scholarly journals High-Resolution Detection of Quantitative Trait Loci for Seven Important Yield Components in Wheat (Triticum aestivum L.) using a High-Density SALF-Seq Genetic Map

2021 ◽  
Author(s):  
Tao Li ◽  
Qiao Li ◽  
Jinhui Wang ◽  
Zhao Yang ◽  
Yanyan Tang ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Expression Patterns ◽  
Phenotypic Variance ◽  
Wheat Varieties ◽  
Major Qtls ◽  
Grain Number Per Spike ◽  
Trait Loci ◽  
Kasp Markers

Abstract Background: Yield-related traits including thousand grain weight (TGW), grain number per spike (GNS), grain width (GW), grain length (GL), plant height (PH), spike length (SL), and spikelet number per spike (SNS) are greatly associated with wheat (Triticum aestivum L.) grain yield. To detect quantitative trait loci (QTL) associated with them, 193 recombinant inbred lines derived from two elite winter wheat varieties Chuanmai42 and Chuanmai39 were employed to perform QTL mapping in six or eight environments. Results: A total of 30 QTLs on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 4A, 5A, 5B, 6A, 6D, 7A, 7B and 7D were identified. Among them, six major QTLs QTgw.cib-6A.1, QTgw.cib-6A.2, QGw.cib-6A, QGl.cib-3A, QGl.cib-6A, and QSl.cib-2D explaining 5.96-23.75% of the phenotypic variance were detected in multiple environments and showed strong and stable effects on corresponding traits. Three QTL clusters on chromosomes 2D and 6A containing 10 QTLs were also detected, which showed significant pleiotropic effects on multiple traits. Additionally, three Kompetitive Allele Specific PCR (KASP) markers linked to five of these major QTLs were developed. Candidate genes of QTgw.cib-6A.1/QGl.cib-6A and QGl.cib-3A were analyzed based on the spatiotemporal expression patterns, gene annotation, and orthologous search. Conclusions: Six major QTLs for TGW, GL, GW and SL were detected. Three KASP markers linked with five of these major QTLs were developed. These QTLs and KASP markers will be useful for elucidating the genetic architecture of grian yield and developing new wheat varieties with high and stable yield in wheat.

scholarly journals Quantitative Trait Loci Mapping and Development of KASP Marker Smut Screening Assay Using High-Density Genetic Map and Bulked Segregant RNA Sequencing in Sugarcane (Saccharum spp.)

2022 ◽  
Vol 12 ◽  
Author(s):  
Yijing Gao ◽  
Shan Zhou ◽  
Yuxin Huang ◽  
Baoqing Zhang ◽  
Yuhui Xu ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Rna Sequencing ◽  
Genetic Map ◽  
Quantitative Trait ◽  
Resistance Breeding ◽  
Phenotypic Variance ◽  
Screening Assay ◽  
Major Qtls ◽  
Trait Loci ◽  
Kasp Markers

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.

Detection of quantitative trait loci for paste viscosity characteristics based on the doubled haploid progeny from a cross between two Chinese wheat varieties

2009 ◽  
Vol 89 (5) ◽  
pp. 837-844 ◽  
Author(s):  
L Zhao ◽  
K Zhang ◽  
B Liu ◽  
J Tian
Keyword(s):  
Quantitative Trait Loci ◽  
Doubled Haploid ◽  
Quantitative Trait ◽  
Additive Effect ◽  
Doubled Haploid Population ◽  
Phenotypic Variance ◽  
Wheat Varieties ◽  
Rapid Visco Analyser ◽  
Trait Loci ◽  
Paste Viscosity

In order to understand the genetic basis of starch pasting viscosity characteristics (the RVA profile, which is produced by the Rapid Visco Analyser) of wheat grain samples, a doubled haploid (DH) population (Huapei 3 × Yumai 57; Yumai 57 is superior to Huapei 3 for RVA profile parameters) and a linkage map consisting of 324 marker loci were used to search QTL. This program was based on mixed linear models and allowed simultaneous mapping of additive effect QTL, epistatic QTL, and QTL × environment interactions (QE). Mapping analysis produced a total of 35 QTL for 6 RVA profile parameters with a single QTL explaining 0.91-21.34% of phenotypic variations. The 35 QTL were distributed on 15 chromosomes. The QBd-4A had the most significant additive effect, accounting for 21.34% of the phenotypic variance. Two QTL clusters for RVA profile parameters were located on chromosomes 2A and 4A, respectively. The information obtained in this study should be useful for manipulating the QTL for RVA profiles parameters by molecular assisted selection (MAS) in wheat breeding programs.Key words: Doubled haploid population, paste viscosity characteristics, rapid visco analyser, quantitative trait loci, wheat (Triticum aestivum L.)

scholarly journals A Major Quantitative Trait Loci Cluster Controlling Three Components of Yield and Plant Height Identified on Chromosome 4B of Common Wheat

2022 ◽  
Vol 12 ◽  
Author(s):  
Shaozhe Wen ◽  
Minghu Zhang ◽  
Keling Tu ◽  
Chaofeng Fan ◽  
Shuai Tian ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Plant Height ◽  
Fine Mapping ◽  
Quantitative Trait ◽  
Wheat Yield ◽  
Phenotypic Variance ◽  
Wheat Varieties ◽  
Qtl Cluster ◽  
Trait Loci ◽  
Three Components

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.

Quantitative Trait Loci for Susceptibility to Tapeworm Infection in the Red Flour Beetle

Genetics ◽  
2003 ◽  
Vol 165 (3) ◽  
pp. 1307-1315
Author(s):  
Daibin Zhong ◽  
Aditi Pai ◽  
Guiyun Yan
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Life Cycles ◽  
Red Flour Beetle ◽  
Phenotypic Variance ◽  
Flour Beetle ◽  
Trait Loci ◽  
Host Ecology ◽  
Tapeworm Infection

Abstract Parasites have profound effects on host ecology and evolution, and the effects of parasites on host ecology are often influenced by the magnitude of host susceptibility to parasites. Many parasites have complex life cycles that require intermediate hosts for their transmission, but little is known about the genetic basis of the intermediate host's susceptibility to these parasites. This study examined the genetic basis of susceptibility to a tapeworm (Hymenolepis diminuta) in the red flour beetle (Tribolium castaneum) that serves as an intermediate host in its transmission. Quantitative trait loci (QTL) mapping experiments were conducted with two independent segregating populations using amplified fragment length polymorphism (AFLP) markers and randomly amplified polymorphic DNA (RAPD) markers. A total of five QTL that significantly affected beetle susceptibility were identified in the two reciprocal crosses. Two common QTL on linkage groups 3 and 6 were identified in both crosses with similar effects on the phenotype, and three QTL were unique to each cross. In one cross, the three main QTL accounted for 29% of the total phenotypic variance and digenic epistasis explained 39% of the variance. In the second cross, the four main QTL explained 62% of the variance and digenic epistasis accounted for only 5% of the variance. The actions of these QTL were either overdominance or underdominance. Our results suggest that the polygenic nature of beetle susceptibility to the parasites and epistasis are important genetic mechanisms for the maintenance of variation within or among beetle strains in susceptibility to tapeworm infection.

scholarly journals The Genetic Basis of the Interspecific Differences in Wing Size in Nasonia (Hymenoptera; Pteromalidae): Major Quantitative Trait Loci and Epistasis

Genetics ◽  
2002 ◽  
Vol 161 (2) ◽  
pp. 673-684
Author(s):  
J Gadau ◽  
R E Page ◽  
J H Werren
Keyword(s):  
Quantitative Trait Loci ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Wing Length ◽  
Size Difference ◽  
Phenotypic Variance ◽  
Wing Size ◽  
Epistatic Interactions ◽  
Trait Loci ◽  
Wing Width

Abstract There is a 2.5-fold difference in male wing size between two haplodiploid insect species, Nasonia vitripennis and N. giraulti. The haploidy of males facilitated a full genomic screen for quantitative trait loci (QTL) affecting wing size and the detection of epistatic interactions. A QTL analysis of the interspecific wing-size difference revealed QTL with major effects and epistatic interactions among loci affecting the trait. We analyzed 178 hybrid males and initially found two major QTL for wing length, one for wing width, three for a normalized wing-size variable, and five for wing seta density. One QTL for wing width explains 38.1% of the phenotypic variance, and the same QTL explains 22% of the phenotypic variance in normalized wing size. This corresponds to a region previously introgressed from N. giraulti into N. vitripennis that accounts for 44% of the normalized wing-size difference between the species. Significant epistatic interactions were also found that affect wing size and density of setae on the wing. Screening for pairwise epistatic interactions between loci on different linkage groups revealed four additional loci for wing length and four loci for normalized wing size that were not detected in the original QTL analysis. We propose that the evolution of smaller wings in N. vitripennis males is primarily the result of major mutations at few genomic regions and involves epistatic interactions among some loci.

Quantitative Trait Loci Affecting Differences in Floral Morphology Between Two Species of Monkeyflower (Mimulus)

Genetics ◽  
1998 ◽  
Vol 149 (1) ◽  
pp. 367-382 ◽  
Author(s):  
H D Bradshaw ◽  
Kevin G Otto ◽  
Barbara E Frewen ◽  
John K McKay ◽  
Douglas W Schemske
Keyword(s):  
Quantitative Trait Loci ◽  
Reproductive Isolation ◽  
Quantitative Trait ◽  
Floral Morphology ◽  
Cumulative Effect ◽  
Sympatric Species ◽  
Accurate Estimate ◽  
Phenotypic Variance ◽  
Trait Loci ◽  
Morphological Differences

Abstract Conspicuous differences in floral morphology are partly responsible for reproductive isolation between two sympatric species of monkeyflower because of their effect on visitation of the flowers by different pollinators. Mimulus lewisii flowers are visited primarily by bumblebees, whereas M. cardinalis flowers are visited mostly by hummingbirds. The genetic control of 12 morphological differences between the flowers of M. lewisii and M. cardinalis was explored in a large linkage mapping population of F2 plants (n = 465) to provide an accurate estimate of the number and magnitude of effect of quantitative trait loci (QTLs) governing each character. Between one and six QTLs were identified for each trait. Most (9/12) traits appear to be controlled in part by at least one major QTL explaining ≥25% of the total phenotypic variance. This implies that either single genes of individually large effect or linked clusters of genes with a large cumulative effect can play a role in the evolution of reproductive isolation and speciation.

scholarly journals Mapping quantitative trait loci associated with common bunt resistance in a spring wheat (Triticum aestivum L.) variety Lillian

2019 ◽  
Vol 132 (11) ◽  
pp. 3023-3033 ◽  
Author(s):  
Firdissa E. Bokore ◽  
Richard D. Cuthbert ◽  
Ron E. Knox ◽  
Arti Singh ◽  
Heather L. Campbell ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Quantitative Trait Loci ◽  
Spring Wheat ◽  
Quantitative Trait ◽  
Triticum Aestivum L ◽  
Common Bunt ◽  
Trait Loci ◽  
Bunt Resistance

scholarly journals Quantitative Trait Loci Affecting Survival and Fertility-Related Traits in Caenorhabditis elegans Show Genotype-Environment Interactions, Pleiotropy and Epistasis

Genetics ◽  
1999 ◽  
Vol 153 (3) ◽  
pp. 1233-1243 ◽  
Author(s):  
David R Shook ◽  
Thomas E Johnson
Keyword(s):  
Caenorhabditis Elegans ◽  
Quantitative Trait Loci ◽  
Population Growth ◽  
Quantitative Trait ◽  
Age Of Onset ◽  
Inbred Strains ◽  
Interval Mapping ◽  
Phenotypic Variance ◽  
Epistatic Interactions ◽  
Trait Loci

Abstract We have identified, using composite interval mapping, quantitative trait loci (QTL) affecting a variety of life history traits (LHTs) in the nematode Caenorhabditis elegans. Using recombinant inbred strains assayed on the surface of agar plates, we found QTL for survival, early fertility, age of onset of sexual maturity, and population growth rate. There was no overall correlation between survival on solid media and previous measures of survival in liquid media. Of the four survival QTL found in these two environments, two have genotype-environment interactions (GEIs). Epistatic interactions between markers were detected for four traits. A multiple regression approach was used to determine which single markers and epistatic interactions best explained the phenotypic variance for each trait. The amount of phenotypic variance accounted for by genetic effects ranged from 13% (for internal hatching) to 46% (for population growth). Epistatic effects accounted for 9–11% of the phenotypic variance for three traits. Two regions containing QTL that affected more than one fertility-related trait were found. This study serves as an example of the power of QTL mapping for dissecting the genetic architecture of a suite of LHTs and indicates the potential importance of environment and GEIs in the evolution of this architecture.

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