scholarly journals Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut

2021 ◽  
Vol 12 ◽  
Author(s):  
Mangesh P. Jadhav ◽  
Sunil S. Gangurde ◽  
Anil A. Hake ◽  
Arati Yadawad ◽  
Supriya S. Mahadevaiah ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Oil Quality ◽  
Genotyping By Sequencing ◽  
Phenotypic Variance ◽  
Potential Candidate ◽  
Quality Traits ◽  
Single Marker Analysis ◽  
Main Effect ◽  
Genomic Regions ◽  
Main Effect Qtls

With an objective of identifying the genomic regions for productivity and quality traits in peanut, a recombinant inbred line (RIL) population developed from an elite variety, TMV 2 and its ethyl methane sulfonate (EMS)-derived mutant was phenotyped over six seasons and genotyped with genotyping-by-sequencing (GBS), Arachis hypogaea transposable element (AhTE) and simple sequence repeats (SSR) markers. The genetic map with 700 markers spanning 2,438.1 cM was employed for quantitative trait loci (QTL) analysis which identified a total of 47 main-effect QTLs for the productivity and oil quality traits with the phenotypic variance explained (PVE) of 10–52% over the seasons. A common QTL region (46.7–50.1 cM) on Ah02 was identified for the multiple traits, such as a number of pods per plant (NPPP), pod weight per plant (PWPP), shelling percentage (SP), and test weight (TW). Similarly, a QTL (7.1–18.0 cM) on Ah16 was identified for both SP and protein content (PC). Epistatic QTL (epiQTL) analysis revealed intra- and inter-chromosomal interactions for the main-effect QTLs and other genomic regions governing these productivity traits. The markers identified by a single marker analysis (SMA) mapped to the QTL regions for most of the traits. Among the five potential candidate genes identified for PC, SP and oil quality, two genes (Arahy.7A57YA and Arahy.CH9B83) were affected by AhMITE1 transposition, and three genes (Arahy.J5SZ1I, Arahy.MZJT69, and Arahy.X7PJ8H) involved functional single nucleotide polymorphisms (SNPs). With major and consistent effects, the genomic regions, candidate genes, and the associated markers identified in this study would provide an opportunity for gene cloning and genomics-assisted breeding for increasing the productivity and enhancing the quality of peanut.

scholarly journals Genome-Wide Detection of Major and Epistatic Effect QTLs for Seed Protein and Oil Content in Soybean Under Multiple Environments Using High-Density Bin Map

2019 ◽  
Vol 20 (4) ◽  
pp. 979 ◽  
Author(s):  
Benjamin Karikari ◽  
Shuguang Li ◽  
Javaid Bhat ◽  
Yongce Cao ◽  
Jiejie Kong ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Oil Content ◽  
Seed Protein ◽  
Average Distance ◽  
Epistatic Effect ◽  
High Density ◽  
Environment Interaction ◽  
Potential Candidate ◽  
Main Effect ◽  
Main Effect Qtls

Seed protein and oil content are the two important traits determining the quality and value of soybean. Development of improved cultivars requires detailed understanding of the genetic basis underlying the trait of interest. However, it is prerequisite to have a high-density linkage map for precisely mapping genomic regions, and therefore the present study used high-density genetic map containing 2267 recombination bin markers distributed on 20 chromosomes and spanned 2453.79 cM with an average distance of 1.08 cM between markers using restriction-site-associated DNA sequencing (RAD-seq) approach. A recombinant inbred line (RIL) population of 104 lines derived from a cross between Linhefenqingdou and Meng 8206 cultivars was evaluated in six different environments to identify main- and epistatic-effect quantitative trait loci (QTLs)as well as their interaction with environments. A total of 44 main-effect QTLs for protein and oil content were found to be distributed on 17 chromosomes, and 15 novel QTL were identified for the first time. Out of these QTLs, four were major and stable QTLs, viz., qPro-7-1, qOil-8-3, qOil-10-2 and qOil-10-4, detected in at least two environments plus combined environment with R2 values >10%. Within the physical intervals of these four QTLs, 111 candidate genes were screened for their direct or indirect involvement in seed protein and oil biosynthesis/metabolism processes based on gene ontology and annotation information. Based on RNA sequencing (RNA-seq) data analysis, 15 of the 111 genes were highly expressed during seed development stage and root nodules that might be considered as the potential candidate genes. Seven QTLs associated with protein and oil content exhibited significant additive and additive × environment interaction effects, and environment-independent QTLs revealed higher additive effects. Moreover, three digenic epistatic QTLs pairs were identified, and no main-effect QTLs showed epistasis. In conclusion, the use of a high-density map identified closely linked flanking markers, provided better understanding of genetic architecture and candidate gene information, and revealed the scope available for improvement of soybean quality through marker assisted selection (MAS).

Prioritisation of candidate genes in QTL regions for seed germination and early seedling growth in bread wheat (Triticum aestivum) under salt-stress conditions

2021 ◽  
Vol 72 (1) ◽  
pp. 1
Author(s):  
Elham Rezaei ◽  
Eslam Majidi Hervan ◽  
Amin Azadi ◽  
Alireza Etminan ◽  
Hossein Ramshini
Keyword(s):  
Triticum Aestivum ◽  
Salt Stress ◽  
Candidate Genes ◽  
Metabolic Process ◽  
Stress Conditions ◽  
Phenotypic Variance ◽  
Fresh Weight ◽  
Main Effect ◽  
Early Seedling ◽  
Go Terms

Salinity and drought are major abiotic stresses affecting wheat (Triticum aestivum L.) production throughout the world, and discovery of loci for traits affecting yield under salinity may lead to the breeding for salt-tolerant plants. In the present study, 186 F10 recombinant inbred line (RIL) populations were evaluated under salt-stress conditions in order to identify main-effect and epistatic-effect quantitative trait loci (QTLs) for 15 traits in wheat during the germination and early-seedling stages. In total, 61 main-effect QTLs on 15 chromosomes and 21 epistatic interactions on 12 chromosomes were detected through composite interval mapping (CIM) and a mixed-model-based CIM method. Two major QTLs for primary-leaf fresh weight and coleoptile fresh weight were detected on chromosome (or linkage group) 5B2 and 2D, respectively, which contributed ~44% and 43% of the phenotypic variance. Additionally, 12 QTL clusters including different traits were detected on 1A1, 3A, 4A, 2B1, 3B, 5B1 and 2D1. Candidate genes were identified within QTL regions and gene ontology (GO) enrichment analysis was performed. In total, 9134 candidate genes were grouped into 274 GO terms (including 79 GO terms involved in the ‘biological process’ category). These genes directly or indirectly play a vital role such as lipid localisation, biological regulation, fatty acid biosynthetic process, cellular process, DNA conformation change, translational elongation, carbohydrate metabolic process, Fe ion homeostasis, hydrogen peroxide metabolic process, and pigment biosynthetic process at the germination and early-seedling stages under salt-stress conditions.

scholarly journals GWAS Discovery Of Candidate Genes for Yield-Related Traits in Peanut and Support from Earlier QTL Mapping Studies

Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 803 ◽  
Author(s):  
Wang ◽  
Yan ◽  
Li ◽  
Li ◽  
Zhao ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Gene Annotation ◽  
Genotyping By Sequencing ◽  
Nucleotide Polymorphisms ◽  
Market Demand ◽  
Oil Crops ◽  
A Genome ◽  
Genomic Regions

Peanut (Arachis hypogaea L.) is one of the most important oil crops worldwide, and its yet increasing market demand may be met by genetic improvement of yield related traits, which may be facilitated by a good understanding of the underlying genetic base of these traits. Here, we have carried out a genome-wide association study (GWAS) with the aim to identify genomic regions and the candidate genes within these regions that may be involved in determining the phenotypic variation at seven yield-related traits in peanut. For the GWAS analyses, 195 peanut accessions were phenotyped and/or genotyped; the latter was done using a genotyping-by-sequencing approach, which produced a total of 13,435 high-quality single nucleotide polymorphisms (SNPs). Analyses of these SNPs show that the analyzed peanut accessions can be approximately grouped into two big groups that, to some extent, agree with the botanical classification of peanut at the subspecies level. By taking this genetic structure as well as the relationships between the analyzed accessions into consideration, our GWAS analyses have identified 93 non-overlapping peak SNPs that are significantly associated with four of the studied traits. Gene annotation of the genome regions surrounding these peak SNPs have found a total of 311 unique candidate genes. Among the 93 yield-related-trait-associated SNP peaks, 12 are found to be co-localized with the quantitative trait loci (QTLs) that were identified by earlier related QTL mapping studies, and these 12 SNP peaks are only related to three traits and are almost all located on chromosomes Arahy.05 and Arahy.16. Gene annotation of these 12 co-localized SNP peaks have found 36 candidates genes, and a close examination of these candidate genes found one very interesting gene (arahy.RI9HIF), the rice homolog of which produces a protein that has been shown to improve rice yield when over-expressed. Further tests of the arahy.RI9HIF gene, as well as other candidate genes especially those within the more confident co-localized genomic regions, may hold the potential for significantly improving peanut yield.

scholarly journals Development and Validation of Markers for the Fertility Restorer Gene Rf1 in Sunflower

2019 ◽  
Vol 20 (6) ◽  
pp. 1260 ◽  
Author(s):  
Renate Horn ◽  
Aleksandra Radanovic ◽  
Lena Fuhrmann ◽  
Yves Sprycha ◽  
Sonia Hamrit ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Fertility Restoration ◽  
Association Studies ◽  
Restorer Gene ◽  
Hybrid Breeding ◽  
P Value ◽  
Potential Candidate ◽  
Association Panel ◽  
Dominant Markers ◽  
Genomic Regions

Hybrid breeding in sunflowers based on CMS PET1 requires development of restorer lines carrying, in most cases, the restorer gene Rf1. Markers for marker-assisted selection have been developed, but there is still need for closer, more versatile, and co-dominant markers linked to Rf1. Homology searches against the reference sunflower genome using sequences of cloned markers, as well as Bacterial Artificial Chromosome (BAC)-end sequences of clones hybridizing to them, allowed the identification of two genomic regions of 30 and 3.9 Mb, respectively, as possible physical locations of the restorer gene Rf1 on linkage group 13. Nine potential candidate genes, encoding six pentatricopeptide repeat proteins, one tetratricopeptide-like helical domain, a probable aldehyde dehydrogenase 22A1, and a probable poly(A) polymerase 3 (PAPS3), were identified in these two genomic regions. Amplicon targeted next generation sequencing of these nine candidate genes for Rf1 was performed in an association panel consisting of 27 maintainer and 32 restorer lines and revealed the presence of 210 Single Nucleotide Polymorphisms (SNPs) and 67 Insertions/Deletions (INDELs). Association studies showed significant associations of 10 SNPs with fertility restoration (p-value < 10−4), narrowing Rf1 down to three candidate genes. Three new markers, one co-dominant marker 67N04_P and two dominant markers, PPR621.5R for restorer, and PPR621.5M for maintainer lines were developed and verified in the association panel of 59 sunflower lines. The versatility of the three newly developed markers, as well as of three existing markers for the restorer gene Rf1 (HRG01 and HRG02, Cleaved Amplified Polymorphic Sequence (CAPS)-marker H13), was analyzed in a large association panel consisting of 557 accessions.

scholarly journals Genome-wide association study (GWAS) for morphological and yield-related traits in an oil palm hybrid (Elaeis oleifera x Elaeis guineensis) population

2019 ◽  
Author(s):  
Jaime Osorio ◽  
Gina Garzón ◽  
Paola Delgadillo ◽  
Silvio Bastidas ◽  
Leidy Moreno ◽  
...  
Keyword(s):  
Association Mapping ◽  
Candidate Genes ◽  
Oil Palm ◽  
Plant Architecture ◽  
Elaeis Guineensis ◽  
Genotyping By Sequencing ◽  
Genome Wide Association ◽  
Elaeis Oleifera ◽  
Genome Wide ◽  
Genomic Regions

Abstract Background The genus Elaeis has two species of economic importance for the oil palm agroindustry: Elaeis oleifera (O), native to the Americas, and Elaeis guineensis (G), native to Africa. This work provides to our knowledge, the first association mapping study in an interspecific OxG oil palm population, which shows tolerance to pests and diseases, high oil quality, and acceptable fruit bunch production. Results Using genotyping-by-sequencing (GBS), we identified a total of 3,776 single nucleotide polymorphisms (SNPs) that were used to perform a genome-wide association analysis (GWAS) in 378 OxG hybrid population for 10 agronomic traits. Twelve genomic regions (SNPs) were located near candidate genes implicated in multiple functional categories, such as tissue growth, cellular trafficking, and physiological processes. Conclusions We provide new insights on genomic regions that mapped on candidate genes involved in plant architecture and yield. These potential candidate genes need to be confirmed for future targeted functional analyses. Associated markers to the traits of interest may be valuable resources for the development of marker-assisted selection in oil palm breeding. Keywords: Association mapping, Elaeis guineensis , Elaeis oleifera , genotyping-by-sequencing, plant architecture, yield.

scholarly journals Comparative QTL analysis and candidate genes identification of seed size, shape and weight in soybean (Glycine max L.)

2021 ◽  
Author(s):  
Mahmoud A Elattar ◽  
Benjamin Karikari ◽  
Shuguang Li ◽  
Shiyu Song ◽  
Yongce Cao ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Seed Size ◽  
Composite Interval Mapping ◽  
Mixed Model ◽  
Interval Mapping ◽  
Genetic Maps ◽  
Potential Candidate ◽  
Go Enrichment ◽  
Glycine Max L ◽  
Genomic Regions

Abstract Dissecting the genetic mechanism underlying seed size, shape and weight is essential to these traits for enhancing soybean cultivars. High-density genetic maps of two recombinant inbred line populations, LM6 and ZM6, evaluated in multiple environments to identify candidate genes behind seed-related traits major and stable QTLs. A total of 239 and 43 M-QTL were mapped by composite interval mapping and mixed-model based composite interval mapping approaches, respectively, from which 22 common QTLs including four major and novel QTLs. CIM and MCIM approaches identified 180 and 18 novel M-QTLs, respectively. Moreover, 18 QTLs showed significant AE effects, and 40 pairwise of the identified QTLs exhibited digenic epistatic effects. Seed flatness index QTLs (34 QTLs) were identified and reported for the first time. Seven QTL clusters underlying the inheritance of seed size, shape and weight on genomic regions of chromosomes 3, 4, 5, 7, 9, 17 and 19 were identified. Gene annotations, gene ontology (GO) enrichment and RNA-seq analyses identified 47 candidate genes for seed-related traits within the genomic regions of those 7 QTL clusters. These genes are highly expressed in seed-related tissues and nodules, that might be deemed as potential candidate genes regulating the above traits in soybean. This study provides detailed information for the genetic bases of the studied traits and candidate genes that could be efficiently implemented by soybean breeders for fine mapping and gene cloning as well as for MAS targeted at improving these traits individually or concurrently.

scholarly journals An Integrative Analysis of Transcriptome and GWAS Data to Identify Potential Candidate Genes Influencing Meat Quality Traits in Pigs

2021 ◽  
Vol 12 ◽  
Author(s):  
Xianxian Liu ◽  
Junjie Zhang ◽  
Xinwei Xiong ◽  
Congying Chen ◽  
Yuyun Xing ◽  
...  
Keyword(s):  
Gene Expression ◽  
Candidate Genes ◽  
Meat Quality ◽  
Integrative Analysis ◽  
Potential Candidate ◽  
Quality Traits ◽  
Eqtl Mapping ◽  
Meat Quality Traits ◽  
Genome Wide ◽  
A Genome

Understanding the genetic factors behind meat quality traits is of great significance to animal breeding and production. We previously conducted a genome-wide association study (GWAS) for meat quality traits in a White Duroc × Erhualian F2 pig population using Illumina porcine 60K SNP data. Here, we further investigate the functional candidate genes and their network modules associated with meat quality traits by integrating transcriptomics and GWAS information. Quantitative trait transcript (QTT) analysis, gene expression QTL (eQTL) mapping, and weighted gene co-expression network analysis (WGCNA) were performed using the digital gene expression (DGE) data from 493 F2 pig’s muscle and liver samples. Among the quantified 20,108 liver and 23,728 muscle transcripts, 535 liver and 1,014 muscle QTTs corresponding to 416 and 721 genes, respectively, were found to be significantly (p &lt; 5 × 10−4) correlated with 22 meat quality traits measured on longissiums dorsi muscle (LM) or semimembranosus muscle (SM). Transcripts associated with muscle glycolytic potential (GP) and pH values were enriched for genes involved in metabolic process. There were 42 QTTs (for 32 genes) shared by liver and muscle tissues, of which 10 QTTs represent GP- and/or pH-related genes, such as JUNB, ATF3, and PPP1R3B. Furthermore, a genome-wide eQTL mapping revealed a total of 3,054 eQTLs for all annotated transcripts in muscle (p &lt; 2.08 × 10−5), including 1,283 cis-eQTLs and 1771 trans-eQTLs. In addition, WGCNA identified five modules relevant to glycogen metabolism pathway and highlighted the connections between variations in meat quality traits and genes involved in energy process. Integrative analysis of GWAS loci, eQTL, and QTT demonstrated GALNT15/GALNTL2 and HTATIP2 as strong candidate genes for drip loss and pH drop from postmortem 45 min to 24 h, respectively. Our findings provide valuable insights into the genetic basis of meat quality traits and greatly expand the number of candidate genes that may be valuable for future functional analysis and genetic improvement of meat quality.

scholarly journals Genome-wide association study (GWAS) for morphological and yield-related traits in an oil palm hybrid (Elaeis oleifera x Elaeis guineensis) population

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Jaime A. Osorio-Guarín ◽  
Gina A. Garzón-Martínez ◽  
Paola Delgadillo-Duran ◽  
Silvio Bastidas ◽  
Leidy P. Moreno ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Oil Palm ◽  
Elaeis Guineensis ◽  
Genome Wide Association ◽  
Hybrid Population ◽  
Potential Candidate ◽  
Elaeis Oleifera ◽  
Genome Wide ◽  
A Genome ◽  
Genomic Regions

Abstract Background The genus Elaeis has two species of economic importance for the oil palm agroindustry: Elaeis oleifera (O), native to the Americas, and Elaeis guineensis (G), native to Africa. This work provides to our knowledge, the first association mapping study in an interspecific OxG oil palm population, which shows tolerance to pests and diseases, high oil quality, and acceptable fruit bunch production. Results Using genotyping-by-sequencing (GBS), we identified a total of 3776 single nucleotide polymorphisms (SNPs) that were used to perform a genome-wide association analysis (GWAS) in 378 OxG hybrid population for 10 agronomic traits. Twelve genomic regions (SNPs) were located near candidate genes implicated in multiple functional categories, such as tissue growth, cellular trafficking, and physiological processes. Conclusions We provide new insights on genomic regions that mapped on candidate genes involved in plant architecture and yield. These potential candidate genes need to be confirmed for future targeted functional analyses. Associated markers to the traits of interest may be valuable resources for the development of marker-assisted selection in oil palm breeding.

scholarly journals Integrating GWAS and Gene Expression Analysis Identifies Candidate Genes for Root Morphology Traits in Maize at the Seedling Stage

Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 773 ◽  
Author(s):  
Wang ◽  
Wei ◽  
Li ◽  
Wang ◽  
Ge ◽  
...  
Keyword(s):  
Root System ◽  
Candidate Genes ◽  
Root Development ◽  
Root Length ◽  
Root Traits ◽  
Root Surface ◽  
Root Surface Area ◽  
Phenotypic Variance ◽  
Potential Candidate ◽  
Short Root

Root system plays an essential role in water and nutrient acquisition in plants. Understanding the genetic basis of root development will be beneficial for breeding new cultivars with efficient root system to enhance resource use efficiency in maize. Here, the natural variation of 13 root and 3 shoot traits was evaluated in 297 maize inbred lines and genome-wide association mapping was conducted to identify SNPs associated with target traits. All measured traits exhibited 2.02- to 21.36-fold variations. A total of 34 quantitative trait loci (QTLs) were detected for 13 traits, and each individual QTL explained 5.7% to 15.9% of the phenotypic variance. Three pleiotropic QTLs involving five root traits were identified; SNP_2_104416607 was associated with lateral root length (LRL), root surface area (RA), root length between 0 and 0.5mm in diameter (RL005), and total root length (TRL); SNP_2_184016997 was associated with RV and RA, and SNP_4_168917747 was associated with LRL, RA and TRL. The expression levels of candidate genes in root QTLs were evaluated by RNA-seq among three long-root lines and three short-root lines. A total of five genes that showed differential expression between the long- and short-root lines were identified as promising candidate genes for the target traits. These QTLs and the potential candidate genes are important source data to understand root development and genetic improvement of root traits in maize.

scholarly journals Identification of Loci Controlling the Dwarfism Trait in the White Sailfin Molly (Poecilia latipinna) Using Genome-Wide Association Studies Based on Genotyping-By-Sequencing

Genes ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 418
Author(s):  
Fan Shao ◽  
Jing Liu ◽  
Mengyuan Ren ◽  
Junying Li ◽  
Haigang Bao ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Association Studies ◽  
Genotyping By Sequencing ◽  
Genome Wide Association ◽  
Expression Level ◽  
Genome Wide Association Studies ◽  
Sailfin Molly ◽  
Genome Wide ◽  
Genomic Regions ◽  
Sailfin Mollies

Dwarfism is a condition defined by low harvest weight in fish, but also results in strange body figures which may have potential for the selective breeding of new ornamental fish strains. The objectives of this study are to reveal the physiological causes of dwarfism and identify the genetic loci controlling this trait in the white sailfin molly. Skeletons of dwarf and normal sailfin mollies were observed by X-ray radioscopy and skeletal staining. Genome-wide association studies based on genotyping-by-sequencing (n = 184) were used to map candidate genomic regions associated with the dwarfism trait. Quantitative real-time PCR was performed to determine the expression level of candidate genes in normal (n = 8) and dwarf (n = 8) sailfin mollies. We found that the dwarf sailfin molly has a short and dysplastic spine in comparison to the normal fish. Two regions, located at NW_015112742.1 and NW_015113621.1, were significantly associated with the dwarfism trait. The expression level of three candidate genes, ADAMTS like 1, Larp7 and PPP3CA, were significantly different between the dwarf and normal sailfin mollies in the hepatopancreas, with PPP3CA also showing significant differences in the vertebrae and Larp7 showing significant differences in the muscle. This study identified genomic regions and candidate genes associated with the dwarfism trait in the white sailfin molly and would provide a reference to determine dwarf-causing variations.

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