scholarly journals The Bnapus50K array: a quick and versatile genotyping tool for Brassica napus genomic breeding and research

2021 ◽  
Author(s):  
Qing Xiao ◽  
Huadong Wang ◽  
Nuan Song ◽  
Zewen Yu ◽  
Khan Imran ◽  
...  
Keyword(s):  
Gene Mapping ◽  
Genome Sequencing ◽  
Agronomic Traits ◽  
Detection Efficiency ◽  
Association Studies ◽  
Average Distance ◽  
Genome Wide Association Studies ◽  
Dna Array ◽  
Sequencing Data ◽  
Genomic Breeding

Abstract Rapeseed is a globally cultivated commercial crop, primarily grown for its oil. High-density single nucleotide polymorphism (SNP) arrays are widely used as a standard genotyping tool for rapeseed research, including for gene mapping, genome-wide association studies, germplasm resource analysis, and cluster analysis. Although considerable rapeseed genome sequencing data has been released, DNA arrays are still an attractive choice for providing additional genetic data in an era of high-throughput whole-genome sequencing. Here, we integrated re-sequencing DNA array data (32,216, and 304 SNPs) from 505 inbred rapeseed lines, allowing us to develop a sensitive and efficient genotyping DNA array, Bnapus50K, with a more consistent genetic and physical distribution of probes. A total of 42,090 high quality probes were filtered and synthesized, with an average distance between adjacent SNPs of 8 kb. To improve the practical application potential of this array in rapeseed breeding, we also added 1,618 functional probes related to important agronomic traits such as oil content, disease resistance, male sterility, and flowering time. The additional probes also included those specifically for detecting genetically modified material. These probes show a good detection efficiency and are therefore useful for gene mapping, along with crop variety improvement and identification. The novel Bnapus50K DNA array developed in this study could prove to be a quick and versatile genotyping tool for B. napus genomic breeding and research.

scholarly journals Breeding signatures of rice improvement revealed by a genomic variation map from a large germplasm collection

2015 ◽  
Vol 112 (39) ◽  
pp. E5411-E5419 ◽  
Author(s):  
Weibo Xie ◽  
Gongwei Wang ◽  
Meng Yuan ◽  
Wen Yao ◽  
Kai Lyu ◽  
...  
Keyword(s):  
Agronomic Traits ◽  
Association Studies ◽  
Rice Genome ◽  
Germplasm Collection ◽  
Genomic Variation ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Heterotic Groups ◽  
Genomic Changes ◽  
Rice Improvement

Intensive rice breeding over the past 50 y has dramatically increased productivity especially in the indica subspecies, but our knowledge of the genomic changes associated with such improvement has been limited. In this study, we analyzed low-coverage sequencing data of 1,479 rice accessions from 73 countries, including landraces and modern cultivars. We identified two major subpopulations, indica I (IndI) and indica II (IndII), in the indica subspecies, which corresponded to the two putative heterotic groups resulting from independent breeding efforts. We detected 200 regions spanning 7.8% of the rice genome that had been differentially selected between IndI and IndII, and thus referred to as breeding signatures. These regions included large numbers of known functional genes and loci associated with important agronomic traits revealed by genome-wide association studies. Grain yield was positively correlated with the number of breeding signatures in a variety, suggesting that the number of breeding signatures in a line may be useful for predicting agronomic potential and the selected loci may provide targets for rice improvement.

PSVIII-31 Genome-wide estimation of linkage disequilibrium using American mink genotyping-by-sequencing data

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 267-267
Author(s):  
Karim Karimi ◽  
A Hossain Farid ◽  
Mehdi Sargolzaei ◽  
Sean Myles ◽  
Younes Miar
Keyword(s):  
Linkage Disequilibrium ◽  
Association Studies ◽  
Average Distance ◽  
American Mink ◽  
Genotyping By Sequencing ◽  
Snp Markers ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Single Nucleotide ◽  
Genome Wide

Abstract Linkage disequilibrium (LD) has been defined as the correlation between alleles at different loci in the genome. The LD levels can be influenced by the evolutionary processes and historical events in populations. The main objective of this study was to estimate the LD levels at different distances of American mink genome using genotyping-by-sequencing (GBS) data. A total of 285 American mink (Neovison vison) were sequenced based on GBS libraries prepared by digesting the genomic DNA with the restriction enzyme ApeKI. After quality control, 13,321 single nucleotide polymorphism (SNP) markers located on 46 Scaffolds were used to determine the extension of LD in the genome. The average r2 was computed for all syntenic SNP pairwise at inter-marker distances from 0 up to 1 Mb. The average r2 between adjacent SNPs was 0.29, ranged from 0.18 to 0.53 across all scaffolds. In addition, the average distance between adjacent markers was 51 kb. The average r2 above 0.3 was observed in less than 1 kb distances and declined with increase in distances between markers. The average r2 was estimated to be less than 0.2 for markers more than 10 kb apart. Furthermore, the average LD level was decreased to 0.08 for inter-marker distances between 0.9 and 1 Mb. The results of this study can be used to determine the optimum maker density required for obtaining enough accuracy and power in both genomic selection and genome-wide association studies.

Exome-Wide Pan-Cancer Analysis of Germline Variants in 8,719 Individuals Finds Little Evidence of Rare Variant Associations

2021 ◽  
pp. 1-10
Author(s):  
Zoe Guan ◽  
Ronglai Shen ◽  
Colin B. Begg
Keyword(s):  
Rare Variant ◽  
Rare Variants ◽  
Association Studies ◽  
The Cancer Genome Atlas ◽  
Considerable Proportion ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Risk Variants ◽  
Cancer Types ◽  
Pan Cancer

<b><i>Background:</i></b> Many cancer types show considerable heritability, and extensive research has been done to identify germline susceptibility variants. Linkage studies have discovered many rare high-risk variants, and genome-wide association studies (GWAS) have discovered many common low-risk variants. However, it is believed that a considerable proportion of the heritability of cancer remains unexplained by known susceptibility variants. The “rare variant hypothesis” proposes that much of the missing heritability lies in rare variants that cannot reliably be detected by linkage analysis or GWAS. Until recently, high sequencing costs have precluded extensive surveys of rare variants, but technological advances have now made it possible to analyze rare variants on a much greater scale. <b><i>Objectives:</i></b> In this study, we investigated associations between rare variants and 14 cancer types. <b><i>Methods:</i></b> We ran association tests using whole-exome sequencing data from The Cancer Genome Atlas (TCGA) and validated the findings using data from the Pan-Cancer Analysis of Whole Genomes Consortium (PCAWG). <b><i>Results:</i></b> We identified four significant associations in TCGA, only one of which was replicated in PCAWG (BRCA1 and ovarian cancer). <b><i>Conclusions:</i></b> Our results provide little evidence in favor of the rare variant hypothesis. Much larger sample sizes may be needed to detect undiscovered rare cancer variants.

scholarly journals Integration of genome wide association studies and whole genome sequencing provides novel insights into fat deposition in chicken

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Gabriel Costa Monteiro Moreira ◽  
Clarissa Boschiero ◽  
Aline Silva Mello Cesar ◽  
James M. Reecy ◽  
Thaís Fernanda Godoy ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Fat Deposition ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Genome Wide

Genome-wide association studies of 14 agronomic traits in rice landraces

2010 ◽  
Vol 42 (11) ◽  
pp. 961-967 ◽  
Author(s):  
Xuehui Huang ◽  
Xinghua Wei ◽  
Tao Sang ◽  
Qiang Zhao ◽  
Qi Feng ◽  
...  
Keyword(s):  
Agronomic Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Rice Landraces ◽  
Genome Wide

scholarly journals Centenary of Soil and Air Borne Wheat Karnal Bunt Disease Research: A Review

Biology ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1152
Author(s):  
Mir Asif Iquebal ◽  
Pallavi Mishra ◽  
Ranjeet Maurya ◽  
Sarika Jaiswal ◽  
Anil Rai ◽  
...  
Keyword(s):  
Agronomic Traits ◽  
Association Studies ◽  
Farmyard Manure ◽  
Wheat Breeding ◽  
Karnal Bunt ◽  
Farm Income ◽  
Resistance Locus ◽  
Genome Wide Association Studies ◽  
Tilletia Indica ◽  
Causal Pathogen

Karnal bunt (KB) of wheat (Triticum aestivum L.), known as partial bunt has its origin in Karnal, India and is caused by Tilletia indica (Ti). Its incidence had grown drastically since late 1960s from northwestern India to northern India in early 1970s. It is a seed, air and soil borne pathogen mainly affecting common wheat, durum wheat, triticale and other related species. The seeds become inedible, inviable and infertile with the precedence of trimethylamine secreted by teliospores in the infected seeds. Initially the causal pathogen was named Tilletia indica but was later renamed Neovossia indica. The black powdered smelly spores remain viable for years in soil, wheat straw and farmyard manure as primary sources of inoculum. The losses reported were as high as 40% in India and also the cumulative reduction of national farm income in USA was USD 5.3 billion due to KB. The present review utilizes information from literature of the past 100 years, since 1909, to provide a comprehensive and updated understanding of KB, its causal pathogen, biology, epidemiology, pathogenesis, etc. Next generation sequencing (NGS) is gaining popularity in revolutionizing KB genomics for understanding and improving agronomic traits like yield, disease tolerance and disease resistance. Genetic resistance is the best way to manage KB, which may be achieved through detection of genes/quantitative trait loci (QTLs). The genome-wide association studies can be applied to reveal the association mapping panel for understanding and obtaining the KB resistance locus on the wheat genome, which can be crossed with elite wheat cultivars globally for a diverse wheat breeding program. The review discusses the current NGS-based genomic studies, assembly, annotations, resistant QTLs, GWAS, technology landscape of diagnostics and management of KB. The compiled exhaustive information can be beneficial to the wheat breeders for better understanding of incidence of disease in endeavor of quality production of the crop.

scholarly journals HAPPI GWAS: Holistic Analysis with Pre and Post Integration GWAS

2020 ◽  
Author(s):  
Marianne L. Slaten ◽  
Yen On Chan ◽  
Vivek Shrestha ◽  
Alexander E. Lipka ◽  
Ruthie Angelovici
Keyword(s):  
Association Studies ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Gwas Analysis ◽  
Genome Wide ◽  
Large Populations ◽  
Unbiased Estimates ◽  
Best Linear Unbiased ◽  
Automated Pipeline

AbstractMotivationAdvanced publicly available sequencing data from large populations have enabled in-formative genome-wide association studies (GWAS) that associate SNPs with phenotypic traits of interest. Many publicly available tools able to perform GWAS have been developed in response to increased demand. However, these tools lack a comprehensive pipeline that includes both pre-GWAS analysis such as outlier removal, data transformation, and calculation of Best Linear Unbiased Predictions (BLUPs) or Best Linear Unbiased Estimates (BLUEs). In addition, post-GWAS analysis such as haploblock analysis and candidate gene identification are lacking.ResultsHere, we present HAPPI GWAS, an open-source GWAS tool able to perform pre-GWAS, GWAS, and post-GWAS analysis in an automated pipeline using the command-line interface.AvailabilityHAPPI GWAS is written in R for any Unix-like operating systems and is available on GitHub (https://github.com/Angelovici-Lab/HAPPI.GWAS.git)[email protected]

scholarly journals Genes identified through genome-wide association studies of osteonecrosis in childhood acute lymphoblastic leukemia patients

2019 ◽  
Vol 20 (17) ◽  
pp. 1189-1197 ◽  
Author(s):  
Vincent Gagné ◽  
Anne Aubry-Morin ◽  
Maria Plesa ◽  
Rachid Abaji ◽  
Kateryna Petrykey ◽  
...  
Keyword(s):  
Association Studies ◽  
Lymphoblastic Leukemia ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Childhood All ◽  
Exome Sequencing Data ◽  
Genome Wide ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

Aim: To evaluate top-ranking genes identified through genome-wide association studies for an association with corticosteroid-related osteonecrosis in children with acute lymphoblastic leukemia (ALL) who received Dana–Farber Cancer Institute treatment protocols. Patients & methods: Lead SNPs from these studies, as well as other variants in the same genes, pooled from whole exome sequencing data, were analyzed for an association with osteonecrosis in childhood ALL patients from Quebec cohort. Top-ranking variants were verified in the replication patient group. Results: The analyses of variants in the ACP1-SH3YL1 locus derived from whole exome sequencing data showed an association of several correlated SNPs (rs11553746, rs2290911, rs7595075, rs2306060 and rs79716074). The rs79716074 defines *B haplotype of the APC1 gene, which is well known for its functional role. Conclusion: This study confirms implication of the ACP1 gene in the treatment-related osteonecrosis in childhood ALL and identifies novel, potentially causal variant of this complication.

scholarly journals Genome-wide association study of agronomic traits in bread wheat reveals novel putative alleles for future breeding programs

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yousef Rahimi ◽  
Mohammad Reza Bihamta ◽  
Alireza Taleei ◽  
Hadi Alipour ◽  
Pär K. Ingvarsson
Keyword(s):  
Bread Wheat ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Wheat Varieties ◽  
Data Set ◽  
Protein Coding ◽  
Genome Wide

Abstract Background Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles. Results GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016–2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (−log10P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively. Conclusions Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.

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