TheSorghum bicolorreference genome: improved assembly and annotations, a transcriptome atlas, and signatures of genome organization

Abstract

2ABSTRACTSorghum bicolor is a drought tolerant C4 grass used for production of grain, forage, sugar, and lignocellulosic biomass and a genetic model for C4 grasses due to its relatively small genome (~800 Mbp), diploid genetics, diverse germplasm, and colinearity with other C4 grass genomes. In this study, deep sequencing, genetic linkage analysis, and transcriptome data were used to produce and annotate a high quality reference genome sequence. Reference genome sequence order was improved, 29.6 Mbp of additional sequence was incorporated, the number of genes annotated increased 24% to 34,211, average gene length and N50 increased, and error frequency was reduced 10-fold to 1 per 100 kbp. Sub-telomeric repeats with characteristics of Tandem Repeats In Miniature (TRIM) elements were identified at the termini of most chromosomes. Nucleosome occupancy predictions identified nucleosomes positioned immediately downstream of transcription start sites and at different densities across chromosomes. Alignment of the reference genome sequence to 56 resequenced genomes from diverse sorghum genotypes identified ~7.4M SNPs and 1.8M indels. Large scale variant features in euchromatin were identified with periodicities of ~25 kbp. An RNA transcriptome atlas of gene expression was constructed from 47 samples derived from growing and developed tissues of the major plant organs (roots, leaves, stems, panicles, seed) collected during the juvenile, vegetative and reproductive phases. Analysis of the transcriptome data indicated that tissue type and protein kinase expression had large influences on transcriptional profile clustering. The updated assembly, annotation, and transcriptome data represent a resource for C4 grass research and crop improvement.

STAG-CNS: An Order-Aware Conserved Noncoding Sequences Discovery Tool for Arbitrary Numbers of Species

“…The genomes and annotations of seven related species were downloaded from Phytozome (https://phytozome.jgi.doe.gov/pz/portal.html): sorghum (Sorghum bicolor v3.1) (McCormick et al, 2017), rice (Oryza sativa v7) (Ouyang et al, 2007), setaria (Setaria italica v2.2) (Bennetzen et al, 2012), brachypodium (Brachypodium distachyon v3.1) (Vogel et al, 2010), maize (Zea mays) (Schnable et al, 2009); and CoGe (https:// genomevolution.org/coge/): oropetium (Oropetium thomaeum v1.0) (VanBuren et al, 2015) and dichanthelium (Dichanthelium oligosanthes v1.001) (Studer et al, 2016). A pan-grass orthologous gene list including all of these seven species generated on the GEvo panel of CoGe is available (https://genomevolution.org/coge/Gevo.pl) (Schnable et al, 2016).…”

Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum using Multiscale Phenotypes

“…Sorghum meets these conditions as it exhibits great diversity in these carbon-partitioning regimes [30], and the sorghum types are further classified based on these traits as cellulosic, forage, grain, or sweet [29]. Sorghum not only meets the requirements as an advanced biofuel feedstock but is capable of rapidly accumulating significant quantities of non-structural [31] and structural carbohydrates [22,32,33] necessary for biofuel [28], forage [34], and grain production [35]. As such, sorghum represents an excellent system for the study of carbon accumulation, partitioning, and designing [29].…”

Wavelet-Based Genomic Signal Processing for Centromere Identification and Hypothesis Generation

“…These different scales of peaks contain different information. Thus, techniques to analyse these signals at different scales are valuable (see Spencer et al, 2006; McCormick et al, 2017). The Wavelet Transform, a signal processing technique, can be used to unpack the information in different scales of a signal, such as a density profile across a chromosome (Spencer et al, 2006).…”