Towards the Human Cancer Genome Project: A Sequence-Ready Physical Map of a Follicular Lymphoma Genome.
Bibliographic record
Abstract
Abstract With the aim of identifying and sequencing mutations in follicular lymphoma genomes, we have begun a project to generate at least 24 deeply redundant sequence-ready Bacterial Artificial Clone (BAC) - based whole genome maps, each from a different individual’s lymphoma. BAC-array CGH and Affymetrix whole-genome sampling assays (WGSA) will be used along with the mapping data to identify genomic amplifications and losses in the lymphomas. Results from the mapping and array studies will be used to prioritize BAC clones for sequence analysis. Because each map will span essentially the entire genome of the corresponding lymphoma, we anticipate that essentially all regions of each tumor genome will be represented in easily sequenced BAC clones. This approach facilitates targeted sequencing of genomic regions of interest, including those containing genes relevant to cancer or harboring amplifications or deletions. Our mapping strategy hinges on the successful creation of deeply redundant high quality BAC libraries from primary lymphomas and large scale high throughput restriction enzyme fingerprinting of individual BACs with a version of the technology we used to map the human, mouse, rat and other genomes. The effort is large-scale, and will result in the generation of at least 2.5 million fingerprinted BAC clones over the next three years. Using the fingerprints, we will align the BACs to the reference human genome to assess genome coverage and to identify candidate genome rearrangements. In parallel, we will assemble the fingerprints into genome maps, looking for larger-scale genome variations between the lymphoma maps and the reference genome sequence. To test the feasibility of our approach, we obtained two restriction digest fingerprints from each of 140,000 individual BAC clones. BACs were sampled from a 7-fold redundant BAC library that had been created from genomic DNA purified from a primary follicular lymphoma sample. The fingerprints are being assembled into a clone map with the intent of reconstructing the entire tumor genome. 90,377 fingerprinted clones with unambiguous single alignments to the reference sequence were automatically assembled into 15,538 contigs. Subsequent rounds of semi-automatic contig merging further reduced the number of contigs to 5,433. Only 1,241 clones remained unassembled. We anchored the tumor genome map to the reference human genome sequence by aligning the clone fingerprints to the restriction map computed from the reference sequence assembly. As a result of this, we identified a BAC that captured the canonical t(14;18) translocation characteristic of follicular lymphomas. We sequenced this BAC and confirmed that it contains the expected translocation. Almost 2.6 gigabases (~91%) of the reference genome are represented in the evolving map, with an additional 50,000 clone fingerprints awaiting incorporation into the map assembly. Among these are repeat-rich and other clones that may well harbor genome rearrangements. Additional prioritization of sequencing targets will be undertaken when map construction and analysis of genome copy number alterations are complete.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".