Haplotype Phasing Research Articles

Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools

We produced an extensive collection of deep re-sequencing datasets for the Venter/HuRef genome using the Illumina massively-parallel DNA sequencing platform. The original Venter genome sequence is a very-high quality phased assembly based on Sanger sequencing. Therefore, researchers developing novel computational tools for the analysis of human genome sequence variation for the dominant Illumina sequencing technology can test and hone their algorithms by making variant calls from these Venter/HuRef datasets and then immediately confirm the detected variants in the Sanger assembly, freeing them of the need for further experimental validation. This process also applies to implementing and benchmarking existing genome analysis pipelines. We prepared and sequenced 200 bp and 350 bp short-insert whole-genome sequencing libraries (sequenced to 100x and 40x genomic coverages respectively) as well as 2 kb, 5 kb, and 12 kb mate-pair libraries (49x, 122x, and 145x physical coverages respectively). Lastly, we produced a linked-read library (128x physical coverage) from which we also performed haplotype phasing.

Accurate Prediction of RH Genotypes Using Whole Genome Sequencing Data

IntroductionRBC alloimmunization is common in patients with sickle cell disease (SCD). Despite serological matching RBCs for major Rh antigens, Rh alloimmunization remains problematic. The Rh blood group is encoded by two genes RHD and RHCE, which exhibit extensive nucleotide polymorphism and chromosome structural changes, resulting in the formation of Rh variant antigens. Rh variants can result in loss of protein epitopes or expression of neo-epitopes, and are common in SCD patients. Hence SCD patients harboring Rh variants can be predisposed to Rh alloimmunization. Given the limitation of traditional serologic antigen typing for detection of Rh variants, molecular genotyping has become required. A DNA microarray-based platform, BioArray RHCE and RHD BeadChip (Immuncor) is available for RH genotyping. However, it detects the most common, but not all, variants. Whole exome sequence data have been used for prediction of Rh variants (Chou, et. al, Blood Adv., 2017), offer some advantages, including detection of rare variants, structural rearrangements and copy number variation. However, whole genome sequence (WGS) analysis of RHD/RHCE is challenging due to difficulties in mapping next generation sequencing (NGS) reads to this duplicated gene family. We developed a computational algorithm to identify RH variants using WGS data.MethodsThe pipeline included three major components, RH allele database construction, RH variant calling, and classification of Rh blood group according the identified variants. The RH allele database was built based on NCBI Blood Group Antigen Gene Mutation (BGMUT) and International Society of Blood Transfusion (ISBT) database. Since the alleles in the BGMUT and ISBT databases were specified according to conventional RH genes (RHD, L08429; RHCE, DQ322275) that are different from those on reference human genome, we first called the variations based on the reference human genome. The positions of the identified variations were subsequently corrected to match with the BGMUT and ISBT annotation system. Next, the NGS reads with low base quality and/or mapping quality were discarded during the variation calling step. Synonymous and non-synonymous amino acid changes were characterized for each polymorphism. Haplotypes were constructed for the segments with NGS read support. Gene sequencing coverage was calculated to determine gene deletions or amplifications. Lastly, we implemented an algorithm to predict RH genotypes based on a selection of candidate alleles by read-mapping profile which considers both sequence variations and sequence consistency followed by a likelihood-based ranking of all pairwise combinations of the selected alleles. The allele combination with the highest likelihood is considered the most likely pair of alleles at a given locus. Patient specimens used in this study were from participants of the Sickle Cell Clinical Research and Intervention Program (SCCRIP, Hankins et al. Pediatr Blood Cancer. 2018).ResultsWe validated our method in a cohort of 58 SCD patients whose RH genotypes had been determined by BioArray RhCE and RhD BeadChip and supplementary molecular tests that identify the most common variants among individuals of African descent. In this validation cohort including a total of 11 RHD and 13 RHCE alleles, our approach achieved a concordance rate of 85.85% (91 of 106 alleles) for RHD and 83.02% (88 of 106 alleles) for RHCE genotyping. WGS was highly sensitive in distinguishing homozygosity from heterozygosity of genes. By comparing the numbers of NGS reads on RH regions and whole genome average coverage, heterozygous deletion can be determined. Since WGS provides comprehensive genotyping, our analysis identified single nucleotide polymorphisms that were not identified by the BeadChip and supplemental molecular testing. The final source of discordance was likely due to the short read length of NGS such that haplotype phases cannot be correctly predicted if the variations are separated by thousands of base pairs, for which long read DNA sequencing or RNA/cDNA sequencing are required. Evaluation of the identified discrepancies is ongoing.ConclusionsWe developed and validated a diagnostic method for RH genotyping that leveraged the accuracy and flexibility of RH genotyping based on WGS data. With further optimization of our method, this may be useful for RBC genotype matching sickle cell patients to blood donors in the future. DisclosuresHankins:Novartis: Research Funding; Global Blood Therapeutics: Research Funding; NCQA: Consultancy; bluebird bio: Consultancy.

Structural Variation within the Beta-Globin Gene Cluster Among HbS Haplotype Groups

BACKGROUNDThe severity of sickle cell anemia (SCA) has been associated with five specific haplotypes in the beta globin cluster, identifiable by distinct patterns of restriction fragment length polymorphism (RFLP). These RFLP-defined haplotypes, named according to the region where they were first discovered - Central Africa region (CAR), Benin, Senegal, Arabic-Indian, and Cameroon - suggested that the sickle cell mutation arose recently at least four independent times in Africa, each time on a different genetic background, and again in India - the Multi-centric Sickle Cell Model. The beta-globin locus, however, is prone to extensive structural rearrangements, and alongside observations of ancestral sequence haplotypes extending several hundreds of kilobases beyond the beta globin cluster, it has been suggested that there is more cis-variation in the beta-globin gene cluster than is evident from RFLP analyses, and current definitions of RFLP haplotypes may not accurately reflect the ancestral origin of the sickle mutation. This undescribed cis-variation is important to understanding inter-individual phenotype variation associated with the different haplotypes.To better define this variation, we have undertaken extended, long-range molecular haplotyping of the beta-globin cluster on differing RFLP haplotype backgrounds using real time single molecule sequencing (SMS). The SMS approach generates long, unbroken reads with uniform coverage, thereby allowing for detailed molecular phasing of RFLP haplotypes and identification of local structural variation that would otherwise be hidden within the complex repetitive elements of the beta-globin cluster. In so doing, we plan to evaluate the molecular evidence for a single origin for the sickle cell allele and identify potential cis-acting, disease-modifying, candidate variants within the beta globin cluster.METHODSDNA from 200 SCA patients from three countries in sub-Saharan Africa - Nigeria, Cameroon, and Kenya - were collected after informed consent. RFLP analysis revealed the majority of the patients to be homozygous for the Benin and CAR haplotypes, with a smaller sampling of Cameroon, Senegal, and Atypical haplotypes. From this group we selected 40 samples - representing the four main classical RFLP haplotypes in sub-Saharan Africa - were selected for SMS. PCR was used to tile barcoded amplicons across the cluster. SMS was performed on a Sequel machine (Pacific Biosciences). The resulting FASTQ sequences were de-multiplexed, read quality control filters were applied, and mapped to human reference genome Hg38, prior to annotation and calling of single nucleotide variants (SNV) and structural variants (SV).RESULTSAnalyses have so far identified 227 insertions, 18 deletions, 7 duplications, 76 inversions and 13 translocations from long-read analyses of the initial 40 samples; the vast majority of these variants are not described in public variant databases. Atypical haplotypes demonstrated more translocation and duplication events than other haplotypes. Insertions ~48 kb upstream of the beta-globin locus control region and 1.3 kb upstream of gamma globin gene 2 (HBG2) were observed on 50% of Senegal and 45% of CAR haplotypes. Also, recurrent insertions ranging between 32bp and 1,184bp in length, 2.3 kb downstream of the beta globin gene (HBB), were seen on 50% of the Benin and 54% of the CAR haplotypes, but only once on Senegal haplotypes.CONCLUSIONSOur findings suggest there are more cis-SVs within the beta-globin gene cluster than previously described. Work to validate these SVs using orthogonal methods and complete similar analyses of SNVs is ongoing. Variation outside of the gene cluster will also be integrated with RFLP and within-cluster molecular haplotypes to investigate the ancestral origin of the mutation, and validated cis-acting variants will be used to identify markers associated with proxies of SCA disease modification. DisclosuresNo relevant conflicts of interest to declare.

McSwan: A joint site frequency spectrum method to detect and date selective sweeps across multiple population genomes.

Inferring the mode and tempo of natural selection helps further our understanding of adaptation to past environmental changes. Here, we introduce McSwan, a method to detect and date past and recent natural selection events in the case of a hard sweep. The method is based on the comparison of site frequency spectra obtained under various demographic models that include selection. McSwan demonstrated high power (high sensitivity and specificity) in capturing hard selective sweep events without requiring haplotype phasing. It performed slightly better than SweeD when the recent effective population size was low and the genomic region was small. We then applied our method to a European (CEU) and an African (LWK) human re-sequencing data set. Most hard sweeps were detected in the CEU population (96%). Moreover, hard sweeps in the African population were estimated to have occurred further back in time (mode: 43,625years BP) compared to those of Europeans (mode: 24,850years BP). Most of the estimated ages of hard sweeps in Europeans were associated with the Last Glacial Maximum and were enriched in immunity-associated genes.

Insights into imprinting from parent-of-origin phased methylomes and transcriptomes.

Imprinting is the preferential expression of one parental allele over the other. It is controlled primarily through differential methylation of cytosine at CpG dinucleotides. Here we combine 285 methylomes and 11,617 transcriptomes from peripheral blood samples with parent-of-origin phased haplotypes, to produce a new map of imprinted methylation and gene expression patterns across the human genome. We demonstrate how imprinted methylation is a continuous rather than a binary characteristic. We describe at high resolution the parent-of-origin methylation pattern at the 15q11.2 Prader-Willi/Angelman syndrome locus, with nearly confluent stochastic paternal methylation punctuated by 'spikes' of maternal methylation. We find examples of polymorphic imprinted methylation unrelated (at VTRNA2-1 and PARD6G) or related (at CHRNE) to nearby SNP genotypes. We observe RNA isoform-specific imprinted expression patterns suggestive of a methylation-sensitive transcriptional elongation block. Finally, we gain new insights into parent-of-origin-specific effects on phenotypes at the DLK1/MEG3 and GNAS loci.

Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity.

Positive natural selection can lead to a decrease in genomic diversity at the selected site and at linked sites, producing a characteristic signature of elevated expected haplotype homozygosity. These selective sweeps can be hard or soft. In the case of a hard selective sweep, a single adaptive haplotype rises to high population frequency, whereas multiple adaptive haplotypes sweep through the population simultaneously in a soft sweep, producing distinct patterns of genetic variation in the vicinity of the selected site. Measures of expected haplotype homozygosity have previously been used to detect sweeps in multiple study systems. However, these methods are formulated for phased haplotype data, typically unavailable for nonmodel organisms, and some may have reduced power to detect soft sweeps due to their increased genetic diversity relative to hard sweeps. To address these limitations, we applied the H12 and H2/H1 statistics proposed in 2015 by Garud et al., which have power to detect both hard and soft sweeps, to unphased multilocus genotypes, denoting them as G12 and G2/G1. G12 (and the more direct expected homozygosity analog to H12, denoted G123) has comparable power to H12 for detecting both hard and soft sweeps. G2/G1 can be used to classify hard and soft sweeps analogously to H2/H1, conditional on a genomic region having high G12 or G123 values. The reason for this power is that, under random mating, the most frequent haplotypes will yield the most frequent multilocus genotypes. Simulations based on parameters compatible with our recent understanding of human demographic history suggest that expected homozygosity methods are best suited for detecting recent sweeps, and increase in power under recent population expansions. Finally, we find candidates for selective sweeps within the 1000 Genomes CEU, YRI, GIH, and CHB populations, which corroborate and complement existing studies.

Linked read technology for assembling large complex and polyploid genomes

BackgroundShort read DNA sequencing technologies have revolutionized genome assembly by providing high accuracy and throughput data at low cost. But it remains challenging to assemble short read data, particularly for large, complex and polyploid genomes. The linked read strategy has the potential to enhance the value of short reads for genome assembly because all reads originating from a single long molecule of DNA share a common barcode. However, the majority of studies to date that have employed linked reads were focused on human haplotype phasing and genome assembly.ResultsHere we describe a de novo maize B73 genome assembly generated via linked read technology which contains ~ 172,000 scaffolds with an N50 of 89 kb that cover 50% of the genome. Based on comparisons to the B73 reference genome, 91% of linked read contigs are accurately assembled. Because it was possible to identify errors with > 76% accuracy using machine learning, it may be possible to identify and potentially correct systematic errors. Complex polyploids represent one of the last grand challenges in genome assembly. Linked read technology was able to successfully resolve the two subgenomes of the recent allopolyploid, proso millet (Panicum miliaceum). Our assembly covers ~ 83% of the 1 Gb genome and consists of 30,819 scaffolds with an N50 of 912 kb.ConclusionsOur analysis provides a framework for future de novo genome assemblies using linked reads, and we suggest computational strategies that if implemented have the potential to further improve linked read assemblies, particularly for repetitive genomes.

OR11 Characteristics of transplant candidates with cPRA ⩾ 99.95% likely to be allocated organs from deceased donors

Aim Since the new KAS, candidates with cPRA = 100% were prioritized for deceased donor (DD) kidneys, their transplant rates increased from 2.7% to as high as 19.1%. A recent simulation (CJSAN 11:505-511, 2016), predicted that not all cPRA=100% are equally advantaged. While ∼ 75% cPRA =100% candidates were compatible with an average of 17 donors (total donors = 6141), ∼ 25% were incompatible with every donor and related to cPRA values of 99.45–>99.99% being ”rounded up” to 100%. Indeed, 91% of candidates without a compatible donor had cPRA values >99.9%. Subsequent data with actual transplants (AJT 16:1834-1847, 2016) supported those predictions. In our program, 61 cPRA = 100% candidates were transplanted from 12/04/14-01/12/18. Surprisingly, 15 recipients had cPRA values ⩾99.95%. In this study, we identified their characteristics. Methods HLA profiles and demographic information from 15 cPRA ⩾99.95% recipients were compared to 30 non-transplanted case controls with cPRA ⩾99.95%. The HLA typing data of each subject was entered into Haplostats (haplostat.org) and the top ranked phased haplotypes for each were recorded. Results Among cPRA⩾99.95% recipients, 11/15 (73%) had one or both of their HLA haplotypes ranked among the top 125 CAU haplotypes. CAU haplotypes were the focus as CAU represent ∼ 67% of kidney donors. Notably, 7/15 recipients had one or both of their HLA haplotypes among the top four ranked CAU haplotypes and 6/15 received transplants from homozygous donors. Among recipients, eight were AA (53%), six were CAU and one was HIS. In contrast, among 30 case controls, 4 (13.3%) had one haplotype ranked in the top 125 and 17 had one haplotype ranked in the top 8000. For 9 candidates, neither HLA haplotype was ranked among the top 10,000 CAU haplotypes. Importantly, 25/30 (83.3%) controls were African American. Conclusions Kidney transplant candidates with cPRA⩾99.95% were more likely to be transplanted when at least one of their HLA haplotypes was frequent (rank ⩽ 125). This novel observation offers an opportunity to medically optimize a subset of highly sensitized candidates before deceased donor transplantation. It also suggests amendments may be necessary to minimize racial disparity in the KAS. Additionally, alternative approaches should be considered for candidates not likely to receive a DD offer. H.M. Gebel: 2. Consultant; Company/Organization; Astellas, Thermofisher.

Evaluation of the precision ID mtDNA whole genome panel on two massively parallel sequencing systems

Sequencing whole mitochondrial genomes by capillary electrophoresis is a costly and time/labor-intensive endeavor. Many of the previous Sanger sequencing-based approaches generated amplicons that were several kilobases in length; lengths that are likely not amenable for most forensic applications. However, with the advent of massively parallel sequencing (MPS) short-amplicon multiplexes covering the entire mitochondrial genome can be sequenced relatively easily and rapidly. Recently, the Precision ID mtDNA Whole Genome Panel (Thermo Fisher Scientific by Applied Biosystems™) has been introduced. This panel is composed of 162 amplicons (in two multiplexes) that are considerably smaller in length (∼163bp) and thus are more amenable to analyzing challenged samples. This panel was evaluated on both the Ion S5™ System (Thermo Fisher Scientific) and the MiSeq™ FGx Desktop Sequencer (Illumina). A script was developed to extract phased haplotypes associated with these amplicons. Levels of read-depth were compared across sequencing pools and between sequencing technologies and haplotype concordances were assessed. Given modest thresholds on read depth, the haplotypes identified by either technology were consistent. Nuclear mitochondrial sequences (Numts) were also inferred, and the effect of different mapping strategies commonly used to filter out Numts were contrasted. Some Numts are co-amplified with this amplification kit, and while the choice of reference sequence can mitigate some of these effects, some data from the mitochondrial genome were lost in the process in this study. This study demonstrates that the Ion and MiSeq platforms provide consistent haplotype estimation of the whole mitochondrial genome, thus providing further support for the reliability and validity of the Precision ID mtDNA Whole Genome Panel.

Abstract 2253: Identifying pathogenic germline variants in 1,172 cancer patients utilizing a novel variant phasing tool and strict public database curation

Abstract The identification of pathogenic or likely pathogenic (P/LP) germline variants in cancer patients is vital in assessing potential genetic causes of cancer risk, as well as incidental rare disease risk. However, sequencing limitations, lack of pedigree data, and unreliable phenotypic data can hinder the discovery of these putative causal germline variants. In order to improve the identification of such variants, we have developed a germline analysis pipeline that phases variants and identifies rare P/LP variants utilizing data from the GnomAD and ClinVar databases. In order to ensure our pipeline is annotating variants with accurate phenotypic data, we rate the quality of submitters to ClinVar based on their submission history. This history includes review status, agreement between population frequencies and stated clinical significance, and the quality of supporting evidence provided. The variant-phenotype relationship data extracted from ClinVar is valuable in directing us towards cancer-contributing variants, as well as incidental disease risk. However, there are many discrepancies between various institutions' assertion criteria submitted to ClinVar. Many variant entries in ClinVar are submitted as P/LP, yet a large number of these submissions lack evidence or criteria supporting the variant's clinical significance. Our pipeline identifies low-quality submissions, allowing for the inclusion of only high-quality P/LP variant annotations. In addition to recognizing known P/LP variants from the ClinVar archive, our pipeline provides additional identification of potentially pathogenic novel germline variants via haplotype phasing. Haplotype phasing of germline variants is vital when determining the impact of multiple heterozygous variants within the same gene, but it is difficult to perform such phasing outside of family studies. Our pipeline utilizes normal DNA, tumor DNA, and tumor RNA to predict the phase of variants without the need for full pedigree information. The pipeline was tested on 1,172 patient samples, with the goal of phasing clinically-associated cancer genes and discovering rare P/LP germline variants. We were able to phase variants in over 50% of the patients, allowing us to identify the nature of compound heterozygosity as it relates to disease risk in these patients. Additionally, our pipeline identified at least 1 high-quality ClinVar P/LP variant per patient in over 25% of the patients. In the vast majority of patients, we were able to identify rare homozygous germline variants. Gene panels specific to cancer type can be used to further investigate which rare variants most likely factor in the patient's disease. Based on these results, as well as our analysis of ClinVar, we assert the need for deep introspection of ClinVar submissions and highlight the utility of RNA data in variant phasing. Citation Format: Amanda Polley, Charles Vaske, Steve Benz, Patrick Soon-Shiong, Shahrooz Rabizadeh, J Zachary Sanborn. Identifying pathogenic germline variants in 1,172 cancer patients utilizing a novel variant phasing tool and strict public database curation [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 2253.

Abstract 1280: Chromosome-scale haplotyping enables comprehensive discovery of cancer rearrangements and germline-related susceptibility mutations

Abstract To understand the complexity of cancer genomes, one needs to define both the structure and order of genomic variants relative to their respective parental chromosome. This process is commonly referred to as phasing and generates haplotypes with group of variants that originated from one parental chromosome or the other. Importantly, genetic variants such as rearrangements are difficult to detect and phase with conventional next-generation sequencing; short reads do not contain long-range genomic information for phasing. Recently, we demonstrated a new technology called linked-read sequencing, which uses droplet barcoding to tag high-molecular-weight (HMW) DNA in order to reconstruct genomic haplotypes and SVs in the range of megabases. Using single nanograms of DNA, we determined the structure of normal and cancer genomes at single-molecule resolution. In this study, we developed a method to generate haplotypes spanning entire chromosome arms and even across centromeric regions. The method is based on leveraging identity-by-descent (IBD) principles in haplotype-resolved sequence data. Taking advantage of shared haplotypes between an individual and a single parent, we exploited the fact that any single chromosomal homologue consists of a contiguous segment from one parent regardless of any recombination events that occurred during meiosis. By determining which of the two homologous segments in a haplotyped segment belongs to a parent, we can then stitch together the haplotypes that are physically contiguous in the child. Using phased haplotypes generated from linked-read sequencing, we improve on the experimentally generated haplotypes by at least an order of magnitude. As a control, we performed this type of analysis on a series of control genomes with comprehensive haplotype information. We achieved near-perfect concordance in the comprehensive phasing of these control samples regardless of which parental genome was used. We performed this analysis on linked-read whole-genome sequence data derived from familial cohorts with an inherited predisposition to cancer of unknown origin. For example, in one family predisposed to cholangiocarcinoma, we resolved the haplotype structure of entire chromosomes and segregated entire segments belonging to affected and unaffected individuals. A similar process was applied to the cancer samples originating from affected family members. The joint information was used to identify potential candidate driver genes for this cancer type. Overall, we demonstrated the utility of linked-read analysis and whole-chromosome haplotypes in discovering cancer genes. Citation Format: Stephanie U. Greer, Billy T. Lau, Lincoln D. Nadauld, Hanlee P. Ji. Chromosome-scale haplotyping enables comprehensive discovery of cancer rearrangements and germline-related susceptibility mutations [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 1280.

Haplotype phasing in single-cell DNA-sequencing data.

MotivationCurrent technologies for single-cell DNA sequencing require whole-genome amplification (WGA), as a single cell contains too little DNA for direct sequencing. Unfortunately, WGA introduces biases in the resulting sequencing data, including non-uniformity in genome coverage and high rates of allele dropout. These biases complicate many downstream analyses, including the detection of genomic variants.ResultsWe show that amplification biases have a potential upside: long-range correlations in rates of allele dropout provide a signal for phasing haplotypes at the lengths of amplicons from WGA, lengths which are generally longer than than individual sequence reads. We describe a statistical test to measure concurrent allele dropout between single-nucleotide polymorphisms (SNPs) across multiple sequenced single cells. We use results of this test to perform haplotype assembly across a collection of single cells. We demonstrate that the algorithm predicts phasing between pairs of SNPs with higher accuracy than phasing from reads alone. Using whole-genome sequencing data from only seven neural cells, we obtain haplotype blocks that are orders of magnitude longer than with sequence reads alone (median length 10.2 kb versus 312 bp), with error rates <2%. We demonstrate similar advantages on whole-exome data from 16 cells, where we obtain haplotype blocks with median length 9.2 kb—comparable to typical gene lengths—compared with median lengths of 41 bp with sequence reads alone, with error rates <4%. Our algorithm will be useful for haplotyping of rare alleles and studies of allele-specific somatic aberrations.Availability and implementationSource code is available at https://www.github.com/raphael-group.Supplementary information Supplementary data are available at Bioinformatics online.

PacBio sequencing, de novo assembly and haplotype phasing of diploid yeast strains

PacBio sequencing, de novo assembly and haplotype phasing of diploid yeast strains

RPASE: Individual-based allele-specific expression detection without prior knowledge of haplotype phase.

Variation in gene expression is believed to make a significant contribution to phenotypic diversity and divergence. The analysis of allele-specific expression (ASE) can reveal important insights into gene expression regulation. We developed a novel method called RPASE (Read-backed Phasing-based ASE detection) to test for genes that show ASE. With mapped RNA-seq data from a single individual and a list of SNPs from the same individual as the only input, RPASE is capable of aggregating information across multiple dependent SNPs and producing individual-based gene-level tests for ASE. RPASE performs well in simulations and comparisons. We applied RPASE to multiple bird species and found a potentially rich landscape of ASE.

Targeted linked-read sequencing for direct haplotype phasing of maternal DMD alleles: a practical and reliable method for noninvasive prenatal diagnosis

For the noninvasive prenatal diagnosis (NIPD) of X-linked recessive diseases such as Duchenne muscular dystrophy (DMD), maternal haplotype phasing is a critical step for dosage analysis of the inherited allele. Until recently, the proband-based indirect haplotyping method has been preferred despite its limitations for use in clinical practice. Here, we describe a method for directly determining the maternal haplotype without requiring the proband’s DNA in DMD families. We used targeted linked-read deep sequencing (mean coverage of 692×) of gDNA from 5 mothers to resolve their haplotypes and predict the mutation status of the fetus. The haplotype of DMD alleles in the carrier mother was successfully phased through a targeted linked-read sequencing platform. Compared with the proband-based phasing method, linked-read sequencing was more accurate in differentiating whether the recombination events occurred in the proband or in the fetus. The predicted inheritance of the DMD mutation was diagnosed correctly in all 5 families in which the mutation had been confirmed using amniocentesis or chorionic villus sampling. Direct haplotyping by this targeted linked-read sequencing method could be used as a phasing method for the NIPD of DMD, especially when the genomic DNA of the proband is unavailable.

Efficient algorithms for polyploid haplotype phasing

BackgroundInference of haplotypes, or the sequence of alleles along the same chromosomes, is a fundamental problem in genetics and is a key component for many analyses including admixture mapping, identifying regions of identity by descent and imputation. Haplotype phasing based on sequencing reads has attracted lots of attentions. Diploid haplotype phasing where the two haplotypes are complimentary have been studied extensively. In this work, we focused on Polyploid haplotype phasing where we aim to phase more than two haplotypes at the same time from sequencing data. The problem is much more complicated as the search space becomes much larger and the haplotypes do not need to be complimentary any more.ResultsWe proposed two algorithms, (1) Poly-Harsh, a Gibbs Sampling based algorithm which alternatively samples haplotypes and the read assignments to minimize the mismatches between the reads and the phased haplotypes, (2) An efficient algorithm to concatenate haplotype blocks into contiguous haplotypes.ConclusionsOur experiments showed that our method is able to improve the quality of the phased haplotypes over the state-of-the-art methods. To our knowledge, our algorithm for haplotype blocks concatenation is the first algorithm that leverages the shared information across multiple individuals to construct contiguous haplotypes. Our experiments showed that it is both efficient and effective.

T152. NRN1 GENE AND FUNCTIONAL MRI: ASSOCIATION ANALYSIS IN SCHIZOPHRENIA PATIENTS AND HEALTHY SUBJECTS

BackgroundAlterations of synaptic plasticity are currently accepted to play a critical role in schizophrenia (SZ). Among genes of neuronal plasticity there is Neuritin1 gene (NRN1), which has been associated with SZ, age at onset and differences in general cognitive performance in this disorder. However, little is known about the brain imaging correlates of NRN1 gene. We aimed: i) to investigate the association of NRN1 with schizophrenia-spectrum disorders (SZ-SD), exploring its role in age at onset through a family-based study, ii) to examine the brain functional correlates of NRN1 sequence variants through a neuroimaging genetics approach using a case-control design.MethodsA family-based association analysis was carried out with a sample of 588 individuals from 159 families (74 early onset / 85 adult onset) with an offspring with a diagnosis of SZ-SD. An independent sample consisting of 45 subjects (26 patients / 19 controls) was used to perform a case-control neuroimaging genetics analysis. DNA was extracted from blood/buccal mucosa samples and eleven Single Nucleotide Polymorphisms (SNPs) in NRN1 were genotyped. The linkage disequilibrium between the SNPs was estimated in the family-based sample with Haploview v4.1. Three haplotype blocks were defined: 1) rs2208870, rs12333117, rs582186, 2) rs645649, rs582262, 3) rs3763180, rs10484320, rs4960155, rs9379002, rs9405890, rs1475157. PLINK-v1.06 was used for the tabulation of possible individual haplotype phases and for the family-based association analyses (Transmission Disequilibrium Test). To explore the brain functional correlates of NRN1, the subjects belonging to case-control sample underwent a single MRI scanning session and performed a virtual reality spatial navigation task (Salgado-Pineda et al. 2016). The standard atlas provided in the FSL package was used to define three separate ROIs (left and right hippocampus and medial frontal region (mPFC)) and the mean value of activation per each subject was used to test the effect of each SNP/haplotypes by means of a linear regression. All the analyses were adjusted by age, sex and premorbid intelligence coefficient (IQ-TAP).ResultsTwo haplotypes including SNP4 and SNP5 (rs645649-rs582262) were associated with early onset SZ-SD: the haplotype CG was undertransmitted from parents to patients (p=0.011, OR (95%CI=0.08(0.01–0.71) - protective haplotype), while the haplotype GG showed an overtransmission trend (p=0.055, OR (95%CI=3.83 (1.40–10.48)). No effect was observed in the adult onset subsample.No differences between patients and controls were observed in the activation of the three ROIs. Within patients, an effect of the haplotype CG (SNP4-5) was detected in the mPFC: carriers of no copies of the protective haplotype showed a higher mean activation (n=15, mean(SD)=-1.17(17.37)) than individuals with at least one copy of the haplotype (n=9, mean(SD)=-21.19(21.94)) (⎕=-0.507 p=0.035).DiscussionFirst, our family-based results are consistent with evidence of a genetic association between NRN1 gene and SZ-SD and extend the knowledge on that NRN1 has a selective impact on early age at onset (Fatjó-Vilas et al. 2016). Second, our data suggest that NRN1 is involved in the regulation of the de-activation of mPFC in patients with SZ during a spatial navigation task. This result is of special interest since mPFC is an area included in the Default Mode Network (DMN) and alterations in this network have been highly documented in SZ patients during performance of different tasks (Pomarol-Clotet et al. 2008; Mannell et al. 2010; Salgado-Pineda et al. 2011).AcknowledgementsFundación Alicia Koplowitz.

Off the street phasing (OTSP): free no hassle haplotype phasing for molecular PGD applications

Purpose Pre-implantation genetic diagnosis (PGD) for molecular disorders requires the construction of parental haplotypes. Classically, haplotype resolution (“phasing”) is obtained by genotyping multiple polymorphic markers in both parents and at least one additional relative. However, this process is time-consuming, and immediate family members are not always available. The recent availability of massive genomic data for many populations promises to eliminate the needs for developing family-specific assays and for recruiting additional family members. In this study, we aimed to validate population-assisted haplotype phasing for PGD.

A Near-Complete Haplotype-Phased Genome of the Dikaryotic Wheat Stripe Rust Fungus Puccinia striiformis f. sp. tritici Reveals High Interhaplotype Diversity.

ABSTRACTA long-standing biological question is how evolution has shaped the genomic architecture of dikaryotic fungi. To answer this, high-quality genomic resources that enable haplotype comparisons are essential. Short-read genome assemblies for dikaryotic fungi are highly fragmented and lack haplotype-specific information due to the high heterozygosity and repeat content of these genomes. Here, we present a diploid-aware assembly of the wheat stripe rust fungus Puccinia striiformis f. sp. tritici based on long reads using the FALCON-Unzip assembler. Transcriptome sequencing data sets were used to infer high-quality gene models and identify virulence genes involved in plant infection referred to as effectors. This represents the most complete Puccinia striiformis f. sp. tritici genome assembly to date (83 Mb, 156 contigs, N50 of 1.5 Mb) and provides phased haplotype information for over 92% of the genome. Comparisons of the phase blocks revealed high interhaplotype diversity of over 6%. More than 25% of all genes lack a clear allelic counterpart. When we investigated genome features that potentially promote the rapid evolution of virulence, we found that candidate effector genes are spatially associated with conserved genes commonly found in basidiomycetes. Yet, candidate effectors that lack an allelic counterpart are more distant from conserved genes than allelic candidate effectors and are less likely to be evolutionarily conserved within the P. striiformis species complex and Pucciniales. In summary, this haplotype-phased assembly enabled us to discover novel genome features of a dikaryotic plant-pathogenic fungus previously hidden in collapsed and fragmented genome assemblies.

Ancient genomic variation underlies repeated ecological adaptation in young stickleback populations.

Adaptation in the wild often involves standing genetic variation (SGV), which allows rapid responses to selection on ecological timescales. However, we still know little about how the evolutionary histories and genomic distributions of SGV influence local adaptation in natural populations. Here, we address this knowledge gap using the threespine stickleback fish (Gasterosteus aculeatus) as a model. We extend restriction site‐associated DNA sequencing (RAD‐seq) to produce phased haplotypes approaching 700 base pairs (bp) in length at each of over 50,000 loci across the stickleback genome. Parallel adaptation in two geographically isolated freshwater pond populations consistently involved fixation of haplotypes that are identical‐by‐descent. In these same genomic regions, sequence divergence between marine and freshwater stickleback, as measured by dXY, reaches tenfold higher than background levels and genomic variation is structured into distinct marine and freshwater haplogroups. By combining this dataset with a de novo genome assembly of a related species, the ninespine stickleback (Pungitius pungitius), we find that this habitat‐associated divergent variation averages six million years old, nearly twice the genome‐wide average. The genomic variation that is involved in recent and rapid local adaptation in stickleback has therefore been evolving throughout the 15‐million‐year history since the two species lineages split. This long history of genomic divergence has maintained large genomic regions of ancient ancestry that include multiple chromosomal inversions and extensive linked variation. These discoveries of ancient genetic variation spread broadly across the genome in stickleback demonstrate how selection on ecological timescales is a result of genome evolution over geological timescales, and vice versa.