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Scientific research relies on computer software, yet software is not always developed following practices that ensure its quality and sustainability. This manuscript does not aim to propose new software development best practices, but rather to provide simple recommendations that encourage the adoption of existing best practices. Software development best practices promote better quality software, and better quality software improves the reproducibility and reusability of research. These recommendations are designed around Open Source values, and provide practical suggestions that contribute to making research software and its source code more discoverable, reusable and transparent. This manuscript is aimed at developers, but also at organisations, projects, journals and funders that can increase the quality and sustainability of research software by encouraging the adoption of these recommendations.

SummaryChromosomal inversions can provide windows onto the cytogenetic, molecular, evolutionary and demographic histories of a species. Here we investigate a paracentric 1.17‐Mb inversion on chromosome 4 of Arabidopsis thaliana with nucleotide precision of its borders. The inversion is created by Vandal transposon activity, splitting an F‐box and relocating a pericentric heterochromatin segment in juxtaposition with euchromatin without affecting the epigenetic landscape. Examination of the RegMap panel and the 1001 Arabidopsis genomes revealed more than 170 inversion accessions in Europe and North America. The SNP patterns revealed historical recombinations from which we infer diverse haplotype patterns, ancient introgression events and phylogenetic relationships. We find a robust association between the inversion and fecundity under drought. We also find linkage disequilibrium between the inverted region and the early flowering Col‐FRIGIDA allele. Finally, SNP analysis elucidates the origin of the inversion to South‐Eastern Europe approximately 5000 years ago and the FRI‐Col allele to North‐West Europe, and reveals the spreading of a single haplotype to North America during the 17th to 19th century. The ‘American haplotype’ was identified from several European localities, potentially due to return migration.

Everything we do today is becoming more and more reliant on the use of computers. The field of biology is no exception; but most biologists receive little or no formal preparation for the increasingly computational aspects of their discipline. In consequence, informal training courses are often needed to plug the gaps; and the demand for such training is growing worldwide. To meet this demand, some training programs are being expanded, and new ones are being developed. Key to both scenarios is the creation of new course materials. Rather than starting from scratch, however, it's sometimes possible to repurpose materials that already exist. Yet finding suitable materials online can be difficult: They're often widely scattered across the internet or hidden in their home institutions, with no systematic way to find them. This is a common problem for all digital objects. The scientific community has attempted to address this issue by developing a set of rules (which have been called the Findable, Accessible, Interoperable and Reusable [FAIR] principles) to make such objects more findable and reusable. Here, we show how to apply these rules to help make training materials easier to find, (re)use, and adapt, for the benefit of all.

There is an increasing interest in complementing RNA-seq experiments with small-RNA (sRNA) expression data to obtain a comprehensive view of a transcriptome. Currently, two main experimental challenges concerning sRNA-seq exist: how to check the size distribution of isolated sRNAs, given the sensitive size-selection steps in the protocol; and how to normalize data between samples, given the low complexity of sRNA types. We here present two separate sets of synthetic RNA spike-ins for monitoring size-selection and for performing data normalization in sRNA-seq. The size-range quality control (SRQC) spike-in set, consisting of 11 oligoribonucleotides (10–70 nucleotides), was tested by intentionally altering the size-selection protocol and verified via several comparative experiments. We demonstrate that the SRQC set is useful to reproducibly track down biases in the size-selection in sRNA-seq. The external reference for data-normalization (ERDN) spike-in set, consisting of 19 oligoribonucleotides, was developed for sample-to-sample normalization in differential-expression analysis of sRNA-seq data. Testing and applying the ERDN set showed that it can reproducibly detect differential expression over a dynamic range of 218. Hence, biological variation in sRNA composition and content between samples is preserved while technical variation is effectively minimized. Together, both spike-in sets can significantly improve the technical reproducibility of sRNA-seq.