Next-generation sequencing technologies rely on high quality DNA that is suitable for library preparation followed by sequencing. Some plant species store large amounts of phenolics and polysaccharides within their leaf tissue making genomic DNA extraction difficult. While many DNA extraction methods exist that contend with the presence of phenolics and polysaccharides, these methods rely on long incubations, multiple precipitations or commercially available kits to produce high molecular weight and contaminant-free DNA. In this protocol, we describe simple modifications to the established CTAB- based extraction method that allows for reliable isolation of high molecular weight genomic DNA from difficult to isolate plant species Corymbia (a eucalypt) and Coffea (coffee). The simplified protocol does not require multiple clean up steps or commercial based kits, and the isolated DNA passed stringent quality control standards for whole genome sequencing on Illumina HiSeq and TruSeq sequencing platforms.

Summary: Plant breeders require access to new genetic diversity to satisfy the demands of a growing human population for more food that can be produced in a variable or changing climate and to deliver the high‐quality food with nutritional and health benefits demanded by consumers. The close relatives of domesticated plants, crop wild relatives (CWRs), represent a practical gene pool for use by plant breeders. Genomics of CWR generates data that support the use of CWR to expand the genetic diversity of crop plants. Advances in DNA sequencing technology are enabling the efficient sequencing of CWR and their increased use in crop improvement. As the sequencing of genomes of major crop species is completed, attention has shifted to analysis of the wider gene pool of major crops including CWR. A combination of de novo sequencing and resequencing is required to efficiently explore useful genetic variation in CWR. Analysis of the nuclear genome, transcriptome and maternal (chloroplast and mitochondrial) genome of CWR is facilitating their use in crop improvement. Genome analysis results in discovery of useful alleles in CWR and identification of regions of the genome in which diversity has been lost in domestication bottlenecks. Targeting of high priority CWR for sequencing will maximize the contribution of genome sequencing of CWR. Coordination of global efforts to apply genomics has the potential to accelerate access to and conservation of the biodiversity essential to the sustainability of agriculture and food production.

Sugarcane, the world’s most harvested crop by tonnage, has shaped global history, trade and geopolitics, and is currently responsible for 80% of sugar production worldwide¹. While traditional sugarcane breeding methods have effectively generated cultivars adapted to new environments and pathogens, sugar yield improvements have recently plateaued². The cessation of yield gains may be due to limited genetic diversity within breeding populations, long breeding cycles and the complexity of its genome, the latter preventing breeders from taking advantage of the recent explosion of whole-genome sequencing that has benefited many other crops. Thus, modern sugarcane hybrids are the last remaining major crop without a reference-quality genome. Here we take a major step towards advancing sugarcane biotechnology by generating a polyploid reference genome for R570, a typical modern cultivar derived from interspecific hybridization between the domesticated species (Saccharum officinarum) and the wild species (Saccharum spontaneum). In contrast to the existing single haplotype (‘monoploid’) representation of R570, our 8.7 billion base assembly contains a complete representation of unique DNA sequences across the approximately 12 chromosome copies in this polyploid genome. Using this highly contiguous genome assembly, we filled a previously unsized gap within an R570 physical genetic map to describe the likely causal genes underlying the single-copy Bru1 brown rust resistance locus. This polyploid genome assembly with fine-grain descriptions of genome architecture and molecular targets for biotechnology will help accelerate molecular and transgenic breeding and adaptation of sugarcane to future environmental conditions.

BackgroundCoffee is one of the most valuable commodities exported worldwide. Greater understanding of the molecular basis of coffee quality is required to meet the increasing demands of consumers. Genotype and environment (G and E) have been shown to influence coffee quality. Analysis of coffee metabolism, the genes governing the accumulation of key components and the influence of environment on their expression during seed development supports the identification of the molecular determinants of coffee quality.Scope and approachThe metabolism of important biochemical components of the coffee bean: caffeine, trigonelline, chlorogenic acids sucrose and lipids in coffee was reviewed. Analysis focused on how coffee metabolism was regulated by G and E throughout seed development and evaluation of transcriptome studies as an effective tool for use in understanding this system.Key findings and conclusionsAn overview of metabolism of the key components of coffee identified critical metabolic steps regulating the final concentration of metabolites that determine coffee quality. Coffee metabolism is influenced by both G and E and explains the higher quality of Arabica when compared to Robusta as well as the improvement of coffee quality by shade. Interaction of G and E (G × E) also contributes to quality. However, coffee metabolism is still not fully understood and there is scope for further studies to explain the contributions of G, E and G X E

Despite the economic importance of sugarcane in sugar and bioenergy production, there is not yet a reference genome available. Most of the sugarcane transcriptomic studies have been based on Saccharum officinarum gene indices (SoGI), expressed sequence tags (ESTs) and de novo assembled transcript contigs from short-reads; hence knowledge of the sugarcane transcriptome is limited in relation to transcript length and number of transcript isoforms. The sugarcane transcriptome was sequenced using PacBio isoform sequencing (Iso-Seq) of a pooled RNA sample derived from leaf, internode and root tissues, of different developmental stages, from 22 varieties, to explore the potential for capturing full-length transcript isoforms. A total of 107,598 unique transcript isoforms were obtained, representing about 71% of the total number of predicted sugarcane genes. The majority of this dataset (92%) matched the plant protein database, while just over 2% was novel transcripts, and over 2% was putative long non-coding RNAs. About 56% and 23% of total sequences were annotated against the gene ontology and KEGG pathway databases, respectively. Comparison with de novo contigs from Illumina RNA-Sequencing (RNA-Seq) of the internode samples from the same experiment and public databases showed that the Iso-Seq method recovered more full-length transcript isoforms, had a higher N50 and average length of largest 1,000 proteins; whereas a greater representation of the gene content and RNA diversity was captured in RNA-Seq. Only 62% of PacBio transcript isoforms matched 67% of de novo contigs, while the non-matched proportions were attributed to the inclusion of leaf/root tissues and the normalization in PacBio, and the representation of more gene content and RNA classes in the de novo assembly, respectively. About 69% of PacBio transcript isoforms and 41% of de novo contigs aligned with the sorghum genome, indicating the high conservation of orthologs in the genic regions of the two genomes. The transcriptome dataset should contribute to improved sugarcane gene models and sugarcane protein predictions; and will serve as a reference database for analysis of transcript expression in sugarcane.

Rice is the most important crop in the world, acting as the staple food for over half of the world’s population. The evolutionary relationships of cultivated rice and its wild relatives have remained contentious and inconclusive. Here we report on the use of whole chloroplast sequences to elucidate the evolutionary and phylogenetic relationships in the AA genomeOryzaspecies, representing the primary gene pool of rice. This is the first study that has produced a well resolved and strongly supported phylogeny of the AA genome species. The pan tropical distribution of these rice relatives was found to be explained by long distance dispersal within the last million years. The analysis resulted in a clustering pattern that showed strong geographical differentiation. The species were defined in two primary clades with a South American/African clade with two species,O glumaepatula and O longistaminata, distinguished from all other species. The largest clade was comprised of an Australian clade including newly identified taxa and the African and Asian clades. This refined knowledge of the relationships between cultivated rice and the related wild species provides a strong foundation for more targeted use of wild genetic resources in rice improvement and efforts to ensure their conservation.