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For transcriptome analysis, it is critical to precisely define all the transcripts across the whole genome. More and more digital gene expression (DGE) scannings have indicated the presence of huge amount of novel transcripts in addition to the known gene models. However, almost all these studies still depend crucially on existing annotation. Here, we present Gene2DGE, a Perl software package for gene model renewal with DGE data. We applied Gene2DGE to the mouse blastomere transcriptome, and defined 98,532 read-enriched regions (RERs) by read clustering supported by more than four reads for each base pair. Taking advantage of this ab initio method, we refined 2,104 exonic regions (4% of a total of 48,501 annotated transcribed regions) with remarkable extension into un-annotated regions (>50bp). For 5% of uniquely mapped reads falling within intron regions, we identified 13,291 additional possible exons. As a result, we renewed 4,788 gene models, which account for 39% of a total of 12,277 transcribed genes. Furthermore, we identified 12,613 intergenic RERs, suggesting the possible presence of novel genes outside the existing gene models. In this study, therefore, we have developed a suitable tool for renewal of known gene models by ab initio prediction in transcriptome dissection. The Gene2DGE package is freely available at http://bighapmap.big.ac.cn/.

The chromosome 17q21.31 inversion is a 900-kb common structural polymorphism found primarily in European population. Although the genetic flux within inversion region was assumed to be considerable suppressed, it is still unclear about the details of genetic exchange between the H1 (non-inverted sequence) and H2 (inverted sequence) haplotypes of this inversion. Here we describe a refined map of genetic exchanges between pairs of gene arrangements within the 17q21.31 region. Using HapMap phase II data of 1,546 single nucleotide polymorphisms, we successfully deduced 96 H1 and 24 H2 haplotypes in European samples by neighbor-joining tree reconstruction. Furthermore, we identified 15 and 26 candidate tracts with reciprocal and non-reciprocal genetic exchanges, respectively. In all 15 regions harboring reciprocal exchange, haplotypes reconstructed by clone sequencing did not support these exchange events, suggesting that such signals of exchange between two sister chromosomes in certain heterozygous individual were caused by phasing error regions. On the other hand, the finished clone sequencing across 4 of 26 tracts with non-reciprocal genetic flux confirmed that this kind of genetic exchange was caused by gene conversion. In summary, as crossover between pairs of gene arrangements had been considerably suppressed, gene conversion might be the most important mechanism for genetic exchange at 17q21.31.

Population genomic approaches, which take advantages of high-throughput genotyping, are powerful yet costly methods to scan for selective sweeps. DNA-pooling strategies have been widely used for association studies because it is a cost-effective alternative to large-scale individual genotyping. Here, we performed an SNP-MaP (single nucleotide polymorphism microarrays and pooling) analysis using samples from Eurasia to evaluate the efficiency of pooling strategy in genome-wide scans for selection. By conducting simulations of allelotype data, we first demonstrated that the boxplot with average heterozygosity (HET) is a promising method to detect strong selective sweeps with a moderate level of pooling error. Based on this, we used a sliding window analysis of HET to detect the large contiguous regions (LCRs) putatively under selective sweeps from Eurasia datasets. This survey identified 63 LCRs in a European population. These signals were further supported by the integrated haplotype score (iHS) test using HapMap II data. We also confirmed the European-specific signatures of positive selection from several previously identified genes (KEL, TRPV5, TRPV6, EPHB6). In summary, our results not only revealed the high credibility of SNP-MaP strategy in scanning for selective sweeps, but also provided an insight into the population differentiation.