Riskoweb: Web-Based Genetic Profiling to Complex Disease Using Genome-Wide SNP Markers

2011 ◽  
pp. 1-8 ◽  
Author(s):  
Sergio Torres-Sánchez ◽  
Rosana Montes-Soldado ◽  
Nuria Medina-Medina ◽  
Andrés R. Masegosa ◽  
María Mar Abad-Grau
Keyword(s):  
Complex Disease ◽  
Snp Markers ◽  
Web Based ◽  
Genetic Profiling ◽  
Genome Wide

scholarly journals 026.Endometriosis — linkage, positional cloning and genome wide association

2004 ◽  
Vol 16 (9) ◽  
pp. 26
Author(s):  
G. W. Montgomery ◽  
J. Wicks ◽  
Z. Z. Zhao ◽  
D. R. Nyholt ◽  
N. G. Martin ◽  
...  
Keyword(s):  
High Throughput ◽  
Positional Cloning ◽  
Complex Disease ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Single Experiment ◽  
Priority List ◽  
Genome Wide

Endometriosis is a complex disease which affects up to 10% of women in their reproductive years. Common symptoms include severe dysmenorrhea and pelvic pain. The disease is associated with subfertility and some malignancies. Genetic and environmental factors both influence endometriosis. The aim of our studies is to identify genetic variation contributing to endometriosis and define pathways leading to disease. We recruited a large cohort of affected sister pair (ASP) families where two sisters have had surgically confirmed disease and conducted a 10�cM genome scan. The results of the linkage analysis identified one chromosomal region with significant linkage and one region of suggestive linkage. The regions implicated by these studies are generally of the order of 20–30�cM and include several hundred genes. Locating the gene or genes contributing to disease within the region is a challenging task. The best approach to the problem is association studies using a high density of SNP markers. The recent development of human SNP maps and high throughput SNP genotyping platforms makes this task easier. We have developed high throughput SNP typing at QIMR using the Sequenom MassARRAY platform. The method allows multiple SNP assays to be genotyped on the same sample in a single experiment. Throughput and genotyping costs depend critically on this level of multiplexing and we routinely genotype 6–8 SNPs in a single assay. We are using bioinformatics and functional approaches to develop a priority list of genes to screen early in the project. SNP markers in these genes are being genotyped using the MassARRAY platform to search for genes contributing to endometriosis. In the future, genome wide association studies with our families may locate additional genes contributing to endometriosis.

Comparison of kinship estimates in Santa Inês sheep using microsatellite and genome-wide SNP markers

2021 ◽  
pp. 106399
Author(s):  
Alzira Regina Silva de Deus ◽  
Geice Ribeiro Silva ◽  
Luciano Silva Sena ◽  
Fábio Barros Britto ◽  
Débora Araújo de Carvalho ◽  
...  
Keyword(s):  
Snp Markers ◽  
Genome Wide ◽  
Santa Inês

scholarly journals Genome wide association analyses to understand genetic basis of flowering and plant height under three levels of nitrogen application in Brassica juncea (L.) Czern & Coss

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Javed Akhatar ◽  
Anna Goyal ◽  
Navneet Kaur ◽  
Chhaya Atri ◽  
Meenakshi Mittal ◽  
...  
Keyword(s):  
Plant Height ◽  
Indian Subcontinent ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Strong Interactions ◽  
N Availability ◽  
Oilseed Crop ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractTimely transition to flowering, maturity and plant height are important for agronomic adaptation and productivity of Indian mustard (B. juncea), which is a major edible oilseed crop of low input ecologies in Indian subcontinent. Breeding manipulation for these traits is difficult because of the involvement of multiple interacting genetic and environmental factors. Here, we report a genetic analysis of these traits using a population comprising 92 diverse genotypes of mustard. These genotypes were evaluated under deficient (N75), normal (N100) or excess (N125) conditions of nitrogen (N) application. Lower N availability induced early flowering and maturity in most genotypes, while high N conditions delayed both. A genotyping-by-sequencing approach helped to identify 406,888 SNP markers and undertake genome wide association studies (GWAS). 282 significant marker-trait associations (MTA's) were identified. We detected strong interactions between GWAS loci and nitrogen levels. Though some trait associated SNPs were detected repeatedly across fertility gradients, majority were identified under deficient or normal levels of N applications. Annotation of the genomic region (s) within ± 50 kb of the peak SNPs facilitated prediction of 30 candidate genes belonging to light perception, circadian, floral meristem identity, flowering regulation, gibberellic acid pathways and plant development. These included over one copy each of AGL24, AP1, FVE, FRI, GID1A and GNC. FLC and CO were predicted on chromosomes A02 and B08 respectively. CDF1, CO, FLC, AGL24, GNC and FAF2 appeared to influence the variation for plant height. Our findings may help in improving phenotypic plasticity of mustard across fertility gradients through marker-assisted breeding strategies.

scholarly journals Genome-Wide SNP Markers Based on SLAF-Seq Uncover Breeding Traces in Rapeseed (Brassica napus L.)

2017 ◽  
Vol 8 ◽  
Author(s):  
Qinghong Zhou ◽  
Can Zhou ◽  
Wei Zheng ◽  
Annaliese S. Mason ◽  
Shuying Fan ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Snp Markers ◽  
Brassica Napus L ◽  
Genome Wide

scholarly journals Genome-wide association for heifer reproduction and calf performance traits in beef cattle

Genome ◽  
2015 ◽  
Vol 58 (12) ◽  
pp. 549-557 ◽  
Author(s):  
Everestus C. Akanno ◽  
Graham Plastow ◽  
Carolyn Fitzsimmons ◽  
Stephen P. Miller ◽  
Vern Baron ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Genome Wide Association Study ◽  
Average Daily Gain ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Research Centre ◽  
Genome Wide ◽  
A Genome ◽  
Starting Point ◽  
And Performance

The aim of this study was to identify SNP markers that associate with variation in beef heifer reproduction and performance of their calves. A genome-wide association study was performed by means of the generalized quasi-likelihood score (GQLS) method using heifer genotypes from the BovineSNP50 BeadChip and estimated breeding values for pre-breeding body weight (PBW), pregnancy rate (PR), calving difficulty (CD), age at first calving (AFC), calf birth weight (BWT), calf weaning weight (WWT), and calf pre-weaning average daily gain (ADG). Data consisted of 785 replacement heifers from three Canadian research herds, namely Brandon Research Centre, Brandon, Manitoba, University of Alberta Roy Berg Kinsella Ranch, Kinsella, Alberta, and Lacombe Research Centre, Lacombe, Alberta. After applying a false discovery rate correction at a 5% significance level, a total of 4, 3, 3, 9, 6, 2, and 1 SNPs were significantly associated with PBW, PR, CD, AFC, BWT, WWT, and ADG, respectively. These SNPs were located on chromosomes 1, 5–7, 9, 13–16, 19–21, 24, 25, and 27–29. Chromosomes 1, 5, and 24 had SNPs with pleiotropic effects. New significant SNPs that impact functional traits were detected, many of which have not been previously reported. The results of this study support quantitative genetic studies related to the inheritance of these traits, and provides new knowledge regarding beef cattle quantitative trait loci effects. The identification of these SNPs provides a starting point to identify genes affecting heifer reproduction traits and performance of their calves (BWT, WWT, and ADG). They also contribute to a better understanding of the biology underlying these traits and will be potentially useful in marker- and genome-assisted selection and management.

SNP discovery by amplicon sequencing and multiplex SNP genotyping in the allopolyploid species Brassica napusThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽  
2010 ◽  
Vol 53 (11) ◽  
pp. 948-956 ◽  
Author(s):  
G. Durstewitz ◽  
A. Polley ◽  
J. Plieske ◽  
H. Luerssen ◽  
E. M. Graner ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Oilseed Rape ◽  
Expressed Sequence Tag ◽  
Diploid Species ◽  
Amplicon Sequencing ◽  
Snp Markers ◽  
Snp Analysis ◽  
Genome Wide ◽  
A Genome ◽  
Illumina Goldengate

Oilseed rape ( Brassica napus ) is an allotetraploid species consisting of two genomes, derived from B. rapa (A genome) and B. oleracea (C genome). The presence of these two genomes makes single nucleotide polymorphism (SNP) marker identification and SNP analysis more challenging than in diploid species, as for a given locus usually two versions of a DNA sequence (based on the two ancestral genomes) have to be analyzed simultaneously during SNP identification and analysis. One hundred amplicons derived from expressed sequence tag (ESTs) were analyzed to identify SNPs in a panel of oilseed rape varieties and within two sister species representing the ancestral genomes. A total of 604 SNPs were identified, averaging one SNP in every 42 bp. It was possible to clearly discriminate SNPs that are polymorphic between different plant varieties from SNPs differentiating the two ancestral genomes. To validate the identified SNPs for their use in genetic analysis, we have developed Illumina GoldenGate assays for some of the identified SNPs. Through the analysis of a number of oilseed rape varieties and mapping populations with GoldenGate assays, we were able to identify a number of different segregation patterns in allotetraploid oilseed rape. The majority of the identified SNP markers can be readily used for genetic mapping, showing that amplicon sequencing and Illumina GoldenGate assays can be used to reliably identify SNP markers in tetraploid oilseed rape and to convert them into successful SNP assays that can be used for genetic analysis.

Genome-wide association analysis of resistance to Pseudoperonospora cubensis in citron watermelon

Plant Disease ◽  
2021 ◽  
Author(s):  
Dennis Katuuramu ◽  
Sandra Branham ◽  
Amnon Levi ◽  
Patrick Wechter
Keyword(s):  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Citrullus Lanatus ◽  
Phenotypic Variability ◽  
Germplasm Collection ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Pseudoperonospora Cubensis ◽  
Genome Wide ◽  
A Genome

Cultivated sweet watermelon (Citrullus lanatus) is an important vegetable crop for millions of people around the world. There are limited sources of resistance to economically important diseases within C. lanatus, whereas Citrullus amarus has a reservoir of traits that can be exploited to improve C. lanatus for resistance to biotic and abiotic stresses. Cucurbit downy mildew (CDM), caused by Pseudoperonospora cubensis, is an emerging threat to watermelon production. We screened 122 C. amarus accessions for resistance to CDM over two tests (environments). The accessions were genotyped by whole-genome resequencing to generate 2,126,759 single nucleotide polymorphic (SNP) markers. A genome-wide association study was deployed to uncover marker-trait associations and identify candidate genes underlying resistance to CDM. Our results indicate the presence of wide phenotypic variability (1.1 - 57.8%) for leaf area infection, representing a 50.7-fold variation for CDM resistance across the C. amarus germplasm collection. Broad-sense heritability estimate was 0.55, implying the presence of moderate genetic effects for resistance to CDM. The peak SNP markers associated with resistance to P. cubensis were located on chromosomes Ca03, Ca05, Ca07, and Ca11. The significant SNP markers accounted for up to 30% of the phenotypic variation and were associated with promising candidate genes encoding disease resistance proteins, leucine-rich repeat receptor-like protein kinase, and WRKY transcription factor. This information will be useful in understanding the genetic architecture of the P. cubensis-Citrullus spp. patho-system as well as development of resources for genomics-assisted breeding for resistance to CDM in watermelon.

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