Genotyping Efforts Research Articles

Trait mapping in diverse arthropods by bulked segregant analysis.

Bulked segregant analysis (BSA) is a cross-based method for genetic mapping in sexually reproducing organisms. The method's use of bulked (pooled) samples markedly reduces the genotyping effort associated with traditional linkage mapping studies. Further, it can be applied to species with life histories or physical attributes (as for micro-insects) that render genetic mapping with other methods impractical. Recent studies in both insects and mites have revealed that advanced BSA experimental designs can resolve causal loci to narrow genomic intervals, facilitating follow-up investigations. As high-quality genomes become more widely available, BSA methods are poised to become an increasingly important tool for the rapid mapping of both monogenic and polygenic traits in diverse arthropod species.

Detailed characterization of repeat motifs of nine canid microsatellite loci in African painted dogs (Lycaon pictus)

Microsatellite loci identified in domestic species are frequently amplified and genotyped in wildlife species for which limited genomic information is available. However, even when the loci amplify successfully, genotyping them accurately in novel species can be complicated when the repeat motif is unknown or when the expected product size in the new target species differs from that reported for the domestic species from which the locus was identified. In this study, we amplified nine microsatellite loci that were identified previously in the domestic dog and genotyped them in 114 endangered African painted dog (Lycaon pictus) individuals. Although primer sequences for these loci were published, minimal details about the repeat motifs were available in the literature, and some of our product sizes differed substantially from those reported for the domestic dog, which complicated initial multiplexing and genotyping efforts. We therefore cloned and sequenced these loci to characterize the repeat structures and amplicon size for each locus, specific to L. pictus. Seven of the nine loci contained imperfect, compound repeats that often were a combination of di- and tetranucleotide repeats or which contained strings of single nucleotides. The resulting amplicons were also considerably smaller or larger than expected based on the homologous domestic dog loci. This information may assist other researchers who are conducting molecular studies on this endangered species or on other closely related canids.

Population Levels Assessment of the Distribution of Disease-Associated Variants With Emphasis on Armenians - A Machine Learning Approach.

Background: During the last decades a number of genome-wide association studies (GWASs) has identified numerous single nucleotide polymorphisms (SNPs) associated with different complex diseases. However, associations reported in one population are often conflicting and did not replicate when studied in other populations. One of the reasons could be that most GWAS employ a case-control design in one or a limited number of populations, but little attention was paid to the global distribution of disease-associated alleles across different populations. Moreover, the majority of GWAS have been performed on selected European, African, and Chinese populations and the considerable number of populations remains understudied.Aim: We have investigated the global distribution of so far discovered disease-associated SNPs across worldwide populations of different ancestry and geographical regions with a special focus on the understudied population of Armenians.Data and Methods: We have used genotyping data from the Human Genome Diversity Project and of Armenian population and combined them with disease-associated SNP data taken from public repositories leading to a final dataset of 44,234 markers. Their frequency distribution across 1039 individuals from 53 populations was analyzed using self-organizing maps (SOM) machine learning. Our SOM portrayal approach reduces data dimensionality, clusters SNPs with similar frequency profiles and provides two-dimensional data images which enable visual evaluation of disease-associated SNPs landscapes among human populations.Results: We find that populations from Africa, Oceania, and America show specific patterns of minor allele frequencies of disease-associated SNPs, while populations from Europe, Middle East, Central South Asia, and Armenia mostly share similar patterns. Importantly, different sets of SNPs associated with common polygenic diseases, such as cancer, diabetes, neurodegeneration in populations from different geographic regions. Armenians are characterized by a set of SNPs that are distinct from other populations from the neighboring geographical regions.Conclusion: Genetic associations of diseases considerably vary across populations which necessitates health-related genotyping efforts especially for so far understudied populations. SOM portrayal represents novel promising methods in population genetic research with special strength in visualization-based comparison of SNP data.

AB014. S3A-3. Precision medicine on the horizon for cholangiocarcinoma

: Cholangiocarcinoma (CCA) is a molecularly heterogenous group of tumors, and tumor genotyping efforts have uncovered multiple actionable targets in both intrahepatic and extrahepatic tumors. IDH1 mutations, FGFR2 fusions, and BRAF V600E mutations are among the most promising targets to date in CCA-specific clinical trials and cohorts, and multiple agents targeting these gene alterations are in development. For patients with IDH1 mutant advanced refractory CCA, a phase III trial of the IDH1 inhibitor AG120 versus placebo recently completed accrual, and the results are anticipated. In FGFR2 fusion positive disease, multiple phase II and III efforts are underway to evaluate the efficacy of selective oral FGFR small molecular inhibitors. In patients with BRAF V600E mutant CCA, the combination of dabrafenib and trametinib has shown promise in a basket trial with a CCA cohort. Additional agents are also under investigation to in patients with alterations in HER2, PIK3CA, MET, and CDKN2A and also in patients with mutations in DNA damage repair pathway or chromatin remodeling genes.

A catalog of annotated high-confidence SNPs from exome capture and sequencing reveals highly polymorphic genes in Norway spruce (Picea abies)

BackgroundNorway spruce [Picea abies (L.) Karst.] is ecologically and economically one of the most important conifer worldwide. Our main goal was to develop a large catalog of annotated high confidence gene SNPs that should sustain the development of genomic tools for the conservation of natural and domesticated genetic diversity resources, and hasten tree breeding efforts in this species.ResultsTargeted sequencing was achieved by capturing P. abies exome with probes previously designed from the sequenced transcriptome of white spruce (Picea glauca (Moench) Voss). Capture efficiency was high (74.5%) given a high level of exome conservation between the two species. Using stringent criteria, we delimited a set of 61,771 high-confidence SNPs across 13,543 genes. To validate SNPs, a high-throughput genotyping array was developed for a subset of 5571 predicted SNPs representing as many different gene loci, and was used to genotype over 1000 trees. The estimated true positive rate of the resource was 84.2%, which was comparable with the genotyping success rate obtained for P. abies control SNPs recycled from previous genotyping efforts. We also analyzed SNP abundance across various gene functional categories. Several GO terms and gene families involved in stress response were found over-represented in highly polymorphic genes.ConclusionThe annotated high-confidence SNP catalog developed herein represents a valuable genomic resource, being representative of over 13 K genes distributed across the P. abies genome. This resource should serve a variety of population genomics and breeding applications in Norway spruce.

Benefits of testing in both bio-secure and production environments in genomic selection breeding programs for commercial broiler chicken

BackgroundA breeding program for commercial broiler chicken that is carried out under strict biosecure conditions can show reduced genetic gain due to genotype by environment interactions (G × E) between bio-secure (B) and commercial production (C) environments. Accuracy of phenotype-based best linear unbiased prediction of breeding values of selection candidates using sib-testing in C is low. Genomic prediction based on dense genetic markers may improve accuracy of selection. Stochastic simulation was used to explore the benefits of genomic selection in breeding schemes for broiler chicken that include birds in both B and C for assessment of phenotype.ResultsWhen genetic correlations (r_{g}) between traits measured in B and C were equal to 0.5 and 0.7, breeding schemes with 15, 30 and 45% of birds assessed in C resulted in higher genetic gain for performance in C compared to those without birds in C. The optimal proportion of birds phenotyped in C for genetic gain was 30%. When the proportion of birds in C was optimal and genotyping effort was limited, allocating 30% of the genotyping effort to birds in C was also the optimal genotyping strategy for genetic gain. When r_{g} was equal to 0.9, genetic gain for performance in C was not improved with birds in C compared to schemes without birds in C. Increasing the heritability of traits assessed in C increased genetic gain significantly. Rates of inbreeding decreased when the proportion of birds in C increased because of a lower selection intensity among birds retained in B and a reduction in the probability of co-selecting close relatives.ConclusionsIf G × E interactions (r_{g} of 0.5 and 0.7) are strong, a genomic selection scheme in which 30% of the birds hatched are phenotyped in C has larger genetic gain for performance in C compared to phenotyping all birds in B. Rates of inbreeding decreased as the proportion of birds moved to C increased from 15 to 45%.

Giardia duodenalis in primates: Classification and host specificity based on phylogenetic analysis of sequence data.

Giardia duodenalis colonizes the gastrointestinal tract of a wide range of hosts, including humans and other primates. It is grouped into eight different Assemblages and, beyond that, into a number of sub-Assemblages, defined ad hoc on the basis of genetic differences; these various groups are often considered to be associated with a specific restricted host range. The aim of this study was to use publicly available genotyping data to investigate the relatedness of human and non-human primate (NHP) Giardia isolates in order to evaluate the usefulness of current taxonomic classification and to assess whether there is potential for zoonotic transmission between humans and NHP. Our final data set consisted of sequence data from 165 isolates, 111 from NHP and 54 from humans. Assemblages were well defined, but sub-Assemblages across Assemblage B were not resolved. Although sub-Assemblages AI and AII were resolved, the terms were not found to capture any useful molecular or host/deme properties. In the phylogenetic tree, NHP isolates were scattered among human isolates across Assemblages A and B, and were even found in Assemblage E. We conclude that there does not appear to be significant molecular distinction between human and NHP Giardia isolates across these four molecular markers. Thus, on the basis of these markers, we cannot exclude a risk for zoonotic and anthropozoonotic transmission of Assemblages A and B isolates, irrespective of sub-Assemblage classification. We further evaluated the relative merit of the four genes used in genotyping studies. The tpi, gdh and bg genes gave relatively congruent tree topologies, but the SSU gene did not resolve Assemblages according to the current classification. Future genotyping efforts should aim for multilocus or whole-genome approaches and, in particular, use of the SSU gene as the sole marker should be avoided when possible.

Evaluation of the potential use of a meta-population for genomic selection in autochthonous beef cattle populations

This study investigated the potential application of genomic selection under a multi-breed scheme in the Spanish autochthonous beef cattle populations using a simulation study that replicates the structure of linkage disequilibrium obtained from a sample of 25 triplets of sire/dam/offspring per population and using the BovineHD Beadchip. Purebred and combined reference sets were used for the genomic evaluation and several scenarios of different genetic architecture of the trait were investigated. The single-breed evaluations yielded the highest within-breed accuracies. Across breed accuracies were found low but positive on average confirming the genetic connectedness between the populations. If the same genotyping effort is split in several populations, the accuracies were lower when compared with single-breed evaluation, but showed a small advantage over small-sized purebred reference sets over the accuracies of subsequent generations. Besides, the genetic architecture of the trait did not show any relevant effect on the accuracy with the exception of rare variants, which yielded slightly lower results and higher loss of predictive ability over the generations.

Profiling Celiac Disease-Related Transcriptional Changes.

Celiac disease (CD) is a chronic, autoimmune disease of the small intestine with a strong but complex genetic component. The disease is triggered by the consumption of dietary gluten through the presentation of immunogenic gliadin peptides to T helper lymphocytes by HLA-DQ2 and DQ8 heterodimers, which are the major contributors to the genetic risk. Recent large-scale genotyping efforts have identified a large number of additional association signals, but the functional role of the underlying genes in the pathogenesis of the disease is still unclear. In the last years, several whole transcriptome analyses have been performed in different tissues, including whole duodenal biopsies, isolated gut epithelial cells or peripheral blood from gluten-consuming CD patients at diagnosis, treated patients on gluten-free diet and nonceliac controls, sometimes after in vitro challenge with gluten-derived gliadin peptides. Although the results from the different experiments are difficult to reconcile, the main findings point to an exacerbation of the immune response, together with the dysregulation of signaling and cell cycle pathways. The effect of associated SNPs on the expression of candidate genes and the role of the noncoding genome are the new territories that the CD research community has only begun to explore.

Abstract LB-161: GAME-ON and OncoArray: Understanding the genetic architecture of cancer risk

Abstract Most common cancers develop as a result of complex interactions among environmental exposures and genetic susceptibility variants. Hundreds of common, low penetrance variants have been identified by genetic association studies, and the discovery and subsequent analyses of these variants has led to and will continue to contribute to new insights into cancer risk. The NCI’s Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative was focused on five common cancers - breast, colorectal, lung, prostate, and ovarian - and included three research areas: meta-analysis of GWAS data, functional analysis of genetic susceptibility variants, and clinical and epidemiological studies of these cancer types. As part of GAME-ON, the OncoArray consortium undertook an extensive genotyping effort to enable new discoveries about the genetic architecture and mechanisms underlying several cancer types by discovering new common and rare susceptibility variants through fine-mapping and high density genotyping. The OncoArray data represents a valuable resource for the research community and will enable a wide range of future studies of genetic susceptibility to cancer, including functional annotation of risk loci, analysis of shared heritability across cancers, risk modeling, and analyses of differences in genetic risk attributable to ancestry. The OncoArray consortium was an international effort that accomplished genotyping of over 500K SNPs in over 500K cases of common cancers and cancer-free controls. The cancer types genotyped included the five common cancers from the GAME-ON initiative and several others, such as endometrial, pancreatic cancer, and glioma. SNPs were chosen based on analyses by GAME-ON members and included variants from loci identified in previous association studies, candidate rare variants from whole genome and whole exome sequencing, variants with potential functional significance, and several pharmacogenomics variants. Tagging SNPs that could capture variability for Asian and African descent populations also were included, as were loci of interest to cancer related phenotypes, such as drug metabolism and radiation response. Genotyping was conducted at 8 sites, primarily at the Center for Inherited Disease Research and included QC measures to ensure comparability across genotyping sites. The data are available at the NIH’s Database of Genotypes and Phenotypes (dbGaP). Citation Format: Stefanie A. Nelson, Charlisse Caga-Anan, Danielle Daee, Maura Kate Costello, Daniela Seminara, Christopher I. Amos, Stephen B. Gruber, Christopher Haiman, David Hunter, Peter Kraft, Thomas Sellers, Elizabeth M. Gillanders. GAME-ON and OncoArray: Understanding the genetic architecture of cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-161. doi:10.1158/1538-7445.AM2017-LB-161

Implications of hepatitis C virus subtype 1a migration patterns for virus genetic sequencing policies in Italy

BackgroundIn-depth phylogeographic analysis can reveal migration patterns relevant for public health planning. Here, as a model, we focused on the provenance, in the current Italian HCV subtype 1a epidemic, of the NS3 resistance-associated variant (RAV) Q80K, known to interfere with the action of NS3/4A protease inhibitor simeprevir. HCV1a migration patterns were analysed using Bayesian phylodynamic tools, capitalising on newly generated and publicly available time and geo-referenced NS3 encoding virus genetic sequence data.ResultsOur results showed that both immigration and local circulation fuel the current Italian HCV1a epidemic. The United States and European continental lineages dominate import into Italy, with the latter taking the lead from the 1970s onwards. Since similar migration patterns were found for Q80K and other lineages, no clear differentiation of the risk for failing simeprevir can be made between patients based on their migration and travel history. Importantly, since HCV only occasionally recombines, these results are readily transferable to the genetic sequencing policy concerning NS5A RAVs.ConclusionsThe patient migration and travel history cannot be used to target only part of the HCV1a infected population for drug resistance testing before start of antiviral therapy. Consequently, it may be cost-effective to expand genotyping efforts to all HCV1a infected patients eligible for simeprevir-based therapies.

Single-Step BLUP with Varying Genotyping Effort in Open-Pollinated Picea glauca.

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce (Picea glauca) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm.

Phylogeography of human Y-chromosome haplogroup Q3-L275 from an academic/citizen science collaboration

BackgroundThe Y-chromosome haplogroup Q has three major branches: Q1, Q2, and Q3. Q1 is found in both Asia and the Americas where it accounts for about 90% of indigenous Native American Y-chromosomes; Q2 is found in North and Central Asia; but little is known about the third branch, Q3, also named Q1b-L275. Here, we combined the efforts of population geneticists and genetic genealogists to use the potential of full Y-chromosome sequencing for reconstructing haplogroup Q3 phylogeography and suggest possible linkages to events in population history.ResultsWe analyzed 47 fully sequenced Y-chromosomes and reconstructed the haplogroup Q3 phylogenetic tree in detail. Haplogroup Q3-L275, derived from the oldest known split within Eurasian/American haplogroup Q, most likely occurred in West or Central Asia in the Upper Paleolithic period. During the Mesolithic and Neolithic epochs, Q3 remained a minor component of the West Asian Y-chromosome pool and gave rise to five branches (Q3a to Q3e), which spread across West, Central and parts of South Asia. Around 3–4 millennia ago (Bronze Age), the Q3a branch underwent a rapid expansion, splitting into seven branches, some of which entered Europe. One of these branches, Q3a1, was acquired by a population ancestral to Ashkenazi Jews and grew within this population during the 1st millennium AD, reaching up to 5% in present day Ashkenazi.ConclusionsThis study dataset was generated by a massive Y-chromosome genotyping effort in the genetic genealogy community, and phylogeographic patterns were revealed by a collaboration of population geneticists and genetic genealogists. This positive experience of collaboration between academic and citizen science provides a model for further joint projects. Merging data and skills of academic and citizen science promises to combine, respectively, quality and quantity, generalization and specialization, and achieve a well-balanced and careful interpretation of the paternal-side history of human populations.

Whole Genome Amplification and Reduced-Representation Genome Sequencing of Schistosoma japonicum Miracidia

BackgroundIn areas where schistosomiasis control programs have been implemented, morbidity and prevalence have been greatly reduced. However, to sustain these reductions and move towards interruption of transmission, new tools for disease surveillance are needed. Genomic methods have the potential to help trace the sources of new infections, and allow us to monitor drug resistance. Large-scale genotyping efforts for schistosome species have been hindered by cost, limited numbers of established target loci, and the small amount of DNA obtained from miracidia, the life stage most readily acquired from humans. Here, we present a method using next generation sequencing to provide high-resolution genomic data from S. japonicum for population-based studies.Methodology/Principal FindingsWe applied whole genome amplification followed by double digest restriction site associated DNA sequencing (ddRADseq) to individual S. japonicum miracidia preserved on Whatman FTA cards. We found that we could effectively and consistently survey hundreds of thousands of variants from 10,000 to 30,000 loci from archived miracidia as old as six years. An analysis of variation from eight miracidia obtained from three hosts in two villages in Sichuan showed clear population structuring by village and host even within this limited sample.Conclusions/SignificanceThis high-resolution sequencing approach yields three orders of magnitude more information than microsatellite genotyping methods that have been employed over the last decade, creating the potential to answer detailed questions about the sources of human infections and to monitor drug resistance. Costs per sample range from $50-$200, depending on the amount of sequence information desired, and we expect these costs can be reduced further given continued reductions in sequencing costs, improvement of protocols, and parallelization. This approach provides new promise for using modern genome-scale sampling to S. japonicum surveillance, and could be applied to other schistosome species and other parasitic helminthes.

Genetic Mapping by Bulk Segregant Analysis in Drosophila: Experimental Design and Simulation-Based Inference.

Identifying the genomic regions that underlie complex phenotypic variation is a key challenge in modern biology. Many approaches to quantitative trait locus mapping in animal and plant species suffer from limited power and genomic resolution. Here, I investigate whether bulk segregant analysis (BSA), which has been successfully applied for yeast, may have utility in the genomic era for trait mapping in Drosophila (and other organisms that can be experimentally bred in similar numbers). I perform simulations to investigate the statistical signal of a quantitative trait locus (QTL) in a wide range of BSA and introgression mapping (IM) experiments. BSA consistently provides more accurate mapping signals than IM (in addition to allowing the mapping of multiple traits from the same experimental population). The performance of BSA and IM is maximized by having multiple independent crosses, more generations of interbreeding, larger numbers of breeding individuals, and greater genotyping effort, but is less affected by the proportion of individuals selected for phenotypic extreme pools. I also introduce a prototype analysis method for simulation-based inference for BSA mapping (SIBSAM). This method identifies significant QTL and estimates their genomic confidence intervals and relative effect sizes. Importantly, it also tests whether overlapping peaks should be considered as two distinct QTL. This approach will facilitate improved trait mapping in Drosophila and other species for which hundreds or thousands of offspring (but not millions) can be studied.

Single nucleotide polymorphism coverage and inference of N-acetyltransferase-2 acetylator phenotypes in wordwide population groups.

Several algorithms have been proposed to reduce the genotyping effort and cost, while retaining the accuracy of N-acetyltransferase-2 (NAT2) phenotype prediction. Data from the 1000 Genomes (1KG) project and an admixed cohort of Black Brazilians were used to assess the accuracy of NAT2 phenotype prediction using algorithms based on paired single nucleotide polymorphisms (SNPs) (rs1041983 and rs1801280) or a tag SNP (rs1495741). NAT2 haplotypes comprising SNPs rs1801279, rs1041983, rs1801280, rs1799929, rs1799930, rs1208 and rs1799931 were assigned according to the arylamine N-acetyltransferases database. Contingency tables were used to visualize the agreement between the NAT2 acetylator phenotypes on the basis of these haplotypes versus phenotypes inferred by the prediction algorithms. The paired and tag SNP algorithms provided more than 96% agreement with the 7-SNP derived phenotypes in Europeans, East Asians, South Asians and Admixed Americans, but discordance of phenotype prediction occurred in 30.2 and 24.8% 1KG Africans and in 14.4 and 18.6% Black Brazilians, respectively. Paired SNP panel misclassification occurs in carriers of NATs haplotypes *13A (282T alone), *12B (282T and 803G), *6B (590A alone) and *14A (191A alone), whereas haplotype *14, defined by the 191A allele, is the major culprit of misclassification by the tag allele. Both the paired SNP and the tag SNP algorithms may be used, with economy of scale, to infer NAT2 acetylator phenotypes, including the ultra-slow phenotype, in European, East Asian, South Asian and American populations represented in the 1KG cohort. Both algorithms, however, perform poorly in populations of predominant African descent, including admixed African-Americans, African Caribbeans and Black Brazilians.

Partial genotyping at polymorphic markers can improve heritability estimates in sibling groups

Accurate estimates of heritability (h2) are necessary to assess adaptive responses of populations and evolution of fitness-related traits in changing environments. For plants, h2 estimates generally rely on maternal progeny designs, assuming that offspring are either half-sibs or unrelated. However, plant mating systems often depart from half-sib assumptions, this can bias h2 estimates. Here, we investigate how to accurately estimate h2 in nonmodel species through the analysis of sibling designs with a moderate genotyping effort. We performed simulations to investigate how microsatellite marker information available for only a subset of offspring can improve h2 estimates based on maternal progeny designs in the presence of nonrandom mating, inbreeding in the parental population or maternal effects. We compared the basic family method, considering or not adjustments based on average relatedness coefficients, and methods based on the animal model. The animal model was used with average relatedness information, or with hybrid relatedness information: associating one-generation pedigree and family assumptions, or associating one-generation pedigree and average relatedness coefficients. Our results highlighted that methods using marker-based relatedness coefficients performed as well as pedigree-based methods in the presence of nonrandom mating (i.e. unequal male reproductive contributions, selfing), offering promising prospects to investigate insitu heritabilities in natural populations. In the presence of maternal effects, only the use of pairwise relatednesses through pedigree information improved the accuracy of h2 estimates. In that case, the amount of father-related offspring in the sibling design is the most critical. Overall, we showed that the method using both one-generation pedigree and average relatedness coefficients was the most robust to various ecological scenarios.

Differential expression of six genes in fat-type Hungarian Mangalica and other pigs

Abstract. In order to identify potential variances in gene expression of phenotypically different pig breeds, six fat-metabolism-related genes were analyzed in backfat and muscle tissues of fat-type Mangalica (MAN), Mangalica × Duroc (MD), and lean-type Hungarian Large White (HLW) and Pietrain × Duroc (PD) pigs by means of quantitative reverse transcription PCR (qRT-PCR). Higher (P < 0.05) adipocyte fatty-acid-binding protein (A-FABP) expression was observed in backfat and muscle tissues of purebred and crossbred MAN than in those of HLW and PD. In all breeds and crosses, adiponectin (ADIPOQ) was predominantly expressed in backfat at a similar level (P > 0.05), whereas muscle ADIPOQ expression was highest (P < 0.05) in MAN and MD. Levels of fatty acid synthase (FASN) mRNA were greatest in MAN, moderate in MD, and lowest in HLW and PD backfat and muscle. The fat mass and obesity-associated gene (FTO) was more abundant in MAN and MD backfat, whereas muscle expressions did not differ (P > 0.05) between breeds. Regarding leptin (LEP) expression, MAN produced the greatest levels in backfat, while HLW produced the lowest. In muscle, highest LEP was detected in MAN and MD. Between groups, perilipin 2 (PLIN2) was expressed similarly in backfat; however, PLIN2 was more abundant in muscle of MAN and MD than in that of HLW and PD. Differences in gene expression can contribute to the development of the characteristic fatty phenotype in MAN pigs. The identification of differentially expressed genes facilitates targeted sequencing and genotyping efforts for further studies.

MAPK1/ERK2 as novel target genes for pain in head and neck cancer patients.

BackgroundGenetic susceptibility plays an important role in the risk of developing pain in individuals with cancer. As a complex trait, multiple genes underlie this susceptibility. We used gene network analyses to identify novel target genes associated with pain in patients newly diagnosed with squamous cell carcinoma of the head and neck (HNSCC).ResultsWe first identified 36 cancer pain-related genes (i.e., focus genes) from 36 publications based on a literature search. The Ingenuity Pathway Analysis (IPA) analysis identified additional genes that are functionally related to the 36 focus genes through pathway relationships yielding a total of 82 genes. Subsequently, 800 SNPs within the 82 IPA-selected genes on the Illumina HumanOmniExpress-12v1 platform were selected from a large-scale genotyping effort. Association analyses between the 800 candidate SNPs (covering 82 genes) and pain in a patient cohort of 1368 patients with HNSCC (206 patients with severe pain vs. 1162 with non-severe pain) showed the highest significance for MAPK1/ERK2, a gene belonging to the MAP kinase family (rs8136867, p value = 8.92 × 10−4; odds ratio [OR] = 1.33, 95 % confidence interval [CI]: 1.13–1.58). Other top genes were PIK3C2G (a member of PI3K [complex], rs10770367, p value = 1.10 × 10−3; OR = 1.46, 95 % CI: 1.16–1.82), TCRA (the alpha chain of T-cell receptor, rs6572493, p value = 2.84 × 10−3; OR = 0.70, 95 % CI: 0.55–0.88), PDGFC (platelet-derived growth factor C, rs6845322, p value = 4.88 × 10−3; OR = 1.32, 95 % CI: 1.09–1.60), and CD247 (a member of CD3, rs2995082, p value = 7.79 × 10−3; OR = 0.76, 95 % CI: 0.62–0.93).ConclusionsOur findings provide novel candidate genes and biological pathways underlying pain in cancer patients. Further study of the variations of these candidate genes could inform clinical decision making when treating cancer pain.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0348-7) contains supplementary material, which is available to authorized users.

Molecular characterization of classical and nonclassical MHC class I genes from the golden pheasant (Chrysolophus pictus).

Classical major histocompatibility complex (MHC) class I allelic polymorphism is essential for competent antigen presentation. To improve the genotyping efforts in the golden pheasant, it is necessary to differentiate more accurately between classical and nonclassical class I molecules. In our study, all MHC class I genes were isolated from one golden pheasant based on two overlapping PCR amplifications. In total, six full-length class I nucleotide sequences (A-F) were identified, and four were novel. Two (A and C) belonged to the IA1 gene, two (B and D) were alleles derived from the IA2 gene through transgene amplification, and two (E and F) comprised a third novel locus, IA3 that was excluded from the core region of the golden pheasant MHC-B. IA1 and IA2 exhibited the broad expression profiles characteristic of classical loci, while IA3 showed no expression in multiple tissues and was therefore defined as a nonclassical gene. Phylogenetic analysis indicated that the three IA genes in the golden pheasant share a much closer evolutionary relationship than the corresponding sequences in other galliform species. This observation was consistent with high sequence similarity among them, which likely arises from the homogenizing effect of recombination. Our careful distinction between the classical and nonclassical MHC class I genes in the golden pheasant lays the foundation for developing locus-specific genotyping and establishing a good molecular marker system of classical MHC I loci.