Allelic Bias Research Articles

Novel parent-of-origin-specific differentially methylated loci on chromosome 16

BackgroundCongenital malformations associated with maternal uniparental disomy of chromosome 16, upd(16)mat, resemble those observed in newborns with the lethal developmental lung disease, alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV). Interestingly, ACDMPV-causative deletions, involving FOXF1 or its lung-specific upstream enhancer at 16q24.1, arise almost exclusively on the maternally inherited chromosome 16. Given the phenotypic similarities between upd(16)mat and ACDMPV, together with parental allelic bias in ACDMPV, we hypothesized that there may be unknown imprinted loci mapping to chromosome 16 that become functionally unmasked by chromosomal structural variants.ResultsTo identify parent-of-origin biased DNA methylation, we performed high-resolution bisulfite sequencing of chromosome 16 on peripheral blood and cultured skin fibroblasts from individuals with maternal or paternal upd(16) as well as lung tissue from patients with ACDMPV-causative 16q24.1 deletions and a normal control. We identified 22 differentially methylated regions (DMRs) with ≥ 5 consecutive CpG methylation sites and varying tissue-specificity, including the known DMRs associated with the established imprinted gene ZNF597 and DMRs supporting maternal methylation of PRR25, thought to be paternally expressed in lymphoblastoid cells. Lastly, we found evidence of paternal methylation on 16q24.1 near LINC01082 mapping to the FOXF1 enhancer.ConclusionsUsing high-resolution bisulfite sequencing to evaluate DNA methylation across chromosome 16, we found evidence for novel candidate imprinted loci on chromosome 16 that would not be evident in array-based assays and could contribute to the birth defects observed in patients with upd(16)mat or in ACDMPV.

Selection on structural allelic variation biases plasticity estimates.

Wang and Althoff (2019) explored the capacity of Drosophila melanogaster to exhibit adaptive plasticity in a novel environment. In a full-sib, half-sib design, they scored the activity of the enzyme alcohol dehydrogenase (ADH) and plastic responses, measured as changes in ADH activity across ethanol concentrations in the range of 0-10% (natural variation) and 16% (the novel environment). ADH activity increased with alcohol concentration, and there was a positive association between larval viability and ADH activity in the novel environment. They also reported that families exhibiting greater plasticity had higher larval survival in the novel environment, concluding that ADH plasticity is adaptive. However, the four authors now concur that, since the study estimated plasticity from phenotypic differences across environments using full-sib families, it is not possible to disentangle the contributions of allele frequency changes at the Adh locus from regulatory control at loci known to influence ADH activity. Selective changes in allele frequencies may thus conflate estimates of plasticity; any type of "plasticity" (adaptive, neutral, or maladaptive) could be inferred depending on allele frequencies. The problem of scoring sib-groups after selection should be considered in any plasticity study that cannot use replicated genotypes. Researchers should monitor changes in allele frequencies as one mechanism to deal with this issue.

Consistent Reanalysis of Genome-wide Imprinting Studies in Plants Using Generalized Linear Models Increases Concordance across Datasets

Genomic imprinting leads to different expression levels of maternally and paternally derived alleles. Over the last years, major progress has been made in identifying novel imprinted candidate genes in plants, owing to affordable next-generation sequencing technologies. However, reports on sequencing the transcriptome of hybrid F1 seed tissues strongly disagree about how many and which genes are imprinted. This raises questions about the relative impact of biological, environmental, technical, and analytic differences or biases. Here, we adopt a statistical approach, frequently used in RNA-seq data analysis, which properly models count overdispersion and considers replicate information of reciprocal crosses. We show that our statistical pipeline outperforms other methods in identifying imprinted genes in simulated and real data. Accordingly, reanalysis of genome-wide imprinting studies in Arabidopsis and maize shows that, at least for Arabidopsis, an increased agreement across datasets could be observed. For maize, however, consistent reanalysis did not yield a larger overlap between the datasets. This suggests that the discrepancy across publications might be partially due to different analysis pipelines but that technical, biological, and environmental factors underlie much of the discrepancy between datasets. Finally, we show that the set of genes that can be characterized regarding allelic bias by all studies with minimal confidence is small (~8,000/27,416 genes for Arabidopsis and ~12,000/39,469 for maize). In conclusion, we propose to use biologically replicated reciprocal crosses, high sequence coverage, and a generalized linear model approach to identify differentially expressed alleles in developing seeds.

Fully Bayesian analysis of allele-specific RNA-seq data.

Diploid organisms have two copies of each gene, called alleles, that can be separately transcribed. The RNA abundance associated to any particular allele is known as allele-specific expression (ASE). When two alleles have polymorphisms in transcribed regions, ASE can be studied using RNA-seq read count data. ASE has characteristics different from the regular RNA-seq expression: ASE cannot be assessed for every gene, measures of ASE can be biased towards one of the alleles (reference allele), and ASE provides two measures of expression for a single gene for each biological samples with leads to additional complications for single-gene models. We present statistical methods for modeling ASE and detecting genes with differential allelic expression. We propose a hierarchical, overdispersed, count regression model to deal with ASE counts. The model accommodates gene-specific overdispersion, has an internal measure of the reference allele bias, and uses random effects to model the gene-specific regression parameters. Fully Bayesian inference is obtained using the fbseq package that implements a parallel strategy to make the computational times reasonable. Simulation and real data analysis suggest the proposed model is a practical and powerful tool for the study of differential ASE.

FORGe: prioritizing variants for graph genomes

There is growing interest in using genetic variants to augment the reference genome into a graph genome, with alternative sequences, to improve read alignment accuracy and reduce allelic bias. While adding a variant has the positive effect of removing an undesirable alignment score penalty, it also increases both the ambiguity of the reference genome and the cost of storing and querying the genome index. We introduce methods and a software tool called FORGe for modeling these effects and prioritizing variants accordingly. We show that FORGe enables a range of advantageous and measurable trade-offs between accuracy and computational overhead.

3'Igh enhancers hs3b/hs4 are dispensable for Myc deregulation in mouse plasmacytomas with T(12;15) translocations.

Myc-deregulating T(12;15) chromosomal translocations are the hallmark cytogenetic abnormalities of murine plasmacytomas (PCTs). In most PCTs, the immunoglobulin heavy chain (Igh) locus is broken between the Eμ enhancer and the 3’ regulatory region (3’RR), making the latter the major candidate for orchestrating Myc deregulation. To elucidate the role of the Igh3’RR in tumorigenesis, we induced PCTs in Bcl-xL-transgenic mice deficient for the major Igh3’RR enhancer elements, hs3b and hs4 (hs3b-4-/-). Contrary to previous observations using a mouse lymphoma model, which showed no tumors with peripheral B-cell phenotype in hs3b-4-/- mice, these animals developed T(12;15)-positive PCTs, although with a lower incidence than hs3b-4+/+ (wild-type, WT) controls. In heterozygous hs3b-4+/- mice there was no allelic bias in targeting Igh for T(12;15). Molecular analyses of Igh/Myc junctions revealed dominance of Sμ region breakpoints versus the prevalence of Sγ or Sα in WT controls. Myc expression and Ig secretion in hs3b-4-/- PCTs did not differ from WT controls. We also evaluated the effect of a complete Igh3’RR deletion on Myc expression in the context of an established Igh/Myc translocation in ARS/Igh11-transgenic PCT cell lines. Cre-mediated deletion of the Igh3’RR resulted in gradual reduction of Myc expression, loss of proliferative activity and increased cell death, confirming the necessity of the Igh3’RR for Myc deregulation by T(12;15).

Genotyping Polyploids from Messy Sequencing Data.

Detecting and quantifying the differences in individual genomes (i.e., genotyping), plays a fundamental role in most modern bioinformatics pipelines. Many scientists now use reduced representation next-generation sequencing (NGS) approaches for genotyping. Genotyping diploid individuals using NGS is a well-studied field, and similar methods for polyploid individuals are just emerging. However, there are many aspects of NGS data, particularly in polyploids, that remain unexplored by most methods. Our contributions in this paper are fourfold: (i) We draw attention to, and then model, common aspects of NGS data: sequencing error, allelic bias, overdispersion, and outlying observations. (ii) Many datasets feature related individuals, and so we use the structure of Mendelian segregation to build an empirical Bayes approach for genotyping polyploid individuals. (iii) We develop novel models to account for preferential pairing of chromosomes, and harness these for genotyping. (iv) We derive oracle genotyping error rates that may be used for read depth suggestions. We assess the accuracy of our method in simulations, and apply it to a dataset of hexaploid sweet potato (Ipomoea batatas). An R package implementing our method is available at https://cran.r-project.org/package=updog.

Unperturbed expression bias of imprinted genes in schizophrenia

How gene expression correlates with schizophrenia across individuals is beginning to be examined through analyses of RNA-seq from postmortem brains of individuals with disease and control brains. Here we focus on variation in allele-specific expression, following up on the CommonMind Consortium (CMC) RNA-seq experiments of nearly 600 human dorsolateral prefrontal cortex (DLPFC) samples. Analyzing the extent of allelic expression bias—a hallmark of imprinting—we find that the number of imprinted human genes is consistent with lower estimates (≈0.5% of all genes), and thus contradicts much higher estimates. Moreover, the handful of putatively imprinted genes are all in close genomic proximity to known imprinted genes. Joint analysis of the imprinted genes across hundreds of individuals allowed us to establish how allelic bias depends on various factors. We find that age and genetic ancestry have gene-specific, differential effect on allelic bias. In contrast, allelic bias appears to be independent of schizophrenia.

Abstract 440: Single-cell whole-genome sequencing reveals somatic mutation signatures in normal somatic cells predictive of cancer later in life

Abstract Single-cell sequencing for analyzing DNA mutations across the genome in somatic tissues is critically important for studying development, cancer and aging. However, current procedures are prone to artifacts and to date a reliable protocol for single-cell somatic mutation analysis remains to be developed. We address the two largest sources of artifacts, i.e., DNA denaturation-related cytosine deamination and allelic bias-driven whole genome amplification errors. We first reconfigured multiple displacement amplification (MDA) into an efficient protocol for whole genome amplification of single cells without cytosine deamination artifacts, i.e., Single Cell MDA (SCMDA). We then developed a new single-cell SNV caller (SCcaller) that distinguishes real somatic mutations and amplification errors by utilizing a SNP-based localized estimate of allelic amplification bias. The procedure was validated by comparing SCMDA-amplified single cells with unamplified clones derived from single cells from the same population. Using this highly accurate single-cell whole-genome sequencing method we analyzed human B lymphocytes from donors varying in age from birth to over 100 year, studying both genome distribution and functional impact of base substitution mutations. Mutations per cell were found to increase with age from less than 500 in cord blood to over 3,000 in cells from individuals over 100. While overall mutations were randomly distributed across the genome with all chromosomes equally affected, 24 hotspot regions were identified, five of which were part of immunoglobulin variable regions subject to somatic hypermutation. Age-related mutation accumulation was found to be significantly slower in genomic sequences directly involved in cellular function, such as exons and gene regulatory sequences. Still, on average, B lymphocytes from aged individuals contained 3-15 damaging mutations in the transcribed part of the exome identified by RNA-seq, plus 15-50 mutations in transcription factor binding sites identified by ATAC-seq. Analysis of the spontaneous mutation spectra in these normal cells revealed signatures similar to those previously found associated with B cell leukemia and other cancers. These results indicate that cancer risk is already part of age-related mutation accumulation in normal cells. Taken together, our single-cell sequencing method provides a firm foundation for analyzing cellular genetic heterogeneity in normal human tissues. Citation Format: Xiao Dong, Lei Zhang, Moonsook Lee, Alexander Y. Maslov, Jan Vijg. Single-cell whole-genome sequencing reveals somatic mutation signatures in normal somatic cells predictive of cancer later in life [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 440.

Dosage compensation and its roles in evolution of sex chromosomes and phenotypic dimorphism: lessons from Drosophila, C.elegans and mammals

In many sexually reproducing species, sex is determined by cytologically distinguishable ‘sex chromosomes’. The popular view is that the consequence of heteromorphic sex chromosomes is detrimental, and evolutionary emergence of dosage compensation mechanism is expected for two fold upregulation of X linked genes in order to restore the balance for the haplo-X in the sex against the diplo X of the other. Since, male and female share nearly identical genome in most animals, and since antagonistic selection operate for the expression divergence of the sex biased genes between sexes for mating type distinction, dosage compensation system is evolved in many species to link global transcription profile of the genome through histone variants and epigenetic modification of the genes for driving sex determination function. Whole genome transcriptome analyses and the investigations on the profiling of accessible chromatin components in male and female at different phase of development of Drosophila, C. elegans and mammal revealed that 50–60% X and autosomal genes of the genomes are expressed under sex specific selection through allelic bias (except some required dosage sensitive genes) expression, ranging from absent to complete compensation. The review focuses the recent development of dosage compensation research and illustrates its roles in sex chromosome evolution and sexual dimorphism in Drosophila, C. elegans and mammals.

Allele-specific expression at the androgen receptor alpha gene in a hybrid unisexual fish, the Amazon molly (Poecilia formosa).

The all-female Amazon molly (Poecilia formosa) is the result of a hybridization of the Atlantic molly (P. mexicana) and the sailfin molly (P. latipinna) approximately 120,000 years ago. As a gynogenetic species, P. formosa needs to copulate with heterospecific males including males from one of its bisexual ancestral species. However, the sperm only triggers embryogenesis of the diploid eggs. The genetic information of the sperm donor typically will not contribute to the next generation of P. formosa. Hence, P. formosa possesses generally one allele from each of its ancestral species at any genetic locus. This raises the question whether both ancestral alleles are equally expressed in P. formosa. Allele-specific expression (ASE) has been previously assessed in various organisms, e.g., human and fish, and ASE was found to be important in the context of phenotypic variability and disease. In this study, we utilized Real-Time PCR techniques to estimate ASE of the androgen receptor alpha (arα) gene in several distinct tissues of Amazon mollies. We found an allelic bias favoring the maternal ancestor (P. mexicana) allele in ovarian tissue. This allelic bias was not observed in the gill or the brain tissue. Sequencing of the promoter regions of both alleles revealed an association between an Indel in a known CpG island and differential expression. Future studies may reveal whether our observed cis-regulatory divergence is caused by an ovary-specific trans-regulatory element, preferentially activating the allele of the maternal ancestor.

Conclusive evidence for hexasomic inheritance in chrysanthemum based on analysis of a 183\xa0k SNP array

BackgroundCultivated chrysanthemum is an outcrossing hexaploid (2n = 6× = 54) with a disputed mode of inheritance. In this paper, we present a single nucleotide polymorphism (SNP) selection pipeline that was used to design an Affymetrix Axiom array with 183 k SNPs from RNA sequencing data (1). With this array, we genotyped four bi-parental populations (with sizes of 405, 53, 76 and 37 offspring plants respectively), and a cultivar panel of 63 genotypes. Further, we present a method for dosage scoring in hexaploids from signal intensities of the array based on mixture models (2) and validation of selection steps in the SNP selection pipeline (3). The resulting genotypic data is used to draw conclusions on the mode of inheritance in chrysanthemum (4), and to make an inference on allelic expression bias (5).ResultsWith use of the mixture model approach, we successfully called the dosage of 73,936 out of 183,130 SNPs (40.4%) that segregated in any of the bi-parental populations. To investigate the mode of inheritance, we analysed markers that segregated in the large bi-parental population (n = 405). Analysis of segregation of duplex x nulliplex SNPs resulted in evidence for genome-wide hexasomic inheritance. This evidence was substantiated by the absence of strong linkage between markers in repulsion, which indicated absence of full disomic inheritance. We present the success rate of SNP discovery out of RNA sequencing data as affected by different selection steps, among which SNP coverage over genotypes and use of different types of sequence read mapping software. Genomic dosage highly correlated with relative allele coverage from the RNA sequencing data, indicating that most alleles are expressed according to their genomic dosage.ConclusionsThe large population, genotyped with a very large number of markers, is a unique framework for extensive genetic analyses in hexaploid chrysanthemum. As starting point, we show conclusive evidence for genome-wide hexasomic inheritance.

Abstract 499: IgH enhancers hs3b/hs4 are dispensable for c-Myc deregulation in mouse plasmacytomas with T(12;15) translocations

Abstract c-Myc deregulating t(12;15) chromosomal translocation is the hallmark cytogenetic abnormality of murine plasmacytomas (PCTs). In the great majority of PCTs, the immunoglobulin heavy chain (IgH) locus is broken between Eμ enhancer and the 3’ regulatory region (3’RR), making the latter the major candidate for orchestrating c-Myc deregulation. To elucidate the role of 3’RR in tumorigenesis, we induced PCTs in mice deficient for the major 3’RR enhancer elements, namely hs3b and hs4 (3’KO). Unexpectedly, and contrary to the previous observations made in a mouse lymphoma model, Hs3b/Hs4 3’KO mice did develop t(12;15)-positive PCTs, although with a lower incidence than wild-type controls. In heterozygous mice, there was no allelic bias in targeting IgH for the t(12;15). Molecular analysis of IgH/Myc junctions revealed dominance of Sμ region breakpoints compared to the prevalence of hits into Sγ or Sα in the controls. Analysis of c-Myc expression as well as Ig secretion in 3’KO PCT cell lines revealed no significant differences from the controls. Our current findings highlight the complexity of the 3’RR and the potential of its components to compensate for each other in the context of differentiation from B-lymphocyte to plasma cell. We next extended our observations to include a PCT model where Cre-mediated deletion can remove all four 3'IgH enhancers: hs3a, hs1,2, hs3b and hs4. In PCT cell lines where c-Myc is translocated to an IgH BAC transgene with a floxed 3’IgH enhancer region, induction of retrovirally-expressed Cre-recombinase causes gradual Myc downregulation and complete cell death within 96 hours. The later observation confirms the requirement of the full 3’RR for c-Myc deregulation by T(12;15). Citation Format: Alexander L. Kovalchuk, Herbert C. Morse. IgH enhancers hs3b/hs4 are dispensable for c-Myc deregulation in mouse plasmacytomas with T(12;15) translocations [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 499. doi:10.1158/1538-7445.AM2017-499

Abstract 5400: Accurate identification of single nucleotide variants in whole genome amplified single cells

Abstract Single cell sequencing for analyzing DNA mutations across the genome in somatic tissues is critically important for studying development, cancer and aging. However, current procedures are prone to artifacts and to date a reliable protocol for single-cell somatic mutation analysis remains to be developed. Here we address the two largest sources of artifacts, i.e., DNA denaturation-related cytosine deamination and allelic bias-driven whole genome amplification errors. We first reconfigured multiple displacement amplification (MDA) into an efficient protocol for whole genome amplification of single cells without cytosine deamination artifacts, i.e., Single Cell MDA (SCMDA). We then developed a new single-cell SNV caller (SCcaller) that distinguishes real somatic mutations and amplification errors by utilizing a SNP-based localized estimate of allelic amplification bias. The procedure was validated by comparing SCMDA-amplified single cells with unamplified clones derived from single cells from the same population. Together with SCcaller, SCMDA provides a firm foundation for analyzing cellular heterogeneity in somatic mutational landscapes in tumor and surrounding, normal tissues. Citation Format: Xiao Dong, Lei Zhang, Brandon Milholland, Moonsook Lee, Alexander Y. Maslov, Tao Wang, Jan Vijg. Accurate identification of single nucleotide variants in whole genome amplified single cells [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 5400. doi:10.1158/1538-7445.AM2017-5400

Association of apelin and apelin receptor with the risk of coronary artery disease: a meta-analysis of observational studies

It is well established that apelin-APLNR (apelin receptor) pathway plays a central role in cardiovascular system. In this meta-analysis, we summarized published results on circulating apelin concentration in association with coronary artery disease (CAD), apelin and APLNR genetic polymorphism(s) in predisposition to CAD risk and circulating apelin changes after surgical treatment for CAD. The results from 15 articles were pooled. Two authors independently took charge of literature search, article selection and information collection. Overall, circulating apelin concentration was significantly lower in CAD patients (N=1021) than in controls (N=654) (weighted mean difference [WMD]: -1.285 ng/mL, 95% confidence interval [CI]: -1.790 to -0.780, P<0001), with significant heterogeneity (I2=99.3%) but without publication bias. For the association of APLNR gene rs9943582 polymorphism with CAD (patients/controls: 5975/4717), the mutant T allele was associated with a 5.2% increased risk relative to the wild C allele (odds ratio: 1.052, 95% CI: 0.990 to 1.117, P=0.100), without heterogeneity (I2=0.0%) or publication bias. Circulating apelin was increased significantly after surgical treatment for CAD (N=202) (WMD: 2.011 ng/mL, 95% CI: 0.541 to 3.481, P=0.007), with significant heterogeneity (I2=98.0%). Stratified analyses showed that circulating apelin was significantly reduced in studies with age- and sex-matched patients and controls (WMD: -1.881 ng/mL, 95% CI: -2.457 to -1.304, P<0.001) and with total sample size ≥125 (WMD: -1.657 ng/mL, 95% CI: -2.378 to -0.936, P<0.001), relative to studies without matching reports and with total sample size <125. In brief, our results suggested that circulating apelin was a prominent athero-protective marker against the development of CAD.

Genetic regulatory signatures underlying islet gene expression and type 2 diabetes

Genome-wide association studies (GWAS) have identified >100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition.

Haplotyping a Non-meiotic Diploid Fungal Pathogen Using Induced Aneuploidies and SNP/CGH Microarray Analysis.

The generation of haplotype information has recently become very attractive due to its utility for identifying mutations associated with human disease and for the development of personalized medicine. Haplotype information also is crucial for studying recombination mechanisms and genetic diversity, and for analyzing allele-specific gene expression. Classic haplotyping methods require the analysis of hundreds of meiotic progeny. To facilitate haplotyping in the non-meiotic human fungal pathogen Candida albicans, we exploited trisomic heterozygous chromosomes generated via the UAU1 selection strategy. Using this system, we obtained phasing information from allelic biases, detected by SNP/CGH microarray analysis. This strategy has the potential to be applicable to other diploid, asexual Candida species that are important causes of human disease.

Sex-specific allelic transmission bias suggests sexual conflict at MC1R.

Sexual conflict arises when selection in one sex causes the displacement of the other sex from its phenotypic optimum, leading to an inevitable tension within the genome - called intralocus sexual conflict. Although the autosomal melanocortin-1-receptor gene (MC1R) can generate colour variation in sexually dichromatic species, most previous studies have not considered the possibility that MC1R may be subject to sexual conflict. In the barn owl (Tyto alba), the allele MC1RWHITE is associated with whitish plumage coloration, typical of males, and the allele MC1RRUFOUS is associated with dark rufous coloration, typical of females, although each sex can express any phenotype. Because each colour variant is adapted to specific environmental conditions, the allele MC1RWHITE may be more strongly selected in males and the allele MC1RRUFOUS in females. We therefore investigated whether MC1R genotypes are in excess or deficit in male and female fledglings compared with the expected Hardy-Weinberg proportions. Our results show an overall deficit of 7.5% in the proportion of heterozygotes in males and of 12.9% in females. In males, interannual variation in assortative pairing with respect to MC1R explained the year-specific deviations from Hardy-Weinberg proportions, whereas in females, the deficit was better explained by the interannual variation in the probability of inheriting the MC1RWHITE or MC1RRUFOUS allele. Additionally, we observed that sons inherit the MC1RRUFOUS allele from their fathers on average slightly less often than expected under the first Mendelian law. Transmission ratio distortion may be adaptive in this sexually dichromatic species if males and females are, respectively, selected to display white and rufous plumages.

Analysis of chromosomal aberrations and recombination by allelic bias in RNA-Seq.

Genomic instability has profound effects on cellular phenotypes. Studies have shown that pluripotent cells with abnormal karyotypes may grow faster, differentiate less and become more resistance to apoptosis. Previously, we showed that microarray gene expression profiles can be utilized for the analysis of chromosomal aberrations by comparing gene expression levels between normal and aneuploid samples. Here we adopted this method for RNA-Seq data and present eSNP-Karyotyping for the detection of chromosomal aberrations, based on measuring the ratio of expression between the two alleles. We demonstrate its ability to detect chromosomal gains and losses in pluripotent cells and their derivatives, as well as meiotic recombination patterns. This method is advantageous since it does not require matched diploid samples for comparison, is less sensitive to global expression changes caused by the aberration and utilizes already available gene expression profiles to determine chromosomal aberrations.

Establishing Chromatin Regulatory Landscape during Mouse Preimplantation Development

How the chromatin regulatory landscape in the inner cell mass cells is established from differentially packaged sperm and egg genomes during preimplantation development is unknown. Here, we develop a low-input DNase I sequencing (liDNase-seq) method that allows us to generate maps of DNase I-hypersensitive site (DHS) of mouse preimplantation embryos from 1-cell to morula stage. The DHS landscape is progressively established with a drastic increase at the 8-cell stage. Paternal chromatin accessibility is quickly reprogrammed after fertilization to the level similar to maternal chromatin, while imprinted genes exhibit allelic accessibility bias. We demonstrate that transcription factor Nfya contributes to zygotic genome activation and DHS formation at the 2-cell stage and that Oct4 contributes to the DHSs gained at the 8-cell stage. Our study reveals the dynamic chromatin regulatory landscape during early development and identifies key transcription factors important for DHS establishment in mammalian embryos.