BackgroundHigh light tolerance of microalgae is a desired phenotype for efficient cultivation in large scale production systems under fluctuating outdoor conditions. Outdoor cultivation requires the use of either wild-type or non-GMO derived mutant strains due to safety concerns. The identification and molecular characterization of such mutants derived from untagged forward genetics approaches was limited previously by the tedious and time-consuming methods involving techniques such as classical meiotic mapping. The combination of mapping with next generation sequencing technologies offers alternative strategies to identify genes involved in high light adaptation in untagged mutants.ResultsWe used the model alga Chlamydomonas reinhardtii in a non-GMO mutation strategy without any preceding crossing step or pooled progeny to identify genes involved in the regulatory processes of high light adaptation. To generate high light tolerant mutants, wildtype cells were mutagenized only to a low extent, followed by a stringent selection. We performed whole-genome sequencing of two independent mutants hit1 and hit2 and the parental wildtype. The availability of a reference genome sequence and the removal of shared bakground variants between the wildtype strain and each mutant, enabled us to identify two single nucleotide polymorphisms within the same gene Cre02.g085050, hereafter called LRS1 (putative Light Response Signaling protein 1). These two independent single amino acid exchanges are both located in the putative WD40 propeller domain of the corresponding protein LRS1. Both mutants exhibited an increased rate of non-photochemical-quenching (NPQ) and an improved resistance against chemically induced reactive oxygen species. In silico analyses revealed homology of LRS1 to the photoregulatory protein COP1 in plants.ConclusionsIn this work we identified the nuclear encoded gene LRS1 as an essential factor for high light adaptation in C. reinhardtii. The causative random mutation within this gene was identified by a rapid and efficient method, avoiding any preceding crossing step, meiotic mapping, or pooled progeny. Our results open up new insights into mechanisms of high light adaptation in microalgae and at the same time provide a simplified strategy for non-GMO forward genetics, a crucial precondition that could result in the identification of key factors for economically relevant biological processes within algae.

The results suggest that using topical fluoride agents with beta titanium and stainless steel wire could decrease the functional unloading mechanical properties of the wires and potentially contribute to prolonged orthodontic treatment.

Rapid identification of agronomically important genes is of pivotal interest for crop breeding. One source of such genes are crop wild relative (CWR) populations. Here we used a CWR population of <200 wild beets (B. vulgaris ssp. maritima), sampled in their natural habitat, to identify the sugar beet (Beta vulgaris ssp. vulgaris) resistance gene Rz2 with a modified version of mapping-by-sequencing (MBS). For that, we generated a draft genome sequence of the wild beet. Our results show the importance of preserving CWR in situ and demonstrate the great potential of CWR for rapid discovery of causal genes relevant for crop improvement. The candidate gene for Rz2 was identified by MBS and subsequently corroborated via RNA interference (RNAi). Rz2 encodes a CC-NB-LRR protein. Access to the DNA sequence of Rz2 opens the path to improvement of resistance towards rhizomania not only by marker-assisted breeding but also by genome editing.

BackgroundThe combination of bulk segregant analysis (BSA) and next generation sequencing (NGS), also known as mapping by sequencing (MBS), has been shown to significantly accelerate the identification of causal mutations for species with a reference genome sequence. The usual approach is to cross homozygous parents that differ for the monogenic trait to address, to perform deep sequencing of DNA from F2 plants pooled according to their phenotype, and subsequently to analyze the allele frequency distribution based on a marker table for the parents studied. The method has been successfully applied for EMS induced mutations as well as natural variation. Here, we show that pooling genetically diverse breeding lines according to a contrasting phenotype also allows high resolution mapping of the causal gene in a crop species. The test case was the monogenic locus causing red vs. green hypocotyl color in Beta vulgaris (R locus).ResultsWe determined the allele frequencies of polymorphic sequences using sequence data from two diverging phenotypic pools of 180 B. vulgaris accessions each. A single interval of about 31 kbp among the nine chromosomes was identified which indeed contained the causative mutation.ConclusionsBy applying a variation of the mapping by sequencing approach, we demonstrated that phenotype-based pooling of diverse accessions from breeding panels and subsequent direct determination of the allele frequency distribution can be successfully applied for gene identification in a crop species. Our approach made it possible to identify a small interval around the causative gene. Sequencing of parents or individual lines was not necessary. Whenever the appropriate plant material is available, the approach described saves time compared to the generation of an F2 population. In addition, we provide clues for planning similar experiments with regard to pool size and the sequencing depth required.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2566-9) contains supplementary material, which is available to authorized users.

BackgroundBarley is the world’s fourth most cultivated cereal and is an important crop model for genetic studies. One layer of genomic information that remains poorly explored in barley is presence/absence variation (PAV), which has been suggested to contribute to phenotypic variation of agronomic importance in various crops.ResultsAn mRNA sequencing approach was used to study genomic PAV and transcriptomic variation in 23 spring barley inbreds. 1502 new genes identified here were physically absent from the Morex reference sequence, and 11,523 previously unannotated genes were not expressed in Morex. The procedure applied to detect expression PAV revealed that more than 50% of all genes of our data set are not expressed in all inbreds. Interestingly, expression PAV were not in strong linkage disequilibrium with neighboring sequence variants (SV), and therefore provided an additional layer of genetic information. Optimal combinations of expression PAV, SV, and gene abundance data could enhance the prediction accuracy of predicting three different agronomic traits.ConclusionsOur results highlight the advantage of mRNA sequencing for genomic prediction over other technologies, as it allows extracting multiple layers of genomic data from a single sequencing experiment. Finally, we propose low coverage mRNA sequencing based characterization of breeding material harvested as seedlings in petri dishes as a powerful and cost efficient approach to replace current single nucleotide polymorphism (SNP) based characterizations.