A benchmark study of ab initio gene prediction methods in diverse eukaryotic organisms

Abstract

Background: The draft genome assemblies produced by new sequencing technologies present important challenges for automatic gene prediction pipelines, leading to less accurate gene models. New benchmark methods are needed to evaluate the accuracy of gene prediction methods in the face of incomplete genome assemblies, low genome coverage and quality, complex gene structures, or a lack of suitable sequences for evidence-based annotations. Results: We describe the construction of a new benchmark, called G3PO (benchmark for Gene and Protein Prediction PrOgrams), designed to represent many of the typical challenges faced by current genome annotation projects. The benchmark is based on a carefully validated and curated set of real eukaryotic genes from 147 phylogenetically disperse organisms, and a number of test sets are defined to evaluate the effects of different features, including genome sequence quality, gene structure complexity, protein length, etc. We used the benchmark to perform an independent comparative analysis of the most widely used ab initio gene prediction programs and identified the main strengths and weaknesses of the programs. More importantly, we highlight a number of features that could be exploited in order to improve the accuracy of current prediction tools. Conclusions: The experiments showed that ab initio gene structure prediction is a very challenging task, which should be further investigated. We believe that the baseline results associated with the complex gene test sets in G3PO provide useful guidelines for future studies.

Construction of a chromosome‐level genome and variation map for the Pacific oyster Crassostrea gigas

“…The NR hits of most of the genes are sequences of the previous release of C. gigas, and only 1,329 predictions had ab initio-based supports. The fact that the algorithms for ab initio gene prediction were mainly designed for a few specific model organisms, such as fruit flies, worms, and humans, and the accurate prediction of a gene model has always been difficult (Salzberg, 2019;Scalzitti et al, 2020), the 7,329 genes without expression or SWISS-PROT support are most probably less accurate predictions.…”

Foster thy young: Enhanced prediction of orphan genes in assembled genomes

“…This method, though highly useful in determining how well a pipeline annotates more ancient genes, does not capture the efficacy of a pipeline in identifying orphans or other young genes. Recently, Scalizati et al 58 have developed a benchmarking approach that takes phylostrata into account; herein we provide a different approach to benchmarking that considers phylostrata, and enables customization of phylostrata to include line-specific genes.…”