Benchmarking phasing software with a whole-genome sequenced cattle pedigree

A precise and cost-efficient whole-genome haplotyping method without probands: preimplantation genetic testing analysis

RESEARCH QUESTION

Is there a precise and efficient haplotyping method to expand the application of preimplantation genetic testing (PGT)?

DESIGN

In this study, eight cell-line families and 18 clinical families including 99 embryos were used to construct whole-genome haplotyping based on link-read sequencing (Phbol-seq) and optimized analytical workflow with a correction algorithm. The correction algorithm was based on a differentiation of assembly errors and homologous recombination, in which the main feature of parental assembly error was that all embryos (embryo number ≥2) had breakpoints at the same chromosome position.

RESULTS

With Phbol-seq, parental assembly errors and homologous recombination were accurately distinguished and corrected. Using the link-reads (>25% long-reads were ≥30 kilobases [kb]), complete genome-wide parental haplotypes were constructed, and the consistency of the typing results of each chromosome with a conventional method requiring other family members was more than 95%. In addition, the length of N50 contigs was 11.03-16.2 million bases (mb), which was far beyond the N50 contigs from long-read sequencing (148-863 kb). The complete haplotype analysis of all embryos could be performed by Phbol-seq and revealed 100% concordance with the available diagnostic results obtained by the conventional method requiring other family members.

CONCLUSIONS

Phbol-seq has high clinical value as a precise and cost-efficient whole-genome haplotyping method without probands as part of PGT and other genetic research, which could promote the application of PGT to decrease the birth of children with genetic diseases and the development of linkage-related genetic research.

Global and local ancestry estimation in a captive baboon colony

The last couple of decades have highlighted the importance of studying hybridization, particularly among primate species, as it allows us to better understand our own evolutionary trajectory. Here, we report on genetic ancestry estimates using dense, full genome data from 881 olive (Papio anubus), yellow (Papio cynocephalus), or olive-yellow crossed captive baboons from the Southwest National Primate Research Center. We calculated global and local ancestry information, imputed low coverage genomes (n = 830) to improve marker quality, and updated the genetic resources of baboons available to assist future studies. We found evidence of historical admixture in some putatively purebred animals and identified errors within the Southwest National Primate Research Center pedigree. We also compared the outputs between two different phasing and imputation pipelines along with two different global ancestry estimation software. There was good agreement between the global ancestry estimation software, with R2 > 0.88, while evidence of phase switch errors increased depending on what phasing and imputation pipeline was used. We also generated updated genetic maps and created a concise set of ancestry informative markers (n = 1,747) to accurately obtain global ancestry estimates.

The shared ancestry between the C9orf72 hexanucleotide repeat expansion and intermediate-length alleles using haplotype sharing trees and HAPTK

The C9orf72 hexanucleotide repeat expansion (HRE) is a common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The inheritance is autosomal dominant, but a high proportion of subjects with the mutation are simplex cases. One possible explanation is de novo expansions of unstable intermediate-length alleles (IAs). Using haplotype sharing trees (HSTs) with the haplotype analysis tool kit (HAPTK), we derived majority-based ancestral haplotypes of HRE samples and discovered that IAs containing ≥18-20 repeats share large haplotypes in common with the HRE. Using HSTs of HRE and IA samples, we demonstrate that the longer IA haplotypes are largely indistinguishable from HRE haplotypes and that several ≥18-20 IA haplotypes share over 5 Mb (>600 markers) haplotypes in common with the HRE haplotypes. These analysis tools allow physical understanding of the haplotype blocks shared with the majority-based ancestral haplotype. Our results demonstrate that the haplotypes with longer IAs belong to the same pool of haplotypes as the HRE and suggest that longer IAs represent potential premutation alleles.

An organism-wide ATAC-seq peak catalog for the bovine and its use to identify regulatory variants

We report the generation of an organism-wide catalog of 976,813 cis-acting regulatory elements for the bovine detected by the assay for transposase accessible chromatin using sequencing (ATAC-seq). We regroup these regulatory elements in 16 components by nonnegative matrix factorization. Correlation between the genome-wide density of peaks and transcription start sites, correlation between peak accessibility and expression of neighboring genes, and enrichment in transcription factor binding motifs support their regulatory potential. Using a previously established catalog of 12,736,643 variants, we show that the proportion of single-nucleotide polymorphisms mapping to ATAC-seq peaks is higher than expected and that this is owing to an approximately 1.3-fold higher mutation rate within peaks. Their site frequency spectrum indicates that variants in ATAC-seq peaks are subject to purifying selection. We generate eQTL data sets for liver and blood and show that variants that drive eQTL fall into liver- and blood-specific ATAC-seq peaks more often than expected by chance. We combine ATAC-seq and eQTL data to estimate that the proportion of regulatory variants mapping to ATAC-seq peaks is approximately one in three and that the proportion of variants mapping to ATAC-seq peaks that are regulatory is approximately one in 25. We discuss the implication of these findings on the utility of ATAC-seq information to improve the accuracy of genomic selection.

Evaluation of Whole-Genome Sequence Imputation Strategies in Korean Hanwoo Cattle

Simple Summary

In this study, we evaluated various imputation strategies for the Korean Hanwoo cattle. We observed that a large reference panel consisting of many cattle breeds did not improve the imputation accuracy when compared to a proportionally small purebred Hanwoo reference. This was because the multi-breed reference did not contain animals sufficiently related to the Hanwoo to improve the accuracies and, although not detrimental, in effect, only added to the computational burden of the imputation. Despite the large multi-breed reference, when the Hanwoo were removed from the reference, the imputation accuracies were low. These results suggest additional sequencing efforts are needed for underrepresented breeds, particularly those less genetically related to the main European breeds.

Abstract

This study evaluated the accuracy of sequence imputation in Hanwoo beef cattle using different reference panels: a large multi-breed reference with no Hanwoo (n = 6269), a much smaller Hanwoo purebred reference (n = 88), and both datasets combined (n = 6357). The target animals were 136 cattle both sequenced and genotyped with the Illumina BovineSNP50 v2 (50K). The average imputation accuracy measured by the Pearson correlation (R) was 0.695 with the multi-breed reference, 0.876 with the purebred Hanwoo, and 0.887 with the combined data; the average concordance rates (CR) were 88.16%, 94.49%, and 94.84%, respectively. The accuracy gains from adding a large multi-breed reference of 6269 samples to only 88 Hanwoo was marginal; however, the concordance rate for the heterozygotes decreased from 85% to 82%, and the concordance rate for fixed SNPs in Hanwoo also decreased from 99.98% to 98.73%. Although the multi-breed panel was large, it was not sufficiently representative of the breed for accurate imputation without the Hanwoo animals. Additionally, we evaluated the value of high-density 700K genotypes (n = 991) as an intermediary step in the imputation process. The imputation accuracy differences were negligible between a single-step imputation strategy from 50K directly to sequence and a two-step imputation approach (50K-700K-sequence). We also observed that imputed sequence data can be used as a reference panel for imputation (mean R = 0.9650, mean CR = 98.35%). Finally, we identified 31 poorly imputed genomic regions in the Hanwoo genome and demonstrated that imputation accuracies were particularly lower at the chromosomal ends.