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Yontao Lu

Publications and source records attributed to Yontao Lu.

2 recordsLinked to original sources

Comparative recombination rates in the rat, mouse, and human genomes.

Levels of recombination vary among species, among chromosomes within species, and among regions within chromosomes in mammals. This heterogeneity may affect levels of diversity, efficiency of selection, and genome composition, as well as have practical consequences for the genetic mapping of traits. We compared the genetic maps to the genome sequence assemblies of rat, mouse, and human to estimate local recombination rates across these genomes. Humans have greater overall levels of recombination, as well as greater variance. In rat and mouse, the size of the chromosome and proximity to telomere have less effect on local recombination rate than in human. At the chromosome level, rat and mouse X chromosomes have the lowest recombination rates, whereas human chromosome X does not show the same pattern. In all species, local recombination rate is significantly correlated with several sequence variables, including GC%, CpG density, repetitive elements, and the neutral mutation rate, with some pronounced differences between species. Recombination rate in one species is not strongly correlated with the rate in another, when comparing homologous syntenic blocks of the genome. This comparative approach provides additional insight into the causes and consequences of genomic heterogeneity in recombination.

Animals↗

Analysis of human mRNAs with the reference genome sequence reveals potential errors, polymorphisms, and RNA editing.

The NCBI Reference Sequence (RefSeq) project and the NIH Mammalian Gene Collection (MGC) together define a set of approximately 30,000 nonredundant human mRNA sequences with identified coding regions representing 17,000 distinct loci. These high-quality mRNA sequences allow for the identification of transcribed regions in the human genome sequence, and many researchers accept them as the correct representation of each defined gene sequence. Computational comparison of these mRNA sequences and the recently published essentially finished human genome sequence reveals several thousand undocumented nonsynonymous substitution and frame shift discrepancies between the two resources. Additional analysis is undertaken to verify that the euchromatic human genome is sufficiently complete--containing nearly the whole mRNA collection, thus allowing for a comprehensive analysis to be undertaken. Many of the discrepancies will prove to be genuine polymorphisms in the human population, somatic cell genomic variants, or examples of RNA editing. It is observed that the genome sequence variant has significant additional support from other mRNAs and ESTs, almost four times more often than does the mRNA variant, suggesting that the genome sequence is more accurate. In approximately 15% of these cases, there is substantial support for both variants, suggestive of an undocumented polymorphism. An initial screening against a 24-individual genomic DNA diversity panel verified 60% of a small set of potential single nucleotide polymorphisms from which successful results could be obtained. We also find statistical evidence that a few of these discrepancies are due to RNA editing. Overall, these results suggest that the mRNA collections may contain a substantial number of errors. For current and future mRNA collections, it may be prudent to fully reconcile each genome sequence discrepancy, classifying each as a polymorphism, site of RNA editing or somatic cell variation, or genome sequence error.

Computational Biology↗