The blackgrass genome reveals patterns of non-parallel evolution of polygenic herbicide resistance.

Globally, weedy plants are a major constraint to sustainable crop production. Much of the success of weeds rests with their ability to rapidly adapt in the face of human-mediated management of agroecosystems. Alopecurus myosuroides (blackgrass) is a widespread and impactful weed affecting agriculture in Europe. Here we report a chromosome-scale genome assembly of blackgrass and use this reference genome to explore the genomic/genetic basis of non-target site herbicide resistance (NTSR). Based on our analysis of F2 seed families derived from two distinct blackgrass populations with the same NTSR phenotype, we demonstrate that the trait is polygenic and evolves from standing genetic variation. We present evidence that selection for NTSR has signatures of both parallel and non-parallel evolution. There are parallel and non-parallel changes at the transcriptional level of several stress- and defence-responsive gene families. At the genomic level, however, the genetic loci underpinning NTSR are different (non-parallel) between seed families. We speculate that variation in the number, regulation and function of stress- and defence-related gene families enable weedy species to rapidly evolve NTSR via exaptation of genes within large multi-functional gene families. These results provide novel insights into the potential for, and nature of plant adaptation in rapidly changing environments.

Mapping and characterization QTLs for phenological traits in seven pedigree-connected peach families.

BACKGROUND: Environmental adaptation and expanding harvest seasons are primary goals of most peach [Prunus persica (L.) Batsch] breeding programs. Breeding perennial crops is a challenging task due to their long breeding cycles and large tree size. Pedigree-based analysis using pedigreed families followed by haplotype construction creates a platform for QTL and marker identification, validation, and the use of marker-assisted selection in breeding programs. RESULTS: Phenotypic data of seven F1 low to medium chill full-sib families were collected over 2 years at two locations and genotyped using the 9 K SNP Illumina array. Three QTLs were discovered for bloom date (BD) and mapped on linkage group 1 (LG1) (172-182 cM), LG4 (48-54 cM), and LG7 (62-70 cM), explaining 17-54%, 11-55%, and 11-18% of the phenotypic variance, respectively. The QTL for ripening date (RD) and fruit development period (FDP) on LG4 was co-localized at the central part of LG4 (40-46 cM) and explained between 40 and 75% of the phenotypic variance. Haplotype analyses revealed SNP haplotypes and predictive SNP marker(s) associated with desired QTL alleles and the presence of multiple functional alleles with different effects for a single locus for RD and FDP. CONCLUSIONS: A multiple pedigree-linked families approach validated major QTLs for the three key phenological traits which were reported in previous studies across diverse materials, geographical distributions, and QTL mapping methods. Haplotype characterization of these genomic regions differentiates this study from the previous QTL studies. Our results will provide the peach breeder with the haplotypes for three BD QTLs and one RD/FDP QTL to create predictive DNA-based molecular marker tests to select parents and/or seedlings that have desired QTL alleles and cull unwanted genotypes in early seedling stages.

Identification and characterization of QTLs for fruit quality traits in peach through a multi-family approach.

BACKGROUND: Fruit quality traits have a significant effect on consumer acceptance and subsequently on peach (Prunus persica (L.) Batsch) consumption. Determining the genetic bases of key fruit quality traits is essential for the industry to improve fruit quality and increase consumption. Pedigree-based analysis across multiple peach pedigrees can identify the genomic basis of complex traits for direct implementation in marker-assisted selection. This strategy provides breeders with better-informed decisions and improves selection efficiency and, subsequently, saves resources and time. RESULTS: Phenotypic data of seven F1 low to medium chill full-sib families were collected over 2 years at two locations and genotyped using the 9 K SNP Illumina array. One major QTL for fruit blush was found on linkage group 4 (LG4) at 40-46 cM that explained from 20 to 32% of the total phenotypic variance and showed three QTL alleles of different effects. For soluble solids concentration (SSC), one QTL was mapped on LG5 at 60-72 cM and explained from 17 to 39% of the phenotypic variance. A major QTL for titratable acidity (TA) co-localized with the major locus for low-acid fruit (D-locus). It was mapped at the proximal end of LG5 and explained 35 to 80% of the phenotypic variance. The new QTL for TA on the distal end of LG5 explained 14 to 22% of the phenotypic variance. This QTL co-localized with the QTL for SSC and affected TA only when the first QTL is homozygous for high acidity (epistasis). Haplotype analyses revealed SNP haplotypes and predictive SNP marker(s) associated with desired QTL alleles. CONCLUSIONS: A multi-family-based QTL discovery approach enhanced the ability to discover a new TA QTL at the distal end of LG5 and validated other QTLs which were reported in previous studies. Haplotype characterization of the mapped QTLs distinguishes this work from the previous QTL studies. Identified predictive SNPs and their original sources will facilitate the selection of parents and/or seedlings that have desired QTL alleles. Our findings will help peach breeders develop new predictive, DNA-based molecular marker tests for routine use in marker-assisted breeding.

Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits.

BACKGROUND: Sweet cherry is consumed widely across the world and provides substantial economic benefits in regions where it is grown. While cherry breeding has been conducted in the Pacific Northwest for over half a century, little is known about the genetic architecture of important traits. We used a genome-enabled mixed model to predict the genetic performance of 505 individuals for 32 phenological, disease response and fruit quality traits evaluated in the RosBREED sweet cherry crop data set. Genome-wide predictions were estimated using a repeated measures model for phenotypic data across 3 years, incorporating additive, dominance and epistatic variance components. Genomic relationship matrices were constructed with high-density SNP data and were used to estimate relatedness and account for incomplete replication across years. RESULTS: High broad-sense heritabilities of 0.83, 0.77, and 0.76 were observed for days to maturity, firmness, and fruit weight, respectively. Epistatic variance exceeded 40% of the total genetic variance for maturing timing, firmness and powdery mildew response. Dominance variance was the largest for fruit weight and fruit size at 34% and 27%, respectively. Omission of non-additive sources of genetic variance from the genetic model resulted in inflation of narrow-sense heritability but minimally influenced prediction accuracy of genetic values in validation. Predicted genetic rankings of individuals from single-year models were inconsistent across years, likely due to incomplete sampling of the population genetic variance. CONCLUSIONS: Predicted breeding values and genetic values revealed many high-performing individuals for use as parents and the most promising selections to advance for cultivar release consideration, respectively. This study highlights the importance of using the appropriate genetic model for calculating breeding values to avoid inflation of expected parental contribution to genetic gain. The genomic predictions obtained will enable breeders to efficiently leverage the genetic potential of North American sweet cherry germplasm by identifying high quality individuals more rapidly than with phenotypic data alone.

A rare SNP mutation in Brachytic2 moderately reduces plant height and increases yield potential in maize.

Plant height has long been an important agronomic trait in maize breeding. Many plant height QTLs have been reported, but few of these have been cloned. In this study, a major plant height QTL, qph1, was mapped to a 1.6kb interval in Brachytic2 (Br2) coding sequence on maize chromosome 1. A naturally occurring rare SNP in qph1, which resulted in an amino acid substitution, was validated as the causative mutation. QPH1 protein is located in the plasma membrane and polar auxin transport is impaired in the short near-isogenic line RIL88(qph1). Allelism testing showed that the SNP variant in qph1 reduces longitudinal cell number and decreases plant height by 20% in RIL88(qph1) compared to RIL88(QPH1), and is milder than known br2 mutant alleles. The effect of qph1 on plant height is significant and has no or a slight influence on yield in four F2 backgrounds and in six pairs of single-cross hybrids. Moreover, qph1 could reduce plant height when heterozygous, allowing it to be easily employed in maize breeding. Thus, a less-severe allele of a known dwarf mutant explains part of the quantitative variation for plant height and has great potential in maize improvement.

Ppe.RPT/SSC-1: from QTL mapping to a predictive KASP test for ripening time and soluble solids concentration in peach.

Genomic regions associated with ripening time (RPT) and soluble solids concentration (SSC) were mapped using a pedigreed population including multiple F1 and F2 families from the Clemson University peach breeding program (CUPBP). RPT and SSC QTLs were consistently identified in two seasons (2011 and 2012) and the average datasets (average of two seasons). A target region spanning 10,981,971-11,298,736 bp on chromosome 4 of peach reference genome used for haplotype analysis revealed four haplotypes with significant differences in trait values among different diplotype combinations. Favorable alleles at the target region for both RPT and SSC were determined and a DNA test for predicting RPT and SSC was developed. Two Kompetitive Allele Specific PCR (KASP) assays were validated on 84 peach cultivars and 163 seedlings from the CUPBP, with only one assay (Ppe.RPT/SSC-1) needed to predict between early and late-season ripening cultivars and low and high SSC. These results advance our understanding of the genetic basis of RPT and SSC and facilitate selection of new peach cultivars with the desired RPT and SSC.

Transcriptomics reveal the genetic coordination of early defense to Armillaria root rot (ARR) in Prunus spp.

Armillaria root rot (ARR) poses a significant threat to the long-term productivity of stone-fruit and nut crops in the predominant production area of the United States. To mitigate this issue, the development of ARR-resistant and horticulturally-acceptable rootstocks is a crucial step towards the maintenance of production sustainability. To date, genetic resistance to ARR has been found in exotic plum germplasm and a peach/plum hybrid rootstock, 'MP-29'. However, the widely-used peach rootstock Guardian® is susceptible to the pathogen. To understand the molecular defense mechanisms involved in ARR resistance in Prunus rootstocks, transcriptomic analyses of one susceptible and two resistant Prunus spp. were performed using two causal agents of ARR, including Armillaria mellea and Desarmillaria tabescens. The results of in vitro co-culture experiments revealed that the two resistant genotypes showed different temporal response dynamics and fungus-specific responses, as seen in the genetic response. Gene expression analysis over time indicated an enrichment of defense-related ontologies, including glucosyltransferase activity, monooxygenase activity, glutathione transferase activity, and peroxidase activity. Differential gene expression and co-expression network analysis highlighted key hub genes involved in the sensing and enzymatic degradation of chitin, GSTs, oxidoreductases, transcription factors, and biochemical pathways likely involved in Armillaria resistance. These data provide valuable resources for the improvement of ARR resistance in Prunus rootstocks through breeding.

Corrigendum: Multi-Locus Genome-Wide Association Studies Reveal Fruit Quality Hotspots in Peach Genome.

[This corrects the article DOI: 10.3389/fpls.2021.644799.].

Convergent selection of a WD40 protein that enhances grain yield in maize and rice.

A better understanding of the extent of convergent selection among crops could greatly improve breeding programs. We found that the quantitative trait locus KRN2 in maize and its rice ortholog, OsKRN2, experienced convergent selection. These orthologs encode WD40 proteins and interact with a gene of unknown function, DUF1644, to negatively regulate grain number in both crops. Knockout of KRN2 in maize or OsKRN2 in rice increased grain yield by ~10% and ~8%, respectively, with no apparent trade-offs in other agronomic traits. Furthermore, genome-wide scans identified 490 pairs of orthologous genes that underwent convergent selection during maize and rice evolution, and these were enriched for two shared molecular pathways. KRN2, together with other convergently selected genes, provides an excellent target for future crop improvement.

Multi-Locus Genome-Wide Association Studies Reveal Fruit Quality Hotspots in Peach Genome.

Peach is one of the most important fruit crops in the world, with the global annual production about 24.6 million tons. The United States is the fourth-largest producer after China, Spain, and Italy. Peach consumption has decreased over the last decade, most likely due to inconsistent quality of the fruit on the market. Thus, marker-assisted selection for fruit quality traits is highly desired in fresh market peach breeding programs and one of the major goals of the RosBREED project. The ability to use DNA information to select for desirable traits would enable peach breeders to efficiently plan crosses and select seedlings with desired quality traits early in the selection process before fruiting. Therefore, we assembled a multi-locus genome wide association study (GWAS) of 620 individuals from three public fresh market peach breeding programs (Arkansas, Texas, and South Carolina). The material was genotyped using 9K SNP array and the traits were phenotyped for three phenological (bloom date, ripening date, and days after bloom) and 11 fruit quality-related traits (blush, fruit diameter, fruit weight, adherence, fruit firmness, redness around pit, fruit texture, pit weight, soluble solid concentration, titratable acidity, and pH) over three seasons (2010, 2011, and 2012). Multi-locus association analyses, carried out using mrMLM 4.0 and FarmCPU R packages, revealed a total of 967 and 180 quantitative trait nucleotides (QTNs), respectively. Among the 88 consistently reliable QTNs detected using multiple multi-locus GWAS methods and/or at least two seasons, 44 were detected for the first time. Fruit quality hotspots were identified on chromosomes 1, 3, 4, 5, 6, and 8. Out of 566 candidate genes detected in the genomic regions harboring the QTN clusters, 435 were functionally annotated. Gene enrichment analyses revealed 68 different gene ontology (GO) terms associated with fruit quality traits. Data reported here advance our understanding of genetic mechanisms underlying important fruit quality traits and further support the development of DNA tools for breeding.

The cherry 6+9K SNP array: a cost-effective improvement to the cherry 6K SNP array for genetic studies.

Cherry breeding and genetic studies can benefit from genome-wide genetic marker assays. Currently, a 6K SNP array enables genome scans in cherry; however, only a third of these SNPs are informative, with low coverage in many genomic regions. Adding previously detected SNPs to this array could provide a cost-efficient upgrade with increased genomic coverage across the 670 cM/352.9 Mb cherry whole genome sequence. For sweet cherry, new SNPs were chosen following a focal point strategy, grouping six to eight SNPs within 10-kb windows with an average of 0.6 cM (627 kb) between focal points. Additional SNPs were chosen to represent important regions. Sweet cherry, the fruticosa subgenome of sour cherry, and cherry organellar genomes were targeted with 6942, 2020, and 38 new SNPs, respectively. The +9K add-on provided 2128, 1091, and 70 new reliable, polymorphic SNPs for sweet cherry and the avium and the fruticosa subgenomes of sour cherry, respectively. For sweet cherry, 1241 reliable polymorphic SNPs formed 237 informative focal points, with another 2504 SNPs in-between. The +9K SNPs increased genetic resolution and genome coverage of the original cherry SNP array and will help increase understanding of the genetic control of key traits and relationships among individuals in cherry.

Genetic Dissection of Bloom Time in Low Chilling Sweet Cherry (Prunus avium L.) Using a Multi-Family QTL Approach.

Bloom time in sweet cherry (Prunus avium L.) is a highly heritable trait that varies between genotypes and depends on the environmental conditions. Bud-break occurs after chill and heat requirements of each genotype are fulfilled, and dormancy is released. Bloom time is a critical trait for fruit production as matching cultivar adaptation to the growing area is essential for adequate fruit set. Additionally, low chilling cultivars are of interest to extend sweet cherry production to warmer regions, and for the crop adaptation to increasing winter and spring temperatures. The aim of this work is to investigate the genetic control of this trait by analyzing multiple families derived from the low chilling and extra-early flowering local Spanish cultivar 'Cristobalina' and other cultivars with higher chilling requirements and medium to late bloom times. Bloom time evaluation in six related sweet cherry populations confirmed a high heritability of this trait, and skewed distribution toward late flowering, revealing possible dominance of the late bloom alleles. SNP genotyping of the six populations (n = 406) resulted in a consensus map of 1269 SNPs. Quantitative trait loci (QTL) analysis using the Bayesian approach implemented by FlexQTL™ software revealed two major QTLs on linkage groups 1 and 2 (qP-BT1.1m and qP-BT2.1m) that explained 47.6% of the phenotypic variation. The QTL on linkage group 1 was mapped to a 0.26 Mbp region that overlaps with the DORMANCY ASSOCIATED MADS-BOX (DAM) genes. This finding is consistent with peach results that indicate that these genes are major determinants of chilling requirement in Prunus. Haplotype analysis of the linkage group 1 and 2 QTL regions showed that 'Cristobalina' was the only cultivar tested that contributed early bloom time alleles for these two QTLs. This work contributes to knowledge of the genetic control of chilling requirement and bloom date and will enable marker-assisted selection for low chilling in sweet cherry breeding programs.

A fruit firmness QTL identified on linkage group 4 in sweet cherry (Prunus avium L.) is associated with domesticated and bred germplasm.

Fruit firmness is an important market driven trait in sweet cherry (Prunus avium L.) where the desirable increase in fruit firmness is associated with landrace and bred cultivars. The aim of this work was to investigate the genetic basis of fruit firmness using plant materials that include wild cherry (syn. mazzard), landrace and bred sweet cherry germplasm. A major QTL for fruit firmness, named qP-FF4.1, that had not previously been reported, was identified in three sweet cherry populations. Thirteen haplotypes (alleles) associated with either soft or firm fruit were identified for qP-FF4.1 in the sweet cherry germplasm, and the "soft" alleles were dominant over the "firm" alleles. The finding that sweet cherry individuals that are homozygous for the "soft" alleles for qP-FF4.1 are exclusively mazzards and that the vast majority of the bred cultivars are homozygous for "firm" alleles suggests that this locus is a signature of selection. Candidate genes related to plant cell wall modification and various plant hormone signaling pathways were identified, with an expansin gene being the most promising candidate. These results advance our understanding of the genetic basis of fruit firmness and will help to enable the use of DNA informed breeding for this trait in sweet cherry breeding programs.

Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array.

The timing of fruit maturity is an important trait in sweet cherry production and breeding. Phenotypic variation for phenology of fruit maturity in sweet cherry appears to be under strong genetic control, but that control might be complicated by phenotypic instability across environments. Although such genotype-by-environment interaction (G × E) is a common phenomenon in crop plants, knowledge about it is lacking for fruit maturity timing and other sweet cherry traits. In this study, 1673 genome-wide SNP markers were used to estimate genomic relationships among 597 weakly pedigree-connected individuals evaluated over two seasons at three locations in Europe and one location in the USA, thus sampling eight 'environments'. The combined dataset enabled a single meta-analysis to investigate the environmental stability of genomic predictions. Linkage disequilibrium among marker loci declined rapidly with physical distance, and ordination of the relationship matrix suggested no strong structure among germplasm. The most parsimonious G × E model allowed heterogeneous genetic variance and pairwise covariances among environments. Narrow-sense genomic heritability was very high (0.60-0.83), as was accuracy of predicted breeding values (>0.62). Average correlation of additive effects among environments was high (0.96) and breeding values were highly correlated across locations. Results indicated that genomic models can be used in cherry to accurately predict date of fruit maturity for untested individuals in new environments. Limited G × E for this trait indicated that phenotypes of individuals will be stable across similar environments. Equivalent analyses for other sweet cherry traits, for which multiple years of data are commonly available among breeders and cultivar testers, would be informative for predicting performance of elite selections and cultivars in new environments.

High-quality, genome-wide SNP genotypic data for pedigreed germplasm of the diploid outbreeding species apple, peach, and sweet cherry through a common workflow.

High-quality genotypic data is a requirement for many genetic analyses. For any crop, errors in genotype calls, phasing of markers, linkage maps, pedigree records, and unnoticed variation in ploidy levels can lead to spurious marker-locus-trait associations and incorrect origin assignment of alleles to individuals. High-throughput genotyping requires automated scoring, as manual inspection of thousands of scored loci is too time-consuming. However, automated SNP scoring can result in errors that should be corrected to ensure recorded genotypic data are accurate and thereby ensure confidence in downstream genetic analyses. To enable quick identification of errors in a large genotypic data set, we have developed a comprehensive workflow. This multiple-step workflow is based on inheritance principles and on removal of markers and individuals that do not follow these principles, as demonstrated here for apple, peach, and sweet cherry. Genotypic data was obtained on pedigreed germplasm using 6-9K SNP arrays for each crop and a subset of well-performing SNPs was created using ASSIsT. Use of correct (and corrected) pedigree records readily identified violations of simple inheritance principles in the genotypic data, streamlined with FlexQTL software. Retained SNPs were grouped into haploblocks to increase the information content of single alleles and reduce computational power needed in downstream genetic analyses. Haploblock borders were defined by recombination locations detected in ancestral generations of cultivars and selections. Another round of inheritance-checking was conducted, for haploblock alleles (i.e., haplotypes). High-quality genotypic data sets were created using this workflow for pedigreed collections representing the U.S. breeding germplasm of apple, peach, and sweet cherry evaluated within the RosBREED project. These data sets contain 3855, 4005, and 1617 SNPs spread over 932, 103, and 196 haploblocks in apple, peach, and sweet cherry, respectively. The highly curated phased SNP and haplotype data sets, as well as the raw iScan data, of germplasm in the apple, peach, and sweet cherry Crop Reference Sets is available through the Genome Database for Rosaceae.

The therapeutic role of inhibition of miR-328 on pulmonary carcinoma induced by chlamydia pneumoniae through targeting histone H2AX.

Lung cancer represents a major healthy concern due to high incidence and morality. Increasing evidences showed critical regulatory role of microRNA (miR) in cell growth, differentiation and apoptosis. It has been indicated that the level of miR-328 is abnormally up regulated in lung cancer cell line, which is correlated with cell apoptosis. An in vitro lung cancer model was established through induction of chlamydia pneumonia. Western blot and real-time quantitative PCR were used to measure miR-328 level and its effects on histone H2AX expression. Bioinformatics analysis and luciferase reporter gene assay were to determine if H2AX was the direct target of miR-328. TUNEL assay, AV-PI staining and Caspase-3 activity assay measured the effect of the decrease of miR-328 on lung cancer cell apoptosis at both in vivo and in vitro level. Bioinformatics analysis predicted histone H2AX as the target of miR-328 during the regulation of lung cancer. Both in vivo and in vitro knockdown of miR-328 up-regulated H2AX expression and elevated TUNEL-positive cell number. In vivo down-regulation of miR-328 decreased incidence of lung cancer induced by chlamydia pneumoniae, suppressed tumor volume, increased caspase 3 activity, and facilitated tumor cell apoptosis. Histone protein H2AX serves as the target of miR-328 and participates in lung cancer regulation. Suppression of miR-328 level promotes lung cancer tissue apoptosis, which provides novel target for lung cancer therapy.

Elucidation of the 'Honeycrisp' pedigree through haplotype analysis with a multi-family integrated SNP linkage map and a large apple (Malus×domestica) pedigree-connected SNP data set.

The apple (Malus×domestica) cultivar Honeycrisp has become important economically and as a breeding parent. An earlier study with SSR markers indicated the original recorded pedigree of 'Honeycrisp' was incorrect and 'Keepsake' was identified as one putative parent, the other being unknown. The objective of this study was to verify 'Keepsake' as a parent and identify and genetically describe the unknown parent and its grandparents. A multi-family based dense and high-quality integrated SNP map was created using the apple 8 K Illumina Infinium SNP array. This map was used alongside a large pedigree-connected data set from the RosBREED project to build extended SNP haplotypes and to identify pedigree relationships. 'Keepsake' was verified as one parent of 'Honeycrisp' and 'Duchess of Oldenburg' and 'Golden Delicious' were identified as grandparents through the unknown parent. Following this finding, siblings of 'Honeycrisp' were identified using the SNP data. Breeding records from several of these siblings suggested that the previously unreported parent is a University of Minnesota selection, MN1627. This selection is no longer available, but now is genetically described through imputed SNP haplotypes. We also present the mosaic grandparental composition of 'Honeycrisp' for each of its 17 chromosome pairs. This new pedigree and genetic information will be useful in future pedigree-based genetic studies to connect 'Honeycrisp' with other cultivars used widely in apple breeding programs. The created SNP linkage map will benefit future research using the data from the Illumina apple 8 and 20 K and Affymetrix 480 K SNP arrays.

Contributions of Zea mays subspecies mexicana haplotypes to modern maize.

Maize was domesticated from lowland teosinte (Zea mays ssp. parviglumis), but the contribution of highland teosinte (Zea mays ssp. mexicana, hereafter mexicana) to modern maize is not clear. Here, two genomes for Mo17 (a modern maize inbred) and mexicana are assembled using a meta-assembly strategy after sequencing of 10 lines derived from a maize-teosinte cross. Comparative analyses reveal a high level of diversity between Mo17, B73, and mexicana, including three Mb-size structural rearrangements. The maize spontaneous mutation rate is estimated to be 2.17 × 10-8 ~3.87 × 10-8 per site per generation with a nonrandom distribution across the genome. A higher deleterious mutation rate is observed in the pericentromeric regions, and might be caused by differences in recombination frequency. Over 10% of the maize genome shows evidence of introgression from the mexicana genome, suggesting that mexicana contributed to maize adaptation and improvement. Our data offer a rich resource for constructing the pan-genome of Zea mays and genetic improvement of modern maize varieties.

Public Availability of a Genotyped Segregating Population May Foster Marker Assisted Breeding (MAB) and Quantitative Trait Loci (QTL) Discovery: An Example Using Strawberry.

Much of the cost associated with marker discovery for marker assisted breeding (MAB) can be eliminated if a diverse, segregating population is generated, genotyped, and made available to the global breeding community. Herein, we present an example of a hybrid, wild-derived family of the octoploid strawberry that can be used by other breeding programs to economically find and tag useful genes for MAB. A pseudo test cross population between two wild species of Fragaria virginiana and F. chiloensis (FVC 11) was generated and evaluated for a set of phenotypic traits. A total of 106 individuals in the FVC 11 were genotyped for 29,251 single nucleotide polymorphisms (SNPs) utilizing a commercially available, genome-wide scanning platform (Affymetrix Axiom IStraw90(TW)). The marker trait associations were deduced using TASSEL software. The FVC 11 population segregating for daughters per mother, inflorescence number, inflorescence height, crown production, flower number, fruit size, yield, internal color, soluble solids, fruit firmness, and plant vigor. Coefficients of variations ranged from 10% for fruit firmness to 68% for daughters per mother, indicating an underlying quantitative inheritance for each trait. A total of 2,474 SNPs were found to be polymorphic in FVC 11 and strong marker trait associations were observed for vigor, daughters per mother, yield and fruit weight. These data indicate that FVC 11 can be used as a reference population for quantitative trait loci detection and subsequent MAB across different breeding programs and geographical locations.

A randomized controlled study of selective microdochectomy guided by ductoscopic wire marking or methylene blue injection.

BACKGROUND: Methylene blue identification of lesions during microdochectomy is often inaccurate, resulting in large dissection and tissue damage. A wire placed via ductoscopy preoperatively into the pathologic duct may aid identification and reduce the amount of dissection required. METHODS: A total of 53 patients being evaluated for nipple discharge were randomized to receive ductoscopy with either methylene blue or wire marking of the lesion before microdochectomy. Patient clinical characteristics and surgical outcomes were evaluated. RESULTS: There were 28 patients who received methylene blue marking and 25 who received wire marking of the lesions. There were no differences between the demographic or clinical characteristics of the groups. Wire marking was associated with less surgical time, smaller incisions, and smaller surgical specimens, but the same diagnostic accuracy. CONCLUSIONS: Wire marking of lesions for microdochectomy is associated with less dissection and tissue damage than methylene blue, yet the same diagnostic accuracy.