scholarly journals Fine-Mapping of Sorghum Stay-Green QTL on Chromosome10 Revealed Genes Associated with Delayed Senescence

Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1026 ◽  
Author(s):  
K. N. S. Usha Kiranmayee ◽  
C. Tom Hash ◽  
S. Sivasubramani ◽  
P. Ramu ◽  
Bhanu Prakash Amindala ◽  
...  
Keyword(s):  
Drought Tolerance ◽  
Fine Mapping ◽  
Mapping Population ◽  
Single Gene ◽  
Genotyping By Sequencing ◽  
Introgression Line ◽  
Genomic Region ◽  
Stay Green ◽  
Delayed Senescence ◽  
Genomic Regions

This study was conducted to dissect the genetic basis and to explore the candidate genes underlying one of the important genomic regions on an SBI-10 long arm (L), governing the complex stay-green trait contributing to post-flowering drought-tolerance in sorghum. A fine-mapping population was developed from an introgression line cross—RSG04008-6 (stay-green) × J2614-11 (moderately senescent). The fine-mapping population with 1894 F2 was genotyped with eight SSRs and a set of 152 recombinants was identified, advanced to the F4 generation, field evaluated with three replications over 2 seasons, and genotyped with the GBS approach. A high-resolution linkage map was developed for SBI-10L using 260 genotyping by sequencing—Single Nucleotide Polymorphism (GBS–SNPs). Using the best linear unpredicted means (BLUPs) of the percent green leaf area (%GL) traits and the GBS-based SNPs, we identified seven quantitative trait loci (QTL) clusters and single gene, mostly involved in drought-tolerance, for each QTL cluster, viz., AP2/ERF transcription factor family (Sobic.010G202700), NBS-LRR protein (Sobic.010G205600), ankyrin-repeat protein (Sobic.010G205800), senescence-associated protein (Sobic.010G270300), WD40 (Sobic.010G205900), CPK1 adapter protein (Sobic.010G264400), LEA2 protein (Sobic.010G259200) and an expressed protein (Sobic.010G201100). The target genomic region was thus delimited from 15 Mb to 8 genes co-localized with QTL clusters, and validated using quantitative real-time (qRT)–PCR.

scholarly journals Fine mapping of a Phytophthora -resistance locus RpsGZ in soybean using genotyping-by-sequencing

2020 ◽  
Author(s):  
Bingzhi Jiang ◽  
Yanbo Cheng ◽  
Zhandong Cai ◽  
Mu Li ◽  
Ze Jiang ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Genetic Linkage Map ◽  
Average Distance ◽  
Recombinant Inbred Lines ◽  
Genotyping By Sequencing ◽  
Genomic Region ◽  
Phytophthora Sojae ◽  
Resistance Locus ◽  
Phytophthora Root Rot ◽  
Phytophthora Resistance

Abstract Background: Phytophthora root rot (PRR) caused by Phytophthora sojae ( P. sojae ), is one of the most serious limitation to soybean-production in the world. Identification of resistant gene(s) and incorporating them into elite varieties are an effective way for breeding to prevent soybean from being harmed by this disease. A valuable mapping population of 228 F 8:11 recombinant inbred lines (RILs) derived from a cross of resistant cultivar Guizao1 and susceptible cultivar BRSMG68 and a high-density genetic linkage map with an average distance of 0.81 centimorgan (cM) between adjacent bin markers in this population were used to map and explore the candidate gene(s).Results: In this study, the PRR resistance in Guizao1 was controlled by a single Mendelian locus, and was fine mapped to a 367.371-kb genomic region on chromosome 3 that harbours 19 genes, including 7 disease resistance (R)-like genes in the reference Willliams 82 genome. Quantitative real-time PCR assays of possible candidate genes revealed that Glyma.03g05300 was likely involved in PRR resistance.Conclusions: These findings of fine mapping of a novel Rps locus will serve as a basis for cloning, transferring of resistant genes and breeding of P. sojae resistant soybean cultivars through marker-assisted selection.

scholarly journals Application of Genomics Approaches for the Improvement in Ascochyta Blight Resistance in Chickpea

Agronomy ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1937
Author(s):  
Shimna Sudheesh ◽  
Hossein V. Kahrood ◽  
Shivraj Braich ◽  
Nicole Dron ◽  
Kristy Hobson ◽  
...  
Keyword(s):  
Plant Breeding ◽  
Ascochyta Blight ◽  
Genotyping By Sequencing ◽  
Genomic Region ◽  
Sequencing Technologies ◽  
Genome Complexity ◽  
Genomic Tools ◽  
Field Phenotyping ◽  
Genome Complexity Reduction ◽  
Genomic Regions

Advancements in high-throughput genotyping and sequencing technologies are enabling the development of a vast range of genomic tools and resources for a new revolution in plant breeding. Several genotyping-by-sequencing (GBS) methods including capture-based, genome complexity reduction and sequencing of cDNA (GBS-t) are available for application in trait dissection, association mapping, and genomic selection (GS) in crop plants. The aims of this study were to identify genomic regions conferring resistance to Ascochyta blight (AB) introgressed from the wild Cicer echinospernum into the domesticated C. arietinum, through a conventional recombinant inbred population genotyped using a variety of GBS methods. Evaluation of GBS methods revealed that capture-based approaches are robust and reproducible while GBS-t is rapid and flexible. A genetic linkage map consisting of 5886 polymorphic loci spanning 717.26 cM was generated. Using field phenotyping data from two years, a single genomic region on LG4 was identified with quantitative trait loci (QTL) mapping. Both GBS methods reported in this study are well suited for applications in genomics assisted plant breeding. Linked markers for AB resistance, identified in the current study, provide an important resource for the deployment into chickpea breeding programs for marker-assisted selection (MAS).

scholarly journals Identifying Meta-QTLs for Stay-Green in Sorghum

2021 ◽  
Author(s):  
Ahmed Aquib ◽  
Shadma Nafis
Keyword(s):  
Quantitative Trait Loci ◽  
Drought Tolerance ◽  
Qtl Mapping ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Strong Association ◽  
Consensus Map ◽  
Climatic Response ◽  
Stay Green ◽  
Genomic Regions

To develop resilient crops it is necessary to understand the underlying genetics of climatic response. A strong association between stay-green and post-flowering drought tolerance in Sorghum has been established. Being a complex quantitative trait, Quantitative Trait Loci (QTL) mapping experiments of stay-green in Sorghum have been frequently performed. The objective of the current study was to find consensus genomic regions that control stay-green by integrating the QTLs mapped in previous studies. Meta-QTL analysis was performed to summarize 115 QTLs projected on the consensus map. The analysis generated 32 Meta-QTL regions within which candidate gene (CG) identification was undertaken. 7 candidate genes were identified using the markers tightly linked to the Meta-QTLs. The results from this study will facilitate future attempts aiming to improve and understand drought tolerance in Sorghum.

scholarly journals Genome-wide association study and Genomic Prediction of spot blotch disease in wheat (Triticum aestivum L.) using genotyping by sequencing

2020 ◽  
Author(s):  
Vipin Tomar ◽  
Ravi P Singh ◽  
Jesse Poland ◽  
Daljit Singh ◽  
Arun K Joshi ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Genomic Prediction ◽  
Prediction Accuracy ◽  
Genome Wide Association Study ◽  
Genotyping By Sequencing ◽  
Spot Blotch ◽  
Genomic Region ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Genomic Regions

Abstract Background Spot blotch caused by Bipolaris sorokiniana is a major constraint in wheat production in tropics and subtropics. There is limited information available on GWAS and study on genomic prediction is completely lacking. To reveal the genetic markers associated with disease resistance, we performed a genome-wide association study (GWAS) for spot blotch disease in 141 spring wheat lines. Results Based on the testing under natural infection in three years at hot spots location in Pusa, India and Jamalpur, Bangladesh, the genotypes showed significant genetic variation for disease severity. Using Genotyping-by-Sequencing (GBS) based 18637 polymorphic SNP markers and phenotyping from diverse environments, we identified 23 genomic regions across the genome ( p < 0.001) on 14 chromosomes associated with disease scores. Consistent with the previous reports, a most stable genomic region on chromosome 2B, 5B and 7D were detected across the environments. The new genomic region on chromosome 3D was also identified. We performed functional annotation with wheat genome assembly annotation (IWGSC Ref Seq v1.0) and identified NBS-LRR and 35 other plant defense-related protein families across multiple chromosome regions. Using a five-fold cross-validation scheme, we observed moderate prediction accuracy for 3 of 4 environments indicated that our model was able to successfully capture the quantitative variation underlying the SB variation in our population. Conclusions The GWAS based on the phenotypic data from PUSA India and BARI Bangladesh resulted in a total of 23 genomic regions on 14 chromosomes. The new genomic region appeared on chromosome 3D associated with Zinc finger protein that play important role in plant disease resistance. The genomic prediction model for spot blotch disease resistance in wheat was tested and obtained moderate prediction accuracy.

scholarly journals A Novel Stay-Green Mutant of Rice with Delayed Leaf Senescence and Better Harvest Index Confers Drought Tolerance

Plants ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 375 ◽  
Author(s):  
M. K. Ramkumar ◽  
S. Senthil Kumar ◽  
Kishor Gaikwad ◽  
Rakesh Pandey ◽  
Viswanathan Chinnusamy ◽  
...  
Keyword(s):  
Drought Tolerance ◽  
Harvest Index ◽  
Agronomic Traits ◽  
Transcript Abundance ◽  
Stay Green ◽  
Delayed Senescence ◽  
Synonymous Mutations ◽  
Index Sequence ◽  
Senescence Associated Genes ◽  
Over Time

Three Ethyl methansulphonate (EMS)-induced stay-green mutants (SGM-1, SGM-2 and SGM-3) and their wild-type (WT), were tested for their Stay-Green (SG) and drought tolerance nature as the relation between these two attributes is not yet established in rice. In the dark induced senescence assay, SGM-3 showed delayed senescence while SGM-1 and SGM-2 showed complete lack of senescence. Mutants showed stable transcript abundance over time, for 15 candidate genes (CGs) associated with senescence, compared to the WT. SGM-3 however showed moderately increasing transcript abundance over time for ATG6a, ATG4a, NYC1, NOL and NYC3. Only SGM-3 performed better than the WT for yield and harvest index under well irrigated as well as drought conditions, though all the mutants showed better performance for other agronomic traits under both the conditions and ascorbate peroxidase activity under drought. Thus, SG trait showed positive correlation with drought tolerance though only SGM-3 could convert this into higher harvest index. Sequence analysis of 80 senescence-associated genes including the 15 CGs showed non-synonymous mutations in four and six genes in SGM-1 and SGM-2 respectively, while no SNPs were found in SGM-3. Analysis of the earlier reported Quantitative Trait Loci (QTL) regions in SGM-3 revealed negligible variations from WT, suggesting it to be a novel SG mutant.

scholarly journals Probable omnigenic effect and evolutionary insights of aerobic adaptation allele OsNCED2T on qDTY12.1 effecting grain yield under reproductive stage drought stress in rice

2021 ◽  
Author(s):  
C Parameswaran ◽  
B Cayalvizhi ◽  
S Sanghamitra ◽  
N Anandan ◽  
K Jawahar Lal ◽  
...  
Keyword(s):  
Drought Stress ◽  
Drought Tolerance ◽  
Grain Yield ◽  
Genomic Region ◽  
Favorable Allele ◽  
Severe Drought ◽  
Evolutionary Analysis ◽  
Synonymous Snps ◽  
Drought Tolerant ◽  
Genomic Regions

AbstractYield associated quantitative trait loci (qDTY) under drought stress provides significant advantage for grain yield in rice. The major, stable qDTY12.1 was identified in a mapping population developed from upland cultivars Vandana and Way Rarem. Further, introgression line comprising of qDTY12.1 genomic region was characterized to have multiple genes (NAM, DECUSSATE) regulating the drought tolerance under severe drought stress substantiated through recently proposed omnigenic model for complex traits. Recently, plastid localized NCED2T allele present within the qDTY12.1 genomic region was characterized for conferring aerobic adaptation in lowland varieties. Since, NCED2T is evolutionary fixed in upland cultivars and Vandana was found to have the favorable allele of NCED2T, we hypothesized that this favorable allele might confer omnigenic effect on qDTY12.1 genes. Our evolutionary analysis using non synonymous SNPs present in genes namely NCED, NAM, and DECUSSATE and qDTY12.1 genomic regions showed specific grouping of Vandana with upland cultivars only for NCED gene and its adjoining genomic regions. However, non synonymous SNPs in NAM and DECUSSATE genes and its adjoining genomic regions of drought tolerant varieties were closely related and grouped together in the phylogenetic analysis. Moreover, ecotype specific differentiation and greater nucleotide difference with wild relatives was also observed for DECUSSATE gene in rice. This finding indicates differential evolution of qDTY12.1 regions for upland and drought tolerance and omnigenic effect of NCED2T gene in qDTY12.1. Further, we propose a breeding model for enhancing genetic gain for yield under severe drought stress by incorporation of NCEDT, qDTY12.1 and other drought tolerant QTLs for membrane stability in rice.

scholarly journals 3D reconstruction of genomic regions from sparse interaction data

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Julen Mendieta-Esteban ◽  
Marco Di Stefano ◽  
David Castillo ◽  
Irene Farabella ◽  
Marc A Marti-Renom
Keyword(s):  
3D Models ◽  
Genomic Region ◽  
Gene Promoters ◽  
Chromosome Conformation ◽  
The Matrix ◽  
Chromatin Structural ◽  
A Cell ◽  
Similar Accuracy ◽  
Genomic Regions ◽  
Interaction Matrices

Abstract Chromosome conformation capture (3C) technologies measure the interaction frequency between pairs of chromatin regions within the nucleus in a cell or a population of cells. Some of these 3C technologies retrieve interactions involving non-contiguous sets of loci, resulting in sparse interaction matrices. One of such 3C technologies is Promoter Capture Hi-C (pcHi-C) that is tailored to probe only interactions involving gene promoters. As such, pcHi-C provides sparse interaction matrices that are suitable to characterize short- and long-range enhancer–promoter interactions. Here, we introduce a new method to reconstruct the chromatin structural (3D) organization from sparse 3C-based datasets such as pcHi-C. Our method allows for data normalization, detection of significant interactions and reconstruction of the full 3D organization of the genomic region despite of the data sparseness. Specifically, it builds, with as low as the 2–3% of the data from the matrix, reliable 3D models of similar accuracy of those based on dense interaction matrices. Furthermore, the method is sensitive enough to detect cell-type-specific 3D organizational features such as the formation of different networks of active gene communities.

scholarly journals Relationship between Yield Components and Partial Resistance to Lecanicillium fungicola in the Button Mushroom, Agaricus bisporus, Assessed by Quantitative Trait Locus Mapping

2012 ◽  
Vol 78 (7) ◽  
pp. 2435-2442 ◽  
Author(s):  
Marie Foulongne-Oriol ◽  
Anne Rodier ◽  
Jean-Michel Savoie
Keyword(s):  
Quantitative Trait ◽  
Wild Strain ◽  
Genomic Region ◽  
Yield Component ◽  
Phenotypic Variance ◽  
Button Mushroom ◽  
Content Type ◽  
Dry Bubble ◽  
Trait Locus ◽  
Genomic Regions

ABSTRACTDry bubble, caused byLecanicillium fungicola, is one of the most detrimental diseases affecting button mushroom cultivation. In a previous study, we demonstrated that breeding for resistance to this pathogen is quite challenging due to its quantitative inheritance. A second-generation hybrid progeny derived from an intervarietal cross between a wild strain and a commercial cultivar was characterized forL. fungicolaresistance under artificial inoculation in three independent experiments. Analysis of quantitative trait loci (QTL) was used to determine the locations, numbers, and effects of genomic regions associated with dry-bubble resistance. Four traits related to resistance were analyzed. Two to four QTL were detected per trait, depending on the experiment. Two genomic regions, on linkage group X (LGX) and LGVIII, were consistently detected in the three experiments. The genomic region on LGX was detected for three of the four variables studied. The total phenotypic variance accounted for by all QTL ranged from 19.3% to 42.1% over all traits in all experiments. For most of the QTL, the favorable allele for resistance came from the wild parent, but for some QTL, the allele that contributed to a higher level of resistance was carried by the cultivar. Comparative mapping with QTL for yield-related traits revealed five colocations between resistance and yield component loci, suggesting that the resistance results from both genetic factors and fitness expression. The consequences for mushroom breeding programs are discussed.

Sign in / Sign up

Export Citation Format

Share Document