Biology subjects

Lonardi, S.

Publications and source records attributed to Lonardi, S..

3 recordsLinked to original sources

bioRxiv2018

Validating genome-wide CRISPR-Cas9 function in the non-conventional yeast Yarrowia lipolytica

Genome-wide mutational screens are central to understanding the genetic underpinnings of evolved and engineered phenotypes. The widespread adoption of CRISPR-Cas9 genome editing has enabled such screens in many organisms, but identifying functional sgRNAs still remains a challenge. To address this limitation, we developed a methodology to quantify the cutting efficiency of each sgRNA in a genome-scale library in the biotechnologically important yeast Yarrowia lipolytica. Screening in the presence and absence of native DNA repair enabled high-throughput quantification of sgRNA function leading to the identification of high efficiency sgRNAs that cover 94% of genes. Library validation enhanced the classification of essential genes by identifying inactive guides that create false negatives and mask the effects of successful disruptions. Quantification of guide effectiveness also creates a dataset from which functional determinants of CRISPR-Cas9 can be identified. Finally, application of the library identified mutations that led to high lipid accumulation and eliminated pseudohyphal morphology.

synthetic biology↗

bioRxiv2017

Comprehensive Benchmarking and Ensemble Approaches for Metagenomic Classifiers

BackgroundOne of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole genome shotgun sequencing data, comprehensive comparisons of these methods are limited. In this study, we use the largest (n=35) to date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of eleven metagenomics classifiers. We also assess the effects of filtering and combining tools to reduce the number of false positives.\n\nResultsTools were characterized on the basis of their ability to (1) identify taxa at the genus, species, and strain levels, (2) quantify relative abundance measures of taxa, and (3) classify individual reads to the species level. Strikingly, the number of species identified by the eleven tools can differ by over three orders of magnitude on the same datasets. However, various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Indeed, leveraging tools with different heuristics is beneficial for improved precision. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species and where customized tools may be required.\n\nConclusionsThe results of this study provide positive controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision and recall. We show that proper experimental design and analysis parameters, including depth of sequencing, choice of classifier or classifiers, database size, and filtering, can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.

genomics↗

bioRxiv2017

A multi-parent advanced generation inter-cross population for genetic analysis of multiple traits in cowpea (Vigna unguiculata L. Walp.)

Development and analysis of Multiparent Advanced Generation Inter-Cross (MAGIC) populations have been conducted with several crop plants to harness the potential for dissecting the genetic structure of traits and improving breeding populations. We developed a first MAGIC population for cowpea (Vigna unguiculata L. Walp.) from eight founder parents which are genetically diverse and carry many abiotic and biotic stress resistance, seed quality and agronomic traits relevant to cowpea improvement in sub-Saharan Africa (SSA) where cowpea is vitally important in the human diet and in local economies. The eight parents were inter-crossed using structured matings to ensure the population would have balanced representation from each of the founder parents, followed by single-seed descent, resulting in 365 F8 recombinant inbred lines (RILs) each carrying a mosaic of genome blocks contributed from all founders. This was confirmed by SNP genotyping with the cowpea Illumina 60K iSelect BeadArray. Following filtering to eliminate duplicates, sister lines and accidental selfing events, a core set of 305 F8 RILs was chosen as the primary population. The F8 lines were on average 99.74% homozygous while also diverse in agronomic traits including flowering time, growth habit, maturity, yield potential and seed characteristics across environments. Trait-associated SNPs were identified for most of the parental traits. Loci with major effects on photoperiod sensitivity and seed size were also verified by genetic mapping in biparental RIL populations. The distribution of recombination frequency varied considerably between chromosomes, with recombination hotspots distributed mostly in the telomeric regions. Due to its broad genetic base, this cowpea MAGIC population promises breakthroughs in genetic gain and high-resolution genetic mapping for gene discovery, enhancement of breeding populations and, for some lines, direct releases as new varieties.

genetics↗