Explore the vast range of titles available.

Resequencing of 302 soybean accessions and GWAS provide a comprehensive resource for soybean geneticists and breeders. Understanding soybean ( Glycine max ) domestication and improvement at a genetic level is important to inform future efforts to further improve a crop that provides the world's main source of oilseed. We detect 230 selective sweeps and 162 selected copy number variants by analysis of 302 resequenced wild, landrace and improved soybean accessions at >11× depth. A genome-wide association study using these new sequences reveals associations between 10 selected regions and 9 domestication or improvement traits, and identifies 13 previously uncharacterized loci for agronomic traits including oil content, plant height and pubescence form. Combined with previous quantitative trait loci (QTL) information, we find that, of the 230 selected regions, 96 correlate with reported oil QTLs and 21 contain fatty acid biosynthesis genes. Moreover, we observe that some traits and loci are associated with geographical regions, which shows that soybean populations are structured geographically. This study provides resources for genomics-enabled improvements in soybean breeding.

The genome of the cellulase-producing fungus Talaromyces cellulolyticus (formerly Acremonium cellulolyticus) was screened for a potent DNA ligase IV gene (ligD homologue). Homologous recombination efficiency in T. cellulolyticus is very low. Therefore, suppression of a non-homologous end-joining system was attempted to enable specific gene knockouts for molecular breeding. The transcript levels of ligD homologue were 0.037 of those of the parental YP-4 strain in the Li20 transformant carrying the RNAi construct targeting the ligD homologue. Transformation of the hairpin-type RNAi vector into T. cellulolyticus could be useful in fungal gene knockdown experiments. Cellulase production and protein secretion were similar in the parental YP-4 strain and the Li20 transformant. Knockout transformation of ligD homologue using the Li20 transformant led to 23.1 % double crossover gene targeting. Our results suggest that the potent DNA ligase IV gene of T. cellulolyticus is related to non-homologous end joining and that the knockdown of the ligD homologue is useful in gene targeting.

Lipid production in the oleaginous microalga Nannocholoropsis gaditana is doubled by decreasing the expression of a transcriptional regulator identified through a CRISPR–Cas9 reverse-genetics approach. Lipid production in the industrial microalga Nannochloropsis gaditana exceeds that of model algal species and can be maximized by nutrient starvation in batch culture. However, starvation halts growth, thereby decreasing productivity. Efforts to engineer N. gaditana strains that can accumulate biomass and overproduce lipids have previously met with little success. We identified 20 transcription factors as putative negative regulators of lipid production by using RNA-seq analysis of N. gaditana during nitrogen deprivation. Application of a CRISPR–Cas9 reverse-genetics pipeline enabled insertional mutagenesis of 18 of these 20 transcription factors. Knocking out a homolog of fungal Zn( II ) 2 Cys 6 -encoding genes improved partitioning of total carbon to lipids from 20% (wild type) to 40–55% (mutant) in nutrient-replete conditions. Knockout mutants grew poorly, but attenuation of Zn( II ) 2 Cys 6 expression yielded strains producing twice as much lipid (∼5.0 g m −2 d −1 ) as that in the wild type (∼2.5 g m −2 d −1 ) under semicontinuous growth conditions and had little effect on growth.

Ten general strategies for the development of industrial microbial strains, together with selected case studies, are discussed. Industrial strain development requires system-wide engineering and optimization of cellular metabolism while considering industrially relevant fermentation and recovery processes. It can be conceptualized as several strategies, which may be implemented in an iterative fashion and in different orders. The key challenges have been the time-, cost- and labor-intensive processes of strain development owing to the difficulties in understanding complex interactions among the metabolic, gene regulatory and signaling networks at the cell level, which are collectively represented as overall system performance under industrial fermentation conditions. These challenges can be overcome by taking systems approaches through the use of state-of-the-art tools of systems biology, synthetic biology and evolutionary engineering in the context of industrial bioprocess. Major systems metabolic engineering achievements in recent years include microbial production of amino acids ( L -valine, L -threonine, L -lysine and L -arginine), bulk chemicals (1,4-butanediol, 1,4-diaminobutane, 1,5-diaminopentane, 1,3-propanediol, butanol, isobutanol and succinic acid) and drugs (artemisinin).

Dividing a metabolic pathway between yeast and Escherichia coli enables synthesis of a small molecule. Metabolic engineering of microorganisms such as Escherichia coli and Saccharomyces cerevisiae to produce high-value natural metabolites is often done through functional reconstitution of long metabolic pathways. Problems arise when parts of pathways require specialized environments or compartments for optimal function. Here we solve this problem through co-culture of engineered organisms, each of which contains the part of the pathway that it is best suited to hosting. In one example, we divided the synthetic pathway for the acetylated diol paclitaxel precursor into two modules, expressed in either S. cerevisiae or E. coli , neither of which can produce the paclitaxel precursor on their own. Stable co-culture in the same bioreactor was achieved by designing a mutualistic relationship between the two species in which a metabolic intermediate produced by E. coli was used and functionalized by yeast. This synthetic consortium produced 33 mg/L oxygenated taxanes, including a monoacetylated dioxygenated taxane. The same method was also used to produce tanshinone precursors and functionalized sesquiterpenes.

A method for rapid cloning of plant disease-resistance genes could provide sustainable, genetic solutions to crop pests and pathogens in place of agrichemicals. Wild relatives of domesticated crop species harbor multiple, diverse, disease resistance (R) genes that could be used to engineer sustainable disease control. However, breeding R genes into crop lines often requires long breeding timelines of 5–15 years to break linkage between R genes and deleterious alleles (linkage drag). Further, when R genes are bred one at a time into crop lines, the protection that they confer is often overcome within a few seasons by pathogen evolution 1 . If several cloned R genes were available, it would be possible to pyramid R genes 2 in a crop, which might provide more durable resistance 1 . We describe a three-step method (MutRenSeq)-that combines chemical mutagenesis with exome capture and sequencing for rapid R gene cloning. We applied MutRenSeq to clone stem rust resistance genes Sr22 and Sr45 from hexaploid bread wheat. MutRenSeq can be applied to other commercially relevant crops and their relatives, including, for example, pea, bean, barley, oat, rye, rice and maize.

Softening in tomatoes is uncoupled from ripening by silencing a pectate lyase, thereby identifying a route to engineering (or breeding) tomatoes with better shelf life and flavor. Controlling the rate of softening to extend shelf life was a key target for researchers engineering genetically modified (GM) tomatoes in the 1990s, but only modest improvements were achieved. Hybrids grown nowadays contain 'non-ripening mutations' that slow ripening and improve shelf life, but adversely affect flavor and color. We report substantial, targeted control of tomato softening, without affecting other aspects of ripening, by silencing a gene encoding a pectate lyase.

Engineering cell metabolism for bioproduction not only consumes building blocks and energy molecules (e.g., ATP) but also triggers energetic inefficiency inside the cell. The metabolic burdens on microbial workhorses lead to undesirable physiological changes, placing hidden constraints on host productivity. We discuss cell physiological responses to metabolic burdens, as well as strategies to identify and resolve the carbon and energy burden problems, including metabolic balancing, enhancing respiration, dynamic regulatory systems, chromosomal engineering, decoupling cell growth with production phases, and co-utilization of nutrient resources. To design robust strains with high chances of success in industrial settings, novel genome-scale models (GSMs), 13C-metabolic flux analysis (MFA), and machine-learning approaches are needed for weighting, standardizing, and predicting metabolic costs. To commercialize recombinant organisms for renewable chemical production, it is essential to characterize the cost and benefit of metabolic burden using metabolic flux analysis tools. Genome-scale modeling can incorporate 13C-fluxome information and machine learning to predict the metabolic burden of synthetic biology modules. Modularized expression of native or recombinant pathways using a variety of experimental tools for controlling expression can substantially reduce the metabolic burden introduced by these pathways. The development of a standard synthetic-biology publication database may allow the use of machine learning or artificial intelligence to harness past knowledge for future rational design. Detailed computational methods have been developed to model macromolecule synthesis (DNA, RNA, proteins) to account for the maintenance costs associated with basal cellular function. Systems-level dynamic simulations and design algorithms can inform new approaches to engineering microbial production strains.