De novo assembly of the cattle reference genome with single-molecule sequencing

Rosen, Benjamin D.; Bickhart, Derek M.; Schnabel, Robert D.; Koren, Sergey; Elsik, Christine G.; Tseng, Elizabeth; Rowan, Troy N.; Low, Wai Yee; Zimin, Aleksey V.; Couldrey, Christine; Hall, Richard J.; Li, Wenli; Rhie, Arang; Ghurye, Jay; McKay, Stephanie; Thibaud‐Nissen, Françoise; Hoffman, Jinna; Murdoch, Brenda M.; Snelling, W. M.; McDaneld, T. G.; Hammond, John A.; Schwartz, John C.; Nandolo, Wilson; Hagen, Darren E.; Dreischer, Christian; Schultheiß, Sebastian J.; Schroeder, Steven G.; Phillippy, Adam M.; Cole, John B.; Tassell, Curtis P. Van; Liu, George E.; Smith, Timothy P. L.; Medrano, Juan F.

doi:10.1093/gigascience/giaa021

Cited by 467 publications

(489 citation statements)

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“…In Bos taurus indicus cattle, the accuracy of imputing 50K genotypes to higher density has been investigated only using the UMD3.1 assembly of the bovine genome (23,24). To the best of our knowledge, our study is the first to evaluate the accuracy of imputing 50K to 777K genotypes in a Bos taurus indicus cattle breed using the ARS-UCD1.2 assembly of the bovine genome (21).…”

Section: Discussionmentioning

confidence: 99%

“…Several iterations of improvement resulted in a highly contiguous and accurate bovine reference sequence (20). However, the correct placement of markers and haplotypes inference remains challenging in repetitive and duplicated regions (21). Recently a highly contiguous version (ARS-UCD1.2) of the bovine refer-ence sequence --assembled using long sequencing reads --filled gaps and resolved repetitive regions of the previous UMD3.1 assembly (21).…”

Section: Introductionmentioning

confidence: 99%

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Investigating the accuracy of imputed genotypes in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome

Hermisdorff

Costa

Albuquerque

et al. 2020

Preprint

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BackgroundImputation accuracy among other things depends on the size of the reference panel, the marker's minor allele frequency (MAF), and the correct placement of variants on the reference genome assembly. Using high-density genotypes of 3938 Nellore cattle from Brazil, we investigated the accuracy of imputation from 50K to 777K SNP density, using map positions determined according to the bovine genome assemblies UMD3.1 and ARS-UCD1.2. We assessed the effect of reference and target panel sizes on the pre-phasing-based imputation quality using ten-fold cross-validation. Further, we compared the reliability of the modelbased imputation quality score (Rsq) from Minimac3 to empirical imputation accuracy.1 ResultsThe overall accuracy of imputation measured as the squared correlation between true and imputed allele dosages (R 2 dose) was virtually identical using either the UMD3.1 or ARS-UCD1.2 genome assembly. When the size of the reference panel increased from 250 to 2000, R 2 dose increased from 0.845 to 0.917, and the number of polymorphic markers in the imputed data set increased from 586,701 to 618,660. Advantages in both accuracy and marker density were also observed when larger target panels were imputed, likely resulting from more accurate haplotype inference. Imputation accuracy and the marker density in the imputed data increased from 0.903 to 0.913 and from 593,239 to 595,570 when haplotypes were inferred in 500 and 2900 target animals, respectively. The model-based imputation quality scores from Minimac3 (Rsq) were highly correlated to but systematically higher than empirically estimated accuracies. The correlation between these metrics increased with the size of the reference panel and MAF of imputed variants. ConclusionsAccurate imputation of BovineHD BeadChip markers is possible in Nellore cattle using the new bovine reference genome assembly ARS-UCD1.2. The use of large reference and target panels improves the accuracy of the imputed genotypes and provides genotypes for more markers segregating at low frequency for downstream genomic analyses. The model-based imputation quality score from Minimac3 (Rsq) can be used to detect poorly imputed variants but its reliability depends on the size of the reference panel used and MAF of the imputed variants.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Investigating the accuracy of imputed genotypes in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome

Hermisdorff

Costa

Albuquerque

et al. 2020

Preprint

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“…Figure 2 presents the distribution of SNPs. BTA1 contained the highest number of SNPs (1,455,295), but the highest SNP density, expressed by the proportion of the number of SNPs to length, was highest for BTA25 (2.6%). BTY was characterized by the lowest number of SNPs (41,500) and the lowest SNP density (0.1%).…”

Section: Variationmentioning

confidence: 98%

“…Of these, 86.3% were SNPs, and 13.7% were InDels. BTA1 contained the highest number of variants (1,689,556), while the BTY contained the lowest number of variants (49,591) ( Figure 2). The total number of SNPs was 23,655,295, 0.9% of the total genome length.…”

Section: Variationmentioning

confidence: 99%

“…Chromosome 1 is the longest bovine chromosome, spanning 158,534,110 bp with 1,218 genes, while chromosome 25 is the shortest bovine chromosome (not much shorter than BTY), spanning 42,350,435 bp with 1,611 genes. BTY contains the lowest number of genes (206), while chromosome 23 contains the highest number of genes (1,708). Clearly, chromosome length is not linearly related to the number of genes.…”

Section: Introductionmentioning

confidence: 99%

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Patterns of DNA variation between the autosomes, the X chromosome and the Y chromosome inBos taurusgenome

Czech

Guldbrandtsen

Szyda

2020

Preprint

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The new ARS-UCD1.2 assembly of the bovine genome has considerable improvements. That might be assumed that a more accurate identification of patterns of genetic variation can be achieved with it. We explored differences in genetic variation between autosomes, the X chromosome, and the Y chromosome. In particular, densities of variants, annotation, lengths (only for InDels), nucleotide divergence, and Tajima's D statistic between chromosomes. Whole-genome DNA sequences of 217 individuals representing different cattle breeds were examined. The analysis included the alignment to the new reference genome and variant calling. 23,655,295 SNPs and 3,758,781 InDels were detected. In contrast to autosomes, both sex chromosomes had negative values of Tajima's D and lower nucleotide divergence. That implies a correlation between nucleotide diversity and recombination rate, which is obviously reduced for sex chromosomes. Moreover, accumulation of nonsynonymous mutations on the Y chromosome could be associated with loss of recombination. Also, the relatively lower effective population size for sex chromosomes leads to a lower expected density of variants. 2/134/13

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Sperm morphometry is affected by increased inbreeding in the Retinta cattle breed: A molecular approach

Teran

Azcona

Ramón

et al. 2021

Molecular Reproduction Devel

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The effect of inbreeding depression on sperm motility is well documented, but its influence on sperm morphometry has been scarcely examined to date. Here, we combined the use of computer‐assisted sperm morphometry analysis (CASMA) with a SNP‐based genomic approach to determine and characterize the effect of inbreeding on the sperm shape of a highly inbred cattle population. We determined seven morphometric parameters on frozen‐thawed sperm samples of 57 Retinta bulls: length (L, µm), width (W, µm), area (A, µm2), perimeter (P, µm), ellipticity (ELI; L/W), elongation (L−W)/(L + W) and perimeter‐to‐area shape factor (p2a; P2/4 × π × A). The comparison of highly inbred (HI) and lowly inbreed (LI) individuals based on runs of homozygosity (ROH) inbreeding values (F ROH) showed no differences between groups. An additional two‐step unsupervised sperm subpopulation analysis based on morphometric parameters showed significant differences in the abundance of different sperm subpopulations between groups (p < 0.05). This analysis revealed that HI bulls harbored a higher percentage of narrow‐head sperm as opposed to the higher percentage of large‐ and round‐headed sperm detected in LI. A further genomic characterization revealed 23 regions differentially affected by inbreeding in both groups, detecting six genes (SPAG6, ARMC3, PARK7, VAMP3, DYNLRB2, and PHF7) previously related to different spermatogenesis‐associated processes.

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De novo assembly of the cattle reference genome with single-molecule sequencing

Cited by 467 publications

References 30 publications

Investigating the accuracy of imputed genotypes in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome

Investigating the accuracy of imputed genotypes in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome

Patterns of DNA variation between the autosomes, the X chromosome and the Y chromosome inBos taurusgenome

Sperm morphometry is affected by increased inbreeding in the Retinta cattle breed: A molecular approach

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