scholarly journals Computational Mining and Genome Wide Distribution of Microsatellite in Fusarium oxysporum f. sp. lycopersici

2012 ◽  
Vol 4 (4) ◽  
pp. 127-131 ◽  
Author(s):  
Sudheer KUMAR ◽  
Deepak MAURYA ◽  
Shalini RAI ◽  
Prem Lal KASHYAP ◽  
Alok Kumar SRIVASTAVA
Keyword(s):  
Fusarium Oxysporum ◽  
Genomic Analysis ◽  
Wide Distribution ◽  
Chromosome 1 ◽  
Coding Region ◽  
Chromosome 11 ◽  
High Throughput Analysis ◽  
Genome Wide ◽  
Baseline Information ◽  
Simple Sequence

Simple sequence repeat (SSR) is currently the most preferred molecular marker system owing to their highly desirable properties viz., abundance, hyper-variability, and suitability for high-throughput analysis. Hence, in present study an attempt was made to mine and analyze microsatellite dynamics in whole genome of Fusarium oxysporum f. sp. lycopersici. The distribution pattern of different SSR motifs provides the evidence of greater accumulation of tetra-nucleotide (3837) repeats followed by tri-nucleotide (3367) repeats. Maximum frequency distribution in coding region was shown by mono-nucleotide SSR motifs (34.8%), where as minimum frequency is observed for penta-nucleotide SSR (0.87%). Highest relative abundance (1023 SSR/Mb) and density of SSRs (114.46 bp/Mb) were observed on chromosome 1, while least density of SSR motifs was recorded on chromosome 11 (7.40 bp/Mb) and 12 (7.41 bp/Mb), respectively. Maximum trinucleotide (34.24%) motifs code for glutamic acid (GAA) while GT/CT were the most frequent repeat of dinucleotide SSRs. Most common and highly repeated SSR motifs were identified as (A)64, (T)48, (GT)24, (GAA)31, (TTTC)24, (TTTCT)28 and (AACCAG)27. Overall, the generated information may serve as baseline information for developing SSR markers that could find applications in genomic analysis of F. oxysporum f. sp. lycopersici for better understanding of evolution, diversity analysis, population genetics, race identification and acquisition of new virulence.

scholarly journals Genome-Wide Analysis of the Five Phosphate Transporter Families in Camelina sativa and Their Expressions in Response to Low-P

2020 ◽  
Vol 21 (21) ◽  
pp. 8365
Author(s):  
Dhondup Lhamo ◽  
Qiaolin Shao ◽  
Renjie Tang ◽  
Sheng Luan
Keyword(s):  
Genomic Analysis ◽  
Nutrient Status ◽  
Camelina Sativa ◽  
Biofuel Production ◽  
Oilseed Crop ◽  
Chromosome 11 ◽  
Preferential Expression ◽  
Genome Wide ◽  
Marginal Soils ◽  
Pi Acquisition

Phosphate transporters (PHTs) play pivotal roles in phosphate (Pi) acquisition from the soil and distribution throughout a plant. However, there is no comprehensive genomic analysis of the PHT families in Camelina sativa, an emerging oilseed crop. In this study, we identified 73 CsPHT members belonging to the five major PHT families. A whole-genome triplication event was the major driving force for CsPHT expansion, with three homoeologs for each Arabidopsis ortholog. In addition, tandem gene duplications on chromosome 11, 18 and 20 further enlarged the CsPHT1 family beyond the ploidy norm. Phylogenetic analysis showed clustering of the CsPHT1 and CsPHT4 family members into four distinct groups, while CsPHT3s and CsPHT5s were clustered into two distinct groups. Promoter analysis revealed widespread cis-elements for low-P response (P1BS) specifically in CsPHT1s, consistent with their function in Pi acquisition and translocation. In silico RNA-seq analysis revealed more ubiquitous expression of several CsPHT1 genes in various tissues, whereas CsPHT2s and CsPHT4s displayed preferential expression in leaves. While several CsPHT3s were expressed in germinating seeds, most CsPHT5s were expressed in floral and seed organs. Suneson, a popular Camelina variety, displayed better tolerance to low-P than another variety, CS-CROO, which could be attributed to the higher expression of several CsPHT1/3/4/5 family genes in shoots and roots. This study represents the first effort in characterizing CsPHT transporters in Camelina, a promising polyploid oilseed crop that is highly tolerant to abiotic stress and low-nutrient status, and may populate marginal soils for biofuel production.

scholarly journals Functional genomics of autoimmune diseases

2021 ◽  
pp. annrheumdis-2019-216794
Author(s):  
Akari Suzuki ◽  
Matteo Maurizio Guerrini ◽  
Kazuhiko Yamamoto
Keyword(s):  
Autoimmune Diseases ◽  
Association Studies ◽  
Linkage Disequilibrium Block ◽  
Causal Variant ◽  
Genome Wide Association Studies ◽  
Coding Region ◽  
Risk Variants ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Long Non Coding Rna

For more than a decade, genome-wide association studies have been applied to autoimmune diseases and have expanded our understanding on the pathogeneses. Genetic risk factors associated with diseases and traits are essentially causative. However, elucidation of the biological mechanism of disease from genetic factors is challenging. In fact, it is difficult to identify the causal variant among multiple variants located on the same haplotype or linkage disequilibrium block and thus the responsible biological genes remain elusive. Recently, multiple studies have revealed that the majority of risk variants locate in the non-coding region of the genome and they are the most likely to regulate gene expression such as quantitative trait loci. Enhancer, promoter and long non-coding RNA appear to be the main target mechanisms of the risk variants. In this review, we discuss functional genetics to challenge these puzzles.

scholarly journals Genome-wide association analysis of metabolic syndrome quantitative traits in the GENNID multiethnic family study

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jia Y. Wan ◽  
Deborah L. Goodman ◽  
Emileigh L. Willems ◽  
Alexis R. Freedland ◽  
Trina M. Norden-Krichmar ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Metabolic Syndrome ◽  
Family Study ◽  
Genome Wide Association ◽  
European American ◽  
Japanese American ◽  
Genetic Associations ◽  
Chromosome 11 ◽  
Genome Wide ◽  
American Families

Abstract Background To identify genetic associations of quantitative metabolic syndrome (MetS) traits and characterize heterogeneity across ethnic groups. Methods Data was collected from GENetics of Noninsulin dependent Diabetes Mellitus (GENNID), a multiethnic resource of Type 2 diabetic families and included 1520 subjects in 259 African-American, European-American, Japanese-Americans, and Mexican-American families. We focused on eight MetS traits: weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein, triglycerides, fasting glucose, and insulin. Using genotyped and imputed data from Illumina’s Multiethnic array, we conducted genome-wide association analyses with linear mixed models for all ethnicities, except for the smaller Japanese-American group, where we used additive genetic models with gene-dropping. Results Findings included ethnic-specific genetic associations and heterogeneity across ethnicities. Most significant associations were outside our candidate linkage regions and were coincident within a gene or intergenic region, with two exceptions in European-American families: (a) within previously identified linkage region on chromosome 2, two significant GLI2-TFCP2L1 associations with weight, and (b) one chromosome 11 variant near CADM1-LINC00900 with pleiotropic blood pressure effects. Conclusions This multiethnic family study found genetic heterogeneity and coincident associations (with one case of pleiotropy), highlighting the importance of including diverse populations in genetic research and illustrating the complex genetic architecture underlying MetS.

scholarly journals Author Correction: Determinants of genome-wide distribution and evolution of uORFs in eukaryotes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hong Zhang ◽  
Yirong Wang ◽  
Xinkai Wu ◽  
Xiaolu Tang ◽  
Changcheng Wu ◽  
...  
Keyword(s):  
Wide Distribution ◽  
Genome Wide

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22435-2

scholarly journals XChromosome Effect on Maternal Recombination and Meiotic Drive in the Mouse

Genetics ◽  
2002 ◽  
Vol 161 (4) ◽  
pp. 1651-1659 ◽  
Author(s):  
Elena de la Casa-Esperón ◽  
J Concepción Loredo-Osti ◽  
Fernando Pardo-Manuel de Villena ◽  
Tammi L Briscoe ◽  
Jan Michel Malette ◽  
...  
Keyword(s):  
Mouse Chromosome ◽  
X Chromosome ◽  
Meiotic Recombination ◽  
Meiotic Drive ◽  
X Chromosome Inactivation ◽  
Chromosome Inactivation ◽  
Chromosome 11 ◽  
Genome Wide ◽  
Mouse Chromosome 11 ◽  
Segregation Of Chromosomes

AbstractWe observed that maternal meiotic drive favoring the inheritance of DDK alleles at the Om locus on mouse chromosome 11 was correlated with the X chromosome inactivation phenotype of (C57BL/ 6-Pgk1a × DDK)F1 mothers. The basis for this unexpected observation appears to lie in the well-documented effect of recombination on meiotic drive that results from nonrandom segregation of chromosomes. Our analysis of genome-wide levels of meiotic recombination in females that vary in their X-inactivation phenotype indicates that an allelic difference at an X-linked locus is responsible for modulating levels of recombination in oocytes.

scholarly journals E-MAGMA: an eQTL-informed method to identify risk genes using genome-wide association study summary statistics

2021 ◽  
Author(s):  
Zachary F Gerring ◽  
Angela Mina-Vargas ◽  
Eric R Gamazon ◽  
Eske M Derks
Keyword(s):  
Genome Wide Association ◽  
Chromosome 1 ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Tissue Specific ◽  
Complex Disorders ◽  
Risk Variants ◽  
Genome Wide ◽  
Causal Genes

Abstract Motivation Genome-wide association studies have successfully identified multiple independent genetic loci that harbour variants associated with human traits and diseases, but the exact causal genes are largely unknown. Common genetic risk variants are enriched in non-protein-coding regions of the genome and often affect gene expression (expression quantitative trait loci, eQTL) in a tissue-specific manner. To address this challenge, we developed a methodological framework, E-MAGMA, which converts genome-wide association summary statistics into gene-level statistics by assigning risk variants to their putative genes based on tissue-specific eQTL information. Results We compared E-MAGMA to three eQTL informed gene-based approaches using simulated phenotype data. Phenotypes were simulated based on eQTL reference data using GCTA for all genes with at least one eQTL at chromosome 1. We performed 10 simulations per gene. The eQTL-h2 (i.e., the proportion of variation explained by the eQTLs) was set at 1%, 2%, and 5%. We found E-MAGMA outperforms other gene-based approaches across a range of simulated parameters (e.g. the number of identified causal genes). When applied to genome-wide association summary statistics for five neuropsychiatric disorders, E-MAGMA identified more putative candidate causal genes compared to other eQTL-based approaches. By integrating tissue-specific eQTL information, these results show E-MAGMA will help to identify novel candidate causal genes from genome-wide association summary statistics and thereby improve the understanding of the biological basis of complex disorders. Availability A tutorial and input files are made available in a github repository: https://github.com/eskederks/eMAGMA-tutorial. Supplementary information Supplementary data are available at Bioinformatics online.

Genome-wide high throughput analysis of DNA methylation in eukaryotes

Methods ◽  
2009 ◽  
Vol 47 (3) ◽  
pp. 142-150 ◽  
Author(s):  
Kyle R. Pomraning ◽  
Kristina M. Smith ◽  
Michael Freitag
Keyword(s):  
Dna Methylation ◽  
High Throughput ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Genome Wide
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