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

Crysnanto, Danang; Pausch, Hubert

doi:10.1101/2019.12.20.882423

Cited by 8 publications

(9 citation statements)

References 85 publications

(127 reference statements)

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“…PacBio HiFi reads for a Nelore x Brown Swiss bull are available at study accession PRJEB42335 under sample accession SAMEA7765441. Data supporting this study, including the multi-assembly graph, non-reference sequences, putatively novel genes, transcript abundances and sequence variants detected from non-reference sequences are available via Zenodo (https://doi.org/10.5281/zenodo.4385983) 68 .…”

Section: Data Availabilitymentioning

confidence: 99%

“…Efforts to mitigate reference allele bias and increase the genetic diversity of reference genomes have led to graph-based references 14,15 . We have previously shown that a bovine genome graph, which integrates linear reference coordinates and pre-selected variants, improves the mapping of reads and enables unbiased variant genotyping 16,17 . However, previous attempts focused on augmenting the bovine reference genome with small variations (<50bp), not the larger class of structural variations.…”

Section: Introductionmentioning

confidence: 99%

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Novel functional sequences uncovered through a bovine multi-assembly graph

Crysnanto

Leonard

Fang

et al. 2021

Preprint

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Linear reference genomes are typically assembled from single individuals. They are unable to reflect the genetic diversity of populations and lack millions of bases. To overcome such limitations and make non-reference sequences amenable to genetic investigations, we build a multi-assembly graph from six reference-quality assemblies from taurine cattle and their close relatives. We uncover 70,329,827 bases that are missing in the bovine linear reference genome. The missing sequences encode novel transcripts that are differentially expressed between individual animals. Reads which were previously poorly or unmapped against the bovine reference genome now align accurately to the non-reference sequences. We show that the non-reference sequences contain polymorphic sites that segregate within and between breeds of cattle. Our efforts to uncover novel functional sequences from a multi-assembly graph pave the way towards the transition to a more representative bovine reference genome.

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Section: Data Availabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Novel functional sequences uncovered through a bovine multi-assembly graph

Crysnanto

Leonard

Fang

et al. 2021

Preprint

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“…Consequently, errors and gaps in the functional annotations of bovine reference-quality assemblies other than ARS-UCD1.2 are a major obstacle to switch references. TThe application of an augmented reference genome that contains ARS-UCD1.2 and its functional annotations as backbone as well as variants detected in other assemblies might solve such problems [12,45].…”

Section: Discussionmentioning

confidence: 99%

“…As a result, read alignments may be erroneous particularly at genomic regions that differ substantially between the sequenced individual and the reference genome [10]. The use of consensus reference genomes or variation-aware reference graphs may mitigate this type of bias [11,12,13].…”

Section: Introductionmentioning

confidence: 99%

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

Lloret-Villas

Bhati

Kadri

et al. 2021

Preprint

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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. 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 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.

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Efficient dynamic variation graphs

et al. 2020

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Motivation Pangenomics is a growing field within computational genomics. Many pangenomic analyses use bidirected sequence graphs as their core data model. However, implementing and correctly using this data model can be difficult, and the scale of pangenomic data sets can be challenging to work at. These challenges have impeded progress in this field. Results Here we present a stack of two C ++ libraries, libbdsg and libhandlegraph, which use a simple, field-proven interface, designed to expose elementary features of these graphs while preventing common graph manipulation mistakes. The libraries also provide a Python binding. Using a diverse collection of pangenome graphs, we demonstrate that these tools allow for efficient construction and manipulation of large genome graphs with dense variation. For instance, the speed and memory usage is up to an order of magnitude better than the prior graph implementation in the VG toolkit, which has now transitioned to using libbdsg’s implementations. Availability libhandlegraph and libbdsg are available under an MIT License from https://github.com/vgteam/libhandlegraph and https://github.com/vgteam/libbdsg. Supplementary information Supplementary data are available at Bioinformatics online.

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

Cited by 8 publications

References 85 publications

Novel functional sequences uncovered through a bovine multi-assembly graph

Novel functional sequences uncovered through a bovine multi-assembly graph

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

Efficient dynamic variation graphs

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