Improvements and impacts of GRCh38 human reference on high throughput sequencing data analysis

Guo, Yan; Dai, Yulin; Yu, Hui; Zhao, Shilin; Samuels, David C.; Shyr, Yu

doi:10.1016/j.ygeno.2017.01.005

Cited by 129 publications

(98 citation statements)

References 38 publications

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“…Our results show that Graphtyper may also produce genotypes for problematic segments when they are split and processed in smaller bits. Moreover, most of these problems disappeared when we considered the latest assembly of the bovine genome, possibly corroborating that more complete and contiguous genome assemblies may facilitate more reliable genotyping from variation-aware graphs [37,57].…”

Section: Discussionmentioning

confidence: 54%

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

Crysnanto

Wurmser

Pausch

2018

Preprint

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Background:The genotyping 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 sequence variation within a species, reference allele bias may occur at highly polymorphic or diverged regions of the genome. Graph-based methods facilitate to compare sequencing reads to a variation-aware genome graph that incorporates a collection of non-redundant DNA sequences that segregate within a species.We compared accuracy and sensitivity of graph-based sequence variant genotyping using the Graphtyper software to two widely used methods, i.e., GATK and SAMtools, that rely on linear reference genomes using whole-genomes sequencing data of 49 Original Braunvieh cattle. Results:We discovered 21,140,196, 20,262,913 and 20,668,459 polymorphic sites using GATK, Graphtyper, and SAMtools, respectively. Comparisons between sequence variant 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 lowest number of mendelian inconsistencies for both SNPs and indels in nine sire-son pairs with sequence data. Genotype phasing and imputation using the Beagle software improved the quality of the sequence variant genotypes for all tools evaluated particularly for animals that have been 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 the genotype concordance slightly but it also decreased sensitivity. Graphtyper required considerably more computing resources than SAMtools but it required less than GATK.Conclusions: Sequence 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 implementations of state-of-the-art methods that rely on linear reference genomes.

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Section: Discussionmentioning

confidence: 54%

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

Crysnanto

Wurmser

Pausch

2018

Preprint

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“…They were aligned to the human genome (hg19) using either Bowtie 2 (Langmead and Salzberg 2012) or STAR 2.3.0e (Dobin et al 2013). Aligning to GRCh38 is expected to provide similar results, as only a small number of bases change genome-wide with the major difference between the releases is in centromere assembly (Guo et al 2017), which is not the focus of our study.…”

Section: Methodsmentioning

confidence: 87%

4q-D4Z4 chromatin architecture regulates the transcription of muscle atrophic genes in FSHD

Cortesi

Pesant

Sinha

et al. 2019

Preprint

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“…GRCh38 differs from the preceding human genome assembly by including 252 additional alternate loci, the mitochondrial genome, and many rectifications in nucleotide calls, misassembled regions, and previous gaps. Although GRCh37 has been used more extensively in large‐scale sequencing projects, GRCh38 provides higher accuracy and richer diversity features . Inmmunohematologists will notice that blood group variant coordinates often shift in the newest assembly, that C4A/C4B gene prediction tracks are more accurate, and that there is an alternate haplotype for the region that encodes for KEL .…”

Section: Discussionmentioning

confidence: 99%

“…Although GRCh37 has been used more extensively in large-scale sequencing projects, GRCh38 provides higher accuracy and richer diversity features. 61 Inmmunohematologists will notice that blood group variant coordinates often shift in the newest assembly, that C4A/ C4B gene prediction tracks are more accurate, and that there is an alternate haplotype for the region that encodes for KEL. Regardless of the reference build used, a critical item is to maintain consistency throughout the entire NGS analysis pipeline.…”

Section: Discussionmentioning

confidence: 99%

Genomic coordinates and continental distribution of 120 blood group variants reported by the 1000 Genomes Project

et al. 2018

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BACKGROUND The 1000 Genomes Project provides a database of genomic variants from whole genome sequencing of 2504 individuals across five continental superpopulations. This database can enrich our background knowledge of worldwide blood group variant geographic distribution and identify novel variants of potential clinical significance. STUDY DESIGN AND METHODS The 1000 Genomes database was analyzed to 1) expand knowledge about continental distributions of known blood group variants, 2) identify novel variants with antigenic potential and their geographic association, and 3) establish a baseline scaffold of chromosomal coordinates to translate next‐generation sequencing output files into a predicted red blood cell (RBC) phenotype. RESULTS Forty‐two genes were investigated. A total of 604 known variants were mapped to the GRCh37 assembly; 120 of these were reported by 1000 Genomes in at least one superpopulation. All queried variants, including the ACKR1 promoter silencing mutation, are located within exon pull‐down boundaries. The analysis yielded 41 novel population distributions for 34 known variants, as well as 12 novel blood group variants that warrant further validation and study. Four prediction algorithms collectively flagged 79 of 109 (72%) known antigenic or enzymatically detrimental blood group variants, while 4 of 12 variants that do not result in an altered RBC phenotype were flagged as deleterious. CONCLUSION Next‐generation sequencing has known potential for high‐throughput and extended RBC phenotype prediction; a database of GRCh37 and GRCh38 chromosomal coordinates for 120 worldwide blood group variants is provided as a basis for this clinical application.

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Improvements and impacts of GRCh38 human reference on high throughput sequencing data analysis

Cited by 129 publications

References 38 publications

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

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

4q-D4Z4 chromatin architecture regulates the transcription of muscle atrophic genes in FSHD

Genomic coordinates and continental distribution of 120 blood group variants reported by the 1000 Genomes Project

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