scholarly journals Microbiome‐wide association studies reveal correlations between the structure and metabolism of the rhizosphere microbiome and disease resistance in cassava

2020 ◽  
Author(s):  
Lin Zhang ◽  
Jiachao Zhang ◽  
Yunxie Wei ◽  
Wei Hu ◽  
Guoyin Liu ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Association Studies ◽  
Rhizosphere Microbiome ◽  
Structure And Metabolism

scholarly journals Meta-Analysis Reveals Consensus Genomic Regions Associated with Multiple Disease Resistance in Wheat ( Triticum Aestivum L.)

2021 ◽  
Author(s):  
Dinesh Kumar Saini ◽  
Amneek Chahal ◽  
Neeraj Pal ◽  
Puja Srivast ◽  
Pushpendra Kumar Gupta
Keyword(s):  
Disease Resistance ◽  
Physical Map ◽  
Association Studies ◽  
Meta Analysis ◽  
Septoria Tritici Blotch ◽  
Septoria Tritici ◽  
Karnal Bunt ◽  
Genome Wide Association Studies ◽  
Head Blight ◽  
Multiple Disease Resistance

Abstract In wheat, meta-QTLs (MQTLs), and candidate genes (CGs) were identified for multiple disease resistance (MDR). For this purpose, information was collected from 58 studies for mapping QTLs for resistance to one or more of the five diseases. As many as 493 QTLs were available from these studies, which were distributed in five diseases as follows: septoria tritici blotch (STB) 126 QTLs; septoria nodorum blotch (SNB), 103; fusarium head blight (FHB), 184; karnal bunt (KB), 66, and loose smut (LS), 14. Of these 493 QTLs, only 291 QTLs could be projected onto a consensus genetic map, giving 63 MQTLs. The CI of the MQTLs ranged from 0.04 to 15.31 cM with an average of 3.09 cM per MQTL. This is a ~ 4.39 fold reduction from the CI of initial QTLs, which ranged from 0 to 197.6 cM, with a mean of 13.57 cM. Of 63 MQTLs, 60 were anchored to the reference physical map of wheat (the physical interval of these MQTLs ranged from 0.30 to 726.01 Mb with an average of 74.09 Mb). Thirty-eight (38) of these MQTLs were verified using marker-trait associations (MTAs) derived from genome-wide association studies. As many as 874 CGs were also identified which were further investigated for differential expression using data from five transcriptome studies, resulting in 194 differentially expressed genes (DEGs). Among the DEGs, 85 genes had functions previously reported to be associated with disease resistance. These results should prove useful for fine mapping of MDR genes and marker-assisted breeding.

scholarly journals Genome-wide Identification of Powdery Mildew Resistance in Common Bean

2020 ◽  
Author(s):  
Papias Hongera Binagwa ◽  
Sy M. Traore ◽  
Marceline Egnin ◽  
Gregory C. Bernard ◽  
Inocent Ritte ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Common Bean ◽  
Resistance Genes ◽  
Agronomic Traits ◽  
Association Studies ◽  
Significant Snps ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Resistance Protein ◽  
Resistance Protein

Abstract Background: Genome-wide association studies (GWAS) was utilized to detect genetic variations related to the powdery mildew (PM) resistance and several agronomic traits in common bean. However, its application in common bean and the PM interactions to identify genes and their location in the common bean genome has not been fully addressed. Results: Genome-wide association studies (GWAS) through marker-trait association are useful molecular tools for the identification of disease resistance and other agronomic traits. SNP genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to resistance to PM disease in a panel of 206 genotypes grown under field conditions for two consecutive years. Significant SNPs identified on chromosomes 4 and 10 (Pv04 and Pv10) were repeatable, confirming the reliability of the phenotypic data scored from the genotypes grown in two locations within two years. A cluster of resistance genes was revealed on the chromosome 4 of common bean genome among which CNL and TNL like resistance genes were identified. Furthermore, two resistance genes Phavu_010G1320001g and Phavu_010G136800g were also identified on Pv10; further sequence analysis showed that these genes were homologs to the Arabidopsis disease resistance protein (RLM1A-like) and the putative disease resistance protein (At4g11170.1), respectively. Two LRR receptor-like kinases (RLK) were also identified on Pv11 in samples collected in 2018 only. Many genes encoding auxin-responsive protein, TIFY10A protein, growth-regulating factor 5-like, ubiquitin-like protein, cell wall protein RBR3-like protein related to PM resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed and may generate several layers of defense barriers or inducible reactions.Conclusion: Our results provide new insights into common bean and PM interactions, and revealed putative resistance genes as well as their location on common bean genome that could be used for marker-assisted selection, functional genomic study approaches to confirm the role of these putative genes; hence, developing common bean resistance lines to the PM disease.

scholarly journals Genome wide association study reveals plant loci controlling heritability of the rhizosphere microbiome

2020 ◽  
Author(s):  
Siwen Deng ◽  
Daniel Caddell ◽  
Jinliang Yang ◽  
Lindsay Dahlen ◽  
Lorenzo Washington ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Population Level ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Host Genotype ◽  
Rhizosphere Microbiome ◽  
Genome Wide ◽  
Sorghum Genotypes

AbstractHost genetics has recently been shown to be a driver of plant microbiome composition. However, identifying the underlying genetic loci controlling microbial selection remains challenging. Genome wide association studies (GWAS) represent a potentially powerful, unbiased method to identify microbes sensitive to host genotype, and to connect them with the genetic loci that influence their colonization. Here, we conducted a population-level microbiome analysis of the rhizospheres of 200 sorghum genotypes. Using 16S rRNA amplicon sequencing, we identify rhizosphere-associated bacteria exhibiting heritable associations with plant genotype, and identify significant overlap between these lineages and heritable taxa recently identified in maize. Furthermore, we demonstrate that GWAS can identify host loci that correlate with the abundance of specific subsets of the rhizosphere microbiome. Finally, we demonstrate that these results can be used to predict rhizosphere microbiome structure for an independent panel of sorghum genotypes based solely on knowledge of host genotypic information.

scholarly journals Genome-wide Identification of Powdery Mildew Resistance in Common Bean

2020 ◽  
Author(s):  
Papias Hongera Binagwa ◽  
Sy M. Traore ◽  
Marceline Egnin ◽  
Gregory C. Bernard ◽  
Inocent Ritte ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Common Bean ◽  
Resistance Genes ◽  
Agronomic Traits ◽  
Association Studies ◽  
Significant Snps ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Resistance Protein ◽  
Resistance Protein

Abstract Background: Genome-wide association studies (GWAS) have been utilized to detect genetic variations related to the powdery mildew (PM) resistance and several agronomic traits in common bean. However, its application in common bean and the PM interactions to identify genes and their location in the common bean genome has not been fully addressed.Results: Genome-wide association studies (GWAS) through marker-trait association are useful molecular tools for the identification of disease resistance and other agronomic traits. SNP genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to resistance to PM disease in a panel of 211 genotypes grown under field conditions for two consecutive years. Significant SNPs identified on chromosomes Pv04 and Pv10 were repeatable, confirming the reliability of the phenotypic data scored from the genotypes grown in two locations within two years. A cluster of resistance genes was revealed on the Pv04 of common bean genome among which CNL and TNL like resistance genes were identified. Furthermore, two resistance genes Phavu_010G1320001g and Phavu_010G136800g were also identified on Pv10; further sequence analysis showed that these genes were homologs to the Arabidopsis disease resistance protein (RLM1A-like) and the putative disease resistance protein (At4g11170.1), respectively. Two LRR receptor-like kinases (RLK) were also identified on Pv11 in samples collected in 2018 only. Many genes encoding auxin-responsive protein, TIFY10A protein, growth-regulating factor 5-like, ubiquitin-like protein, cell wall protein RBR3-like protein related to PM resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed and may generate several layers of defense barriers or inducible reactions.Conclusion: Our results provide new insights into common bean and PM interactions, and revealed putative resistance genes as well as their location on common bean genome that could be used for marker-assisted selection, functional genomic study approaches to confirm the role of these putative genes; hence, developing common bean resistance lines to the PM disease.

scholarly journals Genome wide association study reveals plant loci controlling heritability of the rhizosphere microbiome

2021 ◽  
Author(s):  
Siwen Deng ◽  
Daniel F. Caddell ◽  
Gen Xu ◽  
Lindsay Dahlen ◽  
Lorenzo Washington ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Population Level ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Host Genotype ◽  
Rhizosphere Microbiome ◽  
Genome Wide ◽  
Sorghum Genotypes

AbstractHost genetics has recently been shown to be a driver of plant microbiome composition. However, identifying the underlying genetic loci controlling microbial selection remains challenging. Genome-wide association studies (GWAS) represent a potentially powerful, unbiased method to identify microbes sensitive to the host genotype and to connect them with the genetic loci that influence their colonization. Here, we conducted a population-level microbiome analysis of the rhizospheres of 200 sorghum genotypes. Using 16S rRNA amplicon sequencing, we identify rhizosphere-associated bacteria exhibiting heritable associations with plant genotype, and identify significant overlap between these lineages and heritable taxa recently identified in maize. Furthermore, we demonstrate that GWAS can identify host loci that correlate with the abundance of specific subsets of the rhizosphere microbiome. Finally, we demonstrate that these results can be used to predict rhizosphere microbiome structure for an independent panel of sorghum genotypes based solely on knowledge of host genotypic information.

scholarly journals Characterization of Disease Resistance Loci in the USDA Soybean Germplasm Collection Using Genome-Wide Association Studies

2016 ◽  
Vol 106 (10) ◽  
pp. 1139-1151 ◽  
Author(s):  
Hao-Xun Chang ◽  
Alexander E. Lipka ◽  
Leslie L. Domier ◽  
Glen L. Hartman
Keyword(s):  
Disease Resistance ◽  
Association Studies ◽  
Germplasm Collection ◽  
The United States ◽  
Genome Wide Association ◽  
Bacterial Disease ◽  
United States Department ◽  
Genome Wide Association Studies ◽  
Soybean Germplasm ◽  
Genome Wide

Genetic resistance is a key strategy for disease management in soybean. Over the last 50 years, soybean germplasm has been phenotyped for resistance to many pathogens, resulting in the development of disease-resistant elite breeding lines and commercial cultivars. While biparental linkage mapping has been used to identify disease resistance loci, genome-wide association studies (GWAS) using high-density and high-quality markers such as single nucleotide polymorphisms (SNPs) has become a powerful tool to associate molecular markers and phenotypes. The objective of our study was to provide a comprehensive understanding of disease resistance in the United States Department of Agriculture Agricultural Research Service Soybean Germplasm Collection by using phenotypic data in the public Germplasm Resources Information Network and public SNP data (SoySNP50K). We identified SNPs significantly associated with disease ratings from one bacterial disease, five fungal diseases, two diseases caused by nematodes, and three viral diseases. We show that leucine-rich repeat (LRR) receptor-like kinases and nucleotide-binding site-LRR candidate resistance genes were enriched within the linkage disequilibrium regions of the significant SNPs. We review and present a global view of soybean resistance loci against multiple diseases and discuss the power and the challenges of using GWAS to discover disease resistance in soybean.

scholarly journals Genomic selection in salmonids: new discoveries and future perspectives

2021 ◽  
Author(s):  
Edo D’Agaro ◽  
Andea Favaro ◽  
Stefano Matiussi ◽  
Pier Paolo Gibertoni ◽  
Stefano Esposito
Keyword(s):  
Disease Resistance ◽  
Genomic Selection ◽  
Association Studies ◽  
Single Step ◽  
Molecular Techniques ◽  
Breeding Systems ◽  
Breeding Value ◽  
Genome Wide Association Studies ◽  
Entire Genome ◽  
Breeding Programmes

AbstractOver the past 20 years, the introduction of new molecular techniques has given a new impetus to genetic and genomic studies of fishes. The main traits selected in the aquaculture sector conform to the polygenic model, and, thus far, effective breeding programmes based on genome-wide association studies (GWAS) and marker-assisted selection (MAS) have been applied to simple traits (e.g. disease resistance and sexual maturation of salmonids) and known Quantitative Trait Loci (QTLs). Genomic selection uses the genomic relationships between candidate loci and SNPs distributed over the entire genome and in tight linkage disequilibrium (LD) with genes that encode the traits. SNP (low and high density) arrays are used for genotyping thousands of genetic markers (single nucleotide polymorphisms, SNPs). The genomic expected breeding value (GEBV) of selection candidates is usually calculated by means of the GBLUP or ssGBLUP (single step) methods. In recent years, in several aquaculture breeding programmes, the genomic selection method has been applied to different fish and crustacean species. While routine implementation of genomic selection is now largely carried out in Atlantic salmon (Salmo salar) and rainbow trout (Oncorhynchus mykiss), it is expected that, in the near future, this method will progressively spread to other fish species. However, genomic selection is an expensive method, so it will be relevant mostly for traits of high economic value. In several studies (using different salmonid species), the accuracy of the GEBVs varied from 0.10 to 0.80 for different traits (e.g. growth rate and disease resistance) compared to traditional breeding methods based on geneology. Genomic selection applied to aquaculture species has the potential to improve selection programmes substantially and to change ongoing fish breeding systems. In the long term, the ability to use low-pass genome sequencing methods, low-cost genotyping and novel phenotyping techniques will allow genomic selection to be applied to thousands of animals directly at the farm level.

scholarly journals New QTLs for Spot Blotch Disease Resistance in Wheat (Triticum aestivum L.) Using Genome-Wide Association Mapping

2021 ◽  
Vol 11 ◽  
Author(s):  
Vipin Tomar ◽  
Daljit Singh ◽  
Guriqbal Singh Dhillon ◽  
Ravi Prakash Singh ◽  
Jesse Poland ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Association Studies ◽  
Bipolaris Sorokiniana ◽  
Spot Blotch ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Protein Families ◽  
Wheat Production ◽  
Genome Wide ◽  
Diverse Field

Spot blotch disease caused by Bipolaris sorokiniana is a major constraint for wheat production in tropics and subtropics. The introgression of spot blotch resistance alleles to the disease susceptible lines is critical to securing the wheat production in these regions. Although genome-wide association studies (GWASs) for spot blotch were attempted earlier, the present study focused on identifying new quantitative trait loci (QTLs) for spot blotch under natural disease pressure in diverse field conditions. A total of 139 advanced spring wheat lines were evaluated in three environments (three years and two locations) in India and Bangladesh. The GWAS using 14,063 polymorphic genotyping-by-sequencing (GBS) markers identified eight QTLs associated with spot blotch disease resistance belonging to eight chromosomes across the wheat genome. Here, we report the identified marker–trait associations (MTAs), along with the allele effects associated with the disease. The functional annotation of the significant markers identified NBS-LRR, MADS-box transcription factor, and 34 other plant-related protein families across multiple chromosomal regions. The results indicate four promising new QTLs on chromosomes 1A (497.2 Mb), 1D (89.84 Mb), 2B (421.92 Mb), and 6D (6.84 Mb) associated with several disease resistance protein families. These results provide insights into new genomic regions associated with spot blotch disease, and with additional validation, could be utilized in disease resistance breeding efforts in wheat development.

scholarly journals Genome-wide Identification of Powdery Mildew Resistance in Common Bean

2020 ◽  
Author(s):  
Papias Hongera Binagwa ◽  
Sy M. Traore ◽  
Marceline Egnin ◽  
Gregory C. Bernard ◽  
Inocent Ritte ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Common Bean ◽  
Resistance Genes ◽  
Agronomic Traits ◽  
Association Studies ◽  
Significant Snps ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Resistance Protein ◽  
Resistance Protein

Abstract Background Genome-wide association studies (GWAS) was utilized to detect genetic variations related to the powdery mildew (PM) resistance and several agronomic traits in common bean. However, its application in common bean and the PM interactions to identify genes and their location in the common bean genome has not been fully addressed. Results Genome-wide association studies (GWAS) through marker-trait association are useful molecular tools for identification of disease resistance and other agronomic traits. SNP genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to resistance to PM disease in a panel of 206 genotypes grown under field conditions for two consecutive years. Significant SNPs identified on chromosome 4 and 10 were repeatable, confirming the reliability of the phenotypic data scored from the genotypes grown in two locations within two years. A cluster of resistance genes was revealed on the chromosome 4 of common bean genome among which CNL and TNL like resistance genes were identified. Furthermore, two resistance genes Phavu_010G1320001g and Phavu_010G136800g were also identified on pv10; further sequence analysis showed that these genes were homologs to the Arabidopsis disease resistance protein (RLM1A-like) and the putative disease resistance protein (At4g11170.1), respectively. Two LRR receptor-like kinases (RLK) were also identified on pv11 in samples collected in 2018 only. Many genes encoding auxin-responsive protein, TIFY10A protein, growth-regulating factor 5-like, ubiquitin-like protein, cell wall protein RBR3-like protein related to PM resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed and may generate several layers of defense barriers or inducible reactions. Conclusion Our results provide new insights into common bean and PM interactions, and revealed putative resistance genes as well as their location on common bean genome that could be used for marker-assisted selection, functional genomic study approaches to confirm the role of these putative genes; hence, developing common bean resistance lines to the PM disease.

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