scholarly journals GWAS and Fine-Mapping of Livability and Six Disease Traits in Holstein Cattle

2019 ◽  
Author(s):  
Ellen Freebern ◽  
Daniel JA Santos ◽  
Lingzhao Fang ◽  
Jicai Jiang ◽  
Kristen L. Parker Gaddis ◽  
...  

AbstractBackgroundHealth traits are of significant economic importance to the dairy industry due to their effects on milk production and associated treatment costs. Genome-wide association studies (GWAS) provide a means to identify associated genomic variants and thus reveal insights into the genetic architecture of complex traits and diseases. The objective of this study is to investigate the genetic basis of seven health traits in dairy cattle and to identify potential candidate genes associated with cattle health using GWAS, fine mapping, and analyses of multitissue transcriptome data.ResultsWe studied cow livability and six direct disease traits, mastitis, ketosis, hypocalcemia, displaced abomasum, metritis, and retained placenta, using de-regressed breeding values and more than three million imputed DNA sequence variants. After data edits and filtering on reliability, phenotypes for 11,880 to 24,699 Holstein bulls were included in the analyses of the seven traits. GWAS was performed using a mixed-model association test, and a Bayesian fine-mapping procedure was conducted to calculate a posterior probability of causality to each variant and gene in the candidate regions. The GWAS results detected a total of eight genome-wide significant associations for three traits, cow livability, ketosis, and hypocalcemia, including the bovine MHC region associated with livability. Our fine-mapping of associated regions reported 20 candidate genes with the highest posterior probabilities of causality for cattle health. Combined with transcriptome data across multiple tissues in cattle, we further exploited these candidate genes to identify specific expression patterns in disease-related tissues and relevant biological explanations such as the expression of GC in the liver and association with mastitis as well as the CCDC88C expression in CD8 cells and association with cow livability.ConclusionsCollectively, our analyses report six significant associations and 20 candidate genes of cattle health. With the integration of multi-tissue transcriptome data, our results provide useful information for future functional studies and better understanding of the biological relationship between genetics and disease susceptibility in cattle.


2018 ◽  
Author(s):  
Jean-Michel Michno ◽  
Liana T. Burghardt ◽  
Junqi Liu ◽  
Joseph R. Jeffers ◽  
Peter Tiffin ◽  
...  

ABSTRACTGenome-wide association studies (GWAS) have proven to be a valuable approach for identifying genetic intervals associated with phenotypic variation in Medicago truncatula. These intervals can vary in size, depending on the historical local recombination near each significant interval. Typically, significant intervals span numerous gene models, limiting the ability to resolve high-confidence candidate genes underlying the trait of interest. Additional genomic data, including gene co-expression networks, can be combined with the genetic mapping information to successfully identify candidate genes. Co-expression network analysis provides information about the functional relationships of each gene through its similarity of expression patterns to other well-defined clusters of genes. In this study, we integrated data from GWAS and co-expression networks to pinpoint candidate genes that may be associated with nodule-related phenotypes in Medicago truncatula. We further investigated a subset of these genes and confirmed that several had existing evidence linking them nodulation, including MEDTR2G101090 (PEN3-like), a previously validated gene associated with nodule number.



2017 ◽  
Vol 114 (30) ◽  
pp. 8101-8106 ◽  
Author(s):  
Mei Yang ◽  
Xuncheng Wang ◽  
Diqiu Ren ◽  
Hao Huang ◽  
Miqi Xu ◽  
...  

Heterosis is most frequently manifested by the substantially increased vigorous growth of hybrids compared with their parents. Investigating genomic variations in natural populations is essential to understand the initial molecular mechanisms underlying heterosis in plants. Here, we characterized the genomic architecture associated with biomass heterosis in 200Arabidopsishybrids. The genome-wide heterozygosity of hybrids makes a limited contribution to biomass heterosis, and no locus shows an obvious overdominance effect in hybrids. However, the accumulation of significant genetic loci identified in genome-wide association studies (GWAS) in hybrids strongly correlates with better-parent heterosis (BPH). Candidate genes for biomass BPH fall into diverse biological functions, including cellular, metabolic, and developmental processes and stimulus-responsive pathways. Important heterosis candidates includeWUSCHEL,ARGOS, and some genes that encode key factors involved in cell cycle regulation. Interestingly, transcriptomic analyses in representativeArabidopsishybrid combinations reveal that heterosis candidate genes are functionally enriched in stimulus-responsive pathways, including responses to biotic and abiotic stimuli and immune responses. In addition, stimulus-responsive genes are repressed to low-parent levels in hybrids with high BPH, whereas middle-parent expression patterns are exhibited in hybrids with no BPH. Our study reveals a genomic architecture for understanding the molecular mechanisms of biomass heterosis inArabidopsis, in which the accumulation of the superior alleles of genes involved in metabolic and cellular processes improve the development and growth of hybrids, whereas the overall repressed expression of stimulus-responsive genes prioritizes growth over responding to environmental stimuli in hybrids under normal conditions.



BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shenping Zhou ◽  
Rongrong Ding ◽  
Fanming Meng ◽  
Xingwang Wang ◽  
Zhanwei Zhuang ◽  
...  

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.



Author(s):  
Jianhua Wang ◽  
Dandan Huang ◽  
Yao Zhou ◽  
Hongcheng Yao ◽  
Huanhuan Liu ◽  
...  

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.



2020 ◽  
Author(s):  
Yanjiao Jin ◽  
Jie Yang ◽  
Shuyue Zhang ◽  
Jin Li ◽  
Songlin Wang

Abstract Background: Oral diseases impact the majority of the world’s population. The following traits are common in oral inflammatory diseases: mouth ulcers, painful gums, bleeding gums, loose teeth, and toothache. Despite the prevalence of genome-wide association studies, the associations between these traits and common genomic variants, and whether pleiotropic loci are shared by some of these traits remain poorly understood. Methods: In this work, we conducted multi-trait joint analyses based on the summary statistics of genome-wide association studies of these five oral inflammatory traits from the UK Biobank, each of which is comprised of over 10,000 cases and over 300,000 controls. We estimated the genetic correlations between the five traits. We conducted fine-mapping and functional annotation based on multi-omics data to better understand the biological functions of the potential causal variants at each locus. To identify the pathways in which the candidate genes were mainly involved, we applied gene-set enrichment analysis, and further performed protein-protein interaction (PPI) analyses.Results: We identified 39 association signals that surpassed genome-wide significance, including three that were shared between two or more oral inflammatory traits, consistent with a strong correlation. Among these genome-wide significant loci, two were novel for both painful gums and toothache. We performed fine-mapping and identified causal variants at each novel locus. Further functional annotation based on multi-omics data suggested IL10 and IL12A/TRIM59 as potential candidate genes at the novel pleiotropic loci, respectively. Subsequent analyses of pathway enrichment and protein-protein interaction networks suggested the involvement of candidate genes at genome-wide significant loci in immune regulation.Conclusions: Our results highlighted the importance of immune regulation in the pathogenesis of oral inflammatory diseases. Some common immune-related pleiotropic loci or genetic variants are shared by multiple oral inflammatory traits. These findings will be beneficial for risk prediction, prevention, and therapy of oral inflammatory diseases.



2021 ◽  
Author(s):  
Dev Paudel ◽  
Rocheteau Dareus ◽  
Julia Rosenwald ◽  
Maria Munoz-Amatriain ◽  
Esteban Rios

Cowpea (Vigna unguiculata [L.] Walp., diploid, 2n = 22) is a major crop used as a protein source for human consumption as well as a quality feed for livestock. It is drought and heat tolerant and has been bred to develop varieties that are resilient to changing climates. Plant adaptation to new climates and their yield are strongly affected by flowering time. Therefore, understanding the genetic basis of flowering time is critical to advance cowpea breeding. The aim of this study was to perform genome-wide association studies (GWAS) to identify marker trait associations for flowering time in cowpea using single nucleotide polymorphism (SNP) markers. A total of 367 accessions from a cowpea mini-core collection were evaluated in Ft. Collins, CO in 2019 and 2020, and 292 accessions were evaluated in Citra, FL in 2018. These accessions were genotyped using the Cowpea iSelect Consortium Array that contained 51,128 SNPs. GWAS revealed seven reliable SNPs for flowering time that explained 8-12% of the phenotypic variance. Candidate genes including FT, GI, CRY2, LSH3, UGT87A2, LIF2, and HTA9 that are associated with flowering time were identified for the significant SNP markers. Further efforts to validate these loci will help to understand their role in flowering time in cowpea, and it could facilitate the transfer of some of this knowledge to other closely related legume species.



2020 ◽  
Vol 26 (5) ◽  
pp. 490-500
Author(s):  
A. O. Konradi

The article reviews monogenic forms of hypertension, data on the role of heredity of essential hypertension and candidate genes, as well as genome-wide association studies. Modern approach for the role of genetics is driven by implementation of new technologies and their productivity. High performance speed of new technologies like genome-wide association studies provide data for better knowledge of genetic markers of hypertension. The major goal nowadays for research is to reveal molecular pathways of blood pressure regulation, which can help to move from populational to individual level of understanding of pathogenesis and treatment targets.



2018 ◽  
Vol 19 (9) ◽  
pp. 2794 ◽  
Author(s):  
Rong Zhou ◽  
Komivi Dossa ◽  
Donghua Li ◽  
Jingyin Yu ◽  
Jun You ◽  
...  

Sesame is poised to become a major oilseed crop owing to its high oil quality and adaptation to various ecological areas. However, the seed yield of sesame is very low and the underlying genetic basis is still elusive. Here, we performed genome-wide association studies of 39 seed yield-related traits categorized into five major trait groups, in three different environments, using 705 diverse lines. Extensive variation was observed for the traits with capsule size, capsule number and seed size-related traits, found to be highly correlated with seed yield indexes. In total, 646 loci were significantly associated with the 39 traits (p < 10−7) and resolved to 547 quantitative trait loci QTLs. We identified six multi-environment QTLs and 76 pleiotropic QTLs associated with two to five different traits. By analyzing the candidate genes for the assayed traits, we retrieved 48 potential genes containing significant functional loci. Several homologs of these candidate genes in Arabidopsis are described to be involved in seed or biomass formation. However, we also identified novel candidate genes, such as SiLPT3 and SiACS8, which may control capsule length and capsule number traits. Altogether, we provided the highly-anticipated basis for research on genetics and functional genomics towards seed yield improvement in sesame.



2021 ◽  
Vol 28 ◽  
Author(s):  
Vinutha Kanuganahalli Somegowda ◽  
Laavanya Rayaprolu ◽  
Abhishek Rathore ◽  
Santosh Pandurang Deshpande ◽  
Rajeev Gupta

: 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.



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