scholarly journals MaizeCUBIC: a comprehensive variation database for a maize synthetic population

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Jingyun Luo ◽  
Chengcheng Wei ◽  
Haijun Liu ◽  
Shikun Cheng ◽  
Yingjie Xiao ◽  
...  

Abstract MaizeCUBIC is a free database that describes genomic variations, gene expression, phenotypes and quantitative trait locus (QTLs) for a maize CUBIC population (24 founders and 1404 inbred offspring). The database not only includes information for over 14M single nucleotide polymorphism (SNPs) and 43K indels previously identified but also contains 660K structure variations (SVs) and 600M novel sequences newly identified in the present study, which represents a comprehensive high-density variant map for a diverse population. Based on these genomic variations, the database would demonstrate the mosaic structure for each progeny, reflecting a high-resolution reshuffle across parental genomes. A total of 23 agronomic traits measured on parents and progeny in five locations, where are representative of the maize main growing regions in China, were also included in the database. To further explore the genotype–phenotype relationships, two different methods of genome-wide association studies (GWAS) were employed for dissecting the genetic architecture of 23 agronomic traits. Additionally, the Basic Local Alignment Search Tool and primer design tools are developed to promote follow-up analysis and experimental verification. All the original data and corresponding analytical results can be accessed through user-friendly online queries and web interface dynamic visualization, as well as downloadable files. These data and tools provide valuable resources on genetic and genomic studies of maize and other crops.

2020 ◽  
Vol 21 (6) ◽  
pp. 466-470
Author(s):  
Emine Kandemis ◽  
Gulten Tuncel ◽  
Ozen Asut ◽  
Sehime G. Temel ◽  
Mahmut C. Ergoren

Background: The use of psychoactive substances is one of the most dangerous social problems worldwide. Nicotine dependence results from the interaction between neurobiological, environmental and genetic factors. Serotonin is a neurotransmitter that has a wide range of central nervous system activities. The serotonin transporter gene has been previously linked to psychological traits. Objective: A variable number of tandem repeats within the serotonin transporter-linked polymorphic gene region are believed to alter the transcriptional efficiency of the 5-HTT gene. Therefore, we aimed to investigate the association between this polymorphic site and smoking behavior in the Turkish Cypriot population. Methods: A total of 259 (100 smokers, 100 non-smokers and 59 ex-smokers) Turkish Cypriots were included in this population-based cross-sectional study. Genomic DNA was extracted from peripheral blood samples and the 5-HTTVNTR2 polymorphisms were determined by the PCR-RFLP. Results: The allelic frequency and genotype distribution results of this study showed a strong association (P<0.0001) between smokers and non-smokers. No statistical significance was found between non-smokers and ex-smokers. Conclusion: This is the first genetic epidemiology study to investigate the allelic frequencies of 5-HTTVNTR2 polymorphisms associated with smoking behavior in the Turkish Cypriot population. Based on the results of this study, genome-wide association studies should be designed for preventive medicine in this population.


2020 ◽  
Vol 07 (03) ◽  
pp. 075-079
Author(s):  
Mahamad Irfanulla Khan ◽  
Prashanth CS

AbstractCleft lip with or without cleft palate (CL/P) is one of the most common congenital malformations in humans involving various genetic and environmental risk factors. The prevalence of CL/P varies according to geographical location, ethnicity, race, gender, and socioeconomic status, affecting approximately 1 in 800 live births worldwide. Genetic studies aim to understand the mechanisms contributory to a phenotype by measuring the association between genetic variants and also between genetic variants and phenotype population. Genome-wide association studies are standard tools used to discover genetic loci related to a trait of interest. Genetic association studies are generally divided into two main design types: population-based studies and family-based studies. The epidemiological population-based studies comprise unrelated individuals that directly compare the frequency of genetic variants between (usually independent) cases and controls. The alternative to population-based studies (case–control designs) includes various family-based study designs that comprise related individuals. An example of such a study is a case–parent trio design study, which is commonly employed in genetics to identify the variants underlying complex human disease where transmission of alleles from parents to offspring is studied. This article describes the fundamentals of case–parent trio study, trio design and its significances, statistical methods, and limitations of the trio studies.


2010 ◽  
Vol 42 (11) ◽  
pp. 961-967 ◽  
Author(s):  
Xuehui Huang ◽  
Xinghua Wei ◽  
Tao Sang ◽  
Qiang Zhao ◽  
Qi Feng ◽  
...  

Biology ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1152
Author(s):  
Mir Asif Iquebal ◽  
Pallavi Mishra ◽  
Ranjeet Maurya ◽  
Sarika Jaiswal ◽  
Anil Rai ◽  
...  

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.


2020 ◽  
Author(s):  
Mike A. Nalls ◽  
Cornelis Blauwendraat ◽  
Lana Sargent ◽  
Dan Vitale ◽  
Hampton Leonard ◽  
...  

SUMMARYBackgroundPrevious research using genome wide association studies (GWAS) has identified variants that may contribute to lifetime risk of multiple neurodegenerative diseases. However, whether there are common mechanisms that link neurodegenerative diseases is uncertain. Here, we focus on one gene, GRN, encoding progranulin, and the potential mechanistic interplay between genetic risk, gene expression in the brain and inflammation across multiple common neurodegenerative diseases.MethodsWe utilized GWAS, expression quantitative trait locus (eQTL) mapping and Bayesian colocalization analyses to evaluate potential causal and mechanistic inferences. We integrate various molecular data types from public resources to infer disease connectivity and shared mechanisms using a data driven process.FindingseQTL analyses combined with GWAS identified significant functional associations between increasing genetic risk in the GRN region and decreased expression of the gene in Parkinson’s, Alzheimer’s and amyotrophic lateral sclerosis. Additionally, colocalization analyses show a connection between blood based inflammatory biomarkers relating to platelets and GRN expression in the frontal cortex.InterpretationGRN expression mediates neuroinflammation function related to general neurodegeneration. This analysis suggests shared mechanisms for Parkinson’s, Alzheimer’s and amyotrophic lateral sclerosis.FundingNational Institute on Aging, National Institute of Neurological Disorders and Stroke, and the Michael J. Fox Foundation.


2019 ◽  
Vol 35 (21) ◽  
pp. 4327-4335
Author(s):  
Meiyue Wang ◽  
Shizhong Xu

AbstractMotivationGenomic scanning approaches that detect one locus at a time are subject to many problems in genome-wide association studies and quantitative trait locus mapping. The problems include large matrix inversion, over-conservativeness for tests after Bonferroni correction and difficulty in evaluation of the total genetic contribution to a trait’s variance. Targeting these problems, we take a further step and investigate a multiple locus model that detects all markers simultaneously in a single model.ResultsWe developed a sparse Bayesian learning (SBL) method for quantitative trait locus mapping and genome-wide association studies. This new method adopts a coordinate descent algorithm to estimate parameters (marker effects) by updating one parameter at a time conditional on current values of all other parameters. It uses an L2 type of penalty that allows the method to handle extremely large sample sizes (>100 000). Simulation studies show that SBL often has higher statistical powers and the simulated true loci are often detected with extremely small P-values, indicating that SBL is insensitive to stringent thresholds in significance testing.Availability and implementationAn R package (sbl) is available on the comprehensive R archive network (CRAN) and https://github.com/MeiyueComputBio/sbl/tree/master/R%20packge.Supplementary informationSupplementary data are available at Bioinformatics online.


2019 ◽  
Vol 50 (4) ◽  
pp. 213-220 ◽  
Author(s):  
Lucy Riglin ◽  
Ajay K. Thapar ◽  
Beate Leppert ◽  
Joanna Martin ◽  
Alexander Richards ◽  
...  

AbstractPsychiatric disorders show phenotypic as well as genetic overlaps. There are however also marked developmental changes throughout childhood. We investigated the extent to which, for a full range of early childhood psychopathology, a general “p” factor was explained by genetic liability, as indexed by multiple different psychiatric polygenic risk scores (PRS) and whether these relationships altered with age. The sample was a UK, prospective, population-based cohort with psychopathology data at age 7 (N = 8161) and age 13 (N = 7017). PRS were generated from large published genome-wide association studies. At both ages, we found evidence for a childhood “p” factor as well as for specific factors. Schizophrenia and attention-deficit/hyperactivity disorder (ADHD) PRS were associated with this general “p” factor at both ages but depression and autism spectrum disorder (ASD) PRS were not. We also found some evidence of associations between schizophrenia, ADHD and depression PRS with specific factors, but these were less robust and there was evidence for developmental changes.


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