Differences between the genomes of lymphoblastoid cell lines and blood-derived samples

Joesch-Cohen, Lena M.; Glusman, Gustavo

doi:10.2147/agg.s128824

Cited by 10 publications

(12 citation statements)

References 27 publications

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“…S8, Table S1). The difference in mtDNA copy number seen between the two cell lines is consistent with previous observations that LCLs are known to carry significantly higher mtDNA copy numbers than PBMCs 77-79 . Because annotation for the source DNA is not available for all samples (Table S1), we plotted the density of mtDNA copy number calculated from the low-coverage alignments and observed a clear separation between samples sequenced from PBMCs and LCLs (Fig.…”

Section: Methodssupporting

confidence: 91%

Investigating mitonuclear interactions in human admixed populations

Zaidi

Makova

2019

Nat Ecol Evol

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To function properly, mitochondria utilize products of 37 mitochondrial and >1,000 nuclear genes, which should be compatible with each other. Discordance between mitochondrial and nuclear genetic ancestry could contribute to phenotypic variation in admixed populations. Here we explored potential mito-nuclear incompatibility in six admixed human populations from the Americas: African Americans, African Caribbeans, Colombians, Mexicans, Peruvians, and Puerto Ricans. By comparing nuclear vs. mitochondrial ancestry in these populations, we first show that mtDNA copy number decreases with increasing discordance between nuclear and mitochondrial DNA ancestry. The direction of this effect is consistent across mtDNA haplogroups of different geographic origins. This observation suggests suboptimal regulation of mtDNA replication when its components are encoded by nuclear and mtDNA genes with different ancestry. Second, while most populations analyzed exhibit no such trend, in African Americans and Puerto Ricans, we find a significant enrichment of ancestry at nuclear-encoded mitochondrial genes towards the source populations contributing the most prevalent mtDNA haplogroups (African and Native American, respectively). This possibly reflects compensatory effects of selection in recovering mito-nuclear interactions optimized in the source populations. Our results provide evidence of mito-nuclear interactions in human admixed populations and we discuss their implications for human health and disease.

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Section: Methodssupporting

confidence: 91%

Investigating mitonuclear interactions in human admixed populations

Zaidi

Makova

2019

Nat Ecol Evol

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“…S1, Table S1). The difference in mtDNA copy number seen between the two cell lines is consistent with previous observations that LCLs are known to carry significantly higher mtDNA copy numbers than PBMCs [52][53][54] . Because annotation for the source DNA is not available for all samples (Table S1), we plotted the density of mtDNA copy number calculated from the low-coverage alignments and observed a clear separation between samples sequenced from PBMCs and LCLs (Fig.…”

Section: Materials and Methods Mtdna Copy Number Estimationsupporting

confidence: 91%

Mito-nuclear effects uncovered in admixed populations

Zaidi

Makova

2018

Preprint

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To function properly, mitochondria utilize products of 37 and >1,000 genes encoded by the mitochondrial and nuclear genomes, respectively, which should be compatible with each other. Discordance between mitochondrial and nuclear genetic ancestry could contribute to phenotypic variation in admixed populations. Here we explored potential mito-nuclear incompatibility in six admixed human populations from the Americas: African Americans, African Caribbeans, Colombians, Mexicans, Peruvians, and Puerto Ricans. For individuals in these populations, we determined nuclear genome proportions derived from Africans, Europeans, and Native Americans, the geographic origins of the mitochondrial DNA (mtDNA), as well as mtDNA copy number in lymphoblastoid cell lines. By comparing nuclear vs. mitochondrial ancestry in admixed populations, we show that, first, mtDNA copy number decreases with increasing discordance between nuclear and mitochondrial DNA ancestry, in agreement with mito-nuclear incompatibility. The direction of this effect is consistent across mtDNA haplogroups of different geographic origins. This observation suggests suboptimal regulation of mtDNA replication when its components are encoded by nuclear and mtDNA genes with different ancestry. Second, while most populations analyzed exhibit no such trend, in Puerto Ricans and African Americans we find a significant enrichment of ancestry at nuclear-encoded mitochondrial genes towards the source populations contributing the most prevalent mtDNA haplogroups (Native American and African, respectively). This likely reflects compensatory effects of selection in recovering mito-nuclear interactions optimized in the source populations. Our results provide the first evidence of mito-nuclear effects in human admixed populations and we discuss its implications for human health and disease.

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“…The lower precision of LCL samples may be due to the accumulation of de novo mutations over repeated cell passages, however it is unclear why this would occur primarily in low-complexity regions and not throughout the entire genome. Differences in the distribution of sequencing depth across the genome, observed between LCL and whole blood -derived samples [ 23 ], may also contribute to differences in variant calling performance. Overall, these results suggest that the LCL samples from the iHART dataset are faithful representations of the DNA of their donors, particularly if low-complexity regions of the genome are excluded.…”

Section: Resultsmentioning

confidence: 99%

Estimating sequencing error rates using families

et al. 2021

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Background As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-calling pipelines are continuously evolving, making it difficult to accurately quantify error rates for the particular combination of assay and software parameters used on each sample. Family data provide a unique opportunity for estimating sequencing error rates since it allows us to observe a fraction of sequencing errors as Mendelian errors in the family, which we can then use to produce genome-wide error estimates for each sample. Results We introduce a method that uses Mendelian errors in sequencing data to make highly granular per-sample estimates of precision and recall for any set of variant calls, regardless of sequencing platform or calling methodology. We validate the accuracy of our estimates using monozygotic twins, and we use a set of monozygotic quadruplets to show that our predictions closely match the consensus method. We demonstrate our method’s versatility by estimating sequencing error rates for whole genome sequencing, whole exome sequencing, and microarray datasets, and we highlight its sensitivity by quantifying performance increases between different versions of the GATK variant-calling pipeline. We then use our method to demonstrate that: 1) Sequencing error rates between samples in the same dataset can vary by over an order of magnitude. 2) Variant calling performance decreases substantially in low-complexity regions of the genome. 3) Variant calling performance in whole exome sequencing data decreases with distance from the nearest target region. 4) Variant calls from lymphoblastoid cell lines can be as accurate as those from whole blood. 5) Whole-genome sequencing can attain microarray-level precision and recall at disease-associated SNV sites. Conclusion Genotype datasets from families are powerful resources that can be used to make fine-grained estimates of sequencing error for any sequencing platform and variant-calling methodology.

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Differences between the genomes of lymphoblastoid cell lines and blood-derived samples

Cited by 10 publications

References 27 publications

Investigating mitonuclear interactions in human admixed populations

Investigating mitonuclear interactions in human admixed populations

Mito-nuclear effects uncovered in admixed populations

Estimating sequencing error rates using families

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