Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility

Identification of Differentially Evolved Genes: An Alternative Approach to Detection of Accelerated Molecular Evolution from Genome-Wide Comparative Data

One of the most important measures for detecting molecular adaptations between species/lineages at the gene level is the comparison of relative fixation rates of synonymous (dS) and non-synonymous (dN) mutations. This study shows that the branch model is sensitive to tree topology and proposes an alternative approach, devogs, which does not require phylogenetic topology for analysis. We compared devogs with a branch model method using virtual data and a varying ω ratio, in which parameters were obtained from real data. The positive predictive value, sensitivity, and specificity of the branch model were affected by the phylogenic tree topology. Devogs showed greater positive predictive value, whereas the branch model method had greater sensitivity. In a working example using devogs, a group of human RNA polymerase II-related genes, which are important in mediating alternative splicing, were significantly accelerated compared to four other mammals

A set of stage-specific gene transcripts identified in EK stage X and HH stage 3 chick embryos

<p>Abstract</p> <p>Background</p> <p>The embryonic developmental process in avian species is quite different from that in mammals. The first cleavage begins 4 h after fertilization, but the first differentiation does not occur until laying of the egg (Eyal-Giladi and Kochav (EK) stage X). After 12 to 13 h of incubation (Hamburger and Hamilton (HH) stage 3), the three germ layers form and germ cell segregation in the early chick embryo are completed. Thus, to identify genes associated with early embryonic development, we compared transcript expression patterns between undifferentiated (stage X) and differentiated (HH stage 3) embryos.</p> <p>Results</p> <p>Microarray analysis primarily showed 40 genes indicating the significant changes in expression levels between stage X and HH stage 3, and 80% of the genes (32/40) were differentially expressed with more than a twofold change. Among those, 72% (23/32) were relatively up-regulated at stage X compared to HH stage 3, while 28% (9/32) were relatively up-regulated at HH stage 3 compared to stage X. Verification and gene expression profiling of these GeneChip expression data were performed using quantitative RT-PCR for 32 genes at developmental four points; stage X (0 h), HH stage 3 (12 h), HH stage 6 (24 h), and HH stage 9 (30 h). Additionally, we further analyzed four genes with less than twofold expression increase at HH stage 3. As a result, we identified a set of stage-specific genes during the early chick embryo development; 21 genes were relatively up-regulated in the stage X embryo and 12 genes were relatively up-regulated in the HH stage 3 embryo based on both results of microarray and quantitative RT-PCR.</p> <p>Conclusion</p> <p>We identified a set of genes with stage-specific expression from microarray Genechip and quantitative RT-PCR. Discovering stage-specific genes will aid in uncovering the molecular mechanisms involved the formation of the three germ layers and germ cell segregation in the early chick embryos.</p

Author Correction: Mitonuclear incompatibility as a hidden driver behind the genome ancestry of African admixed cattle

The original article contained minor errors in Figs. 1 and 3 which have both since been corrected

Genome-wide Association Study of Integrated Meat Quality-related Traits of the Duroc Pig Breed

The increasing importance of meat quality has implications for animal breeding programs. Research has revealed much about the genetic background of pigs, and many studies have revealed the importance of various genetic factors. Since meat quality is a complex trait which is affected by many factors, consideration of the overall phenotype is very useful to study meat quality. For integrating the phenotypes, we used principle component analysis (PCA). The significant SNPs refer to results of the GRAMMAR method against PC1, PC2 and PC3 of 14 meat quality traits of 181 Duroc pigs. The Genome-wide association study (GWAS) found 26 potential SNPs affecting various meat quality traits. The loci identified are located in or near 23 genes. The SNPs associated with meat quality are in or near five genes (ANK1, BMP6, SHH, PIP4K2A, and FOXN2) and have been reported previously. Twenty-five of the significant SNPs also located in meat quality-related QTL regions, these result supported the QTL effect indirectly. Each single gene typically affects multiple traits. Therefore, it is a useful approach to use integrated traits for the various traits at the same time. This innovative approach using integrated traits could be applied on other GWAS of complex-traits including meat-quality, and the results will contribute to improving meat-quality of pork

Genome-wide Association Study of Chicken Plumage Pigmentation

To increase plumage color uniformity and understand the genetic background of Korean chickens, we performed a genome-wide association study of different plumage color in Korean native chickens. We analyzed 60K SNP chips on 279 chickens with GEMMA methods for GWAS and estimated the genetic heritability for plumage color. The estimated heritability suggests that plumage coloration is a polygenic trait. We found new loci associated with feather pigmentation at the genome-wide level and from the results infer that there are additional genetic effect for plumage color. The results will be used for selecting and breeding chicken for plumage color uniformity

Deleted copy number variation of Hanwoo and Holstein using next generation sequencing at the population level

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.Abstract Background Copy number variation (CNV), a source of genetic diversity in mammals, has been shown to underlie biological functions related to production traits. Notwithstanding, there have been few studies conducted on CNVs using next generation sequencing at the population level. Results Illumina NGS data was obtained for ten Holsteins, a dairy cattle, and 22 Hanwoo, a beef cattle. The sequence data for each of the 32 animals varied from 13.58-fold to almost 20-fold coverage. We detected a total of 6,811 deleted CNVs across the analyzed individuals (average length = 2732.2 bp) corresponding to 0.74% of the cattle genome (18.6 Mbp of variable sequence). By examining the overlap between CNV deletion regions and genes, we selected 30 genes with the highest deletion scores. These genes were found to be related to the nervous system, more specifically with nervous transmission, neuron motion, and neurogenesis. We regarded these genes as having been effected by the domestication process. Further analysis of the CNV genotyping information revealed 94 putative selected CNVs and 954 breed-specific CNVs. Conclusions This study provides useful information for assessing the impact of CNVs on cattle traits using NGS at the population level

Widespread false gene gains caused by duplication errors in genome assemblies

Abstract Background False duplications in genome assemblies lead to false biological conclusions. We quantified false duplications in popularly used previous genome assemblies for platypus, zebra finch, and Annas Hummingbird, and their new counterparts of the same species generated by the Vertebrate Genomes Project, of which the Vertebrate Genomes Project pipeline attempted to eliminate false duplications through haplotype phasing and purging. These assemblies are among the first generated by the Vertebrate Genomes Project where there was a prior chromosomal level reference assembly to compare with. Results Whole genome alignments revealed that 4 to 16% of the sequences are falsely duplicated in the previous assemblies, impacting hundreds to thousands of genes. These lead to overestimated gene family expansions. The main source of the false duplications is heterotype duplications, where the haplotype sequences were relatively more divergent than other parts of the genome leading the assembly algorithms to classify them as separate genes or genomic regions. A minor source is sequencing errors. Ancient ATP nucleotide binding gene families have a higher prevalence of false duplications compared to other gene families. Although present in a smaller proportion, we observe false duplications remaining in the Vertebrate Genomes Project assemblies that can be identified and purged. Conclusions This study highlights the need for more advanced assembly methods that better separate haplotypes and sequence errors, and the need for cautious analyses on gene gains

Exploring evidence of positive selection reveals genetic basis of meat quality traits in Berkshire pigs through whole genome sequencing

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Abstract Background Natural and artificial selection following domestication has led to the existence of more than a hundred pig breeds, as well as incredible variation in phenotypic traits. Berkshire pigs are regarded as having superior meat quality compared to other breeds. As the meat production industry seeks selective breeding approaches to improve profitable traits such as meat quality, information about genetic determinants of these traits is in high demand. However, most of the studies have been performed using trained sensory panel analysis without investigating the underlying genetic factors. Here we investigate the relationship between genomic composition and this phenotypic trait by scanning for signatures of positive selection in whole-genome sequencing data. Results We generated genomes of 10 Berkshire pigs at a total of 100.6 coverage depth, using the Illumina Hiseq2000 platform. Along with the genomes of 11 Landrace and 13 Yorkshire pigs, we identified genomic variants of 18.9 million SNVs and 3.4 million Indels in the mapped regions. We identified several associated genes related to lipid metabolism, intramuscular fatty acid deposition, and muscle fiber type which attribute to pork quality (TG, FABP1, AKIRIN2, GLP2R, TGFBR3, JPH3, ICAM2, and ERN1) by applying between population statistical tests (XP-EHH and XP-CLR). A statistical enrichment test was also conducted to detect breed specific genetic variation. In addition, de novo short sequence read assembly strategy identified several candidate genes (SLC25A14, IGF1, PI4KA, CACNA1A) as also contributing to lipid metabolism. Conclusions Results revealed several candidate genes involved in Berkshire meat quality; most of these genes are involved in lipid metabolism and intramuscular fat deposition. These results can provide a basis for future research on the genomic characteristics of Berkshire pigs