaat gene family in cotton organization expression sequence variation and association with seed oil content and Fiber Quality
BMC Genomics, 2017Co-Authors: Nuohan Wang, Jinfa Zhang, Man Wu, Haijing Li, Xingli Li, Shuxun Yu, Jiwen YuAbstract:Lysophosphatidic acid acyltransferase (LPAAT) encoded by a multigene family is a rate-limiting enzyme in the Kennedy pathway in higher plants. Cotton is the most important natural Fiber crop and one of the most important oilseed crops. However, little is known on genes coding for LPAATs involved in oil biosynthesis with regard to its genome organization, diversity, expression, natural genetic variation, and association with Fiber development and oil content in cotton. In this study, a comprehensive genome-wide analysis in four Gossypium species with genome sequences, i.e., tetraploid G. hirsutum- AD1 and G. barbadense- AD2 and its possible ancestral diploids G. raimondii- D5 and G. arboreum- A2, identified 13, 10, 8, and 9 LPAAT genes, respectively, that were divided into four subfamilies. RNA-seq analyses of the LPAAT genes in the widely grown G. hirsutum suggest their differential expression at the transcriptional level in developing cottonseeds and Fibers. Although 10 LPAAT genes were co-localised with quantitative trait loci (QTL) for cottonseed oil or protein content within a 25-cM region, only one single strand conformation polymorphic (SSCP) marker developed from a synonymous single nucleotide polymorphism (SNP) of the At-Gh13LPAAT5 gene was significantly correlated with cottonseed oil and protein contents in one of the three field tests. Moreover, transformed yeasts using the At-Gh13LPAAT5 gene with the two sequences for the SNP led to similar results, i.e., a 25–31% increase in palmitic acid and oleic acid, and a 16–29% increase in total triacylglycerol (TAG). The results in this study demonstrated that the natural variation in the LPAAT genes to improving cottonseed oil content and Fiber Quality is limited; therefore, traditional cross breeding should not expect much progress in improving cottonseed oil content or Fiber Quality through a marker-assisted selection for the LPAAT genes. However, enhancing the expression of one of the LPAAT genes such as At-Gh13LPAAT5 can significantly increase the production of total TAG and other fatty acids, providing an incentive for further studies into the use of LPAAT genes to increase cottonseed oil content through biotechnology.
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linkage map construction and quantitative trait locus analysis of agronomic and Fiber Quality traits in cotton
The Plant Genome, 2014Co-Authors: Michael A Gore, Jinfa Zhang, Roy G Cantrell, Gregory N Thyssen, David D Fang, Jesse Poland, Richard G Percy, Alexander E LipkaAbstract:The superior Fiber properties of Gossypium barbadense L. serve as a source of novel variation for improving Fiber Quality in Upland cotton (G. hirsutum L.), but introgression from G. barbadense has been largely unsuccessful due to hybrid breakdown and a lack of genetic and genomic resources. In an effort to overcome these limitations, we constructed a linkage map and conducted a quantitative trait locus (QTL) analysis of 10 agronomic and Fiber Quality traits in a recombinant inbred mapping population derived from a cross between TM-1, an Upland cotton line, and NM24016, an elite G. hirsutum line with stabilized introgression from G. barbadense. The linkage map consisted of 429 simple-sequence repeat (SSR) and 412 genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) marker loci that covered half of the tetraploid cotton genome. Notably, the 841 marker loci were unevenly distributed among the 26 chromosomes of tetraploid cotton. The 10 traits evaluated on the TM-1 × NM24016 population in a multienvironment trial were highly heritable, and most of the Fiber traits showed considerable transgressive variation. Through the QTL analysis, we identified a total of 28 QTLs associated with the 10 traits. Our study provides a novel resource that can be used by breeders and geneticists for the genetic improvement of agronomic and Fiber Quality traits in Upland cotton. A s the world’s foremost natural Fiber crop, cotton supports a multibillion-dollar production and pro
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a comprehensive meta qtl analysis for Fiber Quality yield yield related and morphological traits drought tolerance and disease resistance in tetraploid cotton
BMC Genomics, 2013Co-Authors: Joseph I Said, Mingzhou Song, Xianlong Zhang, Jinfa ZhangAbstract:The study of quantitative trait loci (QTL) in cotton (Gossypium spp.) is focused on traits of agricultural significance. Previous studies have identified a plethora of QTL attributed to Fiber Quality, disease and pest resistance, branch number, seed Quality and yield and yield related traits, drought tolerance, and morphological traits. However, results among these studies differed due to the use of different genetic populations, markers and marker densities, and testing environments. Since two previous meta-QTL analyses were performed on Fiber traits, a number of papers on QTL mapping of Fiber Quality, yield traits, morphological traits, and disease resistance have been published. To obtain a better insight into the genome-wide distribution of QTL and to identify consistent QTL for marker assisted breeding in cotton, an updated comparative QTL analysis is needed. In this study, a total of 1,223 QTL from 42 different QTL studies in Gossypium were surveyed and mapped using Biomercator V3 based on the Gossypium consensus map from the Cotton Marker Database. A meta-analysis was first performed using manual inference and confirmed by Biomercator V3 to identify possible QTL clusters and hotspots. QTL clusters are composed of QTL of various traits which are concentrated in a specific region on a chromosome, whereas hotspots are composed of only one trait type. QTL were not evenly distributed along the cotton genome and were concentrated in specific regions on each chromosome. QTL hotspots for Fiber Quality traits were found in the same regions as the clusters, indicating that clusters may also form hotspots. Putative QTL clusters were identified via meta-analysis and will be useful for breeding programs and future studies involving Gossypium QTL. The presence of QTL clusters and hotspots indicates consensus regions across cultivated tetraploid Gossypium species, environments, and populations which contain large numbers of QTL, and in some cases multiple QTL associated with the same trait termed a hotspot. This study combines two previous meta-analysis studies and adds all other currently available QTL studies, making it the most comprehensive meta-analysis study in cotton to date.
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a comprehensive meta qtl analysis for Fiber Quality yield yield related and morphological traits drought tolerance and disease resistance in tetraploid cotton
BMC Genomics, 2013Co-Authors: Joseph I Said, Zhongxu Lin, Mingzhou Song, Xianlong Zhang, Jinfa ZhangAbstract:Background The study of quantitative trait loci (QTL) in cotton (Gossypium spp.) is focused on traits of agricultural significance. Previous studies have identified a plethora of QTL attributed to Fiber Quality, disease and pest resistance, branch number, seed Quality and yield and yield related traits, drought tolerance, and morphological traits. However, results among these studies differed due to the use of different genetic populations, markers and marker densities, and testing environments. Since two previous meta-QTL analyses were performed on Fiber traits, a number of papers on QTL mapping of Fiber Quality, yield traits, morphological traits, and disease resistance have been published. To obtain a better insight into the genome-wide distribution of QTL and to identify consistent QTL for marker assisted breeding in cotton, an updated comparative QTL analysis is needed.
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mapping quantitative trait loci for lint yield and Fiber Quality across environments in a gossypium hirsutum gossypium barbadense backcross inbred line population
Theoretical and Applied Genetics, 2013Co-Authors: Ke Zhang, Honghong Zhai, Shuli Fan, Meizhen Song, Daigang Yang, Jinfa ZhangAbstract:Identification of stable quantitative trait loci (QTLs) across different environments and mapping populations is a prerequisite for marker-assisted selection (MAS) for cotton yield and Fiber Quality. To construct a genetic linkage map and to identify QTLs for Fiber Quality and yield traits, a backcross inbred line (BIL) population of 146 lines was developed from a cross between Upland cotton (Gossypium hirsutum) and Egyptian cotton (Gossypium barbadense) through two generations of backcrossing using Upland cotton as the recurrent parent followed by four generations of self pollination. The BIL population together with its two parents was tested in five environments representing three major cotton production regions in China. The genetic map spanned a total genetic distance of 2,895 cM and contained 392 polymorphic SSR loci with an average genetic distance of 7.4 cM per marker. A total of 67 QTLs including 28 for Fiber Quality and 39 for yield and its components were detected on 23 chromosomes, each of which explained 6.65–25.27 % of the phenotypic variation. Twenty-nine QTLs were located on the At subgenome originated from a cultivated diploid cotton, while 38 were on the Dt subgenome from an ancestor that does not produce spinnable Fibers. Of the eight common QTLs (12 %) detected in more than two environments, two were for Fiber Quality traits including one for Fiber strength and one for uniformity, and six for yield and its components including three for lint yield, one for seedcotton yield, one for lint percentage and one for boll weight. QTL clusters for the same traits or different traits were also identified. This research represents one of the first reports using a permanent advanced backcross inbred population of an interspecific hybrid population to identify QTLs for Fiber Quality and yield traits in cotton across diverse environments. It provides useful information for transferring desirable genes from G. barbadense to G. hirsutum using MAS.
David D Fang - One of the best experts on this subject based on the ideXlab platform.
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a magic population based genome wide association study reveals functional association of ghrbb1_a07 gene with superior Fiber Quality in cotton
BMC Genomics, 2016Co-Authors: S Islam, Johnie N. Jenkins, Gregory N Thyssen, Linghe Zeng, Christopher D Delhom, Jack C Mccarty, Dewayne D Deng, Doug J Hinchliffe, Don C Jones, David D FangAbstract:Cotton supplies a great majority of natural Fiber for the global textile industry. The negative correlation between yield and Fiber Quality has hindered breeders’ ability to improve these traits simultaneously. A multi-parent advanced generation inter-cross (MAGIC) population developed through random-mating of multiple diverse parents has the ability to break this negative correlation. Genotyping-by-sequencing (GBS) is a method that can rapidly identify and genotype a large number of single nucleotide polymorphisms (SNP). Genotyping a MAGIC population using GBS technologies will enable us to identify marker-trait associations with high resolution. An Upland cotton MAGIC population was developed through random-mating of 11 diverse cultivars for five generations. In this study, Fiber Quality data obtained from four environments and 6071 SNP markers generated via GBS and 223 microsatellite markers of 547 recombinant inbred lines (RILs) of the MAGIC population were used to conduct a genome wide association study (GWAS). By employing a mixed linear model, GWAS enabled us to identify markers significantly associated with Fiber quantitative trait loci (QTL). We identified and validated one QTL cluster associated with four Fiber Quality traits [short Fiber content (SFC), strength (STR), length (UHM) and uniformity (UI)] on chromosome A07. We further identified candidate genes related to Fiber Quality attributes in this region. Gene expression and amino acid substitution analysis suggested that a regeneration of bulb biogenesis 1 (GhRBB1_A07) gene is a candidate for superior Fiber Quality in Upland cotton. The DNA marker CFBid0004 designed from an 18 bp deletion in the coding sequence of GhRBB1_A07 in Acala Ultima is associated with the improved Fiber Quality in the MAGIC RILs and 105 additional commercial Upland cotton cultivars. Using GBS and a MAGIC population enabled more precise Fiber QTL mapping in Upland cotton. The Fiber QTL and associated markers identified in this study can be used to improve Fiber Quality through marker assisted selection or genomic selection in a cotton breeding program. Target manipulation of the GhRBB1_A07 gene through biotechnology or gene editing may potentially improve cotton Fiber Quality.
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quantitative trait loci analysis of Fiber Quality traits using a random mated recombinant inbred population in upland cotton gossypium hirsutum l
BMC Genomics, 2014Co-Authors: David D Fang, Johnie N. Jenkins, Dewayne D Deng, Jack C MccartyAbstract:Background Upland cotton (Gossypium hirsutum L.) accounts for about 95% of world cotton production. Improving Upland cotton cultivars has been the focus of world-wide cotton breeding programs. Negative correlation between yield and Fiber Quality is an obstacle for cotton improvement. Random-mating provides a potential methodology to break this correlation. The suite of Fiber Quality traits that affect the yarn Quality includes the length, strength, maturity, fineness, elongation, uniformity and color. Identification of stable Fiber quantitative trait loci (QTL) in Upland cotton is essential in order to improve cotton cultivars with superior Quality using marker-assisted selection (MAS) strategy.
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quantitative trait loci analysis of Fiber Quality traits using a random mated recombinant inbred population in upland cotton gossypium hirsutum l
BMC Genomics, 2014Co-Authors: David D Fang, Johnie N. Jenkins, Dewayne D Deng, Jack C MccartyAbstract:Upland cotton (Gossypium hirsutum L.) accounts for about 95% of world cotton production. Improving Upland cotton cultivars has been the focus of world-wide cotton breeding programs. Negative correlation between yield and Fiber Quality is an obstacle for cotton improvement. Random-mating provides a potential methodology to break this correlation. The suite of Fiber Quality traits that affect the yarn Quality includes the length, strength, maturity, fineness, elongation, uniformity and color. Identification of stable Fiber quantitative trait loci (QTL) in Upland cotton is essential in order to improve cotton cultivars with superior Quality using marker-assisted selection (MAS) strategy. Using 11 diverse Upland cotton cultivars as parents, a random-mated recombinant inbred (RI) population consisting of 550 RI lines was developed after 6 cycles of random-mating and 6 generations of self-pollination. The 550 RILs were planted in triplicates for two years in Mississippi State, MS, USA to obtain Fiber Quality data. After screening 15538 simple sequence repeat (SSR) markers, 2132 were polymorphic among the 11 parents. One thousand five hundred eighty-two markers covering 83% of cotton genome were used to genotype 275 RILs (Set 1). The marker-trait associations were analyzed using the software program TASSEL. At p < 0.01, 131 Fiber QTLs and 37 QTL clusters were identified. These QTLs were responsible for the combined phenotypic variance ranging from 62.3% for short Fiber content to 82.8% for elongation. The other 275 RILs (Set 2) were analyzed using a subset of 270 SSR markers, and the QTLs were confirmed. Two major QTL clusters were observed on chromosomes 7 and 16. Comparison of these 131 QTLs with the previously published QTLs indicated that 77 were identified before, and 54 appeared novel. The 11 parents used in this study represent a diverse genetic pool of the US cultivated cotton, and 10 of them were elite commercial cultivars. The Fiber QTLs, especially QTL clusters reported herein can be readily implemented in a cotton breeding program to improve Fiber Quality via MAS strategy. The consensus QTL regions warrant further investigation to better understand the genetics and molecular mechanisms underlying Fiber development.
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linkage map construction and quantitative trait locus analysis of agronomic and Fiber Quality traits in cotton
The Plant Genome, 2014Co-Authors: Michael A Gore, Jinfa Zhang, Roy G Cantrell, Gregory N Thyssen, David D Fang, Jesse Poland, Richard G Percy, Alexander E LipkaAbstract:The superior Fiber properties of Gossypium barbadense L. serve as a source of novel variation for improving Fiber Quality in Upland cotton (G. hirsutum L.), but introgression from G. barbadense has been largely unsuccessful due to hybrid breakdown and a lack of genetic and genomic resources. In an effort to overcome these limitations, we constructed a linkage map and conducted a quantitative trait locus (QTL) analysis of 10 agronomic and Fiber Quality traits in a recombinant inbred mapping population derived from a cross between TM-1, an Upland cotton line, and NM24016, an elite G. hirsutum line with stabilized introgression from G. barbadense. The linkage map consisted of 429 simple-sequence repeat (SSR) and 412 genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) marker loci that covered half of the tetraploid cotton genome. Notably, the 841 marker loci were unevenly distributed among the 26 chromosomes of tetraploid cotton. The 10 traits evaluated on the TM-1 × NM24016 population in a multienvironment trial were highly heritable, and most of the Fiber traits showed considerable transgressive variation. Through the QTL analysis, we identified a total of 28 QTLs associated with the 10 traits. Our study provides a novel resource that can be used by breeders and geneticists for the genetic improvement of agronomic and Fiber Quality traits in Upland cotton. A s the world’s foremost natural Fiber crop, cotton supports a multibillion-dollar production and pro
Ke Zhang - One of the best experts on this subject based on the ideXlab platform.
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construction of genetic map and qtl analysis of Fiber Quality traits for upland cotton gossypium hirsutum l
Euphytica, 2015Co-Authors: Shiyi Tang, Xiaomei Fang, Dexin Liu, Dajun Liu, Jian Zhang, Zhonghua Teng, Tengfei Zhai, Fang Liu, Shunfeng Wang, Ke ZhangAbstract:Cotton Fiber Quality traits are controlled by multiple genes of minor effect. Identification of significant and stable quantitative trait loci (QTL) across environments and populations lays foundation for marker-assisted selection for Fiber Quality improvement and studies of its molecular regulation. Here, a detailed genetic map is constructed and QTL are detected based on an intraspecific recombinant inbred line population derived from a cross between Upland cotton cultivar/line Yumian 1 and 7235. A total of 25,313 SSR primer pairs, including 5,000 developed from G. raimondii BAC-ends sequences, were used to construct the genetic map which finally contained 1,540 loci, spanning 2,842.06 cM, with an average of 1.85 cM between adjacent markers. With 4 year Fiber Quality traits data, variance analysis revealed that they were significantly affected by genetic and environmental factors. Significant correlations were also detected between them. A total of 62 QTL were identified with combined analysis and single environment analysis. These QTL explain phenotypic variation from 5.0 to 28.1 %. For each trait, favorable alleles were conferred by both parents. Seventeen QTL were detected in more than one environment. The genetic map and stable QTL are valuable for Upland cotton genome research and breeding projects to improve Fiber Quality.
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mapping quantitative trait loci for lint yield and Fiber Quality across environments in a gossypium hirsutum gossypium barbadense backcross inbred line population
Theoretical and Applied Genetics, 2013Co-Authors: Ke Zhang, Honghong Zhai, Shuli Fan, Meizhen Song, Daigang Yang, Jinfa ZhangAbstract:Identification of stable quantitative trait loci (QTLs) across different environments and mapping populations is a prerequisite for marker-assisted selection (MAS) for cotton yield and Fiber Quality. To construct a genetic linkage map and to identify QTLs for Fiber Quality and yield traits, a backcross inbred line (BIL) population of 146 lines was developed from a cross between Upland cotton (Gossypium hirsutum) and Egyptian cotton (Gossypium barbadense) through two generations of backcrossing using Upland cotton as the recurrent parent followed by four generations of self pollination. The BIL population together with its two parents was tested in five environments representing three major cotton production regions in China. The genetic map spanned a total genetic distance of 2,895 cM and contained 392 polymorphic SSR loci with an average genetic distance of 7.4 cM per marker. A total of 67 QTLs including 28 for Fiber Quality and 39 for yield and its components were detected on 23 chromosomes, each of which explained 6.65–25.27 % of the phenotypic variation. Twenty-nine QTLs were located on the At subgenome originated from a cultivated diploid cotton, while 38 were on the Dt subgenome from an ancestor that does not produce spinnable Fibers. Of the eight common QTLs (12 %) detected in more than two environments, two were for Fiber Quality traits including one for Fiber strength and one for uniformity, and six for yield and its components including three for lint yield, one for seedcotton yield, one for lint percentage and one for boll weight. QTL clusters for the same traits or different traits were also identified. This research represents one of the first reports using a permanent advanced backcross inbred population of an interspecific hybrid population to identify QTLs for Fiber Quality and yield traits in cotton across diverse environments. It provides useful information for transferring desirable genes from G. barbadense to G. hirsutum using MAS.
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genetic mapping and quantitative trait locus analysis of Fiber Quality traits using a three parent composite population in upland cotton gossypium hirsutum l
Molecular Breeding, 2012Co-Authors: Ke Zhang, Shiyi Tang, Dexin Liu, Dajun Liu, Jian Zhang, Zhonghua Teng, Zhengsheng ZhangAbstract:Composite cross populations (CP) developed from three or more cultivars/lines are frequently used to improve agronomic and economic traits in crop cultivar development programs. Employing CP in linkage map construction and quantitative trait locus (QTL) mapping may increase the marker density of upland cotton (Gossypium hirsutum L.) genetic maps, exploit more adequate gene resources and facilitate marker-assisted selection (MAS). To construct a relatively high-density map and identify QTL associated with Fiber Quality traits in upland cotton, three elite upland cultivars/lines, Yumian 1, CRI 35 and 7,235, were used to obtain the segregating population, Yumian 1/CRI 35//Yumian 1/7,235. A genetic map containing 978 simple sequence repeat (SSR) loci and 69 linkage groups was constructed; the map spanned 4,184.4 cM, covering approximately 94.1% of the entire tetraploid cotton genome. A total of 63 QTL were detected, explaining 8.1–55.8% of the total phenotypic variance: 11 QTL for Fiber elongation, 16 QTL for Fiber length, 9 QTL for Fiber micronaire reading, 10 QTL for Fiber strength and 17 QTL for Fiber length uniformity. The genetic map and QTL detected for Fiber Quality traits are promising for further breeding programs of upland cotton with improved Fiber Quality.
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construction of a comprehensive pcr based marker linkage map and qtl mapping for Fiber Quality traits in upland cotton gossypium hirsutum l
Molecular Breeding, 2009Co-Authors: Zhengsheng Zhang, Ke Zhang, Dajun Liu, Jian Zhang, Jing Zheng, Wei Wang, Qun WanAbstract:To facilitate marker assisted selection, there is an urgent need to construct a saturated genetic map of upland cotton (Gossypium hirsutum L.). Four types of markers including SSR, SRAP, morphological marker, and intron targeted intron–exon splice junction (IT-ISJ) marker were used to construct a linkage map with 270 F2:7 recombinant inbred lines derived from an upland cotton cross (T586 × Yumian 1). A total of 7,508 SSR, 740 IT-ISJ and 384 SRAP primer pairs/combinations were used to screen for polymorphism between the two mapping parents, and the average polymorphisms of three types of molecular markers represented 6.8, 6.6 and 7.0%, respectively. The polymorphic primer pairs/combinations and morphological markers were used to genotype 270 recombinant inbred lines, and a map including 604 loci (509 SSR, 58 IT-ISJ, 29 SRAP and 8 morphological loci) and 60 linkage groups was constructed. The map spanned 3,140.9 cM with an average interval of 5.2 cM between two markers, approximately accounting for 70.6% of the cotton genome. Fifty-four of 60 linkage groups were ordered into 26 chromosomes. Multiple QTL mapping was used to identify QTL for Fiber Quality traits in five environments, and thirteen QTL were detected. These QTL included four for Fiber length (FL), two for Fiber strength (FS), two for Fiber fineness (FF), three for Fiber length uniformity (FU), and two for Fiber elongation (FE), respectively. Each QTL explained between 7.4 and 43.1% of phenotypic variance. Five out of thirteen QTL (FL1 and FU1 on chromosome 6, FL2, FU2 and FF1 on chromosome7) were detected in five environments, and they explained more than 20% of the phenotypic variance. Eleven QTL were distributed on A genome, while the other two on D genome.
Jack C Mccarty - One of the best experts on this subject based on the ideXlab platform.
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a magic population based genome wide association study reveals functional association of ghrbb1_a07 gene with superior Fiber Quality in cotton
BMC Genomics, 2016Co-Authors: S Islam, Johnie N. Jenkins, Gregory N Thyssen, Linghe Zeng, Christopher D Delhom, Jack C Mccarty, Dewayne D Deng, Doug J Hinchliffe, Don C Jones, David D FangAbstract:Cotton supplies a great majority of natural Fiber for the global textile industry. The negative correlation between yield and Fiber Quality has hindered breeders’ ability to improve these traits simultaneously. A multi-parent advanced generation inter-cross (MAGIC) population developed through random-mating of multiple diverse parents has the ability to break this negative correlation. Genotyping-by-sequencing (GBS) is a method that can rapidly identify and genotype a large number of single nucleotide polymorphisms (SNP). Genotyping a MAGIC population using GBS technologies will enable us to identify marker-trait associations with high resolution. An Upland cotton MAGIC population was developed through random-mating of 11 diverse cultivars for five generations. In this study, Fiber Quality data obtained from four environments and 6071 SNP markers generated via GBS and 223 microsatellite markers of 547 recombinant inbred lines (RILs) of the MAGIC population were used to conduct a genome wide association study (GWAS). By employing a mixed linear model, GWAS enabled us to identify markers significantly associated with Fiber quantitative trait loci (QTL). We identified and validated one QTL cluster associated with four Fiber Quality traits [short Fiber content (SFC), strength (STR), length (UHM) and uniformity (UI)] on chromosome A07. We further identified candidate genes related to Fiber Quality attributes in this region. Gene expression and amino acid substitution analysis suggested that a regeneration of bulb biogenesis 1 (GhRBB1_A07) gene is a candidate for superior Fiber Quality in Upland cotton. The DNA marker CFBid0004 designed from an 18 bp deletion in the coding sequence of GhRBB1_A07 in Acala Ultima is associated with the improved Fiber Quality in the MAGIC RILs and 105 additional commercial Upland cotton cultivars. Using GBS and a MAGIC population enabled more precise Fiber QTL mapping in Upland cotton. The Fiber QTL and associated markers identified in this study can be used to improve Fiber Quality through marker assisted selection or genomic selection in a cotton breeding program. Target manipulation of the GhRBB1_A07 gene through biotechnology or gene editing may potentially improve cotton Fiber Quality.
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quantitative trait loci analysis of Fiber Quality traits using a random mated recombinant inbred population in upland cotton gossypium hirsutum l
BMC Genomics, 2014Co-Authors: David D Fang, Johnie N. Jenkins, Dewayne D Deng, Jack C MccartyAbstract:Background Upland cotton (Gossypium hirsutum L.) accounts for about 95% of world cotton production. Improving Upland cotton cultivars has been the focus of world-wide cotton breeding programs. Negative correlation between yield and Fiber Quality is an obstacle for cotton improvement. Random-mating provides a potential methodology to break this correlation. The suite of Fiber Quality traits that affect the yarn Quality includes the length, strength, maturity, fineness, elongation, uniformity and color. Identification of stable Fiber quantitative trait loci (QTL) in Upland cotton is essential in order to improve cotton cultivars with superior Quality using marker-assisted selection (MAS) strategy.
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quantitative trait loci analysis of Fiber Quality traits using a random mated recombinant inbred population in upland cotton gossypium hirsutum l
BMC Genomics, 2014Co-Authors: David D Fang, Johnie N. Jenkins, Dewayne D Deng, Jack C MccartyAbstract:Upland cotton (Gossypium hirsutum L.) accounts for about 95% of world cotton production. Improving Upland cotton cultivars has been the focus of world-wide cotton breeding programs. Negative correlation between yield and Fiber Quality is an obstacle for cotton improvement. Random-mating provides a potential methodology to break this correlation. The suite of Fiber Quality traits that affect the yarn Quality includes the length, strength, maturity, fineness, elongation, uniformity and color. Identification of stable Fiber quantitative trait loci (QTL) in Upland cotton is essential in order to improve cotton cultivars with superior Quality using marker-assisted selection (MAS) strategy. Using 11 diverse Upland cotton cultivars as parents, a random-mated recombinant inbred (RI) population consisting of 550 RI lines was developed after 6 cycles of random-mating and 6 generations of self-pollination. The 550 RILs were planted in triplicates for two years in Mississippi State, MS, USA to obtain Fiber Quality data. After screening 15538 simple sequence repeat (SSR) markers, 2132 were polymorphic among the 11 parents. One thousand five hundred eighty-two markers covering 83% of cotton genome were used to genotype 275 RILs (Set 1). The marker-trait associations were analyzed using the software program TASSEL. At p < 0.01, 131 Fiber QTLs and 37 QTL clusters were identified. These QTLs were responsible for the combined phenotypic variance ranging from 62.3% for short Fiber content to 82.8% for elongation. The other 275 RILs (Set 2) were analyzed using a subset of 270 SSR markers, and the QTLs were confirmed. Two major QTL clusters were observed on chromosomes 7 and 16. Comparison of these 131 QTLs with the previously published QTLs indicated that 77 were identified before, and 54 appeared novel. The 11 parents used in this study represent a diverse genetic pool of the US cultivated cotton, and 10 of them were elite commercial cultivars. The Fiber QTLs, especially QTL clusters reported herein can be readily implemented in a cotton breeding program to improve Fiber Quality via MAS strategy. The consensus QTL regions warrant further investigation to better understand the genetics and molecular mechanisms underlying Fiber development.
Joseph I Said - One of the best experts on this subject based on the ideXlab platform.
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a comprehensive meta qtl analysis for Fiber Quality yield yield related and morphological traits drought tolerance and disease resistance in tetraploid cotton
BMC Genomics, 2013Co-Authors: Joseph I Said, Mingzhou Song, Xianlong Zhang, Jinfa ZhangAbstract:The study of quantitative trait loci (QTL) in cotton (Gossypium spp.) is focused on traits of agricultural significance. Previous studies have identified a plethora of QTL attributed to Fiber Quality, disease and pest resistance, branch number, seed Quality and yield and yield related traits, drought tolerance, and morphological traits. However, results among these studies differed due to the use of different genetic populations, markers and marker densities, and testing environments. Since two previous meta-QTL analyses were performed on Fiber traits, a number of papers on QTL mapping of Fiber Quality, yield traits, morphological traits, and disease resistance have been published. To obtain a better insight into the genome-wide distribution of QTL and to identify consistent QTL for marker assisted breeding in cotton, an updated comparative QTL analysis is needed. In this study, a total of 1,223 QTL from 42 different QTL studies in Gossypium were surveyed and mapped using Biomercator V3 based on the Gossypium consensus map from the Cotton Marker Database. A meta-analysis was first performed using manual inference and confirmed by Biomercator V3 to identify possible QTL clusters and hotspots. QTL clusters are composed of QTL of various traits which are concentrated in a specific region on a chromosome, whereas hotspots are composed of only one trait type. QTL were not evenly distributed along the cotton genome and were concentrated in specific regions on each chromosome. QTL hotspots for Fiber Quality traits were found in the same regions as the clusters, indicating that clusters may also form hotspots. Putative QTL clusters were identified via meta-analysis and will be useful for breeding programs and future studies involving Gossypium QTL. The presence of QTL clusters and hotspots indicates consensus regions across cultivated tetraploid Gossypium species, environments, and populations which contain large numbers of QTL, and in some cases multiple QTL associated with the same trait termed a hotspot. This study combines two previous meta-analysis studies and adds all other currently available QTL studies, making it the most comprehensive meta-analysis study in cotton to date.
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a comprehensive meta qtl analysis for Fiber Quality yield yield related and morphological traits drought tolerance and disease resistance in tetraploid cotton
BMC Genomics, 2013Co-Authors: Joseph I Said, Zhongxu Lin, Mingzhou Song, Xianlong Zhang, Jinfa ZhangAbstract:Background The study of quantitative trait loci (QTL) in cotton (Gossypium spp.) is focused on traits of agricultural significance. Previous studies have identified a plethora of QTL attributed to Fiber Quality, disease and pest resistance, branch number, seed Quality and yield and yield related traits, drought tolerance, and morphological traits. However, results among these studies differed due to the use of different genetic populations, markers and marker densities, and testing environments. Since two previous meta-QTL analyses were performed on Fiber traits, a number of papers on QTL mapping of Fiber Quality, yield traits, morphological traits, and disease resistance have been published. To obtain a better insight into the genome-wide distribution of QTL and to identify consistent QTL for marker assisted breeding in cotton, an updated comparative QTL analysis is needed.