Genetic variation in symbiotic islands of natural variant strains of soybean Bradyrhizobium japonicum and Bradyrhizobium diazoefficiens differing in competitiveness and in the efficiency of nitrogen fixation.

Soybean is the most important legume cropped worldwide and can highly benefit from the biological nitrogen fixation (BNF) process. Brazil is recognized for its leadership in the use of inoculants and two strains, Bradyrhizobium japonicum CPAC 15 (=SEMIA 5079) and Bradyrhizobium diazoefficiens CPAC 7 (=SEMIA 5080) compose the majority of the 70 million doses of soybean inoculants commercialized yearly in the country. We studied a collection of natural variants of these two strains, differing in properties of competitiveness and efficiency of BNF. We sequenced the genomes of the parental strain SEMIA 566 of B. japonicum, of three natural variants of this strain (S 204, S 340 and S 370), and compared with another variant of this group, strain CPAC 15. We also sequenced the genome of the parental strain SEMIA 586 of B. diazoefficiens, of three natural variants of this strain (CPAC 390, CPAC 392 and CPAC 394) and compared with the genome of another natural variant, strain CPAC 7. As the main genes responsible for nodulation (nod, noe, nol) and BNF (nif, fix) in soybean Bradyrhizobium are located in symbiotic islands, our objective was to identify genetic variations located in this region, including single nucleotide polymorphisms (SNPs) and insertions and deletions (indels), that could be potentially related to their different symbiotic phenotypes. We detected 44 genetic variations in the B. japonicum strains and three in B. diazoefficiens. As the B. japonicum strains have gone through a longer period of adaptation to the soil, the higher number of genetic variations could be explained by survival strategies under the harsh environmental conditions of the Brazilian Cerrado biome. Genetic variations were detected in genes enconding proteins such as a dephospho-CoA kinase, related to the CoA biosynthesis; a glucosamine-fructose-6-phosphate aminotransferase, key regulator of the hexosamine biosynthetic pathway; a LysR family transcriptional regulator related to nodulation genes; and NifE and NifS proteins, directly related to the BNF process. We suggest potential genetic variations related to differences in the symbiotic phenotypes.

Genome Assembly of a Highly Aldehyde-Resistant Saccharomyces cerevisiae SA1-Derived Industrial Strain.

Here, we report the genome assembly of a Saccharomyces cerevisiae SA1-derived haploid (FMY097) indigenous strain isolated from a Brazilian ethanol distillery. FMY097 was recently reported to be a highly aldehyde-resistant strain capable of producing bioethanol in the presence of up to 40 mM furfural and 80 mM 5-hydroxymethylfurfural.

Expected Genotype Quality and Diploidized Marker Data from Genotyping-by-Sequencing of Urochloa spp. Tetraploids.

CORE IDEAS: Introduced concept of expected genotype quality (EGQ) and software to calculate it Provided read depth guidelines for GBS in tetraploids Developed software to generate diploidized genotype calls from VCF files Demonstrated value of aligning GBS reads to a mock reference genome for SNP discovery Recommend filtering based on GQ and read depth to prevent genotype bias Although genotyping-by-sequencing (GBS) is a well-established marker technology in diploids, the development of best practices for tetraploid species is a topic of current research. We determined the theoretical relationship between read depth and the phred-scaled probability of genotype misclassification conditioned on the true genotype, which we call expected genotype quality (EGQ). If the GBS method has 0.5% allelic error, then 17 reads are needed to classify simplex tetraploids as heterozygous with 95% accuracy (EGQ = 13) vs. 61 reads to determine allele dosage. We developed an R script to convert tetraploid GBS data in variant call format (VCF) into diploidized genotype calls and applied it to 267 interspecific hybrids of the tetraploid forage grass Urochloa. When reads were aligned to a mock reference genome created from GBS data of the Urochloa brizantha (Hochst. ex A. Rich.) R. D. Webster cultivar Marandu, 25,678 biallelic single nucleotide polymorphism (SNPs) were discovered, compared with ∼3000 SNPs when aligning to the closest true reference genomes, Setaria viridis (L.) P. Beauv. and S. italica (L.) P. Beauv. Cross-validation revealed that missing genotypes were imputed by the random forest method with a median accuracy of 0.85 regardless of heterozygote frequency. Using the Urochloa spp. hybrids, we illustrated how filtering samples based only on genotype quality (GQ) creates genotype bias; a depth threshold based on EGQ is also needed regardless of whether genotypes are called using a diploidized or allele dosage model.

Unraveling the genetic basis of xylose consumption in engineered Saccharomyces cerevisiae strains.

The development of biocatalysts capable of fermenting xylose, a five-carbon sugar abundant in lignocellulosic biomass, is a key step to achieve a viable production of second-generation ethanol. In this work, a robust industrial strain of Saccharomyces cerevisiae was modified by the addition of essential genes for pentose metabolism. Subsequently, taken through cycles of adaptive evolution with selection for optimal xylose utilization, strains could efficiently convert xylose to ethanol with a yield of about 0.46 g ethanol/g xylose. Though evolved independently, two strains carried shared mutations: amplification of the xylose isomerase gene and inactivation of ISU1, a gene encoding a scaffold protein involved in the assembly of iron-sulfur clusters. In addition, one of evolved strains carried a mutation in SSK2, a member of MAPKKK signaling pathway. In validation experiments, mutating ISU1 or SSK2 improved the ability to metabolize xylose of yeast cells without adaptive evolution, suggesting that these genes are key players in a regulatory network for xylose fermentation. Furthermore, addition of iron ion to the growth media improved xylose fermentation even by non-evolved cells. Our results provide promising new targets for metabolic engineering of C5-yeasts and point to iron as a potential new additive for improvement of second-generation ethanol production.