Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches

Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.

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Deciphering Rubber Tree Growth Using Network-Based Multi Omics Approaches

10.1101/2021.08.16.456528 ◽

2021 ◽

Author(s):

Felipe Roberto Francisco ◽

Alexandre Hild Aono ◽

Carla Cristina da Silva ◽

Paulo de Souza Gon&ccedilalves ◽

Erivaldo Jos&eacute Scaloppi J&uacutenior ◽

...

Keyword(s):

Plant Growth ◽

Tree Growth ◽

Association Studies ◽

Rubber Tree ◽

Genotyping By Sequencing ◽

Tree Breeding ◽

Genome Wide Association Studies ◽

Rna Seq ◽

Large Tree ◽

Improvement Programs

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Development of a 76k Alpaca (Vicugna pacos) Single Nucleotide Polymorphisms (SNPs) Microarray

Genes ◽

10.3390/genes12020291 ◽

2021 ◽

Vol 12 (2) ◽

pp. 291

Author(s):

Marcos Calderon ◽

Manuel J. More ◽

Gustavo A. Gutierrez ◽

Federico Abel Ponce de León

Keyword(s):

Genetic Improvement ◽

Association Studies ◽

Fiber Quality ◽

Genotyping By Sequencing ◽

Economic Benefits ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Reduced Representation ◽

Improvement Programs

Small farm producers’ sustenance depends on their alpaca herds and the production of fiber. Genetic improvement of fiber characteristics would increase their economic benefits and quality of life. The incorporation of molecular marker technology could overcome current limitations for the implementation of genetic improvement programs. Hence, the aim of this project was the generation of an alpaca single nucleotide polymorphism (SNP) microarray. A sample of 150 Huacaya alpacas from four farms, two each in Puno and Cerro de Pasco were used for SNP discovery by genotyping by sequencing (GBS). Reduced representation libraries, two per animal, were produced after DNA digestion with ApeK1 and double digestion with Pst1-Msp1. Ten alpaca genomes, sequenced at depths between 12× to 30×, and the VicPac3.1 reference genome were used for read alignments. Bioinformatics analysis discovered 76,508 SNPs included in the microarray. Candidate genes SNPs (302) for fiber quality and color are also included. The microarray SNPs cover 90.5% of the genome length with a density of about 39 ± 2.51 SNPs/Mb of DNA at an average interval of 26.45 ± 18.57 kbp. The performance was evaluated by genotyping 30 family trios and comparing them to their pedigrees, as well as comparing microarray to GBS genotypes. Concordance values of 0.93 and 0.94 for ApeK1 and Pst1-Msp1 generated SNPs were observed. Similarly, 290 fiber quality and color candidate gene SNPs were validated. Availability of this microarray will facilitate genome-wide association studies, marker-assisted selection and, in time, genomic selection.

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Exome resequencing and GWAS for growth, ecophysiology, and chemical and metabolomic composition of wood of Populus trichocarpa

BMC Genomics ◽

10.1186/s12864-019-6160-9 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 1

Author(s):

Fernando P. Guerra ◽

Haktan Suren ◽

Jason Holliday ◽

James H. Richards ◽

Oliver Fiehn ◽

...

Keyword(s):

Biomass Production ◽

Complex Traits ◽

Association Studies ◽

Populus Trichocarpa ◽

Significant Snps ◽

Snp Markers ◽

Exome Capture ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Improvement Programs

Abstract Background Populus trichocarpa is an important forest tree species for the generation of lignocellulosic ethanol. Understanding the genomic basis of biomass production and chemical composition of wood is fundamental in supporting genetic improvement programs. Considerable variation has been observed in this species for complex traits related to growth, phenology, ecophysiology and wood chemistry. Those traits are influenced by both polygenic control and environmental effects, and their genome architecture and regulation are only partially understood. Genome wide association studies (GWAS) represent an approach to advance that aim using thousands of single nucleotide polymorphisms (SNPs). Genotyping using exome capture methodologies represent an efficient approach to identify specific functional regions of genomes underlying phenotypic variation. Results We identified 813 K SNPs, which were utilized for genotyping 461 P. trichocarpa clones, representing 101 provenances collected from Oregon and Washington, and established in California. A GWAS performed on 20 traits, considering single SNP-marker tests identified a variable number of significant SNPs (p-value < 6.1479E-8) in association with diameter, height, leaf carbon and nitrogen contents, and δ15N. The number of significant SNPs ranged from 2 to 220 per trait. Additionally, multiple-marker analyses by sliding-windows tests detected between 6 and 192 significant windows for the analyzed traits. The significant SNPs resided within genes that encode proteins belonging to different functional classes as such protein synthesis, energy/metabolism and DNA/RNA metabolism, among others. Conclusions SNP-markers within genes associated with traits of importance for biomass production were detected. They contribute to characterize the genomic architecture of P. trichocarpa biomass required to support the development and application of marker breeding technologies.

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Transcriptome Analysis in Domesticated Species: Challenges and Strategies

Bioinformatics and Biology Insights ◽

10.4137/bbi.s29334 ◽

2015 ◽

Vol 9S4 ◽

pp. BBI.S29334 ◽

Cited By ~ 4

Author(s):

Jessica P. Hekman ◽

Jennifer L Johnson ◽

Anna V. Kukekova

Keyword(s):

Complex Traits ◽

Gene Networks ◽

Association Studies ◽

Cultural Value ◽

Genomic Research ◽

Model Organisms ◽

Genome Wide Association Studies ◽

Rna Seq ◽

Genome Wide ◽

Genome Assemblies

Domesticated species occupy a special place in the human world due to their economic and cultural value. In the era of genomic research, domesticated species provide unique advantages for investigation of diseases and complex phenotypes. RNA sequencing, or RNA-seq, has recently emerged as a new approach for studying transcriptional activity of the whole genome, changing the focus from individual genes to gene networks. RNA-seq analysis in domesticated species may complement genome-wide association studies of complex traits with economic importance or direct relevance to biomedical research. However, RNA-seq studies are more challenging in domesticated species than in model organisms. These challenges are at least in part associated with the lack of quality genome assemblies for some domesticated species and the absence of genome assemblies for others. In this review, we discuss strategies for analyzing RNA-seq data, focusing particularly on questions and examples relevant to domesticated species.

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Chromatin-based techniques map DNA interaction landscapes in psoriasis susceptibility loci and highlight KLF4 as a target gene in 9q31

10.1101/822304 ◽

2019 ◽

Author(s):

Helen Ray-Jones ◽

Kate Duffus ◽

Amanda McGovern ◽

Paul Martin ◽

Chenfu Shi ◽

...

Keyword(s):

Target Gene ◽

Target Genes ◽

Association Studies ◽

Dna Interaction ◽

Genome Wide Association Studies ◽

Susceptibility Loci ◽

Rna Seq ◽

Causal Gene ◽

Genome Wide ◽

Crispr Activation

AbstractGenome-wide association studies (GWAS) have uncovered many genetic risk loci for psoriasis, yet many remain uncharacterised in terms of the causal gene and their biological mechanism in disease. Here, we use a disease-focused Capture Hi-C experiment to link psoriasis-associated variants with their target genes in psoriasis-relevant cell lines (HaCaT keratinocytes and My-La CD8+ T cells). We confirm previously assigned genes, suggest novel candidates and provide evidence for complexity at psoriasis GWAS loci. In the 9q31 risk locus we combine further epigenomic evidence to demonstrate how the psoriasis association forms a functional interaction with the distant (>500 kb) KLF4 gene. We use CRISPR activation coupled with RNA-seq to demonstrate how activation of psoriasis-associated enhancers upregulates KLF4 in HaCaT cells. Our study design provides a robust pipeline for following up on GWAS disease-associated variants, paving the way for functional translation of genetic findings into clinical benefit.

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Genetic Diversity Analysis of Korean Peanut Germplasm Using 48 K SNPs ‘Axiom_Arachis’ Array and Its Application for Cultivar Differentiation

10.21203/rs.3.rs-154213/v1 ◽

2021 ◽

Author(s):

Rizwana Begum Syed Nabi ◽

Kwang-Soo Cho ◽

Rupesh Tayade ◽

Ki Won Oh ◽

Myoung Hee Lee ◽

...

Keyword(s):

Genetic Diversity ◽

Genetic Resources ◽

Association Studies ◽

Diversity Analysis ◽

Genome Wide Association Studies ◽

Genotype Distribution ◽

Genetic Diversity Analysis ◽

Genetic Base ◽

Cultivated Peanut ◽

Improvement Programs

Abstract Cultivated peanut (Arachis hypogaea) is one of the important legume oilseed crops. Cultivated peanut has a narrow genetic base. Therefore, it is necessary to widen its genetic base and diversity for additional use. The objective of the present study was to assess the genetic diversity and population structure of 96 peanut genotypes with 9478 high-resolution SNPs identified from a 48K ‘Axiom_Arachis’ SNP array. Korean set genotypes were also compared with a mini-core of US genotypes. These sets of genotypes were used for genetic diversity analysis. Model-based structure analysis at K = 2 indicated the presence of two subpopulations in both sets of genotypes. Phylogenetic and PCA analysis clustered these genotypes into two major groups. However, clear genotype distribution was not observed for categories of subspecies, botanical variety, or origin. The analysis also revealed that current Korean genetic resources lacked variability. These results suggest that Korean genetic resources need to be expanded by creating new allele combinations and widening the genetic pool to offer new genetic variations for Korean peanut improvement programs. High-quality SNP data generated in this study could be used for identifying varietal contaminant, QTL, and genes associated with desirable traits by performing mapping, genome-wide association studies.

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Identification of Loci Controlling the Dwarfism Trait in the White Sailfin Molly (Poecilia latipinna) Using Genome-Wide Association Studies Based on Genotyping-By-Sequencing

Genes ◽

10.3390/genes10060418 ◽

2019 ◽

Vol 10 (6) ◽

pp. 418

Author(s):

Fan Shao ◽

Jing Liu ◽

Mengyuan Ren ◽

Junying Li ◽

Haigang Bao ◽

...

Keyword(s):

Candidate Genes ◽

Association Studies ◽

Genotyping By Sequencing ◽

Genome Wide Association ◽

Expression Level ◽

Genome Wide Association Studies ◽

Sailfin Molly ◽

Genome Wide ◽

Genomic Regions ◽

Sailfin Mollies

Dwarfism is a condition defined by low harvest weight in fish, but also results in strange body figures which may have potential for the selective breeding of new ornamental fish strains. The objectives of this study are to reveal the physiological causes of dwarfism and identify the genetic loci controlling this trait in the white sailfin molly. Skeletons of dwarf and normal sailfin mollies were observed by X-ray radioscopy and skeletal staining. Genome-wide association studies based on genotyping-by-sequencing (n = 184) were used to map candidate genomic regions associated with the dwarfism trait. Quantitative real-time PCR was performed to determine the expression level of candidate genes in normal (n = 8) and dwarf (n = 8) sailfin mollies. We found that the dwarf sailfin molly has a short and dysplastic spine in comparison to the normal fish. Two regions, located at NW_015112742.1 and NW_015113621.1, were significantly associated with the dwarfism trait. The expression level of three candidate genes, ADAMTS like 1, Larp7 and PPP3CA, were significantly different between the dwarf and normal sailfin mollies in the hepatopancreas, with PPP3CA also showing significant differences in the vertebrae and Larp7 showing significant differences in the muscle. This study identified genomic regions and candidate genes associated with the dwarfism trait in the white sailfin molly and would provide a reference to determine dwarf-causing variations.

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The PF4/PPBP/CXCL5 Gene Cluster Is Associated with Periodontitis

Journal of Dental Research ◽

10.1177/0022034517706311 ◽

2017 ◽

Vol 96 (8) ◽

pp. 945-952 ◽

Cited By ~ 15

Author(s):

A. Shusterman ◽

M. Munz ◽

G. Richter ◽

S. Jepsen ◽

W. Lieb ◽

...

Keyword(s):

Association Studies ◽

Disease Onset ◽

Control Sample ◽

Aggressive Periodontitis ◽

Human Case ◽

Case Control ◽

Candidate Gene Approach ◽

Genome Wide Association Studies ◽

Rna Seq ◽

Coding Region

Periodontitis is a common dysbiotic inflammatory disease with an estimated heritability of 50%. Due to the limited sample size of available periodontitis cohorts and the underlying trait heterogeneity, genome-wide association studies (GWAS) of chronic periodontitis (CP) have been unsuccessful in discovering susceptibility factors. A strategy that combines agnostic GWAS with a well-powered candidate-gene approach has the potential to discover novel loci. We combined RNA-seq data from gingival tissues with quantitative trait loci (QTLs) that were identified in a F2-cross of mice resistant and susceptible to infection with oral bacterial pathogens. Four genes, which were located within the mapped QTLs, showed differential expression. The chromosomal regions across the human orthologous were interrogated for putative periodontitis-associated variants using existing GWAS data from a German case-control sample of aggressive periodontitis (AgP; 651 cases, 4,001 controls), the most severe and early onset form of periodontitis. Two haplotype blocks, one upstream to the coding region of UGT2A1 (rs146712414, P = 9.1 × 10−5; odds ratio [OR], 1.34; 95% confidence interval [CI], 1.16–1.56) and one downstream of the genes PF4/PPBP/CXCL5 (rs1595009, P = 1.3 × 10−4; OR, 1.32; 95% CI, 1.15–1.52), were associated with AgP. The association of rs1595009 was validated in an independent cohort of CP of European Americans (1,961 cases and 1,864 controls; P = 0.03; OR, 1.45; 95% CI, 1.01–1.29). This association was further replicated in another sample of 399 German CP cases (disease onset <60 y of age) and 1,633 controls ( P = 0.03; OR, 1.75; 95% CI, 1.06–2.90). The combined estimates of association from all samples were P = 2.9 × 10−5 (OR, 1.2; 95% CI, 1.1–1.3). This study shows the strength of combining QTL mapping and RNA-Seq data from a mouse model with association studies in human case-control samples to identify genetic risk variants of periodontitis.

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239 Grazing Distribution of Beef Cattle: Acronyms of Technology and Spatial Measures

Journal of Animal Science ◽

10.1093/jas/skaa054.214 ◽

2020 ◽

Vol 98 (Supplement_3) ◽

pp. 125-125

Author(s):

Milton G Thomas ◽

Jasmine Dillon ◽

Derek Bailey ◽

Courtney Pierce ◽

Scott Speidel ◽

...

Keyword(s):

Data Collection ◽

Beef Cattle ◽

Association Studies ◽

Genetic Evaluation ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Pasture Management ◽

Positioning Systems ◽

Spatial Measures ◽

Improvement Programs

Abstract Grazing distribution is an important aspect of pasture management, yet measuring traits for sustainable forage consumption is challenging. Uplands are often un-grazed by beef cattle due to rugged terrain while riparian zones are often heavily grazed; thus, sustainable consumption may be achieved if improved landscape utilization by cattle is encouraged. Modifying grazing behaviour with fencing and (or) water-source and feeding location(s) is effective in improving grazing patterns; however, these infrastructure improvements are typically expensive, supporting the concept of genetic selection for improved grazing distribution. Efforts funded by the Western Sustainable Research and Education Program (WSARE; SW15-015) using global positioning systems (GPS) indicated a genetic influence on quantitative traits describing grazing distribution of 330 Angus-influenced cows (i.e. distance from water, slope, elevation, vertical climb, etc.). Collars fitted with GPS devices for data collection accrued measures at intervals of 5 to 15 min and 10 m resolution for 3-19 weeks in 16 pastures on 14 ranches and experiment stations. Genome-wide association studies involving trait-measures and high-density genotypes (n = 777,962 single nucleotide polymorphisms; SNP) indicated these traits were polygenic. Combining SNP genotypes with trait measures and pedigree has become the norm in genetic evaluation and improvement processes (i.e. genome-enhanced expected progeny difference (GE-EPD). These processes require data from large numbers of animals (n > 10,000). Collecting grazing distribution phenotypes with GPS collars is accurate, but time-consuming; therefore, collaborative research is being conducted in the 2019-2020 academic year exploring the use of unmanned aerial vehicles (UAV) and cameras to ascertain spatial measures of beef cow grazing distribution. This collaboration involves scientists in the Colorado State University Drone Center, Department of Mechanical Engineering, and Department of Animal Sciences. The project objective is to determine if UAV can expedite data collection to support development of genetic evaluation and improvement programs for grazing distribution.

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Genotyping-by-Sequencing-Based Genome-Wide Association Studies of Fusarium Wilt Resistance in Radishes (Raphanus sativus L.)

Genes ◽

10.3390/genes12060858 ◽

2021 ◽

Vol 12 (6) ◽

pp. 858

Author(s):

O New Lee ◽

Hyunjin Koo ◽

Jae Woong Yu ◽

Han Yong Park

Keyword(s):

Fusarium Wilt ◽

Association Studies ◽

Genotyping By Sequencing ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Gwas Study ◽

F2 Population ◽

Genome Wide ◽

Resistant Varieties

Fusarium wilt (FW) is a fungal disease that causes severe yield losses in radish production. The most effective method to control the FW is the development and use of resistant varieties in cultivation. The identification of marker loci linked to FW resistance are expected to facilitate the breeding of disease-resistant radishes. In the present study, we applied an integrated framework of genome-wide association studies (GWAS) using genotyping-by-sequencing (GBS) to identify FW resistance loci among a panel of 225 radish accessions, including 58 elite breeding lines. Phenotyping was conducted by manual inoculation of seedlings with the FW pathogen, and scoring for the disease index was conducted three weeks after inoculation during two constitutive years. The GWAS analysis identified 44 single nucleotide polymorphisms (SNPs) and twenty putative candidate genes that were significantly associated with FW resistance. In addition, a total of four QTLs were identified from F2 population derived from a FW resistant line and a susceptible line, one of which was co-located with the SNPs on chromosome 7, detected in GWAS study. These markers will be valuable for molecular breeding programs and marker-assisted selection to develop FW resistant varieties of R. sativus.

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