Biology subjects

Peng Zhang

Publications and source records attributed to Peng Zhang.

3 recordsLinked to original sources

bioRxiv2016

The haplotype-resolved genome sequence of hexaploid Ipomoea batatas reveals its evolutionary history

Although the sweet potato, Ipomoea batatas, is the seventh most important crop in the world and the fourth most significant in China, its genome has not yet been sequenced. The reason, at least in part, is that the genome has proven very difficult to assemble, being hexaploid and highly polymorphic; it has a presumptive composition of two B1 and four B2 component genomes (B1B1B2B2B2B2). By using a novel haplotyping method based on de novo genome assembly, however, we have produced a half haplotype-resolved genome from [~]267Gb of paired-end sequence reads amounting to roughly 60-fold coverage. By phylogenetic tree analysis of homologous chromosomes, it was possible to estimate the time of two whole genome duplication events as occurring about 525,000 and 341,000 years ago. Our analysis also identified many clusters of genes for specialized compounds biosynthesis in this genome. This half haplotype-resolved hexaploid genome represents the first successful attempt to investigate the complexity of chromosome sequence composition directly in a polyploid genome, using direct sequencing of the polyploid organism itself rather than of any of its simplified proxy relatives. Adaptation and application of our approach should provide higher resolution in future genomic structure investigations, especially for similarly complex genomes.

Genomics↗

bioRxiv2016

Omics Discovery Index - Discovering and Linking Public Omics Datasets

Biomedical data, in particular omics datasets are being generated at an unprecedented rate. This is due to the falling costs of generating experimental data, improved accuracy and better accessibility to different omics platforms such as genomics, proteomics and metabolomics1,2. As a result, the number of deposited datasets in public repositories originating from various omics approaches has increased dramatically in recent years. With strong support from scientific journals and funders, public data sharing is increasingly considered to be a good scientific practice, facilitating the confirmation of original results, increasing the reproducibility of the analyses, enabling the exploration of new or related hypotheses, and fostering the identification of potential errors, discouraging fraud3. This increase in public data deposition of omics results is a good starting point, but opens up a series of new challenges. For example the research community must now find more efficient ways for storing, organizing and providing access to biomedical data across platforms. These challenges range from achieving a common representation framework for the datasets and the associated metadata from different omics fields, to the availability of efficient methods, protocols and file formats for data exchange between multiple repositories. Therefore, there is a great need for development of new platforms and applications to make possible to search datasets across different omics fields, making such information accessible to the end-user. The FAIR paradigm describes a set of guiding principles to address many of these issues, and aims to make data Findable, Accessible, Interoperable and Re-usable(https://www.force11.org/group/fairgroup/fairprinciples).

Bioinformatics↗

bioRxiv2015

Choosing subsamples for sequencing studies by minimizing the average distance to the closest leaf

AO_SCPCAPBSTRACTC_SCPCAPImputation of genotypes in a study sample can make use of sequenced or densely genotyped external reference panels consisting of individuals that are not from the study sample. It can also employ internal reference panels, incorporating a subset of individuals from the study sample itself. Internal panels offer an advantage over external panels, as they can reduce imputation errors arising from genetic dissimilarity between a population of interest and a second, distinct population from which the external reference panel has been constructed. As the cost of next-generation sequencing decreases, internal reference panel selection is becoming increasingly feasible. However, it is not clear how best to select individuals to include in such panels. We introduce a new method for selecting an internal reference panel--minimizing the average distance to the closest leaf (ADCL)--and compare its performance relative to an earlier algorithm: maximizing phylogenetic diversity (PD). Employing both simulated data and sequences from the 1000 Genomes Project, we show that ADCL provides a significant improvement in imputation accuracy, especially for imputation of sites with low-frequency alleles. This improvement in imputation accuracy is robust to changes in reference panel size, marker density, and length of the imputation target region.

Bioinformatics↗