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BMC Genetics

Fekadu Gadissa, Kassahun Tesfaye, Kifle Dagne, Mulatu Geleta
BACKGROUND: Plectranthus edulis (Vatke) Agnew (locally known as Ethiopian dinich or Ethiopian potato) is one of the most economically important edible tuber crops indigenous to Ethiopia. Evaluating the extent of genetic diversity within and among populations is one of the first and most important steps in breeding and conservation measures. Hence, this study was aimed at evaluating the genetic diversity and population structure of this crop using collections from diverse agro-ecologies in Ethiopia...
October 11, 2018: BMC Genetics
Ann-Kathrin Struck, Claudia Dierks, Marina Braun, Maren Hellige, Anna Wagner, Bernd Oelmaier, Andreas Beineke, Julia Metzger, Ottmar Distl
BACKGROUND: Congenital skeletal malformations represent a heterogeneous group of disorders affecting bone and cartilage development. In cattle, particular chondrodysplastic forms have been identified in several miniature breeds. In this study, a phenotypic characterization was performed of an affected Miniature Zebu calf using computed tomography, necropsy and histopathological examinations, whole genome sequencing of the case and its parents on an Illumina NextSeq 500 in 2 × 150 bp paired-end mode and validation using Sanger sequencing and a Kompetitive Allele Specific PCR assay...
October 11, 2018: BMC Genetics
James Liley
BACKGROUND: High dimensional case control studies are ubiquitous in the biological sciences, particularly genomics. To maximise power while constraining cost and to minimise type-1 error rates, researchers typically seek to replicate findings in a second experiment on independent cohorts before proceeding with further analyses. This can be an expensive procedure, particularly when control samples are difficult to recruit or ascertain; for example in inter-disease comparisons, or studies on degenerative diseases...
October 3, 2018: BMC Genetics
Katarina M Jørgensen, Vidar Wennevik, Anne Grete Eide Sørvik, Laila Unneland, Sergey Prusov, Fernando Ayllon, Kevin A Glover
BACKGROUND: Fish may display variations in ploidy, including three sets of chromosomes, known as triploidy. A recent study revealed a frequency of ~ 2% spontaneous (i.e., non-intentional) triploidy in domesticated Atlantic salmon produced in Norwegian aquaculture in the period 2007-2014. In contrast, the frequency of triploidy in wild salmon populations has not been studied thus far, and in wild populations of other organisms, it has been very rarely studied. In population genetic data sets, individuals that potentially display chromosome abnormalities, such as triploids with three alleles, are typically excluded on the premise that they may reflect polluted or otherwise compromised samples...
October 3, 2018: BMC Genetics
Signem Oney-Birol, Sorel Fitz-Gibbon, Jin-Ming Chen, Paul F Gugger, Victoria L Sork
BACKGROUND: Hybridization and introgression are common phenomena among oak species. These processes can be beneficial by introducing favorable genetic variants across species (adaptive introgression). Given that drought is an important stress, impacting physiological and morphological variation and limiting distributions, our goal was to identify drought-related genes that might exhibit patterns of introgression influenced by natural selection. Using RNAseq, we sequenced whole transcriptomes of 24 individuals from three oaks in southern California: (Quercus engelmannii, Quercus berberidifolia, Quercus cornelius-mulleri) and identified genetic variants to estimate admixture rates of all variants and those in drought genes...
October 1, 2018: BMC Genetics
Alicia N Massa, Norma C Manrique-Carpintero, Joseph Coombs, Kathleen G Haynes, Paul C Bethke, Tina L Brandt, Sanjay K Gupta, G Craig Yencho, Richard G Novy, David S Douches
BACKGROUND: Genome-wide single nucleotide polymorphism (SNP) markers coupled with allele dosage information has emerged as a powerful tool for studying complex traits in cultivated autotetraploid potato (Solanum tuberosum L., 2n = 4× = 48). To date, this approach has been effectively applied to the identification of quantitative trait loci (QTLs) underlying highly heritable traits such as disease resistance, but largely unexplored for traits with complex patterns of inheritance...
September 21, 2018: BMC Genetics
Zhi Wang, Tianqing Zhu, Wenjun Ma, Nan Wang, Guanzheng Qu, Shougong Zhang, Junhui Wang
BACKGROUND: Long non-coding RNAs (lncRNAs) have crucial roles in various biological regulatory processes. However, the study of lncRNAs is limited in woody plants. Catalpa bungei is a valuable ornamental tree with a long cultivation history in China, and a deeper understanding of the floral transition mechanism in C. bungei would be interesting from both economic and scientific perspectives. RESULTS: In this study, we categorized C. bungei buds from early flowering (EF) and normal flowering (NF) varieties into three consecutive developmental stages...
September 20, 2018: BMC Genetics
Krzysztof Goryca, Maria Kulecka, Agnieszka Paziewska, Michalina Dabrowska, Marta Grzelak, Magdalena Skrzypczak, Krzysztof Ginalski, Andrzej Mroz, Andrzej Rutkowski, Katarzyna Paczkowska, Michal Mikula, Jerzy Ostrowski
BACKGROUND: Approximately 90% of colorectal cancer (CRC) deaths are caused by tumors ability to migrate into the adjacent tissues and metastase into distant organs. More than 40 genes have been causally linked to the development of CRC but no mutations have been associated with metastasis yet. To identify molecular basis of CRC metastasis we performed whole-exome and genome-scale transcriptome sequencing of 7 liver metastases along with their matched primary tumours and normal tissue...
September 19, 2018: BMC Genetics
Svetlana Cherlin, Maggie Haitian Wang, Heike Bickeböller, Rita M Cantor
BACKGROUND: Fenofibrate (Fb) is a known treatment for elevated triglyceride (TG) levels. The Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study was designed to investigate potential contributors to the effects of Fb on TG levels. Here, we summarize the analyses of 8 papers whose authors had access to the GOLDN data and were grouped together because they pursued investigations into Fb treatment responses as part of GAW20. These papers report explorations of a variety of genetics, epigenetics, and study design questions...
September 17, 2018: BMC Genetics
Mariza de Andrade, E Warwick Daw, Aldi T Kraja, Virginia Fisher, Lan Wang, Ke Hu, Jing Li, Razvan Romanescu, Jenna Veenstra, Rui Sun, Haoyi Weng, Wenda Zhou
BACKGROUND: GAW20 working group 5 brought together researchers who contributed 7 papers with the aim of evaluating methods to detect genetic by epigenetic interactions. GAW20 distributed real data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study, including single-nucleotide polymorphism (SNP) markers, methylation (cytosine-phosphate-guanine [CpG]) markers, and phenotype information on up to 995 individuals. In addition, a simulated data set based on the real data was provided...
September 17, 2018: BMC Genetics
Saurabh Ghosh, David W Fardo
BACKGROUND: The GAW20 group formed on the theme of methods for association analyses of repeated measures comprised 4sets of investigators. The provided "real" data set included genotypes obtained from a human whole-genome association study based on longitudinal measurements of triglycerides (TGs) and high-density lipoprotein in addition to methylation levels before and after administration of fenofibrate. The simulated data set contained 200 replications of methylation levels and posttreatment TGs, mimicking the real data set...
September 17, 2018: BMC Genetics
Xuexia Wang, Felix Boekstegers, Regina Brinster
BACKGROUND: This paper summarizes the contributions from the Genome-wide Association Study group (GWAS group) of the GAW20. The GWAS group contributions focused on topics such as association tests, phenotype imputation, and application of empirical kinships. The goals of the GWAS group contributions were varied. A real or a simulated data set based on the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study was employed by different methods. Different outcomes and covariates were considered, and quality control procedures varied throughout the contributions...
September 17, 2018: BMC Genetics
Jonathan Auerbach, Richard Howey, Lai Jiang, Anne Justice, Liming Li, Karim Oualkacha, Sergi Sayols-Baixeras, Stella W Aslibekyan
BACKGROUND: Increasingly available multilayered omics data on large populations has opened exciting analytic opportunities and posed unique challenges to robust estimation of causal effects in the setting of complex disease phenotypes. The GAW20 Causal Modeling Working Group has applied complementary approaches (eg, Mendelian randomization, structural equations modeling, Bayesian networks) to discover novel causal effects of genomic and epigenomic variation on lipid phenotypes, as well as to validate prior findings from observational studies...
September 17, 2018: BMC Genetics
Haakon E Nustad, Marcio Almeida, Angelo J Canty, Marissa LeBlanc, Christian M Page, Phillip E Melton
BACKGROUND: Longitudinal data and repeated measurements in epigenome-wide association studies (EWAS) provide a rich resource for understanding epigenetics. We summarize 7 analytical approaches to the GAW20 data sets that addressed challenges and potential applications of phenotypic and epigenetic data. All contributions used the GAW20 real data set and employed either linear mixed effect (LME) models or marginal models through generalized estimating equations (GEE). These contributions were subdivided into 3 categories: (a) quality control (QC) methods for DNA methylation data; (b) heritability estimates pretreatment and posttreatment with fenofibrate; and (c) impact of drug response pretreatment and posttreatment with fenofibrate on DNA methylation and blood lipids...
September 17, 2018: BMC Genetics
Angga M Fuady, Samantha Lent, Chloé Sarnowski, Nathan L Tintle
BACKGROUND: The rise in popularity and accessibility of DNA methylation data to evaluate epigenetic associations with disease has led to numerous methodological questions. As part of GAW20, our working group of 8 research groups focused on gene searching methods. RESULTS: Although the methods were varied, we identified 3 main themes within our group. First, many groups tackled the question of how best to use pedigree information in downstream analyses, finding that (a) the use of kinship matrices is common practice, (b) ascertainment corrections may be necessary, and (c) pedigree information may be useful for identifying parent-of-origin effects...
September 17, 2018: BMC Genetics
Runmin Wei, Yanyan Wu
BACKGROUND: Identification of interactions between epigenetic factors and treatments might lead to personalized intervention of diseases. This paper aims to examine the modification effect of fenofibrate therapy on the association of methylation levels and fasting blood triglycerides (TG), and the related biological pathways among methylation sites. RESULTS: Mixed-effects models were employed to assess pre- and posttreatment associations and drug modification effects simultaneously...
September 17, 2018: BMC Genetics
Samantha Lent, Hanfei Xu, Lan Wang, Zhe Wang, Chloé Sarnowski, Marie-France Hivert, Josée Dupuis
BACKGROUND: Single-probe analyses in epigenome-wide association studies (EWAS) have identified associations between DNA methylation and many phenotypes, but do not take into account information from neighboring probes. Methods to detect differentially methylated regions (DMRs) (clusters of neighboring probes associated with a phenotype) may provide more power to detect associations between DNA methylation and diseases or phenotypes of interest. RESULTS: We proposed a novel approach, GlobalP, and perform comparisons with 3 methods-DMRcate, Bumphunter, and comb-p-to identify DMRs associated with log triglycerides (TGs) in real GAW20 data before and after fenofibrate treatment...
September 17, 2018: BMC Genetics
Burcu Darst, Corinne D Engelman, Ye Tian, Justo Lorenzo Bermejo
BACKGROUND: Multiple layers of genetic and epigenetic variability are being simultaneously explored in an increasing number of health studies. We summarize here different approaches applied in the Data Mining and Machine Learning group at the GAW20 to integrate genome-wide genotype and methylation array data. RESULTS: We provide a non-intimidating introduction to some frequently used methods to investigate high-dimensional molecular data and compare the different approaches tried by group members: random forest, deep learning, cluster analysis, mixed models, and gene-set enrichment analysis...
September 17, 2018: BMC Genetics
Xiaoxuan Xia, Haoyi Weng, Ruoting Men, Rui Sun, Benny Chung Ying Zee, Ka Chun Chong, Maggie Haitian Wang
BACKGROUND: An accumulation of evidence has revealed the important role of epigenetic factors in explaining the etiopathogenesis of human diseases. Several empirical studies have successfully incorporated methylation data into models for disease prediction. However, it is still a challenge to integrate different types of omics data into prediction models, and the contribution of methylation information to prediction remains to be fully clarified. RESULTS: A stratified drug-response prediction model was built based on an artificial neural network to predict the change in the circulating triglyceride level after fenofibrate intervention...
September 17, 2018: BMC Genetics
Lindsay Fernández-Rhodes, Annie Green Howard, Ran Tao, Kristin L Young, Mariaelisa Graff, Allison E Aiello, Kari E North, Anne E Justice
BACKGROUND: Transgenerational epigenetic inheritance has been posited as a possible contributor to the observed heritability of metabolic syndrome (MetS). Yet the extent to which estimates of epigenetic inheritance for DNA methylation sites are inflated by environmental and genetic covariance within families is still unclear. We applied current methods to quantify the environmental and genetic contributors to the observed heritability and familial correlations of four previously associated MetS methylation sites at three genes (CPT1A, SOCS3 and ABCG1) using real data made available through the GAW20...
September 17, 2018: BMC Genetics
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