Correction: High throughput approaches reveal splicing of primary microRNA transcripts and tissue specific expression of mature microRNAs in Vitis vinifera

The version of this article published in BMC Genomics 2009, 10:558, contains data in Table 1 which are now known to be unreliable, and an illustration, in Figure 1, of unusual miRNA processing events predicted by these unreliable data. In this full-length correction, new data replace those found to be unreliable, leading to a more straightforward interpretation without altering the principle conclusions of the study. Table 1 and associated methods have been corrected, Figure 1 deleted, supplementary file 1 added, and modifications made to the sections "Deep sequencing of small RNAs from grapevine leaf tissue" and "Microarray analysis of miRNA expression". The editors and authors regret the inconvenience caused to readers by premature publication of the original paper

High throughput approaches reveal splicing of primary microRNA transcripts and tissue specific expression of mature microRNAs in Vitis vinifera

<p>Abstract</p> <p>Background</p> <p>MicroRNAs are short (~21 base) single stranded RNAs that, in plants, are generally coded by specific genes and cleaved specifically from hairpin precursors. MicroRNAs are critical for the regulation of multiple developmental, stress related and other physiological processes in plants. The recent annotation of the genome of the grapevine (<it>Vitis vinifera </it>L.) allowed the identification of many putative conserved microRNA precursors, grouped into multiple gene families.</p> <p>Results</p> <p>Here we use oligonucleotide arrays to provide the first indication that many of these microRNAs show differential expression patterns between tissues and during the maturation of fruit in the grapevine. Furthermore we demonstrate that whole transcriptome sequencing and deep-sequencing of small RNA fractions can be used both to identify which microRNA precursors are expressed in different tissues and to estimate genomic coordinates and patterns of splicing and alternative splicing for many primary miRNA transcripts.</p> <p>Conclusion</p> <p>Our results show that many microRNAs are differentially expressed in different tissues and during fruit maturation in the grapevine. Furthermore, the demonstration that whole transcriptome sequencing can be used to identify candidate splicing events and approximate primary microRNA transcript coordinates represents a significant step towards the large-scale elucidation of mechanisms regulating the expression of microRNAs at the transcriptional and post-transcriptional levels.</p

Genetic properties of the MAGIC maize population: a new platform for high definition QTL mapping in Zea mays.

BACKGROUND: Maize (Zea mays) is a globally produced crop with broad genetic and phenotypic variation. New tools that improve our understanding of the genetic basis of quantitative traits are needed to guide predictive crop breeding. We have produced the first balanced multi-parental population in maize, a tool that provides high diversity and dense recombination events to allow routine quantitative trait loci (QTL) mapping in maize. RESULTS: We produced 1,636 MAGIC maize recombinant inbred lines derived from eight genetically diverse founder lines. The characterization of 529 MAGIC maize lines shows that the population is a balanced, evenly differentiated mosaic of the eight founders, with mapping power and resolution strengthened by high minor allele frequencies and a fast decay of linkage disequilibrium. We show how MAGIC maize may find strong candidate genes by incorporating genome sequencing and transcriptomics data. We discuss three QTL for grain yield and three for flowering time, reporting candidate genes. Power simulations show that subsets of MAGIC maize might achieve high-power and high-definition QTL mapping. CONCLUSIONS: We demonstrate MAGIC maize\u27s value in identifying the genetic bases of complex traits of agronomic relevance. The design of MAGIC maize allows the accumulation of sequencing and transcriptomics layers to guide the identification of candidate genes for a number of maize traits at different developmental stages. The characterization of the full MAGIC maize population will lead to higher power and definition in QTL mapping, and lay the basis for improved understanding of maize phenotypes, heterosis included. MAGIC maize is available to researchers. Genome Biol 2015 Sep 11; 16:167