The fungal genus Aspergillus is of critical importance to humankind. Species include those with industrial applications, important pathogens of humans, animals and crops, a source of potent carcinogenic contaminants of food, and an important genetic model. The genome sequences of eight aspergilli have already been explored to investigate aspects of fungal biology, raising questions about evolution and specialization within this genus. We have generated genome sequences for ten novel, highly diverse Aspergillus species and compared these in detail to sister and more distant genera. Comparative studies of key aspects of fungal biology, including primary and secondary metabolism, stress response, biomass degradation, and signal transduction, revealed both conservation and diversity among the species. Observed genomic differences were validated with experimental studies. This revealed several highlights, such as the potential for sex in asexual species, organic acid production genes being a key feature of black aspergilli, alternative approaches for degrading plant biomass, and indications for the genetic basis of stress response. A genome-wide phylogenetic analysis demonstrated in detail the relationship of the newly genome sequenced species with other aspergilli. Many aspects of biological differences between fungal species cannot be explained by current knowledge obtained from genome sequences. The comparative genomics and experimental study, presented here, allows for the first time a genus-wide view of the biological diversity of the aspergilli and in many, but not all, cases linked genome differences to phenotype. Insights gained could be exploited for biotechnological and medical applications of fungi.

Cryptococcosis, a mycosis presenting mostly as meningoencephalitis, affecting predominantly human immunodeficiency virus (HIV)-infected people, is mainly caused by Cryptococcus neoformans. The genetic variation of 48 C. neoformans isolates, recovered from 20 HIV-positive people in Lima, Peru, during the pre-highly active antiretroviral therapy (HAART) era, was studied retrospectively. The mating type of the isolates was determined by PCR, and the serotype by agglutination and CAP59-restriction fragment length polymorphism (RFLP). Genetic diversity was assessed by URA5-RFLP, PCR-fingerprinting, amplified fragment length polymorphism (AFLP), and multilocus sequence typing (MLST). All isolates were mating type alpha, with 39 molecular type VNI, seven VNII, corresponding to C. neoformans var. grubii serotype A, and two VNIII AD hybrids. Overall, the cryptococcal population from HIV-positive people in Lima shows a low degree of genetic diversity. In most patients with persistent cryptococcal infection, the same genotype was recovered during the follow-up. In four patients with relapse and one with therapy failure, different genotypes were found in isolates from the re-infection and from the isolate recovered at the end of the treatment. In one patient, two genotypes were found in the first cryptococcosis episode. This study contributes data from Peru to the ongoing worldwide population genetic analysis of Cryptococcus.

Many publications have demonstrated the huge potential of NGS methods in terms of new species discovery, environment monitoring, ecological studies, etc. [24,35,92,97,103]. Undoubtedly, NGS will become one the major tools for species identification and for routine diagnostic use. While read lengths are still quite short for most existing systems ranging between 50 bp and 800 bp, they are likely to improve soon. This will enable easier, faster, and more reliable contig assembly and subsequent matching against reference databases. When data generation is no longer a bottleneck, the storage, speed of analysis, and interpretation of DNA sequence data are becoming the major challenges. Also, the integration or the use of data originating from diverse datasets and a variety of data providers are serious issues that need to be addressed. Poor sequence record annotations and species name assignments are known problems that should be instantly addressed and would allow the creation of reference databases used for routine diagnostics based on NGS. Samples with huge amounts of short DNA fragments need to be analyzed and compared against reference databases in an efficient and fast way. Although a number of solutions have been proposed by Industry; offering commercial software, there still remain hurdles to take. One of the challenges that we need to address is data upload from client’s computers to central or distributed data storage and analysis services. Another one is the efficient parallelization of analyses using cloud or grid solutions. The reliability and up-time of storage and analyses facilities is another important problem that need to be addressed if one wants to use it for routine diagnostics. Finally, the management, reporting and visualization of the analyses results are among the last issues, but not the least challenging ones. Considering the constant growth of computational power and storage capacity needed by different bioinformatics applications, working with single or a limited number of servers is no longer realistic. Using a cloud environment and grid computing is becoming a must. Even single cloud service provider can be restrictive for bioinformatics applications and working with more than one cloud can make the workflow more robust in the face of failures and always growing capacity needs. In this white paper we review the current state of the art in this field. We discuss the main limitations and challenges that we need to address such as; data upload from client’s computers to central or distributed data storage and analysis services; efficient parallelization of analyses using grid solutions; reliability and up-time of storage and analyses facilities for routine diagnostics; management, retrieving and visualization of the analyses results.