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The field of transplant infectious diseases is rapidly evolving, presenting a challenge for clinical practice and trainee education. Here we describe the construction of transplantid.net, a free online library, crowdsourced and continuously updated for the dual purpose of point-of-care evidence-based management and teaching.

The Targeting Induced Local Lesions in Genomes (TILLING) technology is a reverse genetic strategy broadly applicable to every kind of genome and represents an attractive tool for functional genomic and agronomic applications. It consists of chemical random mutagenesis followed by high-throughput screening of point mutations in targeted genomic regions. Although multiple methods for mutation discovery in amplicons have been described, next-generation sequencing (NGS) is the tool of choice for mutation detection because it quickly allows for the analysis of a large number of amplicons. The aim of the present work was to screen a previously generated sunflower TILLING population and identify alterations in genes involved in several important and complex physiological processes. Twenty-one candidate sunflower genes were chosen as targets for the screening. The TILLING by sequencing strategy allowed us to identify multiple mutations in selected genes and we subsequently validated 16 mutations in 11 different genes through Sanger sequencing. In addition to addressing challenges posed by outcrossing, our detection and validation of mutations in multiple regulatory loci highlights the importance of this sunflower population as a genetic resource.

Discovery of rare mutations in populations requires methods, such as TILLING (for Targeting Induced Local Lesions in Genomes), for processing and analyzing many individuals in parallel. Previous TILLING protocols employed enzymatic or physical discrimination of heteroduplexed from homoduplexed target DNA. Using mutant populations of rice (Oryza sativa) and wheat (Triticum durum), we developed a method based on Illumina sequencing of target genes amplified from multidimensionally pooled templates representing 768 individuals per experiment. Parallel processing of sequencing libraries was aided by unique tracer sequences and barcodes allowing flexibility in the number and pooling arrangement of targeted genes, species, and pooling scheme. Sequencing reads were processed and aligned to the reference to identify possible single-nucleotide changes, which were then evaluated for frequency, sequencing quality, intersection pattern in pools, and statistical relevance to produce a Bayesian score with an associated confidence threshold. Discovery was robust both in rice and wheat using either bidimensional or tridimensional pooling schemes. The method compared favorably with other molecular and computational approaches, providing high sensitivity and specificity.

Background Wheat (Triticum ssp.) is an important food source for humans in many regions around the world. However, the ability to understand and modify gene function for crop improvement is hindered by the lack of available genomic resources. TILLING is a powerful reverse genetics approach that combines chemical mutagenesis with a high-throughput screen for mutations. Wheat is specially well-suited for TILLING due to the high mutation densities tolerated by polyploids, which allow for very efficient screens. Despite this, few TILLING populations are currently available. In addition, current TILLING screening protocols require high-throughput genotyping platforms, limiting their use. Results We developed mutant populations of pasta and common wheat and organized them for TILLING. To simplify and decrease costs, we developed a non-denaturing polyacrylamide gel set-up that uses ethidium bromide to detect fragments generated by crude celery juice extract digestion of heteroduplexes. This detection method had similar sensitivity as traditional LI-COR screens, suggesting that it represents a valid alternative. We developed genome-specific primers to circumvent the presence of multiple homoeologous copies of our target genes. Each mutant library was characterized by TILLING multiple genes, revealing high mutation densities in both the hexaploid (~1/38 kb) and tetraploid (~1/51 kb) populations for 50% GC targets. These mutation frequencies predict that screening 1,536 lines for an effective target region of 1.3 kb with 50% GC content will result in ~52 hexaploid and ~39 tetraploid mutant alleles. This implies a high probability of obtaining knock-out alleles (P = 0.91 for hexaploid, P = 0.84 for tetraploid), in addition to multiple missense mutations. In total, we identified over 275 novel alleles in eleven targeted gene/genome combinations in hexaploid and tetraploid wheat and have validated the presence of a subset of them in our seed stock. Conclusion We have generated reverse genetics TILLING resources for pasta and bread wheat and achieved a high mutation density in both populations. We also developed a modified screening method that will lower barriers to adopt this promising technology. We hope that the use of this reverse genetics resource will enable more researchers to pursue wheat functional genomics and provide novel allelic diversity for wheat improvement.