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).

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 Dissecting the Genetic Architecture of Seed Protein and Oil Content in Soybean from the Yangtze and Huaihe River Valleys Using Multi-Locus Genome-Wide Association Studies

2019 ◽  
Vol 20 (12) ◽  
pp. 3041 ◽  
Author(s):  
Li ◽  
Xu ◽  
Yang ◽  
Zhao
Keyword(s):  
Candidate Genes ◽  
Genetic Architecture ◽  
Oil Content ◽  
Seed Protein ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Huaihe River ◽  
Genome Wide ◽  
River Valleys

Soybean is a globally important legume crop that provides a primary source of high-quality vegetable protein and oil. Seed protein and oil content are two valuable quality traits controlled by multiple genes in soybean. In this study, the restricted two-stage multi-locus genome-wide association analysis (RTM-GWAS) procedure was performed to dissect the genetic architecture of seed protein and oil content in a diverse panel of 279 soybean accessions from the Yangtze and Huaihe River Valleys in China. We identified 26 quantitative trait loci (QTLs) for seed protein content and 23 for seed oil content, including five associated with both traits. Among these, 39 QTLs corresponded to previously reported QTLs, whereas 10 loci were novel. As reported previously, the QTL on chromosome 20 was associated with both seed protein and oil content. This QTL exhibited opposing effects on these traits and contributed the most to phenotype variation. From the detected QTLs, 55 and 51 candidate genes were identified for seed protein and oil content, respectively. Among these genes, eight may be promising candidate genes for improving soybean nutritional quality. These results will facilitate marker-assisted selective breeding for soybean protein and oil content traits.

scholarly journals Identification of additive and epistatic effects QTLs for seed oil content in soybean based on an integrating map of two RIL populations

2020 ◽  
Author(s):  
Yue Wang ◽  
Shulin Liu ◽  
Jiajing Wang ◽  
Chang Yang ◽  
Zhixi Tian ◽  
...  
Keyword(s):  
Oil Content ◽  
Seed Oil ◽  
Fatty Acid Biosynthesis ◽  
Soybean Seed ◽  
Additive Effect ◽  
Human Consumption ◽  
Environment Interaction ◽  
Potential Candidate ◽  
Seed Oil Content ◽  
Epistatic Effects

Abstract Background Soybean seed oil has been widely used in human consumption and industrial production. Results In order to identify the additive and epistatic effects QTLs and QTLs by environments interactions (AE and AAE) for seed oil content in soybean, an eight-environment conjoint analysis based on two populations RIL3613 and RIL6013 with an integrating map was conducted. An new high-density integrated genetic map containing 2212 SNP markers and covering 5718.01 cM with an average distance of 2.61 cM were constructed by the combination of two linkage maps of two associated recombinant inbred line (A-RIL) populations. A total of 64 additive effect and additive × environment interaction (AE) QTL were identified on 19 chromosomes by both ICIM and IM methods, and the proportion of phenotypic variations explained (PVE) range of QTL related to oil content was 1.29–10.75%, of which 19 QTLs had overlapping marker intervals, and qOil-5-1 was identified simultaneously in both RIL populations. Compared with previous SSR positioning results, it is found 8 SNP sites within the QTL physical interval located in the SSR sites. Among them, 4 QTLs were new found. Twelve pairs of epistatic QTLs (additive × additive, AA) and QTL interactions with environments (AAE) for oil content were identified by the ICIM method, of which 3 QTLs were new found, and 2 additive effect QTLs, qOil-9-2 and qOil-15-1, linked to the other two QTLs to produce epistatic effects. A total of 5 potential candidate genes were identified based on genetic ontology and annotated information showing the relationship with seed oil content and/or fatty acid biosynthesis and metabolism. Conclusion These QTLs with different effects provide the good basis for molecular-assisted breeding of soybean oil content-related traits and further fine mapping of related genes.

scholarly journals High-resolution mapping of a major and consensus quantitative trait locus for oil content to a ~ 0.8-Mb region on chromosome A08 in peanut (Arachis hypogaea L.)

2019 ◽  
Vol 133 (1) ◽  
pp. 37-49 ◽  
Author(s):  
Nian Liu ◽  
Jianbin Guo ◽  
Xiaojing Zhou ◽  
Bei Wu ◽  
Li Huang ◽  
...  
Keyword(s):  
High Resolution ◽  
Genetic Map ◽  
Quantitative Trait ◽  
Oil Content ◽  
Average Distance ◽  
Genomic Region ◽  
High Density ◽  
High Resolution Mapping ◽  
Resolution Mapping ◽  
Trait Locus

Key message ddRAD-seq-based high-density genetic map comprising 2595 loci identified a major and consensus QTL with a linked marker in a 0.8-Mb physical interval for oil content in peanut. Abstract Enhancing oil content is an important breeding objective in peanut. High-resolution mapping of quantitative trait loci (QTLs) with linked markers could facilitate marker-assisted selection in breeding for target traits. In the present study, a recombined inbred line population (Xuhua 13 × Zhonghua 6) was used to construct a genetic map based on double-digest restriction-site-associated DNA sequencing (ddRAD-seq). The resulting high-density genetic map contained 2595 loci, and spanned a length of 2465.62 cM, with an average distance of 0.95 cM/locus. Seven QTLs for oil content were identified on five linkage groups, including the major and stable QTL qOCA08.1 on chromosome A08 with 10.14–27.19% phenotypic variation explained. The physical interval of qOCA08.1 was further delimited to a ~ 0.8-Mb genomic region where two genes affecting oil synthesis had been annotated. The marker SNPOCA08 was developed targeting the SNP loci associated with oil content and validated in peanut cultivars with diverse oil contents. The major and stable QTL identified in the present study could be further dissected for gene discovery. Furthermore, the tightly linked marker for oil content would be useful in marker-assisted breeding in peanut.

scholarly journals Identification of potential candidate genes controlling pea aphid tolerance in a Pisum fulvum high‐density integrated DArTseq SNP‐based genetic map

2020 ◽  
Vol 76 (5) ◽  
pp. 1731-1742
Author(s):  
Eleonora Barilli ◽  
Estefanía Carrillo‐Perdomo ◽  
Maria José Cobos ◽  
Andrzej Kilian ◽  
Jason Carling ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genetic Map ◽  
High Density ◽  
Pea Aphid ◽  
Potential Candidate ◽  
Pisum Fulvum ◽  
Aphid Tolerance

scholarly journals Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Anthony Klein ◽  
Hervé Houtin ◽  
Céline Rond-Coissieux ◽  
Myriam Naudet-Huart ◽  
Michael Touratier ◽  
...  
Keyword(s):  
Protein Content ◽  
Candidate Genes ◽  
Seed Weight ◽  
Seed Protein ◽  
Meta Analysis ◽  
Snp Array ◽  
Grain Legume ◽  
Potential Candidate ◽  
Seed Protein Content ◽  
Breeding Target

Abstract Pea is one of the most important grain legume crops in temperate regions worldwide. Improving pea yield is a critical breeding target. Nine inter-connected pea recombinant inbred line populations were evaluated in nine environments at INRAE Dijon, France and genotyped using the GenoPea 13.2 K SNP array. Each population has been evaluated in two to four environments. A multi-population Quantitative Trait Loci (QTL) analysis for seed weight per plant (SW), seed number per plant (SN), thousand seed weight (TSW) and seed protein content (SPC) was done. QTL were then projected on the multi-population consensus map and a meta-analysis of QTL was performed. This analysis identified 17 QTL for SW, 16 QTL for SN, 35 QTL for TSW and 21 QTL for SPC, shedding light on trait relationships. These QTL were resolved into 27 metaQTL. Some of them showed small confidence intervals of less than 2 cM encompassing less than one hundred underlying candidate genes. The precision of metaQTL and the potential candidate genes reported in this study enable their use for marker-assisted selection and provide a foundation towards map-based identification of causal polymorphisms.

scholarly journals Improved Genetic Map Identified Major QTLs for Drought Tolerance- and Iron Deficiency Tolerance-Related Traits in Groundnut

Genes ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 37
Author(s):  
Manish K. Pandey ◽  
Sunil S. Gangurde ◽  
Vinay Sharma ◽  
Santosh K. Pattanashetti ◽  
Gopalakrishna K. Naidu ◽  
...  
Keyword(s):  
Iron Deficiency ◽  
Drought Tolerance ◽  
Candidate Genes ◽  
Genetic Map ◽  
Deep Understanding ◽  
Soil Conditions ◽  
Glycosyl Hydrolases ◽  
Iron Deficient ◽  
Main Effect ◽  
Main Effect Qtls

A deep understanding of the genetic control of drought tolerance and iron deficiency tolerance is essential to hasten the process of developing improved varieties with higher tolerance through genomics-assisted breeding. In this context, an improved genetic map with 1205 loci was developed spanning 2598.3 cM with an average 2.2 cM distance between loci in the recombinant inbred line (TAG 24 × ICGV 86031) population using high-density 58K single nucleotide polymorphism (SNP) “Axiom_Arachis” array. Quantitative trait locus (QTL) analysis was performed using extensive phenotyping data generated for 20 drought tolerance- and two iron deficiency tolerance-related traits from eight seasons (2004–2015) at two locations in India, one in Niger, and one in Senegal. The genome-wide QTL discovery analysis identified 19 major main-effect QTLs with 10.0–33.9% phenotypic variation explained (PVE) for drought tolerance- and iron deficiency tolerance- related traits. Major main-effect QTLs were detected for haulm weight (20.1% PVE), SCMR (soil plant analytical development (SPAD) chlorophyll meter reading, 22.4% PVE), and visual chlorosis rate (33.9% PVE). Several important candidate genes encoding glycosyl hydrolases; malate dehydrogenases; microtubule-associated proteins; and transcription factors such as MADS-box, basic helix-loop-helix (bHLH), NAM, ATAF, and CUC (NAC), and myeloblastosis (MYB) were identified underlying these QTL regions. The putative function of these genes indicated their possible involvement in plant growth, development of seed and pod, and photosynthesis under drought or iron deficiency conditions in groundnut. These genomic regions and candidate genes, after validation, may be useful to develop molecular markers for deploying genomics-assisted breeding for enhancing groundnut yield under drought stress and iron-deficient soil conditions.

scholarly journals Genome-wide association study and gene network analyses reveal potential candidate genes for high night temperature tolerance in rice

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Raju Bheemanahalli ◽  
Montana Knight ◽  
Cherryl Quinones ◽  
Colleen J. Doherty ◽  
S. V. Krishna Jagadish
Keyword(s):  
Grain Size ◽  
Candidate Genes ◽  
Gene Network ◽  
Genome Wide Association ◽  
Potential Candidate ◽  
Genetic Loci ◽  
Stay Green ◽  
Yield And Quality ◽  
Genome Wide ◽  
Wide Range

AbstractHigh night temperatures (HNT) are shown to significantly reduce rice (Oryza sativa L.) yield and quality. A better understanding of the genetic architecture of HNT tolerance will help rice breeders to develop varieties adapted to future warmer climates. In this study, a diverse indica rice panel displayed a wide range of phenotypic variability in yield and quality traits under control night (24 °C) and higher night (29 °C) temperatures. Genome-wide association analysis revealed 38 genetic loci associated across treatments (18 for control and 20 for HNT). Nineteen loci were detected with the relative changes in the traits between control and HNT. Positive phenotypic correlations and co-located genetic loci with previously cloned grain size genes revealed common genetic regulation between control and HNT, particularly grain size. Network-based predictive models prioritized 20 causal genes at the genetic loci based on known gene/s expression under HNT in rice. Our study provides important insights for future candidate gene validation and molecular marker development to enhance HNT tolerance in rice. Integrated physiological, genomic, and gene network-informed approaches indicate that the candidate genes for stay-green trait may be relevant to minimizing HNT-induced yield and quality losses during grain filling in rice by optimizing source-sink relationships.

scholarly journals Transcriptome profiling analysis of muscle tissue reveals potential candidate genes affecting water holding capacity in Chinese Simmental beef cattle

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lili Du ◽  
Tianpeng Chang ◽  
Bingxing An ◽  
Mang Liang ◽  
Xinghai Duan ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Molecular Mechanism ◽  
Meat Quality ◽  
Relevant Literature ◽  
Transcriptome Profiling ◽  
Water Holding Capacity ◽  
Potential Candidate ◽  
Protein Protein Interaction ◽  
Water Holding

AbstractWater holding capacity (WHC) is an important sensory attribute that greatly influences meat quality. However, the molecular mechanism that regulates the beef WHC remains to be elucidated. In this study, the longissimus dorsi (LD) muscles of 49 Chinese Simmental beef cattle were measured for meat quality traits and subjected to RNA sequencing. WHC had significant correlation with 35 kg water loss (r = − 0.99, p < 0.01) and IMF content (r = 0.31, p < 0.05), but not with SF (r = − 0.20, p = 0.18) and pH (r = 0.11, p = 0.44). Eight individuals with the highest WHC (H-WHC) and the lowest WHC (L-WHC) were selected for transcriptome analysis. A total of 865 genes were identified as differentially expressed genes (DEGs) between two groups, of which 633 genes were up-regulated and 232 genes were down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment revealed that DEGs were significantly enriched in 15 GO terms and 96 pathways. Additionally, based on protein–protein interaction (PPI) network, animal QTL database (QTLdb), and relevant literature, the study not only confirmed seven genes (HSPA12A, HSPA13, PPARγ, MYL2, MYPN, TPI, and ATP2A1) influenced WHC in accordance with previous studies, but also identified ATP2B4, ACTN1, ITGAV, TGFBR1, THBS1, and TEK as the most promising novel candidate genes affecting the WHC. These findings could offer important insight for exploring the molecular mechanism underlying the WHC trait and facilitate the improvement of beef quality.

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