quantitative trait
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2022 ◽  
Vol 293 ◽  
pp. 110729
Wenbing Gong ◽  
Xiaoya Song ◽  
Chunliang Xie ◽  
Yingjun Zhou ◽  
Zuohua Zhu ◽  

2022 ◽  
Pengxun Ren ◽  
Dehui Zhao ◽  
Zhankui Zeng ◽  
Xuefang Yan ◽  
Yue Zhao ◽  

Abstract Wheat (Triticum aestivum L.) is one of the main food crops in the world and a primary source of zinc (Zn) and iron (Fe) in the human body. The genetic mechanisms underlying related traits have been clarified, thereby providing a molecular theoretical foundation for the development of germplasm resources. In this study, 23,536 high-quality DArT markers were used to map quantitative trait loci (QTL) of grain Zn (GZn) and grain Fe (GFe) concentrations in recombinant inbred lines from Avocet/Chilero. A total of 17 QTLs located on chromosomes 1BL, 2BL, 3BL, 4AL, 4BS, 5AL, 5DL, 6AS, 6BS, 6DS, and 7AS accounted for 0.38–16.62% of the phenotypic variance. QGZn.haust-4AL, QGZn.haust-7AS.1, and QGFe.haust-6BS were detected on chromosomes 4AL, 6BS, and 7AS, accounting for 10.63–16.62% of the phenotypic variance. Four stable QTLs, QGZn.haust-4AL, QGFe.haust-1BL, QGFe.haust-4AL, and QGFe.haust-5DL were located on chromosomes 1BL, 4AL, and 5DL. Three pleiotropic effects locus for GZn and GFe concentrations were located on chromosomes 1BL, 4AL, and 5DL. Two high-throughput Kompetitive Allele Specific PCR markers were developed by closely linking single nucleotide polymorphisms on chromosomes 4AL and 5DL, which were validated by a germplasm panel. Therefore, it is the most important that quantitative trait loci and KASP marker for grain zinc and iron concentrations were developed for utilizing in marker-assisted breeding and biofortification of wheat grain in breeding programs.

2022 ◽  
Vol 12 ◽  
Shaozhe Wen ◽  
Minghu Zhang ◽  
Keling Tu ◽  
Chaofeng Fan ◽  
Shuai Tian ◽  

Wheat yield is not only affected by three components of yield, but also affected by plant height (PH). Identification and utilization of the quantitative trait loci (QTL) controlling these four traits is vitally important for breeding high-yielding wheat varieties. In this work, we conducted a QTL analysis using the recombinant inbred lines (RILs) derived from a cross between two winter wheat varieties of China, “Nongda981” (ND981) and “Nongda3097” (ND3097), exhibiting significant differences in spike number per unit area (SN), grain number per spike (GNS), thousand grain weight (TGW), and PH. A total of 11 environmentally stable QTL for these four traits were detected. Among them, four major and stable QTLs (QSn.cau-4B-1.1, QGns.cau-4B-1, QTgw.cau-4B-1.1, and QPh.cau-4B-1.2) explaining the highest phenotypic variance for SN, GNS, TGW, and PH, respectively, were mapped on the same genomic region of chromosome 4B and were considered a QTL cluster. The QTL cluster spanned a genetic distance of about 12.3 cM, corresponding to a physical distance of about 8.7 Mb. Then, the residual heterozygous line (RHL) was used for fine mapping of the QTL cluster. Finally, QSn.cau-4B-1.1, QGns.cau-4B-1, and QPh.cau-4B-1.2 were colocated to the physical interval of about 1.4 Mb containing 31 annotated high confidence genes. QTgw.cau-4B-1.1 was divided into two linked QTL with opposite effects. The elite NILs of the QTL cluster increased SN and PH by 55.71–74.82% and 14.73–23.54%, respectively, and increased GNS and TGW by 29.72–37.26% and 5.81–11.24% in two environments. Collectively, the QTL cluster for SN, GNS, TGW, and PH provides a theoretical basis for improving wheat yield, and the fine-mapping result will be beneficial for marker-assisted selection and candidate genes cloning.

2022 ◽  
Vol 12 ◽  
Hui Yan ◽  
Meng Ma ◽  
Muhammad Qadir Ahmad ◽  
Mohamed Hamed Arisha ◽  
Wei Tang ◽  

Flesh color (FC), skin color (SC), and anthocyanin content (AC) are three important traits being used for commodity evaluation in purple-fleshed sweet potato. However, to date, only a few reports are available on the inheritance of these traits. In this study, we used a biparental mapping population of 274 F1 progeny generated from a cross between a dark purple-fleshed (Xuzishu8) and white-fleshed (Meiguohong) sweet potato variety for genetic analyses. Correlation analysis showed a significant positive correlation among AC, SC, and FC. Medium-to-high heritability was observed for these traits. We detected single nucleotide polymorphisms (SNPs) by specific length amplified fragment sequencing (SLAF-seq) with the average sequencing depth of 51.72 and 25.76 for parents and progeny, respectively. Then we constructed an integrated genetic map consisting of 15 linkage groups (LGS) of sweet potato spanning on 2,233.66 cm with an average map distance of 0.71 cm between adjacent markers. Based on the linkage map, ten major quantitative trait loci (QTLs) associated to FC, SC, and AC were identified on LG12 between 0 and 64.97 cm distance, such as one QTL for SC and FC, respectively, which explained 36.3 and 45.9% of phenotypic variation; eight QTLs for AC, which explained 10.5–28.5% of the variation. These major QTLs were highly consistent and co-localized on LG12. Positive correlation, high heritability, and co-localization of QTLs on the same LG group confirm the significance of this study to establish a marker-assisted breeding program for sweet potato improvement.

2022 ◽  
Vol 12 ◽  
Yijing Gao ◽  
Shan Zhou ◽  
Yuxin Huang ◽  
Baoqing Zhang ◽  
Yuhui Xu ◽  

Sugarcane is one of the most important industrial crops globally. It is the second largest source of bioethanol, and a major crop for biomass-derived electricity and sugar worldwide. Smut, caused by Sporisorium scitamineum, is a major sugarcane disease in many countries, and is managed by smut-resistant varieties. In China, smut remains the single largest constraint for sugarcane production, and consequently it impacts the value of sugarcane as an energy feedstock. Quantitative trait loci (QTLs) associated with smut resistance and linked diagnostic markers are valuable tools for smut resistance breeding. Here, we developed an F1 population (192 progeny) by crossing two sugarcane varieties with contrasting smut resistance and used for genome-wide single nucleotide polymorphism (SNP) discovery and mapping, using a high-throughput genotyping method called “specific locus amplified fragment sequencing (SLAF-seq) and bulked-segregant RNA sequencing (BSR-seq). SLAF-seq generated 148,500 polymorphic SNP markers. Using SNP and previously identified SSR markers, an integrated genetic map with an average 1.96 cM marker interval was produced. With this genetic map and smut resistance scores of the F1 individuals from four crop years, 21 major QTLs were mapped, with a phenotypic variance explanation (PVE) > 8.0%. Among them, 10 QTLs were stable (repeatable) with PVEs ranging from 8.0 to 81.7%. Further, four QTLs were detected based on BSR-seq analysis. aligning major QTLs with the genome of a sugarcane progenitor Saccharum spontaneum, six markers were found co-localized. Markers located in QTLs and functional annotation of BSR-seq-derived unigenes helped identify four disease resistance candidate genes located in major QTLs. 77 SNPs from major QTLs were then converted to Kompetitive Allele-Specific PCR (KASP) markers, of which five were highly significantly linked to smut resistance. The co-localized QTLs, candidate resistance genes, and KASP markers identified in this study provide practically useful tools for marker-assisted sugarcane smut resistance breeding.

2022 ◽  
Vol 12 ◽  
Xueying Liu ◽  
Le Yang ◽  
Jinxia Wang ◽  
Yaqing Wang ◽  
Zhongni Guo ◽  

Fiber quality and yield-related traits are important agronomic traits in cotton breeding. To detect the genetic basis of fiber quality and yield related traits, a recombinant inbred line (RIL) population consisting of 182 lines was established from a cross between Gossypium hirsutum cultivar CCRI35 and G. hirsutum race palmeri accession TX-832. The RIL population was deeply genotyped using SLAF-seq and was phenotyped in six environments. A high-density genetic linkage map with 15,765 SNP markers and 153 SSR markers was constructed, with an average distance of 0.30 cM between adjacent markers. A total of 210 fiber quality quantitative trait loci (QTLs) and 73 yield-related QTLs were identified. Of the detected QTLs, 62 fiber quality QTLs and 10 yield-related QTLs were stable across multiple environments. Twelve and twenty QTL clusters were detected on the At and Dt subgenome, respectively. Twenty-three major QTL clusters were further validated through associated analysis and five candidate genes of four stable fiber quality QTLs were identified. This study revealed elite loci influencing fiber quality and yield and significant phenotypic selection regions during G. hirsutum domestication, and set a stage for future utilization of molecular marker assisted breeding in cotton breeding programs.

2022 ◽  
Vol 109 (1) ◽  
pp. 66-80
Sarah M. Brotman ◽  
Chelsea K. Raulerson ◽  
Swarooparani Vadlamudi ◽  
Kevin W. Currin ◽  
Qiujin Shen ◽  

2021 ◽  
Vol 12 (3) ◽  
pp. 354-367
Muhammad Asad ◽  
Izzah Ihsan ◽  
Muther Mansoor Qaisrani ◽  
Hafiz Muhammad Zeeshan Raza ◽  
Jallat Khan

Based on previous recombination actions and LD (linkage disequilibrium) throughout the genome, genome wide association mapping studies often are employed to find Quantitative trait locus in varied collections of crop germplasm. Generally, diverse panel’s genotyped using high density Single nucleotide polymorphism (SNP) panels are used to test a broad variety of haplotypes and alleles, as well as to track recombination divisions throughout the genome. GWAS, on the other hand, have rarely been used in breeding populations. We studied association mapping for agricultural parameters such as yield and its constituents in a breeding inhabitants of top irrigated tropical rice progenies so that the findings could be used to breeding more directly than those from a diverse panel. GWAS was undertaken with the specific purpose of accelerating selection in the breeding population, and the sample was genotyped with 71,710 Single nucleotide polymorphisms using genotyping-by-sequencing. We found 52 Quantitative trait locus QTL for 11 agronomic characteristics using this breeding panel, including substantial impact Quantitative trait loci (QTLs) for flowering period as well as grain width, grain length, grain length-breadth ratio. Furthermore we discovered haplotypes that may be applied to choose plants for our population with smaller stature (plant height), fast blooming time, with high yield, demonstrating the value of association mapping for advising breeding choices in breeding populations. Furthermore, we explore at how genomic-assisted selection models might be built using the newly discovered important Single nucleotide polymorphisms (SNPs) and deep insight into the genetic structure of these quantitative traits.

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