Genome-Wide Association Studies (GWAS) for Traits Related to Fodder Quality and Biofuel in Sorghum: Progress and Prospects

2021 ◽  
Vol 28 ◽  
Author(s):  
Vinutha Kanuganahalli Somegowda ◽  
Laavanya Rayaprolu ◽  
Abhishek Rathore ◽  
Santosh Pandurang Deshpande ◽  
Rajeev Gupta
Keyword(s):  
Genetic Architecture ◽  
Association Studies ◽  
Current Status ◽  
Genome Wide Association Studies ◽  
Potential Candidate ◽  
Crop Species ◽  
Fodder Quality ◽  
Genome Wide ◽  
Genomic Regions ◽  
Model Crop

: The main focus of this review is to discuss the current status of the use of GWAS for fodder quality and biofuel owing to its similarity of traits. Sorghum is a potential multipurpose crop, popularly cultivated for various uses as food, feed fodder, and biomass for ethanol. Production of a huge quantity of biomass and genetic variation for complex sugars are the main motivation not only to use sorghum as fodder for livestock nutritionists but also a potential candidate for biofuel generation. Few studies have been reported on the knowledge transfer that can be used from the development of biofuel technologies to complement improved fodder quality and vice versa. With recent advances in genotyping technologies, GWAS became one of the primary tools used to identify the genes/genomic regions associated with the phenotype. These modern tools and technologies accelerate the genomic assisted breeding process to enhance the rate of genetic gains. Hence, this mini-review focuses on GWAS studies on genetic architecture and dissection of traits underpinning fodder quality and biofuel traits and their limited comparison with other related model crop species.

scholarly journals Genetic Mapping Reveals Complex Architecture and Candidate Genes Involved in Common Bean Response to Meloidogyne Incognita Infection

2021 ◽  
Author(s):  
Willian Giordani ◽  
Henrique Castro Gama ◽  
Alisson Fernando Chiorato ◽  
João Paulo Rodrigues Marques ◽  
Luis Eduardo Aranha Camargo ◽  
...  
Keyword(s):  
Common Bean ◽  
Candidate Genes ◽  
Resistance Genes ◽  
Meloidogyne Incognita ◽  
Genetic Architecture ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Crop Species ◽  
Egg Masses ◽  
Genomic Regions

Abstract Root-knot nematodes (RKN), particularly Meloidogyne incognita, are among the most damaging and prevalent agricultural pathogens due to their ability to infect roots of almost all crop species, including common bean. The best strategy for their control is through the use of resistant cultivars. However, laborious phenotyping procedures make it difficult to assess nematode resistance in breeding programs. For common bean, this task is especially challenging since little has been done to discover resistance genes or find markers to assist selection. In this study, we performed genome-wide association studies and QTL mapping to explore the genetic architecture and genomic regions underlying the resistance to M. incognita and to identify candidate resistance genes. Phenotypic data were collected by a high-throughput assay, and the number of egg masses and root-galling index were evaluated 30 days after inoculation. Complex genetic architecture and independent genomic regions were associated with each trait according to the Fixed and random model Circulating Probability Unification. SNPs located on chromosomes Pv06, Pv07, Pv08 and Pv11 were associated with the number of egg masses, and on Pv01, Pv02, Pv05 and Pv10 with root-galling. A total of 215 candidate genes were identified, including 14 resistance gene analogs and five differentially expressed in a previous RNA-seq analysis. The histochemical analysis indicated that the reactive oxygen species might play a role in the resistance response. Our findings open new perspectives to improve selection efficiency for RKN resistance in common bean, and the candidate genes are valuable targets for functional investigation and gene editing approaches.

scholarly journals Investigating the genetic architecture of disease resilience in pigs by genome-wide association studies of complete blood count traits collected from a natural disease challenge model

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xuechun Bai ◽  
Tianfu Yang ◽  
Austin M. Putz ◽  
Zhiquan Wang ◽  
Changxi Li ◽  
...  
Keyword(s):  
Blood Cell ◽  
Genetic Architecture ◽  
Blood Count ◽  
Complete Blood Count ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Before And After ◽  
Genomic Regions

Abstract Background Genetic improvement for disease resilience is anticipated to be a practical method to improve efficiency and profitability of the pig industry, as resilient pigs maintain a relatively undepressed level of performance in the face of infection. However, multiple biological functions are known to be involved in disease resilience and this complexity means that the genetic architecture of disease resilience remains largely unknown. Here, we conducted genome-wide association studies (GWAS) of 465,910 autosomal SNPs for complete blood count (CBC) traits that are important in an animal’s disease response. The aim was to identify the genetic control of disease resilience. Results Univariate and multivariate single-step GWAS were performed on 15 CBC traits measured from the blood samples of 2743 crossbred (Landrace × Yorkshire) barrows drawn at 2-weeks before, and at 2 and 6-weeks after exposure to a polymicrobial infectious challenge. Overall, at a genome-wise false discovery rate of 0.05, five genomic regions located on Sus scrofa chromosome (SSC) 2, SSC4, SSC9, SSC10, and SSC12, were significantly associated with white blood cell traits in response to the polymicrobial challenge, and nine genomic regions on multiple chromosomes (SSC1, SSC4, SSC5, SSC6, SSC8, SSC9, SSC11, SSC12, SSC17) were significantly associated with red blood cell and platelet traits collected before and after exposure to the challenge. By functional enrichment analyses using Ingenuity Pathway Analysis (IPA) and literature review of previous CBC studies, candidate genes located nearby significant single-nucleotide polymorphisms were found to be involved in immune response, hematopoiesis, red blood cell morphology, and platelet aggregation. Conclusions This study helps to improve our understanding of the genetic basis of CBC traits collected before and after exposure to a polymicrobial infectious challenge and provides a step forward to improve disease resilience.

scholarly journals Investigating the genetic architecture of disease resilience in pigs by genome-wide association studies of complete blood count traits collected from a natural disease challenge model

2020 ◽  
Author(s):  
Xuechun Bai ◽  
Tianfu Yang ◽  
Austin Putz ◽  
Zhiquan Wang ◽  
Changxi Li ◽  
...  
Keyword(s):  
Blood Cell ◽  
Genetic Architecture ◽  
Blood Count ◽  
Complete Blood Count ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Before And After ◽  
Genomic Regions

Abstract BackgroundGenetic improvement for disease resilience is anticipated to be a practical method to improve efficiency and profitability of the pig industry, as resilient pigs maintain a relatively undepressed level of performance in the face of infection. However, multiple biological functions are known to be involved in disease resilience and this complexity means that the genetic architecture of disease resilience remains largely unknown. Here, we conducted genome-wide association studies (GWAS) of 465,910 autosomal SNPs for complete blood count (CBC) traits that are important in an animal’s disease response. The aim was to identify the genetic control of disease resilience.ResultsUnivariate and multivariate single-step GWAS were performed on fifteen CBC traits measured from the blood samples of 2743 crossbred (Landrace × Yorkshire) barrows drawn at 2-weeks before, and at 2 and 6-weeks after exposure to a polymicrobial infectious challenge. Overall, at a genome-wise false discovery rate of 0.05, five genomic regions located on Sus scrofa chromosome (SSC) 2, SSC4, SSC9, SSC10, and SSC12, were significantly associated with white blood cell traits in response to the polymicrobial challenge, and nine genomic regions on multiple chromosomes (SSC1, SSC4, SSC5, SSC6, SSC8, SSC9, SSC11, SSC12, SSC17) were significantly associated with red blood cell and platelet traits collected before and after exposure to the challenge. By functional enrichment analyses using Ingenuity Pathway Analysis (IPA) and literature review of previous CBC studies, candidate genes located nearby significant single-nucleotide polymorphisms were found to be involved in immune response, hematopoiesis, red blood cell morphology, and platelet aggregation.ConclusionsThis study helps to improve our understanding of the genetic basis of CBC traits collected before and after exposure to a polymicrobial infectious challenge and provides a step forward to improve disease resilience.

scholarly journals A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shenping Zhou ◽  
Rongrong Ding ◽  
Fanming Meng ◽  
Xingwang Wang ◽  
Zhanwei Zhuang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Growth And Development ◽  
Genetic Architecture ◽  
Association Studies ◽  
Meta Analysis ◽  
Average Daily Gain ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Daily Gain

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.

scholarly journals Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture

2016 ◽  
Vol 283 (1835) ◽  
pp. 20160569 ◽  
Author(s):  
M. E. Goddard ◽  
K. E. Kemper ◽  
I. M. MacLeod ◽  
A. J. Chamberlain ◽  
B. J. Hayes
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Quantitative Traits ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Crop Breeding ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Phenotype Identification

Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement.

scholarly journals Genome-wide association studies: assessing trait characteristics in model and crop plants

2021 ◽  
Author(s):  
Saleh Alseekh ◽  
Dimitrina Kostova ◽  
Mustafa Bulut ◽  
Alisdair R. Fernie
Keyword(s):  
Biotic Resistance ◽  
Association Studies ◽  
Critical Evaluation ◽  
Genome Wide Association ◽  
Functional Study ◽  
Genome Wide Association Studies ◽  
Future Perspectives ◽  
Crop Species ◽  
Genome Wide ◽  
Single Feature

AbstractGWAS involves testing genetic variants across the genomes of many individuals of a population to identify genotype–phenotype association. It was initially developed and has proven highly successful in human disease genetics. In plants genome-wide association studies (GWAS) initially focused on single feature polymorphism and recombination and linkage disequilibrium but has now been embraced by a plethora of different disciplines with several thousand studies being published in model and crop species within the last decade or so. Here we will provide a comprehensive review of these studies providing cases studies on biotic resistance, abiotic tolerance, yield associated traits, and metabolic composition. We also detail current strategies of candidate gene validation as well as the functional study of haplotypes. Furthermore, we provide a critical evaluation of the GWAS strategy and its alternatives as well as future perspectives that are emerging with the emergence of pan-genomic datasets.

scholarly journals Better estimation of SNP heritability from summary statistics provides a new understanding of the genetic architecture of complex traits

2018 ◽  
Author(s):  
Doug Speed ◽  
David J Balding
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Large Scale ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Confounding Bias ◽  
Conserved Regions ◽  
Genome Wide ◽  
Variation Explained

LD Score Regression (LDSC) has been widely applied to the results of genome-wide association studies. However, its estimates of SNP heritability are derived from an unrealistic model in which each SNP is expected to contribute equal heritability. As a consequence, LDSC tends to over-estimate confounding bias, under-estimate the total phenotypic variation explained by SNPs, and provide misleading estimates of the heritability enrichment of SNP categories. Therefore, we present SumHer, software for estimating SNP heritability from summary statistics using more realistic heritability models. After demonstrating its superiority over LDSC, we apply SumHer to the results of 24 large-scale association studies (average sample size 121 000). First we show that these studies have tended to substantially over-correct for confounding, and as a result the number of genome-wide significant loci has under-reported by about 20%. Next we estimate enrichment for 24 categories of SNPs defined by functional annotations. A previous study using LDSC reported that conserved regions were 13-fold enriched, and found a further twelve categories with above 2-fold enrichment. By contrast, our analysis using SumHer finds that conserved regions are only 1.6-fold (SD 0.06) enriched, and that no category has enrichment above 1.7-fold. SumHer provides an improved understanding of the genetic architecture of complex traits, which enables more efficient analysis of future genetic data.

scholarly journals Genetics of COPD

2020 ◽  
Vol 82 (1) ◽  
pp. 413-431 ◽  
Author(s):  
Edwin K. Silverman
Keyword(s):  
Association Studies ◽  
Chronic Obstructive ◽  
Genome Wide Association Studies ◽  
Obstructive Pulmonary Disease ◽  
Functional Variants ◽  
Genome Wide ◽  
Antitrypsin Deficiency ◽  
Alpha 1 Antitrypsin Deficiency ◽  
Alpha 1 Antitrypsin ◽  
Genomic Regions

Although chronic obstructive pulmonary disease (COPD) risk is strongly influenced by cigarette smoking, genetic factors are also important determinants of COPD. In addition to Mendelian syndromes such as alpha-1 antitrypsin deficiency, many genomic regions that influence COPD susceptibility have been identified in genome-wide association studies. Similarly, multiple genomic regions associated with COPD-related phenotypes, such as quantitative emphysema measures, have been found. Identifying the functional variants and key genes within these association regions remains a major challenge. However, newly identified COPD susceptibility genes are already providing novel insights into COPD pathogenesis. Network-based approaches that leverage these genetic discoveries have the potential to assist in decoding the complex genetic architecture of COPD.

scholarly journals Genetic Analysis of Stem Diameter and Water Contents To Improve Sorghum Bioenergy Efficiency

2020 ◽  
Vol 10 (11) ◽  
pp. 3991-4000
Author(s):  
Wenqian Kong ◽  
Huizhe Jin ◽  
Valorie H. Goff ◽  
Susan A. Auckland ◽  
Lisa K. Rainville ◽  
...  
Keyword(s):  
Water Content ◽  
Plant Traits ◽  
Association Studies ◽  
Duplication Event ◽  
Stem Diameter ◽  
Biofuel Production ◽  
Genome Wide Association Studies ◽  
Energy Demands ◽  
Genome Wide ◽  
Genomic Regions

Biofuel made from agricultural products has the potential in contribute to a stable supply of fuel for growing energy demands. Some salient plant traits, such as stem diameter and water content, and their relationship to other important biomass-related traits are so far poorly understood. Here, we performed QTL mapping for three stem diameter and two water content traits in a S. bicolor BTx623 x IS3620c recombinant inbred line population of 399 genotypes, and validated the genomic regions identified using genome-wide association studies (GWAS) in a diversity panel of 354 accessions. The discovery of both co-localized and non-overlapping loci affecting stem diameter traits suggests that stem widths at different heights share some common genetic control, but also have some distinct genetic influences. Co-localizations of stem diameter and water content traits with other biomass traits including plant height, flowering time and the ‘dry’ trait, suggest that their inheritance may be linked functionally (pleiotropy) or physically (linkage disequilibrium). Water content QTL in homeologous regions resulting from an ancient duplication event may have been retained and continue to have related functions for an estimated 96 million years. Integration of QTL and GWAS data advanced knowledge of the genetic basis of stem diameter and water content components in sorghum, which may lead to tools and strategies for either enhancing or suppressing these traits, supporting advances toward improved quality of plant-based biomass for biofuel production.

Sign in / Sign up

Export Citation Format

Share Document