Allelic Bias Research Articles

Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo

Accurate single cell mutational profiles can reveal genomic cell-to-cell heterogeneity. However, sequencing libraries suitable for genotyping require whole genome amplification, which introduces allelic bias and copy errors. The resulting data violates assumptions of variant callers developed for bulk sequencing. Thus, only dedicated models accounting for amplification bias and errors can provide accurate calls. We present ProSolo for calling single nucleotide variants from multiple displacement amplified (MDA) single cell DNA sequencing data. ProSolo probabilistically models a single cell jointly with a bulk sequencing sample and integrates all relevant MDA biases in a site-specific and scalable—because computationally efficient—manner. This achieves a higher accuracy in calling and genotyping single nucleotide variants in single cells in comparison to state-of-the-art tools and supports imputation of insufficiently covered genotypes, when downstream tools cannot handle missing data. Moreover, ProSolo implements the first approach to control the false discovery rate reliably and flexibly. ProSolo is implemented in an extendable framework, with code and usage at: https://github.com/prosolo/prosolo

Functional organization of the maternal and paternal human 4D Nucleome

SummaryEvery human somatic cell inherits a maternal and a paternal genome, which work together to give rise to cellular phenotypes. However, the allele-specific relationship between gene expression and genome structure through the cell cycle is largely unknown. By integrating haplotype-resolved genome-wide chromosome conformation capture, mature and nascent mRNA, and protein binding data from a B lymphoblastoid cell line, we investigate this relationship both globally and locally. We introduce the maternal and paternal 4D Nucleome, enabling detailed analysis of the mechanisms and dynamics of genome structure and gene function for diploid organisms. Our analyses find significant coordination between allelic expression biases and local genome conformation, and notably absent expression bias in universally essential cell cycle and glycolysis genes. We propose a model in which coordinated biallelic expression reflects prioritized preservation of essential gene sets.

Introns control stochastic allele expression bias

Monoallelic expression (MAE) or extreme allele bias can account for incomplete penetrance, missing heritability and non-Mendelian diseases. In cancer, MAE is associated with shorter patient survival times and higher tumor grade. Prior studies showed that stochastic MAE is caused by stochastic epigenetic silencing, in a gene and tissue-specific manner. Here, we used C. elegans to study stochastic MAE in vivo. We found allele bias/MAE to be widespread within C. elegans tissues, presenting as a continuum from fully biallelic to MAE. We discovered that the presence of introns within alleles robustly decreases MAE. We determined that introns control MAE at distinct loci, in distinct cell types, with distinct promoters, and within distinct coding sequences, using a 5’-intron position-dependent mechanism. Bioinformatic analysis showed human intronless genes are significantly enriched for MAE. Our experimental evidence demonstrates a role for introns in regulating MAE, possibly explaining why some mutations within introns result in disease.

Genome-Wide Analysis of Allele-Specific Expression Genes in Pediatric B-Cell Precursor Acute Lymphoblastic Leukemia

Introduction. Pediatric B-cell precursor acute lymphoblastic leukemia (BCP ALL) is the most common pediatric hematological malignancy and it remains an important cause of morbidity and mortality in children. In this study, we performed an allele-specific expression (ASE) analysis of pediatric BCP ALL with the aim to investigate the relationship between cis-regulatory mutations and gene expression patterns.Materials and methods. Twenty-two high hyperdiploid ALL, twenty ETV6/RUNX1-positive ALL, seven TCF3/PBX1-positive ALL and twenty-eight genetically unclassified BCP ALL (“B-other”) were subjected to whole genome sequencing, SNP array analysis and RNA sequencing. The binomial test was applied to estimate the allelic bias of heterozygous exonic single nucleotide variants (SNVs) in the RNA sequencing data against the genomic data. Allelic ratios >2 or <0.5, and P values <0.05 were used to identify allele-specific expression protein-coding genes.Results. We identified 12,693 expressed genes, of which 9,672 (76%) had heterozygous exonic SNVs (informative genes), in multiple BCP ALL samples (n>2) in 77 of the investigated samples. Genes with ASE were distributed evenly across the autosomal chromosomes in the different subtypes with a range of 30 - 165 ASE genes per case (median number, 86). We found that 630 (6.5%) genes displayed ASE in multiple BCP ALL samples (n>2), of which only eight autosomal genes had monoallelic expression in more than two investigated samples. This suggests that ASE and monoallelic expression are relatively rare in BCP ALL. Gene enrichment analyses showed that pathways involving negative regulation of natural killer cell-mediated cytotoxicity and cell proliferation were enriched, indicating that ASE events possibly were associated with the cell proliferation and leukemia progression in BCP ALL. Furthermore, the hematopoiesis pathway was also enriched in ASE genes that showed high allelic expression bias (allelic ratios >2.5), suggesting that ASE genes might be associated with leukemia development. Somatic genomic aberrations that could cause ASE were also investigated in this study. All informative cases with TCF3/PBX1 rearrangement (n=4) showed monoallelic expression of the PBX1 gene, likely associated with the PBX1 truncation caused by the fusion. Additionally, CHP1, located in 15q15.1, displayed ASE in one case with an inversion involving that chromosome band, indicating a potential cis-acting element in the inversion region that regulated the CHP1 gene expression. Notably, PAX5 displayed various patterns of ASE in BCP ALL. One of three cases with PAX5/ZCCHC7 gene rearrangements displayed PAX5 ASE while the other two did not, indicating a potential uncovered cis-regulatory element around the PAX5/ZCCHC7 breakpoints. Furthermore, two cases with no PAX5 gene rearrangement displayed monoallelic expression of the PAX5 gene, suggesting that there are additional epigenetic alterations were also involved in the regulation of PAX5 gene expression in BCP ALL.Conclusions. In this study, we have characterized genes displaying ASE in childhood BCP ALL. Our data provide new insight into pathogenesis of BCP ALL and may be used to identify novel targets for treatment. DisclosuresNo relevant conflicts of interest to declare.

Allele-specific expression analysis reveals conserved and unique features of preimplantation development in equine ICSI embryos†.

Embryonic genome activation and dosage compensation are major genetic events in early development. Combined analysis of single embryo RNA-seq data and parental genome sequencing was used to evaluate parental contributions to early development and investigate X-chromosome dynamics. In addition, we evaluated dimorphism in gene expression between male and female embryos. Evaluation of parent-specific gene expression revealed a minor increase in paternal expression at the 4-cell stage that increased at the 8-cell stage. We also detected eight genes with allelic expression bias that may have an important role in early development, notably NANOGNB. The main actor in X-chromosome inactivation, XIST, was significantly upregulated at the 8-cell, morula, and blastocyst stages in female embryos, with high expression at the latter. Sexual dimorphism in gene expression was identified at all stages, with strong representation of the X-chromosome in females from the 16-cell to the blastocyst stage. Female embryos showed biparental X-chromosome expression at all stages after the 4-cell stage, demonstrating the absence of imprinted X-inactivation at the embryo level. The analysis of gene dosage showed incomplete dosage compensation (0.5 < X:A < 1) in MII oocytes and embryos up to the 4-cell stage, an increase of the X:A ratio at the 16-cell and morula stages after genome activation, and a decrease of the X:A ratio at the blastocyst stage, which might be associated with the beginning of X-chromosome inactivation. This study represents the first critical analysis of parent- and sex-specific gene expression in early equine embryos produced in vitro.

Haploid Genome Analysis Reveals a Tandem Cluster of Four HSP20 Genes Involved in the High-Temperature Adaptation of Coriolopsis trogii.

ABSTRACTCoriolopsis trogii is a typical thermotolerant basidiomycete fungus, but its thermotolerance mechanisms are currently unknown. In this study, two monokaryons of C. trogii strain Ct001 were assembled: Ct001_29 had a genome assembly size of 38.85 Mb and encoded 13,113 genes, while Ct001_31 was 40.19 Mb in length and encoded 13,309 genes. Comparative intra- and interstrain genomic analysis revealed the rich genetic diversity of C. trogii, which included more than 315,194 single-nucleotide polymorphisms (SNPs), 30,387 insertion/deletions (indels), and 1,460 structural variations. Gene family analysis showed that the expanded families of C. trogii were functionally enriched in lignocellulose degradation activities. Furthermore, a total of 14 allelic pairs of heat shock protein 20 (HSP20) genes were identified in the C. trogii genome. The expression profile obtained from RNA sequencing (RNA-Seq) showed that four tandem-duplicated allelic pairs, HSP20.5 to HSP20.8, had more than 5-fold higher expression at 35°C than at 25°C. In particular, HSP20.5 and HSP20.8 were the most highly expressed HSP20 genes. Allelic expression bias was found for HSP20.5 and HSP20.8; the expression of Ct29HSP20.8 was at least 1.34-fold higher than that of Ct31HSP20.8, and that of Ct31HSP20.5 was at least 1.5-fold higher than that of Ct29HSP20.5. The unique structural and expression profiles of the HSP20 genes revealed by these haplotype-resolved genomes provide insight into the molecular mechanisms of high-temperature adaptation in C. trogii.IMPORTANCE Heat stress is one of the most frequently encountered environmental stresses for most mushroom-forming fungi. Currently available fungal genomes are mostly haploid because high heterozygosity hinders diploid genome assembly. Here, two haplotype genomes of C. trogii, a thermotolerant basidiomycete, were assembled separately. A conserved tandem cluster of four HSP20 genes showing allele-specific expression was found to be closely related to high-temperature adaptation in C. trogii. The obtained haploid genomes and their comparison offer a more thorough understanding of the genetic background of C. trogii. In addition, the responses of HSP20 genes at 35°C, which may contribute to the growth and survival of C. trogii at high temperatures, could inform the selection and breeding of elite strains in the future.

Zfp57 inactivation illustrates the role of ICR methylation in imprinted gene expression during neural differentiation of mouse ESCs

ZFP57 is required to maintain the germline-marked differential methylation at imprinting control regions (ICRs) in mouse embryonic stem cells (ESCs). Although DNA methylation has a key role in genomic imprinting, several imprinted genes are controlled by different mechanisms, and a comprehensive study of the relationship between DMR methylation and imprinted gene expression is lacking. To address the latter issue, we differentiated wild-type and Zfp57-/- hybrid mouse ESCs into neural precursor cells (NPCs) and evaluated allelic expression of imprinted genes. In mutant NPCs, we observed a reduction of allelic bias of all the 32 genes that were imprinted in wild-type cells, demonstrating that ZFP57-dependent methylation is required for maintaining or acquiring imprinted gene expression during differentiation. Analysis of expression levels showed that imprinted genes expressed from the non-methylated chromosome were generally up-regulated, and those expressed from the methylated chromosome were down-regulated in mutant cells. However, expression levels of several imprinted genes acquiring biallelic expression were not affected, suggesting the existence of compensatory mechanisms that control their RNA level. Since neural differentiation was partially impaired in Zfp57-mutant cells, this study also indicates that imprinted genes and/or non-imprinted ZFP57-target genes are required for proper neurogenesis in cultured ESCs.

Investigating the impact of reference assembly choice on genomic analyses in a cattle breed

BackgroundReference-guided read alignment and variant genotyping are prone to reference allele bias, particularly for samples that are greatly divergent from the reference genome. A Hereford-based assembly is the widely accepted bovine reference genome. Haplotype-resolved genomes that exceed the current bovine reference genome in quality and continuity have been assembled for different breeds of cattle. Using whole genome sequencing data of 161 Brown Swiss cattle, we compared the accuracy of read mapping and sequence variant genotyping as well as downstream genomic analyses between the bovine reference genome (ARS-UCD1.2) and a highly continuous Angus-based assembly (UOA_Angus_1).ResultsRead mapping accuracy did not differ notably between the ARS-UCD1.2 and UOA_Angus_1 assemblies. We discovered 22,744,517 and 22,559,675 high-quality variants from ARS-UCD1.2 and UOA_Angus_1, respectively. The concordance between sequence- and array-called genotypes was high and the number of variants deviating from Hardy-Weinberg proportions was low at segregating sites for both assemblies. More artefactual INDELs were genotyped from UOA_Angus_1 than ARS-UCD1.2 alignments. Using the composite likelihood ratio test, we detected 40 and 33 signatures of selection from ARS-UCD1.2 and UOA_Angus_1, respectively, but the overlap between both assemblies was low. Using the 161 sequenced Brown Swiss cattle as a reference panel, we imputed sequence variant genotypes into a mapping cohort of 30,499 cattle that had microarray-derived genotypes using a two-step imputation approach. The accuracy of imputation (Beagle R2) was very high (0.87) for both assemblies. Genome-wide association studies between imputed sequence variant genotypes and six dairy traits as well as stature produced almost identical results from both assemblies.ConclusionsThe ARS-UCD1.2 and UOA_Angus_1 assemblies are suitable for reference-guided genome analyses in Brown Swiss cattle. Although differences in read mapping and genotyping accuracy between both assemblies are negligible, the choice of the reference genome has a large impact on detecting signatures of selection that already reached fixation using the composite likelihood ratio test. We developed a workflow that can be adapted and reused to compare the impact of reference genomes on genome analyses in various breeds, populations and species.

Biased allelic expression in tissues of F1 hybrids between tropical and temperate lotus (Nelumbo nuicfera).

The genome-wide allele-specific expression in F1 hybrids from the cross of tropical and temperate lotus unveils how cis-regulatory divergences affect genes in key pathways related to ecotypic divergence. Genetic variation, particularly cis-regulatory variation, plays a crucial role in phenotypic variation and adaptive evolution in plants. Temperate and tropical lotus, the two ecotypes of Nelumbo nucifera, show distinction in the degree of rhizome enlargement, which is associated with winter dormancy. To understand the roles of genome-wide cis-regulatory divergences on adaptive evolution of temperate and tropical lotus (Nelumbo nucifera), here we performed allele-specific expression (ASE) analyses on the tissues including flowers, leaves and rhizome from F1 hybrids of tropical and temperate lotus. For all investigated tissues in F1s, about 36% of genes showed ASE and about 3% of genes showed strong consistent ASE. Most of ASEs were biased towards the tropical parent in all surveyed samples, indicating that the tropical genome might be dominant over the temperate genome in gene expression of tissues from their F1 hybrids. We found that promoter sequences with similar allelic expression are more conserved than genes with significant or conditional ASE, suggesting the cis-regulatory sequence divergence underlie the allelic expression bias. We further uncovered biased genes being related to phenotypic differentiation between two lotus ecotypes, especially metabolic and phytohormone-related pathways in the rhizome. Overall, our study provides a global landscape of cis-regulatory variations between two lotus ecotypes and highlights their roles in rhizome growth variation for the climatic adaptation.

MIPP-Seq: ultra-sensitive rapid detection and validation of low-frequency mosaic mutations

BackgroundMosaic mutations contribute to numerous human disorders. As such, the identification and precise quantification of mosaic mutations is essential for a wide range of research applications, clinical diagnoses, and early detection of cancers. Currently, the low-throughput nature of single allele assays (e.g., allele-specific ddPCR) commonly used for genotyping known mutations at very low alternate allelic fractions (AAFs) have limited the integration of low-level mosaic analyses into clinical and research applications. The growing importance of mosaic mutations requires a more rapid, low-cost solution for mutation detection and validation.MethodsTo overcome these limitations, we developed Multiple Independent Primer PCR Sequencing (MIPP-Seq) which combines the power of ultra-deep sequencing and truly independent assays. The accuracy of MIPP-seq to quantifiable detect and measure extremely low allelic fractions was assessed using a combination of SNVs, insertions, and deletions at known allelic fractions in blood and brain derived DNA samples.ResultsThe Independent amplicon analyses of MIPP-Seq markedly reduce the impact of allelic dropout, amplification bias, PCR-induced, and sequencing artifacts. Using low DNA inputs of either 25 ng or 50 ng of DNA, MIPP-Seq provides sensitive and quantitative assessments of AAFs as low as 0.025% for SNVs, insertion, and deletions.ConclusionsMIPP-Seq provides an ultra-sensitive, low-cost approach for detecting and validating known and novel mutations in a highly scalable system with broad utility spanning both research and clinical diagnostic testing applications. The scalability of MIPP-Seq allows for multiplexing mutations and samples, which dramatically reduce costs of variant validation when compared to methods like ddPCR. By leveraging the power of individual analyses of multiple unique and independent reactions, MIPP-Seq can validate and precisely quantitate extremely low AAFs across multiple tissues and mutational categories including both indels and SNVs. Furthermore, using Illumina sequencing technology, MIPP-seq provides a robust method for accurate detection of novel mutations at an extremely low AAF.

Fixation of allelic gene expression landscapes and expression bias pattern shape the transcriptome of the clonal Amazon molly

The Amazon molly is a unique clonal fish species that originated from an interspecies hybrid between Poecilia species P. mexicana and P. latipinna. It reproduces by gynogenesis, which eliminates paternal genomic contribution to offspring. An earlier study showed that Amazon molly shows biallelic expression for a large portion of the genome, leading to two main questions: (1) Are the allelic expression patterns from the initial hybridization event stabilized or changed during establishment of the asexual species and its further evolution? (2) Is allelic expression biased toward one parental allele a stochastic or adaptive process? To answer these questions, the allelic expression of P. formosa siblings was assessed to investigate intra- and inter-cohort allelic expression variability. For comparison, interspecies hybrids between P. mexicana and P. latipinna were produced in the laboratory to represent the P. formosa ancestor. We have identified inter-cohort and intra-cohort variation in parental allelic expression. The existence of inter-cohort divergence suggests functional P. formosa allelic expression patterns do not simply reflect the atavistic situation of the first interspecies hybrid but potentially result from long-term selection of transcriptional fitness. In addition, clonal fish show a transcriptional trend representing minimal intra-clonal variability in allelic expression patterns compared to the corresponding hybrids. The intra-clonal similarity in gene expression translates to sophisticated genetic functional regulation at the individuum level. These findings suggest the parental alleles inherited by P. formosa form tightly regulated genetic networks that lead to a stable transcriptomic landscape within clonal individuals.

Allele-specific alternative splicing and its functional genetic variants in human tissues.

Alternative splicing is an RNA processing mechanism that affects most genes in human, contributing to disease mechanisms and phenotypic diversity. The regulation of splicing involves an intricate network of cis-regulatory elements and trans-acting factors. Due to their high sequence specificity, cis-regulation of splicing can be altered by genetic variants, significantly affecting splicing outcomes. Recently, multiple methods have been applied to understanding the regulatory effects of genetic variants on splicing. However, it is still challenging to go beyond apparent association to pinpoint functional variants. To fill in this gap, we utilized large-scale data sets of the Genotype-Tissue Expression (GTEx) project to study genetically modulated alternative splicing (GMAS) via identification of allele-specific splicing events. We demonstrate that GMAS events are shared across tissues and individuals more often than expected by chance, consistent with their genetically driven nature. Moreover, although the allelic bias of GMAS exons varies across samples, the degree of variation is similar across tissues versus individuals. Thus, genetic background drives the GMAS pattern to a similar degree as tissue-specific splicing mechanisms. Leveraging the genetically driven nature of GMAS, we developed a new method to predict functional splicing-altering variants, built upon a genotype-phenotype concordance model across samples. Complemented by experimental validations, this method predicted >1000 functional variants, many of which may alter RNA-protein interactions. Lastly, 72% of GMAS-associated SNPs were in linkage disequilibrium with GWAS-reported SNPs, and such association was enriched in tissues of relevance for specific traits/diseases. Our study enables a comprehensive view of genetically driven splicing variations in human tissues.

Overcoming Expressional Drop-outs in Lineage Reconstruction from Single-Cell RNA-Sequencing Data

Single-cell lineage tracing provides crucial insights into the fates of individual cells. Single-cell RNA sequencing (scRNA-seq) is commonly applied in modern biomedical research, but genetics-based lineage tracing for scRNA-seq data is still unexplored. Variant calling from scRNA-seq data uniquely suffers from "expressional drop-outs," including low expression and allelic bias in gene expression, which presents significant obstacles for lineage reconstruction. We introduce SClineager, which infers accurate evolutionary lineages from scRNA-seq data by borrowing information from related cells to overcome expressional drop-outs. We systematically validate SClineager and show that genetics-based lineage tracing is applicable for single-cell-sequencing studies of both tumor and non-tumor tissues using SClineager. Overall, our work provides a powerful tool that can be applied to scRNA-seq data to decipher the lineage histories of cells and that could address a missing opportunity to reveal valuable information from the large amounts of existing scRNA-seq data.

Genomic architecture and evolutionary antagonism drive allelic expression bias in the social supergene of red fire ants.

Supergene regions maintain alleles of multiple genes in tight linkage through suppressed recombination. Despite their importance in determining complex phenotypes, our empirical understanding of early supergene evolution is limited. Here we focus on the young 'social' supergene of fire ants, a powerful system for disentangling the effects of evolutionary antagonism and suppressed recombination. We hypothesize that gene degeneration and social antagonism shaped the evolution of the fire ant supergene, resulting in distinct patterns of gene expression. We test these ideas by identifying allelic differences between supergene variants, characterizing allelic expression across populations, castes and body parts, and contrasting allelic expression biases with differences in expression between social forms. We find strong signatures of gene degeneration and gene-specific dosage compensation. On this background, a small portion of the genes has the signature of adaptive responses to evolutionary antagonism between social forms.

Bovine breed-specific augmented reference graphs facilitate accurate sequence read mapping and unbiased variant discovery

BackgroundThe current bovine genomic reference sequence was assembled from a Hereford cow. The resulting linear assembly lacks diversity because it does not contain allelic variation, a drawback of linear references that causes reference allele bias. High nucleotide diversity and the separation of individuals by hundreds of breeds make cattle ideally suited to investigate the optimal composition of variation-aware references.ResultsWe augment the bovine linear reference sequence (ARS-UCD1.2) with variants filtered for allele frequency in dairy (Brown Swiss, Holstein) and dual-purpose (Fleckvieh, Original Braunvieh) cattle breeds to construct either breed-specific or pan-genome reference graphs using the vg toolkit. We find that read mapping is more accurate to variation-aware than linear references if pre-selected variants are used to construct the genome graphs. Graphs that contain random variants do not improve read mapping over the linear reference sequence. Breed-specific augmented and pan-genome graphs enable almost similar mapping accuracy improvements over the linear reference. We construct a whole-genome graph that contains the Hereford-based reference sequence and 14 million alleles that have alternate allele frequency greater than 0.03 in the Brown Swiss cattle breed. Our novel variation-aware reference facilitates accurate read mapping and unbiased sequence variant genotyping for SNPs and Indels.ConclusionsWe develop the first variation-aware reference graph for an agricultural animal (https://doi.org/10.5281/zenodo.3759712). Our novel reference structure improves sequence read mapping and variant genotyping over the linear reference. Our work is a first step towards the transition from linear to variation-aware reference structures in species with high genetic diversity and many sub-populations.

Bumblebee Workers Show Differences in Allele-Specific DNA Methylation and Allele-Specific Expression.

Allele-specific expression is when one allele of a gene shows higher levels of expression compared with the other allele, in a diploid organism. Recent work has identified allele-specific expression in a number of Hymenopteran species. However, the molecular mechanism which drives this allelic expression bias remains unknown. In mammals, DNA methylation is often associated with genes which show allele-specific expression. DNA methylation systems have been described in species of Hymenoptera, providing a candidate mechanism. Using previously generated RNA-Seq and whole-genome bisulfite sequencing from reproductive and sterile bumblebee (Bombus terrestris) workers, we have identified genome-wide allele-specific expression and allele-specific DNA methylation. The majority of genes displaying allele-specific expression are common between reproductive and sterile workers and the proportion of allele-specific expression bias generally varies between genetically distinct colonies. We have also identified genome-wide allele-specific DNA methylation patterns in both reproductive and sterile workers, with reproductive workers showing significantly more genes with allele-specific methylation. Finally, there is no significant overlap between genes showing allele-specific expression and allele-specific methylation. These results indicate that cis-acting DNA methylation does not directly drive genome-wide allele-specific expression in this species.

Loss of Imprinting in Human Placentas Is Widespread, Coordinated, and Predicts Birth Phenotypes.

Genomic imprinting leads to mono-allelic expression of genes based on parent of origin. Therian mammals and angiosperms evolved this mechanism in nutritive tissues, the placenta, and endosperm, where maternal and paternal genomes are in conflict with respect to resource allocation. We used RNA-seq to analyze allelic bias in the expression of 91 known imprinted genes in term human placentas from a prospective cohort study in Mali. A large fraction of the imprinted exons (39%) deviated from mono-allelic expression. Loss of imprinting (LOI) occurred in genes with either maternal or paternal expression bias, albeit more frequently in the former. We characterized LOI using binomial generalized linear mixed models. Variation in LOI was predominantly at the gene as opposed to the exon level, consistent with a single promoter driving the expression of most exons in a gene. Some genes were less prone to LOI than others, particularly lncRNA genes were rarely expressed from the repressed allele. Further, some individuals had more LOI than others and, within a person, the expression bias of maternally and paternally imprinted genes was correlated. We hypothesize that trans-acting maternal effect genes mediate correlated LOI and provide the mother with an additional lever to control fetal growth by extending her influence to LOI of the paternally imprinted genes. Limited evidence exists to support associations between LOI and offspring phenotypes. We show that birth length and placental weight were associated with allelic bias, making this the first comprehensive report of an association between LOI and a birth phenotype.

ISoLDE: a data-driven statistical method for the inference of allelic imbalance in datasets with reciprocal crosses.

Allelic imbalance (AI), i.e. the unequal expression of the alleles of the same gene in a single cell, affects a subset of genes in diploid organisms. One prominent example of AI is parental genomic imprinting, which results in parent-of-origin-dependent, mono-allelic expression of a limited number of genes in metatherian and eutherian mammals and in angiosperms. Currently available methods for identifying AI rely on data modeling and come with the associated limitations. We have designed ISoLDE (Integrative Statistics of alleLe Dependent Expression), a novel nonparametric statistical method that takes into account both AI and the characteristics of RNA-seq data to infer allelic expression bias when at least two biological replicates are available for reciprocal crosses. ISoLDE learns the distribution of a specific test statistic from the data and calls genes 'allelically imbalanced', 'bi-allelically expressed' or 'undetermined'. Depending on the number of replicates, predefined thresholds or permutations are used to make calls. We benchmarked ISoLDE against published methods, and showed that ISoLDE compared favorably with respect to sensitivity, specificity and robustness to the number of replicates. Using ISoLDE on different RNA-seq datasets generated from hybrid mouse tissues, we did not discover novel imprinted genes (IGs), confirming the most conservative estimations of IG number. ISoLDE has been implemented as a Bioconductor package available at http://bioconductor.org/packages/ISoLDE/. Supplementary data are available at Bioinformatics online.

Molecular Characterisation of a Supergene Conditioning Super-High Vitamin C in Kiwifruit Hybrids.

During analysis of kiwifruit derived from hybrids between the high vitamin C (ascorbic acid; AsA) species Actinidia eriantha and A. chinensis, we observed bimodal segregation of fruit AsA concentration suggesting major gene segregation. To test this hypothesis, we performed whole-genome sequencing on pools of hybrid genotypes with either high or low AsA fruit. Pool-GWAS (genome-wide association study) revealed a single Quantitative Trait Locus (QTL) spanning more than 5 Mbp on chromosome 26, which we denote as qAsA26.1. A co-dominant PCR marker was used to validate this association in four diploid (A. chinensis × A. eriantha) × A. chinensis backcross families, showing that the A. eriantha allele at this locus increases fruit AsA levels by 250 mg/100 g fresh weight. Inspection of genome composition and recombination in other A. chinensis genetic maps confirmed that the qAsA26.1 region bears hallmarks of suppressed recombination. The molecular fingerprint of this locus was examined in leaves of backcross validation families by RNA sequencing (RNASEQ). This confirmed strong allelic expression bias across this region as well as differential expression of transcripts on other chromosomes. This evidence suggests that the region harbouring qAsA26.1 constitutes a supergene, which may condition multiple pleiotropic effects on metabolism.

Accurate sequence variant genotyping in cattle using variation-aware genome graphs

BackgroundGenotyping of sequence variants typically involves, as a first step, the alignment of sequencing reads to a linear reference genome. Because a linear reference genome represents only a small fraction of all the DNA sequence variation within a species, reference allele bias may occur at highly polymorphic or divergent regions of the genome. Graph-based methods facilitate the comparison of sequencing reads to a variation-aware genome graph, which incorporates a collection of non-redundant DNA sequences that segregate within a species. We compared the accuracy and sensitivity of graph-based sequence variant genotyping using the Graphtyper software to two widely-used methods, i.e., GATK and SAMtools, which rely on linear reference genomes using whole-genome sequencing data from 49 Original Braunvieh cattle.ResultsWe discovered 21,140,196, 20,262,913, and 20,668,459 polymorphic sites using GATK, Graphtyper, and SAMtools, respectively. Comparisons between sequence variant genotypes and microarray-derived genotypes showed that Graphtyper outperformed both GATK and SAMtools in terms of genotype concordance, non-reference sensitivity, and non-reference discrepancy. The sequence variant genotypes that were obtained using Graphtyper had the smallest number of Mendelian inconsistencies between sequence-derived single nucleotide polymorphisms and indels in nine sire-son pairs. Genotype phasing and imputation using the Beagle software improved the quality of the sequence variant genotypes for all the tools evaluated, particularly for animals that were sequenced at low coverage. Following imputation, the concordance between sequence- and microarray-derived genotypes was almost identical for the three methods evaluated, i.e., 99.32, 99.46, and 99.24% for GATK, Graphtyper, and SAMtools, respectively. Variant filtration based on commonly used criteria improved genotype concordance slightly but it also decreased sensitivity. Graphtyper required considerably more computing resources than SAMtools but less than GATK.ConclusionsSequence variant genotyping using Graphtyper is accurate, sensitive and computationally feasible in cattle. Graph-based methods enable sequence variant genotyping from variation-aware reference genomes that may incorporate cohort-specific sequence variants, which is not possible with the current implementation of state-of-the-art methods that rely on linear reference genomes.