Toward a Kinh Vietnamese Reference Genome: Constructing a De Novo Genome Assembly Using Long-Read Sequencing and Optical Mapping
Bibliographic record
Abstract
Background: Population-specific reference genomes are essential for improving the accuracy and reliability of genomic analyses across diverse human populations. Although Vietnam ranks as the 16th most populous country in the world, with more than 86% of its population identifying as Kinh, studies specifically focusing on the Kinh Vietnamese reference genome remain scarce. Therefore, constructing a Kinh Vietnamese reference genome is valuable in the genetic research of Vietnamese. Methods: In this study, we combined PacBio long-read sequencing and Bionano optical mapping data to generate a de novo assembly of a Kinh Vietnamese genome (VHG), which was subsequently polished using multiple Kinh Vietnamese short-read whole-genome sequences (WGSs). Results: The final assembly, named VHG1.2, comprised 3.22 gigabase pairs of high-quality sequence data, demonstrating high accuracy (QV: 48), completeness (BUSCO: 92%), and continuity (295 super scaffolds, super scaffold N50: 50 Kbp). Using multiple bioinformatic tools for variant calling, we observed significant variants when the population-specific reference VHG1.2 was used compared to the standard reference genome hg38. Conclusions: Overall, our genome assembly demonstrates the advantages of a long-read hybrid sequencing approach for de novo assembly and highlights the benefit of using population-specific reference genomes in population genomic analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".