Haplotype Phasing Research Articles

ExoCET: exonuclease in vitro assembly combined with RecET recombination for highly efficient direct DNA cloning from complex genomes.

The exponentially increasing volumes of DNA sequence data highlight the need for new DNA cloning methods to explore the new information. Here, we describe 'ExoCET' (Exonuclease Combined with RecET recombination) to directly clone any chosen region from bacterial and mammalian genomes with nucleotide precision into operational plasmids. ExoCET combines in vitro exonuclease and annealing with the remarkable capacity of full length RecET homologous recombination (HR) to retrieve specified regions from genomic DNA preparations. Using T4 polymerase (T4pol) as the in vitro exonuclease for ExoCET, we directly cloned large regions (>50 kb) from bacterial and mammalian genomes, including DNA isolated from blood. Employing RecET HR or Cas9 cleavage in vitro, the directly cloned region can be chosen with nucleotide precision to position, for example, a gene into an expression vector without the need for further subcloning. In addition to its utility for bioprospecting in bacterial genomes, ExoCET presents straightforward access to mammalian genomes for various applications such as region-specific DNA sequencing that retains haplotype phasing, the rapid construction of optimal, haplotypic, isogenic targeting constructs or a new way to genotype that presents advantages over Southern blotting or polymerase chain reaction. The direct cloning capacities of ExoCET present new freedoms in recombinant DNA technology.

ExoCET: exonuclease in vitro assembly combined with RecET recombination for highly efficient direct DNA cloning from complex genomes.

The exponentially increasing volumes of DNA sequence data highlight the need for new DNA cloning methods to explore the new information. Here, we describe ‘ExoCET’ (Exonuclease Combined with RecET recombination) to directly clone any chosen region from bacterial and mammalian genomes with nucleotide precision into operational plasmids. ExoCET combines in vitro exonuclease and annealing with the remarkable capacity of full length RecET homologous recombination (HR) to retrieve specified regions from genomic DNA preparations. Using T4 polymerase (T4pol) as the in vitro exonuclease for ExoCET, we directly cloned large regions (>50 kb) from bacterial and mammalian genomes, including DNA isolated from blood. Employing RecET HR or Cas9 cleavage in vitro, the directly cloned region can be chosen with nucleotide precision to position, for example, a gene into an expression vector without the need for further subcloning. In addition to its utility for bioprospecting in bacterial genomes, ExoCET presents straightforward access to mammalian genomes for various applications such as region-specific DNA sequencing that retains haplotype phasing, the rapid construction of optimal, haplotypic, isogenic targeting constructs or a new way to genotype that presents advantages over Southern blotting or polymerase chain reaction. The direct cloning capacities of ExoCET present new freedoms in recombinant DNA technology.

Blocks of chromosomes identical by descent in a population: Models and predictions.

With the highly dense genomic data available nowadays, ignoring linkage between genes would result in a huge loss of information. One way to prevent such a loss is to focus on the blocks of chromosomes shared identical by descent (IBD) in populations. The development of the theoretical framework modelling IBD processes is essential to support the advent of new tools such as haplotype phasing, imputation, inferring population structure and demographic history, mapping loci or detecting signatures of selection. This article aims to present the relevant models used in this context, and specify the underlying definitions of identity by descent that are yet to be gathered at one place. In light of this, we derived a general expression for the expected IBD block length, for any population model at any generation after founding.

Genomic regions associated with susceptibility to Barrett's esophagus and esophageal adenocarcinoma in African Americans: The cross BETRNet admixture study.

BackgroundBarrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) are far more prevalent in European Americans than in African Americans. Hypothesizing that this racial disparity in prevalence might represent a genetic susceptibility, we used an admixture mapping approach to interrogate disease association with genomic differences between European and African ancestry.MethodsFormalin fixed paraffin embedded samples were identified from 54 African Americans with BE or EAC through review of surgical pathology databases at participating Barrett’s Esophagus Translational Research Network (BETRNet) institutions. DNA was extracted from normal tissue, and genotyped on the Illumina OmniQuad SNP chip. Case-only admixture mapping analysis was performed on the data from both all 54 cases and also on a subset of 28 cases with high genotyping quality. Haplotype phases were inferred with Beagle 3.3.2, and local African and European ancestries were inferred with SABER plus. Disease association was tested by estimating and testing excess European ancestry and contrasting it to excess African ancestry.ResultsBoth datasets, the 54 cases and the 28 cases, identified two admixture regions. An association of excess European ancestry on chromosome 11p reached a 5% genome-wide significance threshold, corresponding to -log10(P) = 4.28. A second peak on chromosome 8q reached -log10(P) = 2.73. The converse analysis examining excess African ancestry found no genetic regions with significant excess African ancestry associated with BE and EAC. On average, the regions on chromosomes 8q and 11p showed excess European ancestry of 15% and 20%, respectively.ConclusionsChromosomal regions on 11p15 and 8q22-24 are associated with excess European ancestry in African Americans with BE and EAC. Because GWAS have not reported any variants in these two regions, low frequency and/or rare disease associated variants that confer susceptibility to developing BE and EAC may be driving the observed European ancestry association evidence.

OR20 De novo generation of MHC haplotypes using single molecule sequencing

Aim Utilizing a previously developed long-fragment DNA capture methodology, PacBio single molecule real-time (SMRT) sequencing and a custom de novo assembly analysis pipeline, we aim to resolve the long-range, fully phased MHC haplotypes for a single heterozygous individual. Methods Long fragment DNA enrichment for the MHC was performed on fresh blood obtained from a heterozygous individual using our previously described method, RSE. Captured DNA was sequenced on the PacBio RSII sequencing platform. Raw reads were selected to include only those reads that map to annotated MHC haplotype sequences (n = 8). De novo assembly was performed using the CANU pipeline with tuned algorithm parameters to optimize continuity and accuracy of haplotigs (phased contigs) as compared to phased SNP genotyping data. Results Following de novo assembly, PacBio reads were assembled into 27 contiguous fragments (contigs) covering 97% of the 4Mbp MHC (as aligned to the COX MHC haplotype). Phased contigs (haplotigs) were found to agree with phased SNP genotyping data at ∼78% of interrogated positions (n = 4,779 probes) indicating that the majority of haplotigs are properly phased. Phased SNP genotyping data was also used to phase across breaks in the assembly, resulting in the generation of two distinct MHC haplotypes for the sequenced sample. Conclusions Our results demonstrate the capacity to generate de novo assembled, fully phased MHC haplotypes from PacBio single molecule sequencing reads. Although phasing across contig breaks caused by coverage gaps remains a challenge, we hope to resolve this issue using BioNano genomics optical maps, so as not to rely on phased SNP genotyping data. In essence, this method has the capacity to resolve full-length MHC haplotype sequences without the need for any reference genome or familial trio analysis.

De novo PacBio long-read and phased avian genome assemblies correct and add to reference genes generated with intermediate and short reads.

Reference-quality genomes are expected to provide a resource for studying gene structure, function, and evolution. However, often genes of interest are not completely or accurately assembled, leading to unknown errors in analyses or additional cloning efforts for the correct sequences. A promising solution is long-read sequencing. Here we tested PacBio-based long-read sequencing and diploid assembly for potential improvements to the Sanger-based intermediate-read zebra finch reference and Illumina-based short-read Anna's hummingbird reference, 2 vocal learning avian species widely studied in neuroscience and genomics. With DNA of the same individuals used to generate the reference genomes, we generated diploid assemblies with the FALCON-Unzip assembler, resulting in contigs with no gaps in the megabase range, representing 150-fold and 200-fold improvements over the current zebra finch and hummingbird references, respectively. These long-read and phased assemblies corrected and resolved what we discovered to be numerous misassemblies in the references, including missing sequences in gaps, erroneous sequences flanking gaps, base call errors in difficult-to-sequence regions, complex repeat structure errors, and allelic differences between the 2 haplotypes. These improvements were validated by single long-genome and transcriptome reads and resulted for the first time in completely resolved protein-coding genes widely studied in neuroscience and specialized in vocal learning species. These findings demonstrate the impact of long reads, sequencing of previously difficult-to-sequence regions, and phasing of haplotypes on generating the high-quality assemblies necessary for understanding gene structure, function, and evolution.

Conditional Displacement Hybridization Assay for Multiple SNP Phasing.

The two chromosomal copies of the human genome are highly polymorphic, and the allelic content on each strand can dictate a person's biological outcomes. While many of the current diagnostic tools are able to detect the presence of multiple mutations at the same time, most cannot determine the phase of these mutations unless long-range PCR or sequencing techniques are used or if templates are compartmentalized into single copies prior to amplification. Here, an enzyme-coupled hybridization assay, named conditional displacement hybridization assay (CDHA), is described for the concurrent and rapid determination of the presence and phase of SNP variants. In this approach, short DNA probes were utilized to first quantify the amount of SNPs on the templates using a two-channel fluorescence measurement. The hybrids formed between the probes and the templates then set up the right condition for the subsequent enzymatic displacement and quenching of a fluorophore-labeled strand, which happens only if both SNPs are present on the same strand. The drop in the fluorescence signal thereby indicates the phase of the two SNPs. As a proof of concept, we tested the assay on four variants of an arbitrary sequence-with or without mutation on two sites 100 nts apart. The assay described herein was able to determine the haplotype phase of the samples in less than 1 h. This method promises a direct, cost-effective, and laboratory-based test to extract further genetic information to determine and/or predict diseases and traits dependent on SNP phasing.

Dissecting differentiation landscapes: a linked selection's perspective.

Dissecting differentiation landscapes: a linked selection's perspective.

A population-specific reference panel empowers genetic studies of Anabaptist populations

Genotype imputation is a powerful strategy for achieving the large sample sizes required for identification of variants underlying complex phenotypes, but imputation of rare variants remains problematic. Genetically isolated populations offer one solution, however population-specific reference panels are needed to assure optimal imputation accuracy and allele frequency estimation. Here we report the Anabaptist Genome Reference Panel (AGRP), the first whole-genome catalogue of variants and phased haplotypes in people of Amish and Mennonite ancestry. Based on high-depth whole-genome sequence (WGS) from 265 individuals, the AGRP contains >12 M high-confidence single nucleotide variants and short indels, of which ~12.5% are novel. These Anabaptist-specific variants were more deleterious than variants with comparable frequencies observed in the 1000 Genomes panel. About 43,000 variants showed enriched allele frequencies in AGRP, consistent with drift. When combined with the 1000 Genomes Project reference panel, the AGRP substantially improved imputation, especially for rarer variants. The AGRP is freely available to researchers through an imputation server.

Security controls in an integrated Biobank to protect privacy in data sharing: rationale and study design

BackgroundWith the goal of realizing genome-based personalized healthcare, we have developed a biobank that integrates personal health, genome, and omics data along with biospecimens donated by volunteers of 150,000. Such a large-scale of data integration involves obvious risks of privacy violation. The research use of personal genome and health information is a topic of global discussion with regard to the protection of privacy while promoting scientific advancement. The present paper reports on our plans, current attempts, and accomplishments in addressing security problems involved in data sharing to ensure donor privacy while promoting scientific advancement.MethodsBiospecimens and data have been collected in prospective cohort studies with the comprehensive agreement. The sample size of 150,000 participants was required for multiple researches including genome-wide screening of gene by environment interactions, haplotype phasing, and parametric linkage analysis.ResultsWe established the TohokuMedicalMegabank (TMM) data sharing policy: a privacy protection rule that requires physical, personnel, and technological safeguards against privacy violation regarding the use and sharing of data. The proposed policy refers to that of NCBI and that of the Sanger Institute. The proposed policy classifies shared data according to the strength of re-identification risks. Local committees organized by TMM evaluate re-identification risk and assign a security category to a dataset. Every dataset is stored in an assigned segment of a supercomputer in accordance with its security category. A security manager should be designated to handle all security problems at individual data use locations. The proposed policy requires closed networks and IP-VPN remote connections.ConclusionThe mission of the biobank is to distribute biological resources most productively. This mission motivated us to collect biospecimens and health data and simultaneously analyze genome/omics data in-house. The biobank also has the mission of improving the quality and quantity of the contents of the biobank. This motivated us to request users to share the results of their research as feedback to the biobank. The TMM data sharing policy has tackled every security problem originating with the missions. We believe our current implementation to be the best way to protect privacy in data sharing.

Abstract 3572: Characterization of chromosomal allelic imbalances through RNA-seq

Abstract Transcriptome sequencing (mRNA-seq) is becoming a very versatile technique for profiling tumors, extending beyond its original intent of transcript quantification, identification of alternative transcripts, and detection of gene fusions. For instance, through recent advancements in RNA-seq data analyses, one can now computationally assess allele-specific gene expression and generate profiles of expressed somatic mutations. Here, we demonstrate the ability to identify chromosomal allelic imbalances (AI) through detection of haplotype-specific patterns in gene transcripts. This class of RNA-based observations may potentially reveal DNA-level chromosomal allelic imbalances or uncover large regions of transcription deregulation. From the TCGA Uterine Carcinosarcoma project, we downloaded exome and RNA sequencing data for 48 patients’ tumor/normal sample pairs in addition to their clinical annotations. We also downloaded Affymetrix SNP6-based DNA copy number event calls made by the TCGA for use as a gold standard when evaluating the AI calls in the exome and RNA-seq. AI calls were made in both the exome and RNA-seq data by: (1) calling 1000 Genomes genotypes in the sequencing data, (2) phasing haplotypes and then (3) characterizing haplotype imbalances using a tool that we developed called hapLOHseq. hapLOHseq applied to the exome and RNA-seq data both resulted in a 72% specificity for identifying the gold standard AI events. In RNA-seq data we detected 43% of the chromosomal AI events identified in the exome sequencing data. When considering AI events specifically detected in the RNA-seq and not the gold standard (RNA-specific AI), the data suggest that higher RNA-specific AI loads could be negatively associated with survival (p-val = 0.076), with higher RNA-specific AI load patients having a median survival of 771 days compared to 1526 days for those patients with lower loads of RNA-specific AI. In conclusion, our results suggest that analysis of chromosomal AI in RNA-seq has equal specificity for detecting DNA-level AI when compared to exome sequencing, although at lower sensitivities. Clinically, our analyses suggest that patients with higher RNA-specific AI load may have a worse overall survival prognosis. The AI we are identifying in the RNA-seq samples may reflect large-scale transcription defects, resulting in a negative impact on the survival of patients. One possible cause of RNA-specific allelic imbalance could be the presence of cis mutations that impact a large-region of the transcription of one of the two haplotypes. Currently, we are identifying areas for improvement in our analytical methods, while interrogating and characterizing exome and RNA-seq AI in additional data sets. Citation Format: Francis A. San Lucas, Yihua Liu, Zachary Weber, Erik Ehli, Gareth Davies, Paul Scheet. Characterization of chromosomal allelic imbalances through RNA-seq [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 3572. doi:10.1158/1538-7445.AM2017-3572

Single‐tube tetradecaplex panel of highly polymorphic microsatellite markers < 1 Mb from F8 for simplified preimplantation genetic diagnosis of hemophilia A

Background It is currently not possible to perform single-cell preimplantation genetic diagnosis (PGD) to directly detect the common inversion mutations of the factor VIII (F8) gene responsible for severe hemophilia A (HEMA). As such, PGD for such inversion carriers relies on indirect analysis of linked polymorphic markers. Objectives To simplify linkage-based PGD of HEMA, we aimed to develop a panel of highly polymorphic microsatellite markers located near the F8 gene that could be simultaneously genotyped in a multiplex-PCR reaction. Methods We assessed the polymorphism of various microsatellite markers located ≤ 1 Mb from F8 in 177 female subjects. Highly polymorphic markers were selected for co-amplification with the AMELX/Y indel dimorphism in a single-tube reaction. Results Thirteen microsatellite markers located within 0.6 Mb of F8 were successfully co-amplified with AMELX/Y in a single-tube reaction. Observed heterozygosities of component markers ranged from 0.43 to 0.84, and ∼70-80% of individuals were heterozygous for ≥ 5 markers. The tetradecaplex panel successfully identified fully informative markers in a couple interested in PGD for HEMA because of an intragenic F8 point mutation, with haplotype phasing established through a carrier daughter. In-vitro fertilization (IVF)-PGD involved single-tube co-amplification of fully informative markers with AMELX/Y and the mutation-containing F8 amplicon, followed by microsatellite analysis and amplicon mutation-site minisequencing analysis. Conclusions The single-tube multiplex-PCR format of this highly polymorphic microsatellite marker panel simplifies identification and selection of informative markers for linkage-based PGD of HEMA. Informative markers can also be easily co-amplified with mutation-containing F8 amplicons for combined mutation detection and linkage analysis.

Haplotype phasing of whole human genomes using bead-based barcode partitioning in a single tube.

Haplotype-resolved genome sequencing promises to unlock a wealth of information in population and medical genetics. However, for the vast majority of genomes sequenced to date, haplotypes have not been determined because of cumbersome haplotyping workflows that require fractions of the genome to be sequenced in a large number of compartments. Here we demonstrate barcode partitioning of long DNA molecules in a single compartment using "on-bead" barcoded tagmentation. The key to the method that we call "contiguity preserving transposition" sequencing on beads (CPTv2-seq) is transposon-mediated transfer of homogenous populations of barcodes from beads to individual long DNA molecules that get fragmented at the same time (tagmentation). These are then processed to sequencing libraries wherein all sequencing reads originating from each long DNA molecule share a common barcode. Single-tube, bulk processing of long DNA molecules with ∼150,000 different barcoded bead types provides a barcode-linked read structure that reveals long-range molecular contiguity. This technology provides a simple, rapid, plate-scalable and automatable route to accurate, haplotype-resolved sequencing, and phasing of structural variants of the genome.

Revealing allele-specific gene expression by single-cell transcriptomics

Single-cell sequencing has emerged as a revolutionary method that reveals biological processes with unprecedented resolution and scale, and has already greatly impacted biology and medicine. To investigate processes such as alternative splicing, novel exon detection and allele-specific expression (ASE), full-length based single-cell RNA-seq methods are required for broad sequence coverage and single nucleotide polymorphism (SNP) identification. In this review, we revisit recent achievements from studies that used single-cell RNA-seq to advance our understanding of ASE in the context of both autosomal and X-chromosome genes. We also recapitulate useful bioinformatic tools developed to identify haplotype phase.

Highly Accurate and Efficient Data-Driven Methods for Genotype Imputation.

High-throughput sequencing techniques have generated massive quantities of genotype data. Haplotype phasing has proven to be a useful and effective method for analyzing these data. However, the quality of phasing is undermined due to missing information. Imputation provides an effective means of improving the underlying genotype information. For model organisms, imputation can rely on an available reference genotype panel and a physical or genetic map. For non-model organisms, which often do not have a genotype panel, it is important to design an imputation technique that does not rely on reference data. Here, we present Accurate Data-Driven Imputation Technique (ADDIT), which is composed of two data-driven algorithms capable of handling data generated from model and non-model organisms. The non-model variant of ADDIT (referred to as ADDIT-NM) employs statistical inference methods to impute missing genotypes, whereas the model variant (referred to as ADDIT-M) leverages a supervised learning-based approach for imputation. We demonstrate that both variants of ADDIT are more accurate, faster, and require less memory than leading state-of-the-art imputation tools using model (human) and non-model (maize, apple, and grape) genotype data. Software Availability: The source code of ADDIT and test data sets are available at https://github.com/NDBL/ADDIT.

Haplostrips: revealing population structure through haplotype visualization

Summary Population genetic analyses often identify polymorphic variants in regions of the genome that indicate the effect of non‐neutral evolutionary processes. However, in order to obtain deeper insights into the evolutionary processes at play, we often resort to summary statistics, sacrificing the information encoded in the complexity of the original data. Here, we present haplostrips, a tool to visualize polymorphisms of a given region of the genome in the form of independently clustered and sorted haplotypes. Haplostrips is a command‐line tool written in Python and R, that uses variant call format files as input and generates a heatmap view. Haplostrips is available at: https://bitbucket.org/dmarnetto/haplostrips. It can be applied in several fields and in all living systems for which a phased haplotype is available to visualize complex effects of, among others: introgression, domestication, selection, demographic events. Haplostrips can reveal hidden patterns of genetic variation without losing the basic information encoded in variant sequences.

STRait Razor v2s: Advancing sequence-based STR allele reporting and beyond to other marker systems

STRait Razor has provided the forensic community a free-to-use, open-source tool for short tandem repeat (STR) analysis of massively parallel sequencing (MPS) data. STRait Razor v2s (SRv2s) allows users to capture physically phased haplotypes within the full amplicon of both commercial (ForenSeq) and “early access” panels (PowerSeq, Mixture ID). STRait Razor v2s may be run in batch mode to facilitate population-level analysis and is supported by all Unix distributions (including MAC OS). Data are reported in tables in string (haplotype), length-based (e.g., vWA allele 14), and International Society of Forensic Genetics (ISFG)-recommended (vWA [CE 14]-GRCh38-chr12:5983950-5984049 (TAGA)10 (CAGA)3 TAGA) formats. STRait Razor v2s currently contains a database of ∼2500 unique sequences. This database is used by SRv2s to match strings to the appropriate allele in ISFG-recommended format. In addition to STRs, SRv2s has configuration files necessary to capture and report haplotypes from all marker types included in these multiplexes (e.g., SNPs, InDels, and microhaplotypes). To facilitate mixture interpretation, data may be displayed from all markers in a format similar to that of electropherograms displayed by traditional forensic software. The download package for SRv2s may be found at https://www.unthsc.edu/graduate-school-of-biomedical-sciences/molecular-and-medical-genetics/laboratory-faculty-and-staff/strait-razor.

Abstract P109: Detection of Haplotypes Underlying a Coronary Artery Calcification Linkage Peak in the Family Heart Study

Coronary artery calcification (CAC) is the buildup of calcium deposits in the arteries leading to the heart, and is an indicator of atherosclerosis. CAC is known to have a genetic component, and a genome-wide linkage screen in the Family Heart Study identified significant evidence of linkage on chromosome 9 in the area near rs13293430, but no common variant in the linkage region showed significant evidence of association. Linkage screens attempt to identify covariance due to common ancestry at a genomic locus. This is robust to the presence of rare variation or multiple variants in a region, but is unable to identify the genomic feature causing the signal and additional research is needed to identify potential causative variants. Pairs of individuals who have inherited a locus from a common ancestor will share an identical sequence of alleles (a haplotype) within the region. To identify haplotypes influencing the trait in the region, a mixed effects model was used. CAC was modeled as a trait influenced by polygenic effects and locus-specific haplotype effects. This model has the benefit of jointly estimating the effect of each haplotype while separating the haplotype effect from the background polygenic effect. From the study, 2,687 individuals of European descent from 508 pedigrees with CAC scores were genotyped on the Illumina Human 1M-DuoV3 single nucleotide polymorphisms (SNP) array. Of these, 180 individuals from 23 pedigrees were for subsequent analysis due to membership in a pedigree contributing to the linkage signal. CAC scores were determined by cardiac CT scan and adjusted for age, sex, and principal components before analysis. Phased haplotypes were generated for 906,856 common SNPs across the genome using SHAPEIT. The region between 25Mb and 35Mb (3,500 SNPs) was divided into 250kb sections, and within each section haplotypes were created based on 24 evenly spaced SNPs. Statistical significance for each region was determined by likelihood ratio test. Haplotype analysis identified two regions showing strong evidence of association (p&amp;lt;10 -7 ) with CAC. The region 28-28.25Mb is located completely within the gene LINGO2, which has been associated with BMI and cholesterol. The region 27.5-27.75Mb contains MOBKL2B, IFNK and C9orf72. Additional work will be needed to validate haplotypes used in the model and identify the particular haplotype influencing the trait.

Universal Haplotype-Based Noninvasive Prenatal Testing for Single Gene Diseases.

Researchers have developed approaches for the noninvasive prenatal testing of single gene diseases. One approach that allows for the noninvasive assessment of both maternally and paternally inherited mutations involves the analysis of single nucleotide polymorphisms (SNPs) in maternal plasma DNA with reference to parental haplotype information. In the past, parental haplotypes were resolved by complex experimental methods or inferential approaches, such as through the analysis of DNA from other affected family members. Recently, microfluidics-based linked-read sequencing technology has become available and allows the direct haplotype phasing of the whole genome rapidly. We explored the feasibility of applying this direct haplotyping technology in noninvasive prenatal testing. We first resolved the haplotypes of parental genomes with the use of linked-read sequencing technology. Then, we identified SNPs within and flanking the genes of interest in maternal plasma DNA by targeted sequencing. Finally, we applied relative haplotype dosage analysis to deduce the mutation inheritance status of the fetus. Haplotype phasing and relative haplotype dosage analysis of 12 out of 13 families were successfully achieved. The mutational status of these 12 fetuses was correctly classified. High-throughput linked-read sequencing followed by maternal plasma-based relative haplotype dosage analysis represents a streamlined approach for noninvasive prenatal testing of inherited single gene diseases. The approach bypasses the need for mutation-specific assays and is not dependent on the availability of DNA from other affected family members. Thus, the approach is universally applicable to pregnancies at risk for the inheritance of a single gene disease.

A comparison of different algorithms for phasing haplotypes using Holstein cattle genotypes and pedigree data

Phasing genotypes to haplotypes is becoming increasingly important due to its applications in the study of diseases, population and evolutionary genetics, imputation, and so on. Several studies have focused on the development of computational methods that infer haplotype phase from population genotype data. The aim of this study was to compare phasing algorithms implemented in Beagle, Findhap, FImpute, Impute2, and ShapeIt2 software using 50k and 777k (HD) genotyping data. Six scenarios were considered: no-parents, sire-progeny pairs, sire-dam-progeny trios, each with and without pedigree information in Holstein cattle. Algorithms were compared with respect to their phasing accuracy and computational efficiency. In the studied population, Beagle and FImpute were more accurate than other phasing algorithms. Across scenarios, phasing accuracies for Beagle and FImpute were 99.49-99.90% and 99.44-99.99% for 50k, respectively, and 99.90-99.99% and 99.87-99.99% for HD, respectively. Generally, FImpute resulted in higher accuracy when genotypic information of at least one parent was available. In the absence of parental genotypes and pedigree information, Beagle and Impute2 (with double the default number of states) were slightly more accurate than FImpute. Findhap gave high phasing accuracy when parents' genotypes and pedigree information were available. In terms of computing time, Findhap was the fastest algorithm followed by FImpute. FImpute was 30 to 131, 87 to 786, and 353 to 1,400 times faster across scenarios than Beagle, ShapeIt2, and Impute2, respectively. In summary, FImpute and Beagle were the most accurate phasing algorithms. Moreover, the low computational requirement of FImpute makes it an attractive algorithm for phasing genotypes of large livestock populations.