Use Of Sequence Data Research Articles

HerpesDRG: a comprehensive resource for human herpesvirus antiviral drug resistance genotyping

The prevention and treatment of many herpesvirus associated diseases is based on the utilization of antiviral therapies, however therapeutic success is limited by the development of drug resistance. Currently no single database cataloguing resistance mutations exists, which hampers the use of sequence data for patient management. We therefore developed HerpesDRG, a drug resistance mutation database that incorporates all the known resistance genes and current treatment options, built from a systematic review of available genotype to phenotype literature. The database is released along with an R package that provides a simple approach to resistance variant annotation and clinical implication analysis from common sanger and next generation sequencing data. This represents the first openly available and community maintainable database of drug resistance mutations for the human herpesviruses (HHV), developed for the community of researchers and clinicians tackling HHV drug resistance.

Predicted resistance to broadly neutralizing antibodies (bnAbs) and associated HIV-1 envelope characteristics among seroconverting adults in Botswana

We used HIV-1C sequences to predict (in silico) resistance to 33 known broadly neutralizing antibodies (bnAbs) and evaluate the different HIV-1 Env characteristics that may affect virus neutralization. We analyzed proviral sequences from adults with documented HIV-1 seroconversion (N = 140) in Botswana (2013–2018). HIV-1 env sequences were used to predict bnAb resistance using bNAb-ReP, to determine the number of potential N-linked glycosylation sites (PNGS) and evaluate Env variable region characteristics (VC). We also assessed the presence of signature mutations that may affect bnAb sensitivity in vitro. We observe varied results for predicted bnAb resistance among our cohort. 3BNC117 showed high predicted resistance (72%) compared to intermediate levels of resistance to VRC01 (57%). We predict low resistance to PGDM100 and 10-1074 and no resistance to 4E10. No difference was observed in the frequency of PNGS by bNAb susceptibility patterns except for higher number of PNGs in V3 bnAb resistant strains. Associations of VC were observed for V1, V4 and V5 loop length and net charge. We also observed few mutations that have been reported to confer bnAb resistance in vitro. Our results support use of sequence data and machine learning tools to predict the best bnAbs to use within populations.

Diagnostic Yield From a Nationwide Implementation of Precision Medicine for all Children With Cancer.

Several studies have indicated that broad genomic characterization of childhood cancer provides diagnostically and/or therapeutically relevant information in selected high-risk cases. However, the extent to which such characterization offers clinically actionable data in a prospective broadly inclusive setting remains largely unexplored. We implemented prospective whole-genome sequencing (WGS) of tumor and germline, complemented by whole-transcriptome sequencing (RNA-Seq) for all children diagnosed with a primary or relapsed solid malignancy in Sweden. Multidisciplinary molecular tumor boards were set up to integrate genomic data in the clinical decision process along with a medicolegal framework enabling secondary use of sequencing data for research purposes. During the study's first 14 months, 118 solid tumors from 117 patients were subjected to WGS, with complementary RNA-Seq for fusion gene detection in 52 tumors. There was no significant geographic bias in patient enrollment, and the included tumor types reflected the annual national incidence of pediatric solid tumor types. Of the 112 tumors with somatic mutations, 106 (95%) exhibited alterations with a clear clinical correlation. In 46 of 118 tumors (39%), sequencing only corroborated histopathological diagnoses, while in 59 cases (50%), it contributed to additional subclassification or detection of prognostic markers. Potential treatment targets were found in 31 patients (26%), most commonly ALK mutations/fusions (n = 4), RAS/RAF/MEK/ERK pathway mutations (n = 14), FGFR1 mutations/fusions (n = 5), IDH1 mutations (n = 2), and NTRK2 gene fusions (n = 2). In one patient, the tumor diagnosis was revised based on sequencing. Clinically relevant germline variants were detected in 8 of 94 patients (8.5%). Up-front, large-scale genomic characterization of pediatric solid malignancies provides diagnostically valuable data in the majority of patients also in a largely unselected cohort.

Stock Price Prediction using ML algorithms

Abstract: Stock Price Prediction using ML( Machine Learning) helps to determine the unborn value of stocks of any fiscal means traded on an exchange. The entire generality of prognosticating stock prices is to gain significant gains by minimizing losses vaticinating the stock request price is always challenging for numerous business judges and experimenters. vaticination of the stock request plays a vital part in the stock business. The compass gradationally expanded. The time series model cannot contribute to the non-linear part of the stock data and is therefore hamstrung for the long term, and LSTM neural network makes better use of non-sequential data and has better use of sequence data. Useful information in the long term which makes the root mean square error of the vaticination result, the LSTM neural network needs lower than the time series model, showing LSTM is a better stock price soothsaying system. Machine Learning approach to predict or sense the behavior tracking of the stock market Sensex. Random Forest is the Machine Learning model implemented effectively in predicting the stock prices anddefining the activity between the exchanges the securities between the buyers and sellers.

Prioritization of genes associated with type 2 diabetes mellitus for functional studies.

Existing therapies for type 2 diabetes mellitus (T2DM) show limited efficacy or have adverse effects. Numerous genetic variants associated with T2DM have been identified, but progress in translating these findings into potential drug targets has been limited. Here, we describe the tools and platforms available to identify effector genes from T2DM-associated coding and non-coding variants and prioritize them for functional studies. We discuss QSER1 and SLC12A8 as examples of genes that have been identified as possible T2DM candidate genes using these tools and platforms. We suggest further approaches, including the use of sequencing data with increased sample size and ethnic diversity, single-cell omics data for analyses, glycaemic trait associations to predict gene function and, potentially, human induced pluripotent stem cell 'village' cultures, to strengthen current gene functionalization workflows. Effective prioritization of T2DM-associated genes for experimental validation could expedite our understanding of the genetic mechanisms responsible for T2DM to facilitate the use of precision medicine in its treatment.

Intraguild predation is increased in areas of low prey diversity in a generalist predator community.

Niche differentiation and intraguild predation (IGP) can allow ecologically similar species to coexist, although it is unclear which coexistence mechanism predominates in consumer communities. Until now, a limited ability to quantify diets from metabarcoding data has precluded the use of sequencing data to determine the relative importance of these mechanisms. Here, we pair a recent metabarcoding quantification approach with stable isotope analysis to examine diet composition in a wolf spider community. We compare the prevalence of resource partitioning and IGP in these spiders and test whether factors that influence foraging performance, including individual identity, morphology, prey community and environmental conditions, can explain variation in diet composition and IGP. Extensive IGP is likely the primary coexistence mechanism in this community, and other factors to which foraging variation is often attributed do not explain diet composition and IGP here. Rather, IGP increases as prey diversity decreases. Foragers are driven to IGP where resource niches are limited. We highlight the need to examine how drivers of predator-prey interaction strengths translate into foraging in natural systems.

Perceptions of forensic scientists on statistical models, sequence data, and ethical implications for DNA evidence evaluations: A qualitative assessment

With the introduction of next generation sequencing (NGS) technology in the forensic field, it will be of interest to assess if forensic scientists feel equipped to interpret and present DNA evidence for sequence data. Here, we describe perceptions of sixteen U.S.-based forensic scientists on statistical models, sequence data, and ethical implications for DNA evidence evaluations.To get an in-depth understanding of the current situation, we used a qualitative research approach with a cross-sectional study design. Semi-structured interviews (N = 16) were conducted with U.S. forensic scientists working with DNA evidence. Open-ended interview questions were used to explore participants’ views and needs surrounding the use of statistical models and sequence data for forensic purposes. We conducted a conventional content analysis using ATLAS. ti software and employed a second coder to ensure reliability of our results.Eleven themes emerged: 1) a statistical model that maximizes the value of the evidence is preferred; 2) a high-level understanding of the statistical model used is generally sufficient; 3) transparency is key in minimizing the risk of creating black boxes; 4) training and education should be an ongoing effort; 5) the effectiveness of presenting results in court can be improved; 6) NGS has the potential to become revolutionary; 7) some hesitations surrounding the use of sequence data remain; 8) there is a need for a concrete plan to alleviate barriers to the implementation of sequencing techniques; 9) ethics plays a major part in the role of a forensic scientist; 10) ethical barriers for sequence data depend on the application; 11) DNA evidence has its limitations.The results of this study give insight into the perceptions of forensic scientists regarding the use of statistical models and sequence data, providing valuable information in the move towards implementing sequencing methods for DNA evidence evaluations.

Predicting Dihydropyrimidine Dehydrogenase Deficiency and Related 5-Fluorouracil Toxicity: Opportunities and Challenges of DPYD Exon Sequencing and the Role of Phenotyping Assays.

Deficiency of dihydropyrimidine dehydrogenase (DPD), encoded by the DPYD gene, is associated with severe toxicity induced by the anti-cancer drug 5-Fluorouracil (5-FU). DPYD genotyping of four recommended polymorphisms is widely used to predict toxicity, yet their prediction power is limited. Increasing availability of next generation sequencing (NGS) will allow us to screen rare variants, predicting a larger fraction of DPD deficiencies. Genotype-phenotype correlations were investigated by performing DPYD exon sequencing in 94 patients assessed for DPD deficiency by the 5-FU degradation rate (5-FUDR) assay. Association of common variants with 5-FUDR was analyzed with the SNPStats software. Functional interpretation of rare variants was performed by in-silico analysis (using the HSF system and PredictSNP) and literature review. A total of 23 rare variants and 8 common variants were detected. Among common variants, a significant association was found between homozygosity for the rs72728438 (c.1974+75A>G) and decreased 5-FUDR. Haplotype analysis did not detect significant associations with 5-FUDR. Overall, in our sample cohort, NGS exon sequencing allowed us to explain 42.5% of the total DPD deficiencies. NGS sharply improves prediction of DPD deficiencies, yet a broader collection of genotype-phenotype association data is needed to enable the clinical use of sequencing data.

Development of reverse-transcriptase, real-time PCR assays to distinguish the Southern African Territories (SAT) serotypes 1 and 3 and topotype VII of SAT2 of Foot-and-Mouth Disease Virus.

Foot-and-Mouth Disease Virus (FMDV), the causative agent of Foot-and-Mouth Disease, is a highly feared, economically devastating transboundary pathogen. This is due to the virus' extremely contagious nature and its ability to utilize multiple transmission routes. As such, rapid and accurate diagnostic testing is imperative to the control of FMD. Identification of the FMDV serotype is necessary as it provides the foundation for appropriate vaccine selection and aids in outbreak source tracing. With the vast genetic diversity, there is a desperate need to be able to characterize FMDV without relying on prior knowledge of viral serotypes. In this study, the Neptune bioinformatics tool was used to identify genetic signatures specific to each Southern African Territories (SAT) 1, 2 and 3 genomes but exclusionary to the other circulating FMDV serotypes (A, O, Asia1, and the heterologous SAT1, SAT2 and/or SAT3). Identification of these unique genomic regions allowed the design of TaqMan-based real-time reverse transcriptase PCR (rRT-PCR) primer/probe sets for SAT1, SAT2 and SAT3 viruses. These assays were optimized using prototypic FMDV cell culture isolates using the same reagents and thermocycling conditions as the FMDV pan-serotype 3D rRT-PCR assay. Cross-reactivity was evaluated in tandem with the FMDV pan-serotype 3D rRT-PCR utilizing representative strains from FMDV serotypes A, O, Asia1, SAT1, SAT2 and SAT3. The SAT1, SAT2, and SAT3 primer/probe sets were specific for the homologous serotype and exclusionary to all others. SAT1 and SAT3 primer/probe sets were able to detect several topotypes, whereas the SAT2 assay was revealed to be specific for topotype VII. The SAT2 topotype VII specificity was possibly due to the use of sequence data deposited post-2011to design the rRT-PCR primers and probes. Each assay was tested against a panel of 99 bovine tissue samples from Nigeria, where SAT2 topotype VII viruses were correctly identified and no cross-reactivity was exhibited by the SAT1 and 3 assays. These novel SAT1, SAT3 and SAT2 topotype VII rRT-PCR assays have the potential to detect and differentiate circulating FMD SAT viruses.

Challenge and Prospect of Pre Implantation Genetic Diagnosis-A Mini Review

Pre-implantation genetic diagnosis (PIGD) is the genetic profiling of the embryos prior to implantation and sometimes even of oocytes prior to fertilization. PGD is considered in a similar fashion to prenatal diagnosis. Initially offered for diagnosis in couples at risk for single gene genetic disorders, such as cystic fibrosis, spinal muscular atrophy and Huntington’s disease, preimplantation genetic diagnosis (PGD) has most frequently been employed in assisted reproduction for detection of chromosome aneuploidy from advancing maternal age or structural chromosome rearrangements. Major improvements have been seen in PGD analysis with movement away from older, less effective technologies, such as fluorescence in situ hybridization (FISH), to newer molecular tools, such as DNA microarrays and next generation sequencing. Discussions regarding the scientific, ethical, legal and social issues surrounding the use of sequence data from embryo biopsy have begun and must continue to avoid concern regarding eugenic or inappropriate use of this technology.

Catching change in microbial diversity indicators under different soil organic matter managements: Higher taxonomic resolution, better discrimination?

Recent advances in molecular ecology have dramatically improved our knowledge of soil microbial diversity and offers new indicators of soil quality. The usefulness of diversity indices has never been greater as the astronomical amounts of data generated in the literature needs to be synthesized. Despite technical guidelines have been proposed to characterize soil microbiomes using high throughput sequencing, the effect of taxonomic resolution on diversity indices is still largely unknown. Here, we explored how downscaling to higher taxonomic resolution levels may affect α- and β-diversity indices of bacterial communities exposed to different soil organic matter management. To this aim, we collected soil samples in a long-term experimental site (Ultuna, Sweden) where different mineral and organic fertilizers have been applied for since 1956. We used both massive amplicon sequencing from phylum to species (OTU) and molecular fingerprints (PLFA, DGGE and T-RFLP). Our results showed that the discrimination potential increased at finer taxonomic resolution for β-diversity but not for α-diversity indices such as richness and evenness. Also, the relative importance of hierarchical drivers of soil microbial communities such as C, N and pH varied depending on the taxonomic resolution. This study also demonstrated that indicators generated by molecular fingerprints such as PLFA, DGGE and T-RFLP are still consistent to monitor the effect of agricultural management on β-diversity but not on α-diversity, which is useful information as it allows for a better use of results in past literature. We encourage performing such comparative studies on wider surveys, including different contexts and other indicators, in order to increase the efficiency and the robustness of the use of sequencing data in soil biodiversity monitoring.

Efficient Exploration of Sequence Space by Sequence-Guided Protein Engineering and Design.

The rapid growth of sequence databases over the past two decades means that protein engineers faced with optimizing a protein for any given task will often have immediate access to a vast number of related protein sequences. These sequences encode information about the evolutionary history of the protein and the underlying sequence requirements to produce folded, stable, and functional protein variants. Methods that can take advantage of this information are an increasingly important part of the protein engineering tool kit. In this Perspective, we discuss the utility of sequence data in protein engineering and design, focusing on recent advances in three main areas: the use of ancestral sequence reconstruction as an engineering tool to generate thermostable and multifunctional proteins, the use of sequence data to guide engineering of multipoint mutants by structure-based computational protein design, and the use of unlabeled sequence data for unsupervised and semisupervised machine learning, allowing the generation of diverse and functional protein sequences in unexplored regions of sequence space. Altogether, these methods enable the rapid exploration of sequence space within regions enriched with functional proteins and therefore have great potential for accelerating the engineering of stable, functional, and diverse proteins for industrial and biomedical applications.

An implementation science approach to evaluating pathogen whole genome sequencing in public health

BackgroundPathogen whole genome sequencing (WGS) is being incorporated into public health surveillance and disease control systems worldwide and has the potential to make significant contributions to infectious disease surveillance, outbreak investigation and infection prevention and control. However, to date, there are limited data regarding (i) the optimal models for integration of genomic data into epidemiological investigations and (ii) how to quantify and evaluate public health impacts resulting from genomic epidemiological investigations.MethodsWe developed the Pathogen Genomics in Public HeAlth Surveillance Evaluation (PG-PHASE) Framework to guide examination of the use of WGS in public health surveillance and disease control. We illustrate the use of this framework with three pathogens as case studies: Listeria monocytogenes, Mycobacterium tuberculosis and SARS-CoV-2.ResultsThe framework utilises an adaptable whole-of-system approach towards understanding how interconnected elements in the public health application of pathogen genomics contribute to public health processes and outcomes. The three phases of the PG-PHASE Framework are designed to support understanding of WGS laboratory processes, analysis, reporting and data sharing, and how genomic data are utilised in public health practice across all stages, from the decision to send an isolate or sample for sequencing to the use of sequence data in public health surveillance, investigation and decision-making. Importantly, the phases can be used separately or in conjunction, depending on the need of the evaluator. Subsequent to conducting evaluation underpinned by the framework, avenues may be developed for strategic investment or interventions to improve utilisation of whole genome sequencing.ConclusionsComprehensive evaluation is critical to support health departments, public health laboratories and other stakeholders to successfully incorporate microbial genomics into public health practice. The PG-PHASE Framework aims to assist public health laboratories, health departments and authorities who are either considering transitioning to whole genome sequencing or intending to assess the integration of WGS in public health practice, including the capacity to detect and respond to outbreaks and associated costs, challenges and facilitators in the utilisation of microbial genomics and public health impacts.

Leveraging Pathogen Sequence and Contact Tracing Data to Enhance Vaccine Trials in Emerging Epidemics.

Advance planning of vaccine trials conducted during outbreaks increases our ability to rapidly define the efficacy and potential impact of a vaccine. Vaccine efficacy against infectiousness (VEI) is an important measure for understanding a vaccine's full impact, yet it is currently not identifiable in many trial designs because it requires knowledge of infectors' vaccination status. Recent advances in genomics have improved our ability to reconstruct transmission networks. We aim to assess if augmenting trials with pathogen sequence and contact tracing data can permit them to estimate VEI. We develop a transmission model with a vaccine trial in an outbreak setting, incorporate pathogen sequence data and contact tracing data, and assign probabilities to likely infectors. We then propose and evaluate the performance of an estimator of VEI. We find that under perfect knowledge of infector-infectee pairs, we are able to accurately estimate VEI. Use of sequence data results in imperfect reconstruction of transmission networks, biasing estimates of VEI towards the null, with approaches using deep sequence data performing better than approaches using consensus sequence data. Inclusion of contact tracing data reduces the bias. Pathogen genomics enhance identifiability of VEI, but imperfect transmission network reconstruction biases estimate toward the null and limits our ability to detect VEI. Given the consistent direction of the bias, estimates obtained from trials using these methods will provide lower bounds on the true VEI. A combination of sequence and epidemiologic data results in the most accurate estimates, underscoring the importance of contact tracing.

Using sequence variants of a QTL region improves the accuracy of genomic evaluation in French Saanen goats

The enhanced availability of sequence data in livestock provides an opportunity for more accurate predictions in routine genomic evaluations. Such evaluations would therefore no longer rely only on the linkage disequilibrium between a chip marker and the causal mutation. The objective of this study was to assess the usefulness of sequence data in Saanen goats (n = 33) to better capture a quantitative trait locus (QTL) on chromosome 19 (CHI19) and improve the accuracy of predictions for 3 milk production traits, 5 type traits, and somatic cell scores. All 1,207 50K genotypes were imputed to the sequence level. Four scenarios, each using a subset of CHI19 imputed variants, were then tested. Sequence-derived information included all CHI19 variants (529,576), all variants in the QTL region (22,269), 178 variants selected in the QTL region and added to an updated chip, or 178 randomly selected variants on CHI19. Two genomic evaluation models were applied: single-step genomic BLUP and weighted single-step genomic BLUP. All scenarios were compared with single-step genomic BLUP using 50K genotypes. Best overall results were obtained using single-step genomic BLUP on 50K genotypes completed with all variants in the QTL region of chromosome 19 (6.2% average increase in accuracy for 9 traits) with the highest accuracy gain for fat yield (17.9%), significant increases for milk (13.7%) and protein yields (12.5%), and type traits associated with CHI19. Despite its association with the QTL region of chromosome 19, the somatic cell score showed decreased accuracy in every alternative scenario. Using all CHI19 variants led to an overall decrease of 4.8% in prediction accuracy. The updated chip was efficient and improved genomic evaluations by 3.1 to 6.4% on average, depending on the scenario. Indeed, information from only a few carefully selected variants increased accuracies for traits of interest when used in a single-step genomic BLUP model. In conclusion, using QTL region variants imputed from sequence data in single-step genomic evaluations represents a promising perspective for such evaluations in dairy goats. Furthermore, using only a limited number of selected variants in QTL regions, as available on SNP chip updates, significantly increases the accuracy for QTL-associated traits without deteriorating the evaluation accuracy for other traits. The latter approach is interesting, as it avoids time-consuming imputation and data formatting processes and provides reliable genotypes.

High-Throughput Reclassification of SCN5A Variants

Partial or complete loss-of-function variants in SCN5A are the most common genetic cause of the arrhythmia disorder Brugada syndrome (BrS1). However, the pathogenicity of SCN5A variants is often unknown or disputed; 80% of the 1,390 SCN5A missense variants observed in at least one individual to date are variants of uncertain significance (VUSs). The designation of VUS is a barrier to the use of sequence data in clinical care. We selected 83 variants: 10 previously studied control variants, 10 suspected benign variants, and 63 suspected Brugada syndrome-associated variants, selected on the basis of their frequency in the general population and in individuals with Brugada syndrome. We used high-throughput automated patch clamping to study the function of the 83 variants, with the goal of reclassifying variants with functional data. The ten previously studied controls had functional properties concordant with published manual patch clamp data. All 10 suspected benign variants had wild-type-like function. 22 suspected BrS variants had loss of channel function (<10% normalized peak current) and 22 variants had partial loss of function (10%-50% normalized peak current). The previously unstudied variants were initially classified as likely benign (n = 2), likely pathogenic (n = 10), or VUSs (n = 61). After the patch clamp studies, 16 variants were benign/likely benign, 45 were pathogenic/likely pathogenic, and only 12 were still VUSs. Structural modeling identified likely mechanisms for loss of function including altered thermostability and disruptions to alpha helices, disulfide bonds, or the permeation pore. High-throughput patch clamping enabled reclassification of the majority of tested VUSs in SCN5A.

Genome wide association analysis on semen volume and milk yield using different strategies of imputation to whole genome sequence in French dairy goats

BackgroundGoats were domesticated 10,500 years ago to supply humans with useful resources. Since then, specialized breeds that are adapted to their local environment have been developed and display specific genetic profiles. The VarGoats project is a 1000 genomes resequencing program designed to cover the genetic diversity of the Capra genus. In this study, our main objective was to assess the use of sequence data to detect genomic regions associated with traits of interest in French Alpine and Saanen breeds.ResultsDirect imputation from the GoatSNP50 BeadChip genotypes to sequence level was investigated in these breeds using FImpute and different reference panels: within-breed, all Capra hircus sequenced individuals, European goats and French mainland goats. The best results were obtained with the French goat panel with allele and genotype concordance rates reaching 0.86 and 0.75 in the Alpine and 0.86 and 0.73 in the Saanen breed respectively. Mean correlations tended to be low in both breeds due to the high proportion of variants with low frequencies.For association analysis, imputation was performed using FImpute for 1129 French Alpine and Saanen males using within-breed and French panels on 23,338,436 filtered variants. The association results of both imputation scenarios were then compared. In Saanen goats, a large region on chromosome 19 was significantly linked to semen volume and milk yield in both scenarios. Significant variants for milk yield were annotated for 91 genes on chromosome 19 in Saanen goats. For semen volume, the annotated genes include YBOX2 which is related to azoospermia or oligospermia in other species. New signals for milk yield were detected on chromosome 2 in Alpine goats and on chromosome 5 in Saanen goats when using a multi-breed panel.ConclusionEven with very small reference populations, an acceptable imputation quality can be achieved in French dairy goats. GWAS on imputed sequences confirmed the existence of QTLs and identified new regions of interest in dairy goats. Adding identified candidates to a genotyping array and sequencing more individuals might corroborate the involvement of identified regions while removing potential imputation errors.

Clinical impact of laboratory critical result notifications

Genomic medicine is the use of sequence data from an individual's entire genetic code to aid diagnosis and personalise therapeutic options. An important goal of the 100,000 genomes project in the UK is to embed the infrastructure for the widespread use of whole genome sequencing into the National Health Service. Paediatricians will be at the forefront in using this new technology in the diagnosis of children with multiple congenital anomalies, developmental delay and other suspected genetic conditions. This article provides a description of the basic concepts of genomic medicine. The types of genomic testing that are available are discussed and examples of how genomics is already being used in paediatrics are given. Finally, the challenges for genomic medicine are summarised.

Mapping of quantitative trait loci for reproductive traits in pigs

This paper reviews the major approaches used to map quantitative trait loci (QTL) and current knowledge about QTL affecting reproductive trait loci in pigs. Three different approaches, i.e. functional candidate gene analyses, genome-wide linkage studies (GWLS) and genome-wide association studies (GWAS) have been used to map QTL in pigs. The interest and limits of each of the three approaches are discussed. Candidate genes and QTL have been reviewed based on PigQTLdb at http://www.animalgenome. org. A total of 29 candidate genes affecting reproductive traits located on 14 autosomes have been considered. Some of them are well established results, but most results originate from single studies of limited scale and need to be confirmed. Several thousands of QTL affecting 15 male and 15 female reproductive traits have been identified on 17 and 19 different chromosomes, respectively, using GWLS. Yet, the majority of them are only putative QTL and few QTL regions overlap between studies. Epistatic interactions between QTL appear as rather important in the single study investigating the effects of epistasis on pig reproductive traits. A large number of QTL distributed over almost all pig chromosomes have been identified in the single GWAS study published so far for pig reproductive traits. Use of sequence data, of more complex genetic models and of integrative biology approaches should be considered for more thoroughly investigating the genetic architecture of pig reproductive traits in the future.

Genomic medicine for the paediatrician

Abstract Genomic medicine is the use of sequence data from an individual's entire genetic code to aid diagnosis and personalise therapeutic options. An important goal of the 100,000 genomes project in the UK is to embed the infrastructure for the widespread use of whole genome sequencing into the National Health Service. Paediatricians will be at the forefront in using this new technology in the diagnosis of children with multiple congenital anomalies, developmental delay and other suspected genetic conditions. This article provides a description of the basic concepts of genomic medicine. The types of genomic testing that are available are discussed and examples of how genomics is already being used in paediatrics are given. Finally, the challenges for genomic medicine are summarised.