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Tang, Haibao

Publications and source records attributed to Tang, Haibao.

Allele-defined genome of the autopolyploid sugarcane Saccharum spontaneum L.

Modern sugarcanes are polyploid interspecific hybrids, combining high sugar content from Saccharum officinarum with hardiness, disease resistance and ratooning of Saccharum spontaneum. Sequencing of a haploid S. spontaneum, AP85-441, facilitated the assembly of 32 pseudo-chromosomes comprising 8 homologous groups of 4 members each, bearing 35,525 genes with alleles defined. The reduction of basic chromosome number from 10 to 8 in S. spontaneum was caused by fissions of 2 ancestral chromosomes followed by translocations to 4 chromosomes. Surprisingly, 80% of nucleotide binding site-encoding genes associated with disease resistance are located in 4 rearranged chromosomes and 51% of those in rearranged regions. Resequencing of 64 S. spontaneum genomes identified balancing selection in rearranged regions, maintaining their diversity. Introgressed S. spontaneum chromosomes in modern sugarcanes are randomly distributed in AP85-441 genome, indicating random recombination among homologs in different S. spontaneum accessions. The allele-defined Saccharum genome offers new knowledge and resources to accelerate sugarcane improvement.

09 BIOMASS FUELS↗

GOATOOLS: A Python library for Gene Ontology analyses

The biological interpretation of gene lists with interesting shared properties, such as up- or downregulation in a particular experiment, is typically accomplished using gene ontology enrichment analysis tools. Given a list of genes, a gene ontology (GO) enrichment analysis may return hundreds of statistically significant GO results in a “fat” list, which can be challenging to summarize. It can also be difficult to keep pace with rapidly expanding biological knowledge, which often results in daily changes to any of the over 47,000 gene ontologies that describe biological knowledge. GOATOOLS, a Python-based library, makes it more efficient to stay current with the latest ontologies and annotations, perform gene ontology enrichment analyses to determine over- and under-represented terms, and organize results for greater clarity and easier interpretation using a novel GOATOOLS GO grouping method. We performed functional analyses on both stochastic simulation data and real data from a published RNA-seq study to compare the enrichment results from GOATOOLS to two other popular tools: DAVID and GOstats. GOATOOLS is freely available through GitHub: https://github.com/ tanghaibao/goatools.

59 BASIC BIOLOGICAL SCIENCES↗