EST contig-based SSR linkage maps for Malus × domestica cv Royal Gala and an apple scab resistant accession of M. sieversii , the progenitor species of domestic apple

Malus sieversii is a progenitor species of domestic apple M.×domestica. Using population "GMAL 4595” of 188 individuals derived from a cross of Royal Gala×PI 613988 (apple scab resistant, M. sieversii), 287 SSR (simple sequence repeats) loci were mapped. Of these SSRs, 80 are published anchors and 207 are newly developed EST (expressed sequence tag) contig-based SSRs, representing 1,630 Malus EST accessions in GenBank. Putative gene functions of these EST contigs are diverse, including regulating plant growth, development and response to environmental stresses. Among the 80 published SSRs, 18 are PI 613988 specific, 38 are common and 24 are Royal Gala specific. Out of the 207 newly developed EST contig-based SSRs, 79 are PI 613988 specific, 45 are common and 83 are Royal Gala specific. These results led to the construction of a M. sieversii map (1,387.0cM) of 180 SSR markers and a Royal Gala map (1,283.4cM) of 190 SSR markers. Mapping of scab resistance was independently conducted in two subsets of population "GMAL 4595” that were inoculated with Ventura inaequalis races (1) and (2), respectively. In combination with the two major resistance reactions Chl (chlorotic lesions) and SN (stellate necrosis) to each race, four subsets of resistance data, i.e., Chl/race (1), SN/race (1), Chl/race (2) and SN/race (2), were constituted and analyzed, leading to four resistance loci mapped to the linkage group 2 of PI 613988; SNR1 (stellate necrosis resistance to race (1)) and SNR2 are tightly linked in a region of known scab resistance genes, and ChlR1 (Chlorotic lesion resistance to race (1)) and ChlR2 are also linked tightly but in a region without known scab resistance genes. The utility of the two linkage maps, the new EST contig-based markers and M. sieversii as sources of apple scab resistance are discusse

Genome-wide SNP identification, linkage map construction and QTL mapping for seed mineral concentrations and contents in pea (Pisum sativum L.)

Linkage map. This file contains the details of the linkage map. (XLSX 38 kb

Genome wide identification of chilling responsive microRNAs in Prunus persica

BACKGROUND: MicroRNAs (miRNAs) are small RNAs (sRNAs) approximately 21 nucleotides in length that negatively control gene expression by cleaving or inhibiting the translation of target gene transcripts. Within this context, miRNAs and siRNAs are coming to the forefront as molecular mediators of gene regulation in plant responses to annual temperature cycling and cold stress. For this reason, we chose to identify and characterize the conserved and non-conserved miRNA component of peach (Prunus persica (L.) Batsch) focusing our efforts on both the recently released whole genome sequence of peach and sRNA transcriptome sequences from two tissues representing non-dormant leaves and dormant leaf buds. Conserved and non-conserved miRNAs, and their targets were identified. These sRNA resources were used to identify cold-responsive miRNAs whose gene targets co-localize with previously described QTLs for chilling requirement (CR). RESULTS: Analysis of 21 million peach sRNA reads allowed us to identify 157 and 230 conserved and non-conserved miRNA sequences. Among the non-conserved miRNAs, we identified 205 that seem to be specific to peach. Comparative genome analysis between peach and Arabidopsis showed that conserved miRNA families, with the exception of miR5021, are similar in size. Sixteen of these conserved miRNA families are deeply rooted in land plant phylogeny as they are present in mosses and/or lycophytes. Within the other conserved miRNA families, five families (miR1446, miR473, miR479, miR3629, and miR3627) were reported only in tree species (Populustrichocarpa, Citrus trifolia, and Prunus persica). Expression analysis identified several up-regulated or down-regulated miRNAs in winter buds versus young leaves. A search of the peach proteome allowed the prediction of target genes for most of the conserved miRNAs and a large fraction of non-conserved miRNAs. A fraction of predicted targets in peach have not been previously reported in other species. Several conserved and non-conserved miRNAs and miRNA-regulated genes co-localize with Quantitative Trait Loci (QTLs) for chilling requirement (CR-QTL) and bloom date (BD-QTL). CONCLUSIONS: In this work, we identified a large set of conserved and non-conserved miRNAs and describe their evolutionary footprint in angiosperm lineages. Several of these miRNAs were induced in winter buds and co-localized with QTLs for chilling requirement and bloom date thus making their gene targets potential candidates for mediating plant responses to cold stress. Several peach homologs of genes participating in the regulation of vernalization in Arabidopsis were identified as differentially expressed miRNAs targets, potentially linking these gene activities to cold responses in peach dormant buds. The non-conserved miRNAs may regulate cellular, physiological or developmental processes specific to peach and/or other tree species

Advanced Imaging for Quantitative Evaluation of Aphanomyces Root Rot Resistance in Lentil

Aphanomyces root rot (ARR) is a soil-borne disease that results in severe yield losses in lentil. The development of resistant cultivars is one of the key strategies to control this pathogen. However, the evaluation of disease severity is limited to visual scores that can be subjective. This study utilized image-based phenotyping approaches to evaluate Aphanomyces euteiches resistance in lentil genotypes in greenhouse (351 genotypes from lentil single plant/LSP derived collection and 191 genotypes from recombinant inbred lines/RIL using digital Red-Green-Blue/RGB and hyperspectral imaging) and field (173 RIL genotypes using unmanned aerial system-based multispectral imaging) conditions. Moderate to strong correlations were observed between RGB, multispectral, and hyperspectral derived features extracted from lentil shoots/roots and visual scores. In general, root features extracted from RGB imaging were found to be strongly associated with disease severity. With only three root traits, elastic net regression model was able to predict disease severity across and within multiple datasets (R2 = 0.45–0.73 and RMSE = 0.66–1.00). The selected features could represent visual disease scores. Moreover, we developed twelve normalized difference spectral indices (NDSIs) that were significantly correlated with disease scores: two NDSIs for lentil shoot section – computed from wavelengths of 1170, 1160, 1270, and 1280 nm (0.12 ≤ |r| ≤ 0.24, P < 0.05) and ten NDSIs for lentil root sections – computed from wavelengths in the range of 630–670, 700–840, and 1320–1530 nm (0.10 ≤ |r| ≤ 0.50, P < 0.05). Root-derived NDSIs were more accurate in predicting disease scores with an R2 of 0.54 (RMSE = 0.86), especially when the model was trained and tested on LSP accessions, compared to R2 of 0.25 (RMSE = 1.64) when LSP and RIL genotypes were used as train and test datasets, respectively. Importantly, NDSIs – computed from wavelengths of 700, 710, 730, and 790 nm – had strong positive correlations with disease scores (0.35 ≤r ≤ 0.50, P < 0.0001), which was confirmed in field phenotyping with similar correlations using vegetation index with red edge wavelength (normalized difference red edge, 0.36 ≤ |r| ≤ 0.57, P < 0.0001). The adopted image-based phenotyping approaches can help plant breeders to objectively quantify ARR resistance and reduce the subjectivity in selecting potential genotypes

A roadmap for research in octoploid strawberry

The cultivated strawberry (Fragaria × ananassa) is an allo-octoploid species, originating nearly 300 years ago from wild progenitors from the Americas. Since that time the strawberry has become the most widely cultivated fruit crop in the world, universally appealing due to its sensory qualities and health benefits. The recent publication of the first high-quality chromosome-scale octoploid strawberry genome (cv. Camarosa) is enabling rapid advances in genetics, stimulating scientific debate and provoking new research questions. In this forward-looking review we propose avenues of research toward new biological insights and applications to agriculture. Among these are the origins of the genome, characterization of genetic variants, and big data approaches to breeding. Key areas of research in molecular biology will include the control of flowering, fruit development, fruit quality, and plant–pathogen interactions. In order to realize this potential as a global community, investments in genome resources must be continually augmented.Peer reviewe

Tripal, a community update after 10 years of supporting open source, standards-based genetic, genomic and breeding databases

Online, open access databases for biological knowledge serve as central repositories for research communities to store, find and analyze integrated, multi-disciplinary datasets. With increasing volumes, complexity and the need to integrate genomic, transcriptomic, metabolomic, proteomic, phenomic and environmental data, community databases face tremendous challenges in ongoing maintenance, expansion and upgrades. A common infrastructure framework using community standards shared by many databases can reduce development burden, provide interoperability, ensure use of common standards and support long-term sustainability. Tripal is a mature, open source platform built to meet this need. With ongoing improvement since its first release in 2009, Tripal provides full functionality for searching, browsing, loading and curating numerous types of data and is a primary technology powering at least 31 publicly available databases spanning plants, animals and human data, primarily storing genomics, genetics and breeding data. Tripal software development is managed by a shared, inclusive governance structure including both project management and advisory teams. Here, we report on the most important and innovative aspects of Tripal after 11 years development, including integration of diverse types of biological data, successful collaborative projects across member databases, and support for implementing FAIR principles

A framework physical map for peach, a model Rosaceae species

A genome-wide framework physical map of peach was constructed using high-information content fingerprinting (HICF) and FPC software. The resulting HICF assembly contained 2,138 contigs composed of 15,655 clones (4.3× peach genome equivalents) from two complementary bacterial artificial chromosome libraries. The total physical length of all contigs is estimated at 303 Mb or 104.5% of the peach genome. The framework physical map is anchored on the Prunus genetic reference map and integrated with the peach transcriptome map. The physical length of anchored contigs is estimated at 45.0 Mb or 15.5% of the genome. Altogether, 2,636 markers, i.e., genetic markers, peach unigene expressed sequence tags, and gene-specific and overgo probes, were incorporated into the physical framework and supported the accuracy of contig assembly.This project was supported by the United States Department of Agriculture NRI Award # 2005-35300-15452.Peer reviewe

There and back again: historical perspective and future directions for Vaccinium breeding and research studies

The genus Vaccinium L. (Ericaceae) contains a wide diversity of culturally and economically important berry crop species. Consumer demand and scientific research in blueberry (Vaccinium spp.) and cranberry (Vaccinium macrocarpon) have increased worldwide over the crops' relatively short domestication history (~100 years). Other species, including bilberry (Vaccinium myrtillus), lingonberry (Vaccinium vitis-idaea), and ohelo berry (Vaccinium reticulatum) are largely still harvested from the wild but with crop improvement efforts underway. Here, we present a review article on these Vaccinium berry crops on topics that span taxonomy to genetics and genomics to breeding. We highlight the accomplishments made thus far for each of these crops, along their journey from the wild, and propose research areas and questions that will require investments by the community over the coming decades to guide future crop improvement efforts. New tools and resources are needed to underpin the development of superior cultivars that are not only more resilient to various environmental stresses and higher yielding, but also produce fruit that continue to meet a variety of consumer preferences, including fruit quality and health related trait

Development and evaluation of a 9K SNP array for peach by internationally coordinated SNP detection and validation in breeding germplasm

Although a large number of single nucleotide polymorphism (SNP) markers covering the entire genome are needed to enable molecular breeding efforts such as genome wide association studies, fine mapping, genomic selection and marker-assisted selection in peach [Prunus persica (L.) Batsch] and related Prunus species, only a limited number of genetic markers, including simple sequence repeats (SSRs), have been available to date. To address this need, an international consortium (The International Peach SNP Consortium; IPSC) has pursued a coordinated effort to perform genome-scale SNP discovery in peach using next generation sequencing platforms to develop and characterize a high-throughput Illumina Infinium® SNP genotyping array platform. We performed whole genome re-sequencing of 56 peach breeding accessions using the Illumina and Roche/454 sequencing technologies. Polymorphism detection algorithms identified a total of 1,022,354 SNPs. Validation with the Illumina GoldenGate® assay was performed on a subset of the predicted SNPs, verifying ∼75% of genic (exonic and intronic) SNPs, whereas only about a third of intergenic SNPs were verified. Conservative filtering was applied to arrive at a set of 8,144 SNPs that were included on the IPSC peach SNP array v1, distributed over all eight peach chromosomes with an average spacing of 26.7 kb between SNPs. Use of this platform to screen a total of 709 accessions of peach in two separate evaluation panels identified a total of 6,869 (84.3%) polymorphic SNPs.The almost 7,000 SNPs verified as polymorphic through extensive empirical evaluation represent an excellent source of markers for future studies in genetic relatedness, genetic mapping, and dissecting the genetic architecture of complex agricultural traits. The IPSC peach SNP array v1 is commercially available and we expect that it will be used worldwide for genetic studies in peach and related stone fruit and nut species