Biology subjects

Pereira, G. d. S.

Publications and source records attributed to Pereira, G. d. S..

3 recordsLinked to original sources

bioRxiv2025

Tests for segregation distortion in higher ploidy F1 populations

F1 populations are widely used in genetic mapping studies in agriculture, where known pedigrees enable rigorous quality control measures such as segregation distortion testing. However, conventional tests for segregation distortion are inadequate for polyploids, as they fail to account for double reduction, preferential pairing, and genotype uncertainty, leading to inflated type I error rates. Gerard et al. (2025) (doi:10.1007/s00122-025-04816-z) developed a statistical framework to address these issues in tetraploids. Here, we extend these methods to higher even ploidy levels and introduce additional strategies to mitigate the influence of outliers. Through extensive simulations, we demonstrate that our tests maintain appropriate type I error control while retaining power to detect true segregation distortion. We further validate our approach using empirical data from a hexaploid mapping population. Our methods are implemented in the segtest R package, available on the GitHub (https://github.com/dcgerard/segtest).

bioinformatics↗

bioRxiv2022

Developing best practices for genotyping-by-sequencing analysis using linkage maps as benchmarks

BackgroundGenotyping-by-Sequencing (GBS) provides affordable methods for genotyping hundreds of individuals using millions of markers. However, this challenges bioinformatic procedures that must overcome possible artifacts such as the bias generated by PCR duplicates and sequencing errors. Genotyping errors lead to data that deviate from what is expected from regular meiosis. This, in turn, leads to difficulties in grouping and ordering markers resulting in inflated and incorrect linkage maps. Therefore, genotyping errors can be easily detected by linkage map quality evaluations. ResultsWe developed and used the Reads2Map workflow to build linkage maps with simulated and empirical GBS data of diploid outcrossing populations. The workflows run GATK, Stacks, TASSEL, and Freebayes for SNP calling and updog, polyRAD, and SuperMASSA for genotype calling, and OneMap and GUSMap to build linkage maps. Using simulated data, we observed which genotype call software fails in identifying common errors in GBS sequencing data and proposed specific filters to better handle them. We tested whether it is possible to overcome errors in a linkage map using genotype probabilities from each software or global error rates to estimate genetic distances with an updated version of OneMap. We also evaluated the impact of segregation distortion, contaminant samples, and haplotype-based multiallelic markers in the final linkage maps. Through our evaluations, we observed that some of the approaches produce different results depending on the dataset (dataset-dependent) and others produce consistent advantageous results among them (dataset-independent). ConclusionsWe set as default in the Reads2Map workflows the approaches that showed to be dataset-independent for GBS datasets according to our results. This reduces the number required of tests to identify optimal pipelines and parameters for other empirical datasets. Using Reads2Map, users can select the pipeline and parameters that best fit their data context. The Reads2MapApp shiny app provides a graphical representation of the results to facilitate their interpretation.

bioinformatics↗

bioRxiv2018

Genetic variation in a complex polyploid: unveiling the dynamic allelic features of sugarcane

BackgroundSugarcane (Saccharum spp.) is highly polyploid and aneuploid. Modern cultivars are derived from hybridization between S. officinarum and S. spontaneum. This combination results in a genome exhibiting variable ploidy among different loci, a huge genome size (approximately 10 Gb) and a high content of repetitive regions. Gene expression mechanisms are poorly understood in these cultivars. An approach using genomic, transcriptomic and genetic mapping can improve our knowledge of the behavior of genetics in sugarcane.\n\nResultsThe hypothetical HP600 and centromere protein C (CENP-C) genes from sugarcane were used to elucidate the allelic expression and genomic and genetic behavior of this complex polyploid. The genomically side-by-side genes HP600 and CENP-C were found in two different homeologous chromosome groups with ploidies of eight and ten. The first region (Region01) was a Sorghum bicolor ortholog with all haplotypes of HP600 and CENP- C expressed, but HP600 exhibited an unbalanced haplotype expression. The second region (Region02) was a scrambled sugarcane sequence formed from different noncollinear genes containing duplications of HP600 and CENP-C (paralogs). This duplication occurred before the Saccharum genus formation and after the separation of sorghum and sugarcane, resulting in a nonexpressed HP600 pseudogene and a recombined fusion version of CENP-C and orthologous gene Sobic.003G299500 with at least two chimerical gene haplotypes expressed. The genetic map construction supported the difficulty of mapping markers located in duplicated regions of complex polyploid genomes.\n\nConclusionAll these findings describe a low synteny region in sugarcane, formed by events occurring in all members of the Saccharum genus. Additionally, evidence of duplicated and truncate gene expression and the behavior of genetic markers in a duplicated region was found. Thus, we describe the complexity involved in sugarcane genetics and genomics and allelic dynamics, which can be useful for understanding the complex polyploid genome.

plant biology↗