Draft genome sequence of Wickerhamomyces anomalus LBCM1105, isolated from cachaça fermentation

Wickerhamomyces anomalus LBCM1105 is a yeast isolated from cachaça distillery fermentation vats, notable for exceptional glycerol consumption ability. We report its draft genome with 20.5x in-depth coverage and around 90% extension and completeness. It harbors the sequences of proteins involved in glycerol transport and metabolism.The authors gratefully acknowledge Laboratorio Nacional de Ciencia e Tecnologia do Bioetanol (CTBE) and the Centro Nacional de Pesquisa em Energia e Materiais (CNPEM) for support with the sequencing of LBCM1105. This work was supported by CAPES/Brazil (PNPD 2755/2011; PCF-PVE 021/2012), by CNPq (Brazil), processes 304815/2012 (research grant) and 305135/2015-5, and by AUXPE-PVES 1801/2012 (Process 23038.015294/2016-18) from Brazilian Government and by UFOP. C.L. is supported by the strategic program UID/BIA/04050/2013 [POCI-01-0145-FEDER-007569] funded by national funds through the FCT I.P. and by the ERDF through the COMPETE2020 - Programa Operacional de Competitividade e Internacionalizacao (POCI). DMRP is a fellow from the CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico) - Brazil (310080/2018-5)

High-Throughput Sequencing Strategy for Microsatellite Genotyping Using Neotropical Fish as a Model

Genetic diversity and population studies are essential for conservation and wildlife management programs. However, monitoring requires the analysis of multiple loci from many samples. These processes can be laborious and expensive. The choice of microsatellites and PCR calibration for genotyping are particularly daunting. Here we optimized a low-cost genotyping method using multiple microsatellite loci for simultaneous genotyping of up to 384 samples using next-generation sequencing (NGS). We designed primers with adapters to the combinatorial barcoding amplicon library and sequenced samples by MiSeq. Next, we adapted a bioinformatics pipeline for genotyping microsatellites based on read-length and sequence content. Using primer pairs for eight microsatellite loci from the fish Prochilodus costatus, we amplified, sequenced, and analyzed the DNA of 96, 288, or 384 individuals for allele detection. The most cost-effective methodology was a pseudo-multiplex reaction using a low-throughput kit of 1 M reads (Nano) for 384 DNA samples. We observed an average of 325 reads per individual per locus when genotyping eight loci. Assuming a minimum requirement of 10 reads per loci, two to four times more loci could be tested in each run, depending on the quality of the PCR reaction of each locus. In conclusion, we present a novel method for microsatellite genotyping using Illumina combinatorial barcoding that dispenses exhaustive PCR calibrations, since non-specific amplicons can be eliminated by bioinformatics analyses. This methodology rapidly provides genotyping data and is therefore a promising development for large-scale conservation-genetics studies

Data from: Reducing cryptic relatedness in genomic datasets via a central node exclusion algorithm

Cryptic relatedness is a confounding factor in genetic diversity and genetic association studies. Development of strategies to reduce cryptic relatedness in a sample is a crucial step for downstream genetic analyzes. The present study uses a node selection algorithm, based on network degrees of centrality, to evaluate its applicability and impact on evaluation of genetic diversity and population stratification. 1,036 Guzerá (Bos indicus) females were genotyped using Illumina Bovine SNP50 v2 BeadChip. Four strategies were compared. The first and second strategies consists on a iterative exclusion of most related individuals based on PLINK kinship coefficient (φij) and VanRaden’s φij, respectively. The third and fourth strategies were based on a node selection algorithm. The fourth strategy, Network G matrix, preserved the larger number of individuals with a better diversity and representation from the initial sample. Determining the most probable number of populations was directly affected by the kinship metric. Network G matrix was the better strategy for reducing relatedness due to producing a larger sample, with more distant individuals, a more similar distribution when compared with the full dataset in the MDS plots and keeping a better representation of the population structure. Resampling strategies using VanRaden’s φij as a relationship metric was better to infer the relationships among individuals. Moreover, the resampling strategies directly impact the genomic inflation values in Genome-wide association studies. The use of the node selection algorithm also implies better selection of the most central individuals to be removed, providing a more representative sample