Large Genomic Regions Research Articles

Identification and sequencing of novel alleles: Utility of next-generation sequencing methods

Aim Sanger sequencing-based typing (SBT) requires multiple steps to sequence novel HLA alleles, as allele-specific (AS) primers are needed to separate novel from other encoded alleles. Next-generation sequencing (NGS) includes phase information, and has the potential to sequence novel alleles without AS primers. Here we compare the process of novel allele identification and sequencing using SBT and NGS assays. Methods Novel alleles were identified in peripheral blood during routine clinical testing using Atria SBT kits (Abbot Molecular). Germline encoding was verified by typing buccal samples. For Sanger sequencing of novel alleles, AS amplification primers were designed to take advantage of nucleotide polymorphisms between encoded alleles, and patients with homozygous loci were used to verify primer specificity. Amplified products were Sanger sequenced using custom or commercially-available primers. For NGS sequencing, the Holotype X4 (Omixon) kit was used in its default configuration. Results Four novel, germline-encoded HLA alleles were identified in three patients. Novel HLA-A and B alleles were sequenced using AS amplification primers and Sanger sequencing. A novel DQB1 allele previously identified but not resolved by SBT was sequenced using the NGS assay. A novel DQB1 allele not identified by SBT, as the polymorphism was outside the covered region, was identified and sequenced by NGS. The names HLA-A∗66:22, B∗07:238, DQB1∗03:180, and DQB1∗06:01:15 have been officially assigned by the WHO Nomenclature Committee. Conclusions While SBT assays used in the clinical setting are able to identify novel alleles, subsequent sequencing is a cumbersome and time-consuming process. Furthermore, SBT assays may miss novel polymorphisms outside of the exons covered by the assay. NGS systems, on the other hand, can identify and sequence novel alleles over a larger genomic region as part of the normal clinical workflow. However, we experienced issues with the Omixon NGS kit, including the inability to sequence buccal cell DNA, and difficulties amplifying the DQB1 locus, which could have impacted clinical workflow had NGS been the primary method of testing. As the emerging technology of NGS is introduced to complement established SBT assays, it is important to evaluate the strengths and weaknesses of each.

Extensive de novo mutation rate variation between individuals and across the genome of Chlamydomonas reinhardtii.

Describing the process of spontaneous mutation is fundamental for understanding the genetic basis of disease, the threat posed by declining population size in conservation biology, and much of evolutionary biology. Directly studying spontaneous mutation has been difficult, however, because new mutations are rare. Mutation accumulation (MA) experiments overcome this by allowing mutations to build up over many generations in the near absence of natural selection. Here, we sequenced the genomes of 85 MA lines derived from six genetically diverse strains of the green alga Chlamydomonas reinhardtii. We identified 6843 new mutations, more than any other study of spontaneous mutation. We observed sevenfold variation in the mutation rate among strains and that mutator genotypes arose, increasing the mutation rate approximately eightfold in some replicates. We also found evidence for fine-scale heterogeneity in the mutation rate, with certain sequence motifs mutating at much higher rates, and clusters of multiple mutations occurring at closely linked sites. There was little evidence, however, for mutation rate heterogeneity between chromosomes or over large genomic regions of 200 kbp. We generated a predictive model of the mutability of sites based on their genomic properties, including local GC content, gene expression level, and local sequence context. Our model accurately predicted the average mutation rate and natural levels of genetic diversity of sites across the genome. Notably, trinucleotides vary 17-fold in rate between the most and least mutable sites. Our results uncover a rich heterogeneity in the process of spontaneous mutation both among individuals and across the genome.

Global DNA methylation changes and differential gene expression in Anaplasma phagocytophilum-infected human neutrophils

BackgroundAnaplasma phagocytophilum is an obligate intracellular prokaryotic pathogen that both infects and replicates within human neutrophils. The bacterium represses multiple antimicrobial functions while simultaneously increasing proinflammatory functions by reprogramming the neutrophil genome. Previous reports show that many observed phenotypic changes are in part explained by altered gene transcription. We recently identified that large chromosomal regions of the neutrophil genome are differentially expressed during A. phagocytophilum infection. Because of this, we sought to determine whether gene expression programs altered by infection were the result of changes in the host neutrophil DNA methylome.ResultsWithin 24 h of infection, marked increases in DNA methylation were observed genome-wide as compared with mock-infected controls and pharmacologic inhibition of DNA methyltransferases resulted in decreased bacterial growth. New regions of DNA methylation were enriched at intron and exon junctions; however, intragenic methylation did not correlate with altered gene expression. In contrast, intergenic DNA methylation was associated with A. phagocytophilum-induced gene expression changes. Within the major histocompatibility complex locus on chromosome 6, a region with marked changes in infection-induced differential gene expression, new regions of methylation were localized to boundaries of active and inactive chromatin.ConclusionsThese data strongly suggest that A. phagocytophilum infection, in addition to altering histone structure, alters DNA methylation and the epigenome of its host cell to promote survival and replication, providing evidence that such bacterial infection can radically alter the epigenome of its host cell.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-015-0105-1) contains supplementary material, which is available to authorized users.

Cytopathology meets basic science.

Cytopathology meets basic science.

Inferring the genetic history of lactase persistence along the Italian peninsula from a large genomic interval surrounding the LCT gene.

Although genetic variants related to lactase persistence in European populations were supposed to have firstly undergone positive selection in farmers from the Balkans and Central Europe, demographic and evolutionary dynamics that subsequently shaped the distribution of this adaptive trait across the continent have still to be elucidated. To deepen the knowledge about potential routes of diffusion of lactase persistence to Western Europe we investigated variation at a large genomic region surrounding the LCT gene along the Italian peninsula, a geographical area that played a key role in population movements responsible for Neolithic diffusion across Europe. By genotyping 40 highly selected SNPs in more than 400 Italian individuals we described gradients of nucleotide and haplotype variation potentially related to lactase persistence and compared them with those observed in several European and Mediterranean human groups. Multiple migratory events responsible for earlier introduction of the examined alleles in Italy than in Northern European regions could be invoked. Different demic processes occurred along the western and eastern sides of the peninsula were also inferred via linkage disequilibrium and population structure analyses. The appreciable genetic continuum observed between people from Northern or Central-Western Italy and Central European populations suggested a local arrival of lactase persistence-related variants mainly via overland routes. On the contrary, diversity of Central-Eastern and Southern Italian groups entailed also gene flow from South-Eastern Mediterranean regions, in accordance to the earlier entrance of the Neolithic in Southern Italy via maritime population movements along the Mediterranean coastlines.

Synthetic and Evolutionary Construction of a Chlorate-Reducing Shewanella oneidensis MR-1.

ABSTRACTDespite evidence for the prevalence of horizontal gene transfer of respiratory genes, little is known about how pathways functionally integrate within new hosts. One example of a mobile respiratory metabolism is bacterial chlorate reduction, which is frequently encoded on composite transposons. This implies that the essential components of the metabolism are encoded on these mobile elements. To test this, we heterologously expressed genes for chlorate reduction from Shewanella algae ACDC in the non-chlorate-reducing Shewanella oneidensis MR-1. The construct that ultimately endowed robust growth on chlorate included cld, a cytochrome c gene, clrABDC, and two genes of unknown function. Although strain MR-1 was unable to grow on chlorate after initial insertion of these genes into the chromosome, 11 derived strains capable of chlorate respiration were obtained through adaptive evolution. Genome resequencing indicated that all of the evolved chlorate-reducing strains replicated a large genomic region containing chlorate reduction genes. Contraction in copy number and loss of the ability to reduce chlorate were also observed, indicating that this phenomenon was extremely dynamic. Although most strains contained more than six copies of the replicated region, a single strain with less duplication also grew rapidly. This strain contained three additional mutations that we hypothesized compensated for the low copy number. We remade the mutations combinatorially in the unevolved strain and determined that a single nucleotide polymorphism (SNP) upstream of cld enabled growth on chlorate and was epistatic to a second base pair change in the NarP binding sequence between narQP and nrfA that enhanced growth.

Abstract 164: Identification of Genetic Regulators of the Atherosclerosis-Associated Metabolite Trimethylamine-N-Oxide in the Diversity Outbred Mice Population

Dietary choline and its derivatives have been associated with various aspects of lipid metabolism. Recently, the choline metabolite trimethylamine-N-oxide (TMAO) has been associated with atherosclerosis in both mice and humans. Traditional studies of atherosclerosis in mice use genetic or dietary manipulation to induce atherosclerosis in inbred mouse strains. However, traditional quantitative trait locus (QTL) mapping studies using inbred strains often identify large genomic regions, containing many genes, due to limited recombination and/or sample size which hamper candidate gene identification and translation of these results into possible risk factors and therapeutic targets. As an alternative approach, here we use the multi-parental Diversity Outbred (DO) mouse panel for genetic mapping in order to aid in the identification of causal genes and variants associated with TMAO and its precursor choline. We fed DO mice either a high-fat, cholesterol-containing (HFCA) diet or a low-fat, high-protein diet for 18 weeks and measured circulating metabolites at baseline and after diet. Among our highly significant loci, we detected a 4.6 Mb QTL interval on Chromosome 12 (LOD = 10.0, p<0.05) associated with plasma concentrations of the metabolite trimethylamine-N-oxide at baseline, containing 116 genes; the same QTL was also identified after dietary treatment (LOD= 6.7, p<0.1). By using a database of mouse gene expression and measuring gene expression in the eight progenitor strains by RNA-Sequencing, we identified three potential candidate genes, including the positional candidate gene Numb, which encodes a clathrin adapter with a role in endocytosis that was recently shown to modulate intestinal cholesterol absorption. We show that TMAO and Numb exhibit inverse strain variation across the DO founder strains and that the novel Chromosome 12 TMAO locus co-localizes with a highly significant cis-expression QTL for Numb, indicating a potential functional relationship.

Abstract P4-02-08: Global quantitative measures using next-generation sequencing for breast cancer presence outperform individual tumor markers in plasma

Abstract Background: Analytically and clinically validated non-invasive blood tests that quantify breast cancer burden and clinical drug response/resistance are greatly needed. Many groups have successfully detected tumor markers in blood using a variety of technologies, including next generation sequencing (NGS). We performed a comprehensive NGS study on a small number of patients to evaluate the value of global versus individual markers for the quantitation of tumor-derived cell free DNA (cfDNA) in plasma. Methods: DNA isolated from formalin-fixed primary tumor, buffy coat cells, and plasma from 2 patients with metastatic breast cancer were characterized simultaneously for copy number aberrations (CNAs) and differentially methylated regions (DMRs) using whole genome bisulfite sequencing (WBGS), and targeted sequencing-based genotyping of 346 cancer-associated single nucleotide variations (SNVs). CNA and DMR regions were identified from log normalized, GC content corrected counts and DMR data using Poisson and binomial distribution theory and false discovery rate controlling methods. Percent tumor in cfDNA was estimated from the normalized ratio (plasma: primary tumor) of CNA or DMR compared to buffy coat, aggregating over genomic regions. Sample sets from 8 non-metastatic patients were also profiled using the targeted SNV panel in order to compare SNVs between samples and estimate percent tumor cfDNA. Results: WGBS detected tumor specific alterations in each primary tumor compared to buffy coat. By analyzing the genome using 100 Kb bins, we observed over 1000 bins with detectable CNA signal and, among 56 million CpG sites, over 30,000 DMRs. As expected, 5 or fewer informative somatic SNVs were detected in each patient. Analysis of these somatic changes in plasma revealed that the tumor fraction estimated from SNV detected in cfDNA varied widely between sites originally discovered in the patient’s primary tumor. In contrast, similar estimates of tumor fraction in cfDNA were obtained using CNA and DMR profiles within each patient; both methods yielded similar estimates of over 50% in one patient and less than 10% in the other. For the patient with high tumor fraction, both CNA and DMR profiles contained examples of individual large genomic regions that displayed additional clear aberrations in the plasma compared to the original tumor, such as a striking loss of a >25 Mb region of chromosome 4. Conclusions: Although individual somatic SNV in cfDNA can be detected in metastatic disease, calculated allelic fraction based on individual SNVs varies greatly within the same patient. Measuring and integrating CNA or DMR across the genome provided more consistent and reliable estimates of tumor DNA fraction in plasma, and also revealed alterations in plasma from patients with metastatic disease that were not prominent in the primary tumor. Citation Format: Ellen M Beasley, Richard D Abramson, Gregory E Alexander, David Chan, Kristen Bradley, Francois Collin, Michael Crager, Andrew Dei Rossi, Joseph Dorado, Adam Friedman, William J Gibb, Jennie Jeong, Col Jones, C J Ku, Yan Ma, John Morlan, Kunbin Qu, Aibing Rao, Aaron Scott, Haluk Tezcan. Global quantitative measures using next-generation sequencing for breast cancer presence outperform individual tumor markers in plasma [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-02-08.

Abstract P2-03-14: Long range expression patterns detected by RNASeq in breast cancer reveal cluster enriched with triple negative breast cancer

Abstract Background: Breast cancer subtyping using gene expression is well established in breast cancer research. While it is known that there are large chromosomal regions affected by copy number polymorphisms in breast cancer, it is not clear whether expression patterns reflect large genomic events affecting longer portion of the chromosome. We present a method to quantify long range gene expression patterns of larger genomic regions at 23kb, 100kb and 1mb. Methods: We used TCGA-level 2 breast cancer gene expression data (RNA-Seq) generated at the Carolina Center for Genome Sciences, UNC at Chapel Hill. We evaluated the long range expression patterns of 649 patients for which we had ER, PR and Her2 status data by IHC. For 221 samples we had ER, PR, Her2, age, menopausal status, p53 and PIK3CA mutation status. Our method defines long range expression within a window of a particular length (e.g. 23kb, 100kb). We take the mean expression scores for all genes that fall within each window and concatenate these windows to obtain larger chromosome-wide patterns. The final chromosome-wide vectors are concatenated to represent long range expression patterns across the entire genome. We then evaluate the variation of these window scores across all samples and keep top 2% varying windows. Then, we apply hierarchical clustering, and evaluate enrichment of clinically meaningful subtypes using hypergeometric test. Results: Simple hierarchical clustering revealed clear separation of triple negative breast cancer samples at any level of resolution: 23kb, 100kb in the available data set. While the 100kb resolution showed two distinct clusters, the 23kb resolution showed three distinct clusters. Interestingly, the hierarchical clustering of samples (n=649) using the top 214 (2%) highly varying long 100kb regions revealed a cluster which contained 99 samples and was enriched with 75 TNBC samples (out of 102 TNBC in the entire set) (p=1.7E-53). The long range expression of 23Kb regions on 221 samples revealed 319 (2%) such regions which further segregate the samples into three different clusters: Cluster1: Luminal enriched cluster with 147 samples out of which 104 are ER+PR+Her2- samples (p-value <<0.01), Cluster2: Her2+ enriched cluster with 31 samples out of which 23 are Her2+ (p-value<<0. 01), and Cluster3: TNBC enriched cluster containing 33 samples out of which 26 are TNBC (p=1.5E-18). There are a total number of 38 TNBC samples. Furthermore, in the TNBC cluster with 33 samples, 28 had p53 mutations and 24 of those were both TNBC and had p53 mutations (p-value << 0.05). In this TNBC cluster, there is enrichment of samples lacking PIK3CA mutations (n=31)(p-value <<0.01). We found no clear association with age and menopausal status. Conclusions: Hierarchical clustering relying on long range expression regions produces clusters that are enriched with well known clinically relevant subtypes. The associations with known tumor biology are strong for different region sizes (23kb and 100kb). This is the first study to report long range gene expression patterns that reveal data-driven close association with tumor biology. Citation Format: Alex Mankovich, Vartika Agrawal, Nilanjana Banerjee, Nevenka Dimitrova. Long range expression patterns detected by RNASeq in breast cancer reveal cluster enriched with triple negative breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P2-03-14.

Chromosome number varies in humans

Human Genetics Pregnancy loss is often associated with a loss of chromosome number, a condition known as aneuploidy. When examining aneuploid embryos during in vitro fertilization cycles, McCoy et al. found a large genomic region associated with defects in maternal chromosome number (see the Perspective by Vohr and Green). This region contains a gene, Polo-like Kinase 4 ( PLK4 ), that is known to affect chromosome segregation and has variants that correlate with an increased rate of maternal aneuploidy. Surprisingly, such variants occur at relatively high levels in human populations and may be under positive selection. Science , this issue p. [235][1]; see also p. [180][2] [1]: /lookup/doi/10.1126/science.aaa3337 [2]: /lookup/doi/10.1126/science.aab0877

Common variants spanning PLK4 are associated with mitotic-origin aneuploidy in human embryos.

Aneuploidy, the inheritance of an atypical chromosome complement, is common in early human development and is the primary cause of pregnancy loss. By screening day-3 embryos during in vitro fertilization cycles, we identified an association between aneuploidy of putative mitotic origin and linked genetic variants on chromosome 4 of maternal genomes. This associated region contains a candidate gene, Polo-like kinase 4 (PLK4), that plays a well-characterized role in centriole duplication and has the ability to alter mitotic fidelity upon minor dysregulation. Mothers with the high-risk genotypes contributed fewer embryos for testing at day 5, suggesting that their embryos are less likely to survive to blastocyst formation. The associated region coincides with a signature of a selective sweep in ancient humans, suggesting that the causal variant was either the target of selection or hitchhiked to substantial frequency.

Nuclear lamins are not required for lamina-associated domain organization in mouse embryonic stem cells.

In mammals, the nuclear lamina interacts with hundreds of large genomic regions, termed lamina-associated domains (LADs) that are generally in a transcriptionally repressed state. Lamins form the major structural component of the lamina and have been reported to bind DNA and chromatin. Here, we systematically evaluate whether lamins are necessary for the LAD organization in murine embryonic stem cells. Surprisingly, removal of essentially all lamins does not have any detectable effect on the genome-wide interaction pattern of chromatin with emerin, a marker of the inner nuclear membrane. This suggests that other components of the lamina mediate these interactions.

Recent and massive expansion of the mating-type-specific region in the smut fungus Microbotryum.

The presence of large genomic regions with suppressed recombination (SR) is a key shared property of some sex- and mating-type determining (mat) chromosomes identified to date in animals, plants, and fungi. Why such regions form and how they evolve remain central questions in evolutionary genetics. The smut fungus Microbotryum lychnis-dioicae is a basidiomycete fungus in which dimorphic mat chromosomes have been reported, but the size, age, and evolutionary dynamics of the SR region remains unresolved. To identify the SR region in M. lychnis-dioicae and to study its evolution, we sequenced 12 genomes (6 per mating type) of this species and identified the genomic contigs that show fixed sequence differences between the mating types. We report that the SR region spans more than half of the mat chromosome (>2.3 Mbp) and that it is of very recent origin (∼2 × 10(6) years) as the average sequence divergence between mating types was only 2% in the SR region. This contrasts with a much higher divergence in and around the mating-type determining pheromone receptor locus in the SR, suggesting a recent and massive expansion of the SR region. Our results comprise the first reported case of recent massive SR expansion documented in a basidiomycete fungus.

In silico identification and characterisation of 17 polymorphic anonymous non-coding sequence markers (ANMs) for red grouse (Lagopus lagopus scotica)

Anonymous non-coding sequence markers (ANMs) are powerful neutral genetic markers with great utility in phylogeography, population genetics and population genomics. Developing ANMs has previously relied on sequencing random fragments of genomic DNA in the target species and then querying bioinformatics databases to identify unannotated, putatively neutral fragments. Here, we describe an alternative in silico approach that is based on identifying large unannotated genomic regions in model species to provide a priori neutral targets for candidate ANMs that are remote from exonic regions. We illustrate this approach by developing a set of 17 polymorphic ANMs for red grouse (Lagopus lagopus scotica) from c. 1 Mbp non-coding chromosome regions of chicken, turkey and zebrafinch genomes. This pipeline presents a powerful and efficient approach when appropriate model genomes are available for the target species of interest.

Genomic, Epigenomic, and Transcriptomic Profiling towards Identifying Omics Features and Specific Biomarkers That Distinguish Uterine Leiomyosarcoma and Leiomyoma at Molecular Levels.

Uterine leiomyosarcoma (LMS) is the worst malignancy among the gynecologic cancers. Uterine leiomyoma (LM), a benign tumor of myometrial origin, is the most common among women of childbearing age. Because of their similar symptoms, it is difficult to preoperatively distinguish the two conditions only by ultrasound and pelvic MRI. While histopathological diagnosis is currently the main approach used to distinguish them postoperatively, unusual histologic variants of LM tend to be misdiagnosed as LMS. Therefore, development of molecular diagnosis as an alternative or confirmatory means will help to diagnose LMS more accurately. We adopted omics-based technologies to identify genome-wide features to distinguish LMS from LM and revealed that copy number, gene expression, and DNA methylation profiles successfully distinguished these tumors. LMS was found to possess features typically observed in malignant solid tumors, such as extensive chromosomal abnormalities, overexpression of cell cycle-related genes, hypomethylation spreading through large genomic regions, and frequent hypermethylation at the polycomb group target genes and protocadherin genes. We also identified candidate expression and DNA methylation markers, which will facilitate establishing postoperative molecular diagnostic tests based on conventional quantitative assays. Our results demonstrate the feasibility of establishing such tests and the possibility of developing preoperative and noninvasive methods.

Transcriptome assembly and alternative splicing analysis.

Alternative Splicing (AS) is the molecular phenomenon whereby multiple transcripts are produced from the same gene locus. As a consequence, it is responsible for the expansion of eukaryotic transcriptomes. Aberrant AS is involved in the onset and progression of several human diseases. Therefore, the characterization of exon-intron structure of a gene and the detection of corresponding transcript isoforms is an extremely relevant biological task. Nonetheless, the computational prediction of AS events and the repertoire of alternative transcripts is yet a challenging issue. Hereafter we introduce PIntron, a software package to predict the exon-intron structure and the full-length isoforms of a gene given a genomic region and a set of transcripts (ESTs and/or mRNAs). The software is open source and available at http://pintron.algolab.eu. PIntron has been designed for (and extensively tested on) a standard workstation without requiring dedicated expensive hardware. It easily manages large genomic regions and more than 20,000 ESTs, achieving good accuracy as shown in an experimental evaluation performed on 112 well-annotated genes selected from the ENCODE human regions used as training set in the EGASP competition.

Common polygenic variation and risk for childhood-onset schizophrenia

Childhood-onset schizophrenia (COS) is a rare and severe form of the disorder, with more striking abnormalities with respect to prepsychotic developmental disorders and abnormities in the brain development compared with later-onset schizophrenia. We previously documented that COS patients, compared with their healthy siblings and with adult-onset patients (AOS), carry significantly more rare chromosomal copy number variations, spanning large genomic regions (>100 kb) (Ahn et al. 2014). Here, we interrogated the contribution of common polygenic variation to the genetic susceptibility for schizophrenia. We examined the association between a direct measure of genetic risk of schizophrenia in 130 COS probands and 103 healthy siblings. Using data from the schizophrenia and autism GWAS of the Psychiatric Genomic Consortia, we selected three risk-related sets of single nucleotide polymorphisms from which we conducted polygenic risk score comparisons for COS probands and their healthy siblings. COS probands had higher genetic risk scores of both schizophrenia and autism than their siblings (P<0.05). Given the small sample size, these findings suggest that COS patients have more salient genetic risk than do AOS.

Strategies to Identify Adaptive Genes in Hybridizing Trees like Oaks and Poplars

Ecologically divergent, hybridizing species such as oaks and poplars provide models to identify genomic regions under selection and adaptive alleles that are transferred between species in hybrid zones. Oaks show patterns of genomic divergence characteristic for early stages of speciation with gene flow, in which large genomic regions are homogenized by interspecific gene flow interspersed by smaller regions (outlier regions) with high interspecific differentiation as result of divergent selection. These outlier regions can be identified using genome scans in hybrid zones and anchored to the Quercus robur genome sequence which will become available in the near future. Combined outlier and association genetic approaches can assess the role of individual genes in outlier genomic regions in adaptive trait variation. In contrast, hybridizing poplar species show a pattern of genomic divergence with large genomic regions of high interspecific differentiation punctuated by smaller regions of low differentiation as the result of interspecific gene flow. Genome scans in multiple hybrid zones of interfertile poplar species and in populations outside the area of sympatry will allow for the identification of genes that are exchanged between species by interspecific gene flow using the Populus trichocarpa genome sequence as a reference. Again association genetic approaches can be used for the characterization of variation in these introgressed genes with adaptive trait variation. In the present paper, the application of genomic approaches to identify genes for adaptive species divergence and reproductive isolation, and introgressed genes between species is discussed.

High-resolution genetic mapping in the diversity outbred mouse population identifies Apobec1 as a candidate gene for atherosclerosis.

Inbred mice exhibit strain-specific variation in susceptibility to atherosclerosis and dyslipidemia that renders them useful in dissecting the genetic architecture of these complex diseases. Traditional quantitative trait locus (QTL) mapping studies using inbred strains often identify large genomic regions, containing many genes, due to limited recombination and/or sample size. This hampers candidate gene identification and translation of these results into possible risk factors and therapeutic targets. An alternative approach is the use of multiparental outbred lines for genetic mapping, such as the Diversity Outbred (DO) mouse panel, which can be more informative than traditional two-parent crosses and can aid in the identification of causal genes and variants associated with QTL. We fed 292 female DO mice either a high-fat, cholesterol-containing (HFCA) diet, to induce atherosclerosis, or a low-fat, high-protein diet for 18 wk and measured plasma lipid levels before and after diet treatment. We measured markers of atherosclerosis in the mice fed the HFCA diet. The mice were genotyped on a medium-density single-nucleotide polymorphism array and founder haplotypes were reconstructed using a hidden Markov model. The reconstructed haplotypes were then used to perform linkage mapping of atherosclerotic lesion size as well as plasma total cholesterol, triglycerides, insulin, and glucose. Among our highly significant QTL we detected a ~100 kb QTL interval for atherosclerosis on Chromosome 6, as well as a 1.4 Mb QTL interval on Chromosome 9 for triglyceride levels at baseline and a coincident 22.2 Mb QTL interval on Chromosome 9 for total cholesterol after dietary treatment. One candidate gene within the Chromosome 6 peak region associated with atherosclerosis is Apobec1, the apolipoprotein B (ApoB) mRNA-editing enzyme, which plays a role in the regulation of ApoB, a critical component of low-density lipoprotein, by editing ApoB mRNA. This study demonstrates the value of the DO population to improve mapping resolution and to aid in the identification of potential therapeutic targets for cardiovascular disease. Using a DO mouse population fed an HFCA diet, we were able to identify an A/J-specific isoform of Apobec1 that contributes to atherosclerosis.

Dorothy Hodgkin Lecture 2014. Understanding genes identified by genome-wide association studies for type 2 diabetes.

Whilst the heritable nature of Type 2 diabetes has been recognized for many years, only in the past two decades have linkage analyses in families and genome-wide association studies in large populations begun to reveal the genetic landscape of the disease in detail. Whilst the former have provided a powerful means of identifying the genes responsible for monogenic forms of the disease, the latter highlight relatively large genomic regions. These often harbour multiple genes, whose relative contribution to exaggerated disease risk is uncertain. In the present study, the approaches that have been used to dissect the role of just a few (TCF7L2, SLC30A8, ADCY5, MTNR1B and CDKAL1) of the ~500 genes identified at dozens of implicated loci are described. These are usually selected based on the strength of their effect on disease risk, and predictions as to their likely biological role. Direct determination of the effects of identified polymorphisms on gene expression in disease-relevant tissues, notably the pancreatic islet, are then performed to identify genes whose expression is affected by a particular polymorphism. Subsequent functional analyses then involve perturbing gene expression in vitro in β-cell lines or isolated islets and in vivo in animal models. Although the majority of polymorphisms affect insulin production rather than action, and mainly affect the β cell, effects via other tissues may also contribute, requiring careful consideration in the design and interpretation of experiments in model systems. These considerations illustrate the scale of the task needed to exploit genome-wide association study data for the development of new therapeutic strategies.