scholarly journals Fine Mapping of Leaf Trichome Density Revealed a 747-kb Region on Chromosome 1 in Cold-Hardy Hybrid Wine Grape Populations

2021 ◽  
Vol 12 ◽  
Author(s):  
Lu Yin ◽  
Avinash Karn ◽  
Lance Cadle-Davidson ◽  
Cheng Zou ◽  
Anna Underhill ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genotyping By Sequencing ◽  
Strong Relationship ◽  
Interval Mapping ◽  
Chromosome 1 ◽  
Trichome Density ◽  
Ef Hand ◽  
Trait Locus ◽  
Cold Hardy ◽  
Leaf Trichome

Segregation for leaf trichome density was observed in a cold-hardy hybrid grape population GE1025 (N = ∼125, MN1264 × MN1246) that was previously used to detect a quantitative trait locus (QTL) underlying foliar phylloxera resistance on chromosome 14. Our hypothesis was that high trichome density was associated with resistance to phylloxera. Existing literature found trichome density QTL on chromosomes 1 and 15 using a hybrid grape population of “Horizon” × Illinois 547-1 and suggested a few candidate genes. To validate the reported QTL and our hypothesis, interval mapping was conducted in GE1025 with previous genotyping-by-sequencing (GBS) single nucleotide polymorphism (SNP) genotype data and phenotypic scores collected using a 0–6 trichome density scale at several leaf positions. Evaluations were done on replicated forced dormant cuttings in 2 years and on field-grown leaves in 1 year. There was no strong relationship between trichome density and phylloxera resistance except for a Pearson’s correlation (r) of about -0.2 between a few trichome density traits and phylloxera severity traits at 2 and 3 weeks after infestation. Two genetic regions were repeatedly detected for multiple trichome density traits: from 10 to 20.7 Mbp (∼10 Mbp) on chromosome 1 for ribbon and simple density traits and from 2.4 to 8.9 Mbp on chromosome 10 for ribbon density traits, explaining 12.1–48.2 and 12.6–27.5% of phenotypic variation, respectively. To fine map, we genotyped a larger population, GE1783 (N = ∼1,023, MN1264 × MN1246), with conserved rhAmpSeq haplotype markers across multiple Vitis species and phenotyped 233 selected potential recombinants. Evaluations were conducted on field-grown leaves in a single year. The QTL for ribbon trichome density on adaxial vein and adaxial leaf and simple density on abaxial vein was fine mapped to 12.63–13.38 Mbp (747 kb) on chromosome 1. We found variations of MN1264 and MN1246 at candidate genes NAC transcription factor 29, EF-hand protein, and MYB140 in this region and three other surrounding candidate genes proposed previously. Even though no strong relationship between foliar phylloxera resistance and trichome density was found, this study validated and fine mapped a major QTL for trichome density using a cold-hardy hybrid grape population and shed light on a few candidate genes that have implications for different breeding programs.

scholarly journals Identification of candidate genes that underlie the QTL on chromosome 1 that mediates genetic differences in stress-ethanol interactions

2015 ◽  
Vol 47 (8) ◽  
pp. 308-317 ◽  
Author(s):  
Melloni N. Cook ◽  
Jessica A. Baker ◽  
Scott A. Heldt ◽  
Robert W. Williams ◽  
Kristin M. Hamre ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Zinc Finger Protein ◽  
Genetic Differences ◽  
Chromosome 1 ◽  
Protein Tyrosine ◽  
Finger Protein ◽  
Genome Wide ◽  
Trait Locus ◽  
Tyrosine Phosphate

Alcoholism, stress, and anxiety are strongly interacting heritable, polygenetic traits. In a previous study, we identified a quantitative trait locus (QTL) on murine chromosome (Chr) 1 between 23.0 and 31.5 Mb that modulates genetic differences in the effects of ethanol on anxiety-related phenotypes. The goal of the present study was to extend the analysis of this locus with a focus on identifying candidate genes using newly available data and tools. Anxiety-like behavior was evaluated with an elevated zero maze following saline or ethanol injections (1.8 g/kg) in C57BL/6J, DBA2J, and 72 BXD strains. We detected significant effects of strain and treatment and their interaction on anxiety-related behaviors, although surprisingly, sex was not a significant factor. The Chr1 QTL is specific to the ethanol-treated cohort. Candidate genes in this locus were evaluated using now standard bioinformatic criteria. Collagen 19a1 ( Col19a1) and family sequence 135a ( Fam135a) met most criteria but have lower expression levels and lacked biological verification and, therefore, were considered less likely candidates. In contrast, two other genes, the prenylated protein tyrosine phosphate family member Ptp4a1 (protein tyrosine phosphate 4a1) and the zinc finger protein Phf3 (plant homeoDomain finger protein 3) met each of our bioinformatic criteria and are thus strong candidates. These findings are also of translational relevance because both Ptp4a1 and Phf3 have been nominated as candidates genes for alcohol dependence in a human genome-wide association study. Our findings support the hypothesis that variants in one or both of these genes modulate heritable differences in the effects of ethanol on anxiety-related behaviors.

scholarly journals Genomic Locus Modulating IOP in the BXD RI Mouse Strains

2017 ◽  
Author(s):  
Rebecca King ◽  
Ying Li ◽  
Jiaxing Wang ◽  
Felix L. Struebing ◽  
Eldon E. Geisert
Keyword(s):  
Candidate Genes ◽  
Quantitative Trait ◽  
Significant Quantitative Trait Locus ◽  
Interval Mapping ◽  
Mouse Strains ◽  
Genomic Locus ◽  
Quantitative Trait Analysis ◽  
Significant Locus ◽  
Trait Locus ◽  
Different Strains

AbstractPurposeIntraocular pressure (IOP) is the primary risk factor for developing glaucoma. The present study examines genomic contribution to the normal regulation of IOP in the mouse.MethodsThe BXD recombinant inbred (RI) strain set was used to identify genomic loci modulating IOP. We measured the IOP from 532 eyes from 33 different strains. The IOP data will be subjected to conventional quantitative trait analysis using simple and composite interval mapping along with epistatic interactions to define genomic loci modulating normal IOP.ResultsThe analysis defined one significant quantitative trait locus (QTL) on Chr.8 (100 to 106 Mb). The significant locus was further examined to define candidate genes that modulate normal IOP. There are only two good candidate genes within the 6 Mb over the peak, Cdh8 (Cadherin 8) and Cdh11 (Cadherin 11). Expression analysis on gene expression and immunohistochemistry indicate that Cdh11 is the best candidate for modulating the normal levels of IOP.ConclusionsWe have examined the genomic regulation of IOP in the BXD RI strain set and found one significant QTL on Chr. 8. Within this QTL that are two potential candidates for modulating IOP with the most likely gene being Cdh11.

scholarly journals QTL mapping and candidate gene identification in rice using a Kalarata-Azucena population under salt stress

2020 ◽  
Author(s):  
Marjorie P. de Ocampo ◽  
Ho Viet The ◽  
Michael J. Thomson ◽  
Shiro Mitsuya ◽  
Akira Yamauchi ◽  
...  
Keyword(s):  
Salt Stress ◽  
Salt Tolerance ◽  
Candidate Gene ◽  
Candidate Genes ◽  
Evaluation System ◽  
Average Distance ◽  
Chlorophyll Concentration ◽  
Interval Mapping ◽  
Chromosome 1 ◽  
Rice Varieties

Abstract Background Salt stress is a major constraint across large rice production areas in Asia, because of the high sensitivity of modern rice varieties. To identify quantitative trait loci (QTL) associated with salt tolerance in rice, we developed an F2 population from a cross between the salt-tolerant landrace, Kalarata, and the salt-sensitive parent, Azucena. An F2 population was used for DNA extraction, and F2:3 families from this population were screened in a phytotron in a saline nutrient solution at the seedling stage. Results After 2 weeks at an EC of 12 dS m− 1, the F2:3 families were scored for salt tolerance using IRRI’s Standard evaluation system (SES). Growth, biomass, Na+ and K+ concentrations in leaf tissues, and chlorophyll concentration were determined. A genetic linkage map was constructed with 151 SSRs and InDel markers, which cover 1463 cM with an average distance of 9.69 cM between loci. A total of 13 QTL were identified using Composite Interval Mapping for 16 traits. The short arm of chromosome 1 had the highest density of QTL associated with salt tolerance, which coincides with the Saltol locus; emphasizing the importance of this locus for candidate gene discovery and for use in rice breeding. Several novel QTL were identified on other chromosomes. Conclusions The novel QTL identified in this study constitute future targets for molecular breeding, to combine them with other QTLs identified before, for higher and stable performance of rice varieties in salt affected soils. Candidate genes for the large effect QTL on chromosome 3 were found to be involved in diverse biological processes, cellular components, and molecular functions. Several candidate genes in this locus were functionally associated with salt stress tolerance and should further be considered for genetic improvement of rice varieties.

scholarly journals Genomic Locus Modulating IOP in the BXD RI Mouse Strains

2017 ◽  
Author(s):  
Rebecca King ◽  
Ying Li ◽  
Jiaxing Wang ◽  
Felix L. Struebing ◽  
Eldon E. Geisert
Keyword(s):  
Candidate Genes ◽  
Quantitative Trait ◽  
Significant Quantitative Trait Locus ◽  
Interval Mapping ◽  
Mouse Strains ◽  
Genomic Locus ◽  
Quantitative Trait Analysis ◽  
Significant Locus ◽  
Trait Locus ◽  
Different Strains

AbstractPurposeIntraocular pressure (IOP) is the primary risk factor for developing glaucoma. The present study examines genomic contribution to the normal regulation of IOP in the mouse.MethodsThe BXD recombinant inbred (RI) strain set was used to identify genomic loci modulating IOP. We measured the IOP from 532 eyes from 34 different strains. The IOP data will be subjected to conventional quantitative trait analysis using simple and composite interval mapping along with epistatic interactions to define genomic loci modulating normal IOP.ResultsThe analysis defined one significant quantitative trait locus (QTL) on Chr.8 (100 to 106 Mb). The significant locus was further examined to define candidate genes that modulate normal IOP. There are only two good candidate genes within the 6 Mb over the peak, Cdh8 (Cadherin 8) and Cdh11 (Cadherin 11). Expression analysis on gene expression and immunohistochemistry indicate that Cdh11 is the best candidate for modulating the normal levels of IOP.ConclusionsWe have examined the genomic regulation of IOP in the BXD RI strain set and found one significant QTL on Chr. 8. Within this QTL that are two potential candidates for modulating IOP with the most likely gene being Cdh11.

scholarly journals Genotyping by sequencing for identification and mapping of QTLs for bioenergy-related traits in sweet sorghum

2020 ◽  
Author(s):  
Kanokwan Teingtham ◽  
David M. Braun ◽  
Ismail Dweikat
Keyword(s):  
Sweet Sorghum ◽  
Recombinant Inbred Lines ◽  
Genotyping By Sequencing ◽  
Interval Mapping ◽  
Chromosome 1 ◽  
Total Biomass ◽  
Sequencing Analysis ◽  
Nucleotide Polymorphisms ◽  
Sugar Transporter ◽  
Major Qtls

AbstractSweet sorghum (Sorghum bicolor L. Moench) is a promising bioenergy crop. To increase the productivity of this crop, marker-assisted breeding will be important to advance genetic improvement of sweet sorghum. The objective of the present study was to identify quantitative trait loci (QTLs) associated with bioenergy-related traits in sweet sorghum. We used 188 F7 recombinant inbred lines (RILs) derived from a cross between sweet sorghum (Wray) and grain sorghum (Macia). The RILs and their parental lines were grown at two locations in 2012 and 2013. Genotyping-by-sequencing analysis of the RILs allowed the construction of a map with 979 single nucleotide polymorphisms. Using the inclusive composite interval mapping of additive QTLs, major QTLs for flowering time and head moisture content were detected on chromosome 6, and explained 29.45% and 20.65% of the phenotypic variances (PVE), respectively. Major QTLs for plant height (29.51% PVE) and total biomass yield (16.46% PVE) were detected on chromosome 7, and QTLs for stem diameter (9.43% PVE) and 100 seed weight (22.97% PVE) were detected on chromosome 1. A major QTL for brix (39.92% PVE) and grain yield (49.14%) PVE co-localized on chromosome 3, was detected consistently across four environments, and is closely associated with a SWEET sugar transporter gene. Additionally, several other QTLs for brix identified in this study or reported previously were found to be associated with sugar transporter genes. The identified QTLs in this study will help to further understand the underlying genes associated with bioenergy-related traits and could be used for development of molecular markers for marker-assisted selection.

scholarly journals Novel QTL and Meta-QTL Mapping for Major Quality Traits in Soybean

2021 ◽  
Vol 12 ◽  
Author(s):  
Heng Chen ◽  
Xiangwen Pan ◽  
Feifei Wang ◽  
Changkai Liu ◽  
Xue Wang ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Candidate Genes ◽  
Gene Annotation ◽  
Recombinant Inbred Lines ◽  
Meta Analysis ◽  
Interval Mapping ◽  
Quality Traits ◽  
Important Quality ◽  
Trait Locus ◽  
Whole Genome Resequencing

Isoflavone, protein, and oil are the most important quality traits in soybean. Since these phenotypes are typically quantitative traits, quantitative trait locus (QTL) mapping has been an efficient way to clarify their complex and unclear genetic background. However, the low-density genetic map and the absence of QTL integration limited the accurate and efficient QTL mapping in previous researches. This paper adopted a recombinant inbred lines (RIL) population derived from ‘Zhongdou27’and ‘Hefeng25’ and a high-density linkage map based on whole-genome resequencing to map novel QTL and used meta-analysis methods to integrate the stable and consentaneous QTL. The candidate genes were obtained from gene functional annotation and expression analysis based on the public database. A total of 41 QTL with a high logarithm of odd (LOD) scores were identified through composite interval mapping (CIM), including 38 novel QTL and 2 Stable QTL. A total of 660 candidate genes were predicted according to the results of the gene annotation and public transcriptome data. A total of 212 meta-QTL containing 122 stable and consentaneous QTL were mapped based on 1,034 QTL collected from previous studies. For the first time, 70 meta-QTL associated with isoflavones were mapped in this study. Meanwhile, 69 and 73 meta-QTL, respectively, related to oil and protein were obtained as well. The results promote the understanding of the biosynthesis and regulation of isoflavones, protein, and oil at molecular levels, and facilitate the construction of molecular modular for great quality traits in soybean.

scholarly journals Meta-Analysis of Yield-Related and N-Responsive Genes Reveals Chromosomal Hotspots, Key Processes and Candidate Genes for Nitrogen-Use Efficiency in Rice

2021 ◽  
Vol 12 ◽  
Author(s):  
Supriya Kumari ◽  
Narendra Sharma ◽  
Nandula Raghuram
Keyword(s):  
Candidate Genes ◽  
Protein Interactions ◽  
Nitrogen Use Efficiency ◽  
Meta Analysis ◽  
Photosynthetic Performance ◽  
Chromosome 1 ◽  
Functional Evaluation ◽  
Nitrogen Use ◽  
Use Efficiency ◽  
Trait Locus

Nitrogen-use efficiency (NUE) is a function of N-response and yield that is controlled by many genes and phenotypic parameters that are poorly characterized. This study compiled all known yield-related genes in rice and mined them from the N-responsive microarray data to find 1,064 NUE-related genes. Many of them are novel genes hitherto unreported as related to NUE, including 80 transporters, 235 transcription factors (TFs), 44 MicroRNAs (miRNAs), 91 kinases, and 8 phosphatases. They were further shortlisted to 62 NUE-candidate genes following hierarchical methods, including quantitative trait locus (QTL) co-localization, functional evaluation in the literature, and protein–protein interactions (PPIs). They were localized to chromosomes 1, 3, 5, and 9, of which chromosome 1 with 26 genes emerged as a hotspot for NUE spanning 81% of the chromosomes. Further, co-localization of the NUE genes on NUE-QTLs resolved differences in the earlier studies that relied mainly on N-responsive genes regardless of their role in yield. Functional annotations and PPIs for all the 1,064 NUE-related genes and also the shortlisted 62 candidates revealed transcription, redox, phosphorylation, transport, development, metabolism, photosynthesis, water deprivation, and hormonal and stomatal function among the prominent processes. In silico expression analysis confirmed differential expression of the 62 NUE-candidate genes in a tissue/stage-specific manner. Experimental validation in two contrasting genotypes revealed that high NUE rice shows better photosynthetic performance, transpiration efficiency and internal water-use efficiency in comparison to low NUE rice. Feature Selection Analysis independently identified one-third of the common genes at every stage of hierarchical shortlisting, offering 6 priority targets to validate for improving the crop NUE.

scholarly journals High resolution mapping and candidate gene identification of downy mildew race 16 resistance in spinach

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Gehendra Bhattarai ◽  
Wei Yang ◽  
Ainong Shi ◽  
Chunda Feng ◽  
Braham Dhillon ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Downy Mildew ◽  
Association Analysis ◽  
Spinacia Oleracea ◽  
Genotyping By Sequencing ◽  
Significant Snps ◽  
Snp Markers ◽  
Resistance Locus ◽  
Downy Mildew Resistance ◽  
Mildew Resistance

Abstract Background Downy mildew, the most devastating disease of spinach (Spinacia oleracea L.), is caused by the oomycete Peronospora effusa [=P. farinosa f. sp. spinaciae]. The P. effusa shows race specificities to the resistant host and comprises 19 reported races and many novel isolates. Sixteen new P. effusa races were identified during the past three decades, and the new pathogen races are continually overcoming the genetic resistances used in commercial cultivars. A spinach breeding population derived from the cross between cultivars Whale and Lazio was inoculated with P. effusa race 16 in an environment-controlled facility; disease response was recorded and genotyped using genotyping by sequencing (GBS). The main objective of this study was to identify resistance-associated single nucleotide polymorphism (SNP) markers from the cultivar Whale against the P. effusa race 16. Results Association analysis conducted using GBS markers identified six significant SNPs (S3_658,306, S3_692697, S3_1050601, S3_1227787, S3_1227802, S3_1231197). The downy mildew resistance locus from cultivar Whale was mapped to a 0.57 Mb region on chromosome 3, including four disease resistance candidate genes (Spo12736, Spo12784, Spo12908, and Spo12821) within 2.69–11.28 Kb of the peak SNP. Conclusions Genomewide association analysis approach was used to map the P. effusa race 16 resistance loci and identify associated SNP markers and the candidate genes. The results from this study could be valuable in understanding the genetic basis of downy mildew resistance, and the SNP marker will be useful in spinach breeding to select resistant lines.

scholarly journals Integration and Modularity of Quantitative Trait Locus Effects on Geometric Shape in the Mouse Mandible

Genetics ◽  
2004 ◽  
Vol 166 (4) ◽  
pp. 1909-1921
Author(s):  
Christian Peter Klingenberg ◽  
Larry J Leamy ◽  
James M Cheverud
Keyword(s):  
Quantitative Trait ◽  
Parametric Bootstrap ◽  
Interval Mapping ◽  
Procrustes Analysis ◽  
Bootstrap Test ◽  
Mandible Shape ◽  
Trait Locus ◽  
F2 Generation ◽  
Analysis Interval ◽  
Qtl Effects

Abstract The mouse mandible has long served as a model system for complex morphological structures. Here we use new methodology based on geometric morphometrics to test the hypothesis that the mandible consists of two main modules, the alveolar region and the ascending ramus, and that this modularity is reflected in the effects of quantitative trait loci (QTL). The shape of each mandible was analyzed by the positions of 16 morphological landmarks and these data were analyzed using Procrustes analysis. Interval mapping in the F2 generation from intercrosses of the LG/J and SM/J strains revealed 33 QTL affecting mandible shape. The QTL effects corresponded to a variety of shape changes, but ordination or a parametric bootstrap test of clustering did not reveal any distinct groups of QTL that would affect primarily one module or the other. The correlations of landmark positions between the two modules tended to be lower than the correlations between arbitrary subsets of landmarks, indicating that the modules were relatively independent of each other and confirming the hypothesized location of the boundary between them. While these results are in agreement with the hypothesis of modularity, they also underscore that modularity is a question of the relative degrees to which QTL contribute to different traits, rather than a question of discrete sets of QTL contributing to discrete sets of traits.

scholarly journals Genetic Architecture of a Morphological Shape Difference Between Two Drosophila Species

Genetics ◽  
2000 ◽  
Vol 154 (1) ◽  
pp. 299-310 ◽  
Author(s):  
Zhao-Bang Zeng ◽  
Jianjun Liu ◽  
Lynn F Stam ◽  
Chen-Hung Kao ◽  
John M Mercer ◽  
...  
Keyword(s):  
Interval Mapping ◽  
Additive Effect ◽  
Parameter Estimates ◽  
Effect Estimate ◽  
Interspecific Difference ◽  
Posterior Lobe ◽  
Complete Dominance ◽  
Backcross Populations ◽  
History Of ◽  
Trait Locus

AbstractThe size and shape of the posterior lobe of the male genital arch differs dramatically between Drosophila simulans and D. mauritiana. This difference can be quantified with a morphometric descriptor (PC1) based on elliptical Fourier and principal components analyses. The genetic basis of the interspecific difference in PC1 was investigated by the application of quantitative trait locus (QTL) mapping procedures to segregating backcross populations. The parental difference (35 environmental standard deviations) and the heritability of PC1 in backcross populations (>90%) are both very large. The use of multiple interval mapping gives evidence for 19 different QTL. The greatest additive effect estimate accounts for 11.4% of the parental difference but could represent multiple closely linked QTL. Dominance parameter estimates vary among loci from essentially no dominance to complete dominance, and mauritiana alleles tend to be dominant over simulans alleles. Epistasis appears to be relatively unimportant as a source of variation. All but one of the additive effect estimates have the same sign, which means that one species has nearly all plus alleles and the other nearly all minus alleles. This result is unexpected under many evolutionary scenarios and suggests a history of strong directional selection acting on the posterior lobe.

Sign in / Sign up

Export Citation Format

Share Document