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Identification of errors introduced during high throughput sequencing of the T cell receptor repertoire.

Nguyen P, Ma J, Pei D, Obert C, Cheng C, Geiger TL - BMC Genomics (2011)

Bottom Line: Filtering for lower quality sequences diminished but did not eliminate sequence errors, which occurred within 1-6% of sequences.Caution is needed in interpreting repertoire data due to potential contamination with mis-sequence reads.However, a high association of errors with phred score, high relatedness of erroneous sequences with the parental sequence, dominance of specific nt substitutions, and skewed ratio of forward to reverse reads among erroneous sequences indicate approaches to filter erroneous sequences from repertoire data sets.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Pathology, St, Jude Children's Research Hospital, 262 Danny Thomas Pl., Memphis, TN 38105, USA.

ABSTRACT

Background: Recent advances in massively parallel sequencing have increased the depth at which T cell receptor (TCR) repertoires can be probed by >3log10, allowing for saturation sequencing of immune repertoires. The resolution of this sequencing is dependent on its accuracy, and direct assessments of the errors formed during high throughput repertoire analyses are limited.

Results: We analyzed 3 monoclonal TCR from TCR transgenic, Rag-/- mice using Illumina® sequencing. A total of 27 sequencing reactions were performed for each TCR using a trifurcating design in which samples were divided into 3 at significant processing junctures. More than 20 million complementarity determining region (CDR) 3 sequences were analyzed. Filtering for lower quality sequences diminished but did not eliminate sequence errors, which occurred within 1-6% of sequences. Erroneous sequences were pre-dominantly of correct length and contained single nucleotide substitutions. Rates of specific substitutions varied dramatically in a position-dependent manner. Four substitutions, all purine-pyrimidine transversions, predominated. Solid phase amplification and sequencing rather than liquid sample amplification and preparation appeared to be the primary sources of error. Analysis of polyclonal repertoires demonstrated the impact of error accumulation on data parameters.

Conclusions: Caution is needed in interpreting repertoire data due to potential contamination with mis-sequence reads. However, a high association of errors with phred score, high relatedness of erroneous sequences with the parental sequence, dominance of specific nt substitutions, and skewed ratio of forward to reverse reads among erroneous sequences indicate approaches to filter erroneous sequences from repertoire data sets.

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Multiple errors in CDR3 sequences. Plot shows mean+1 s.d. of the frequency of correct-length erroneous sequences with the indicated number of nt substitutions as a percent of the total correct-length erroneous sequences for the 5C.C7 (A), OT-1 (B), and DO11.10 TCR, and with phred cutoff scores of 0 or 30.
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Figure 3: Multiple errors in CDR3 sequences. Plot shows mean+1 s.d. of the frequency of correct-length erroneous sequences with the indicated number of nt substitutions as a percent of the total correct-length erroneous sequences for the 5C.C7 (A), OT-1 (B), and DO11.10 TCR, and with phred cutoff scores of 0 or 30.

Mentions: Virtually all of the erroneous sequences were of the correct length, and this comprised >99% of the error population acquired either with a q = 0 or 30. Most of the remaining sequences were truncated (Figure 2a-c). Among erroneous sequences of correct length that were not filtered based on phred score, an average of 79%, 88%, and 88% for 5C.C7, OT-1, and DO11.10 had a single error, with progressively decreasing frequency of sequences with greater numbers of errors (Figure 3a-c). Increasing the q value to 30 increased the percent of erroneous sequences with single nt replacements to >98% for each of the TCR.


Identification of errors introduced during high throughput sequencing of the T cell receptor repertoire.

Nguyen P, Ma J, Pei D, Obert C, Cheng C, Geiger TL - BMC Genomics (2011)

Multiple errors in CDR3 sequences. Plot shows mean+1 s.d. of the frequency of correct-length erroneous sequences with the indicated number of nt substitutions as a percent of the total correct-length erroneous sequences for the 5C.C7 (A), OT-1 (B), and DO11.10 TCR, and with phred cutoff scores of 0 or 30.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3045962&req=5

Figure 3: Multiple errors in CDR3 sequences. Plot shows mean+1 s.d. of the frequency of correct-length erroneous sequences with the indicated number of nt substitutions as a percent of the total correct-length erroneous sequences for the 5C.C7 (A), OT-1 (B), and DO11.10 TCR, and with phred cutoff scores of 0 or 30.
Mentions: Virtually all of the erroneous sequences were of the correct length, and this comprised >99% of the error population acquired either with a q = 0 or 30. Most of the remaining sequences were truncated (Figure 2a-c). Among erroneous sequences of correct length that were not filtered based on phred score, an average of 79%, 88%, and 88% for 5C.C7, OT-1, and DO11.10 had a single error, with progressively decreasing frequency of sequences with greater numbers of errors (Figure 3a-c). Increasing the q value to 30 increased the percent of erroneous sequences with single nt replacements to >98% for each of the TCR.

Bottom Line: Filtering for lower quality sequences diminished but did not eliminate sequence errors, which occurred within 1-6% of sequences.Caution is needed in interpreting repertoire data due to potential contamination with mis-sequence reads.However, a high association of errors with phred score, high relatedness of erroneous sequences with the parental sequence, dominance of specific nt substitutions, and skewed ratio of forward to reverse reads among erroneous sequences indicate approaches to filter erroneous sequences from repertoire data sets.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Pathology, St, Jude Children's Research Hospital, 262 Danny Thomas Pl., Memphis, TN 38105, USA.

ABSTRACT

Background: Recent advances in massively parallel sequencing have increased the depth at which T cell receptor (TCR) repertoires can be probed by >3log10, allowing for saturation sequencing of immune repertoires. The resolution of this sequencing is dependent on its accuracy, and direct assessments of the errors formed during high throughput repertoire analyses are limited.

Results: We analyzed 3 monoclonal TCR from TCR transgenic, Rag-/- mice using Illumina® sequencing. A total of 27 sequencing reactions were performed for each TCR using a trifurcating design in which samples were divided into 3 at significant processing junctures. More than 20 million complementarity determining region (CDR) 3 sequences were analyzed. Filtering for lower quality sequences diminished but did not eliminate sequence errors, which occurred within 1-6% of sequences. Erroneous sequences were pre-dominantly of correct length and contained single nucleotide substitutions. Rates of specific substitutions varied dramatically in a position-dependent manner. Four substitutions, all purine-pyrimidine transversions, predominated. Solid phase amplification and sequencing rather than liquid sample amplification and preparation appeared to be the primary sources of error. Analysis of polyclonal repertoires demonstrated the impact of error accumulation on data parameters.

Conclusions: Caution is needed in interpreting repertoire data due to potential contamination with mis-sequence reads. However, a high association of errors with phred score, high relatedness of erroneous sequences with the parental sequence, dominance of specific nt substitutions, and skewed ratio of forward to reverse reads among erroneous sequences indicate approaches to filter erroneous sequences from repertoire data sets.

Show MeSH