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 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 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.

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 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 Genome-Wide Association Studies and Whole-Genome Prediction Reveal the Genetic Architecture of KRN in Maize

2020 ◽  
Author(s):  
Yixin An ◽  
Lin Chen ◽  
Yongxiang Li ◽  
Chunhui Li ◽  
Yunsu Shi ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Association Studies ◽  
Genome Wide Association ◽  
Cytokinin Oxidase ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Maize Breeding ◽  
Candidate Gene Association ◽  
Genome Wide ◽  
Genome Prediction

Abstract Background: Kernel row number (KRN) is an important trait for the domestication and improvement of maize. To explore the genetic basis of KRN has great research significance and can provide the valuable information for molecular assisted selection.Results: In this study, one single-locus method (MLM) and six multi-locus methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB and ISIS EM-BLASSO) of genome-wide association studies (GWASs) were used to identify significant quantitative trait nucleotides (QTNs) for KRN in an association panel including 639 maize inbred lines that were genotyped by the MaizeSNP50 BeadChip. In three phenotyping environments and with best linear unbiased prediction (BLUP) values, seven GWAS methods revealed different numbers of KRN-associated QTNs, ranging from 11 to 177. Based on these results, seven important regions for KRN located on chromosomes 1, 2, 3, 5, 9, and 10 were identified by at least three methods and in at least two environments. Moreover, 49 genes from the seven regions were expressed in different maize tissues. Among the 49 genes, ARF29 (Zm00001d026540, encoding auxin response factor 29) and CKO4 (Zm00001d043293, encoding cytokinin oxidase protein) were significantly related to KRN based on expression analysis and candidate gene association mapping. Whole-genome prediction (WGP) for KRN was also performed, and we found that the KRN-associated tagSNPs achieved a high prediction accuracy. The best strategy was to integrate the total KRN-associated tagSNPs identified by all GWAS models.Conclusions: These results aid in our understanding of the genetic architecture of KRN and provide useful information for genomic selection for KRN in maize breeding.

scholarly journals Bench Research Informed by GWAS Results

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3184
Author(s):  
Nikolay V. Kondratyev ◽  
Margarita V. Alfimova ◽  
Arkadiy K. Golov ◽  
Vera E. Golimbet
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Reverse Genetics ◽  
Genetic Factors ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually ‘highly polygenic’. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise ‘wet biologists’ with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.

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