LUIS DIAZ-GARCIA

Dr. LUIS DIAZ-GARCIA


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 October 2023 in Horticulture Research
Verified
Journal Article
Open access
PDF file
AYAlan E Yocca
Alan E Yocca
APAdrian Platts
Adrian Platts
EAElizabeth Alger
Elizabeth Alger
STScott Teresi
Scott Teresi
MMMolla F Mengist
Molla F Mengist
PEPatrick P Edger
Patrick P Edger
Domestication of cranberry and blueberry began in the United States in the early 1800s and 1900s, respectively, and in part owing to their flavors and health-promoting benefits are now cultivated and consumed worldwide. The industry continues to face a wide variety of production challenges (e.g. disease pressures), as well as a demand for higher-yielding cultivars with improved fruit quality characteristics. Unfortunately, molecular tools to help guide breeding efforts for these species have been relatively limited compared with those for other high-value crops. Here, we describe the construction and analysis of the first pangenome for both blueberry and cranberry. Our analysis of these pangenomes revealed both crops exhibit great genetic diversity, including the presence–absence variation of 48.4% genes in highbush blueberry and 47.0% genes in cranberry. Auxiliary genes, those not shared by all cultivars, are significantly enriched with molecular functions associated with disease resistance and the biosynthesis of specialized metabolites, including compounds previously associated with improving fruit quality traits. The discovery of thousands of genes, not present in the previous reference genomes for blueberry and cranberry, will serve as the basis of future research and as potential targets for future breeding efforts. The pangenome, as a multiple-sequence alignment, as well as individual annotated genomes, are publicly available for analysis on the Genome Database for Vaccinium—a curated and integrated web-based relational database. Lastly, the core-gene predictions from the pangenomes will serve useful to develop a community genotyping platform to guide future molecular breeding efforts across the family.

21 April 2016 in BMC Genetics
Verified
Journal Article
Open access
PDF file
GCGiovanny Covarrubias-Pazaran
Giovanny Covarrubias-Pazaran
LDLUIS DIAZ-GARCIA
LUIS DIAZ-GARCIA
Brandon SchlautmanBrandon Schlautman
Brandon Schlautman
WSWalter Salazar
Walter Salazar
JZJuan Zalapa
Juan Zalapa
Determination of microsatellite lengths or other DNA fragment types is an important initial component of many genetic studies such as mutation detection, linkage and quantitative trait loci (QTL) mapping, genetic diversity, pedigree analysis, and detection of heterozygosity. A handful of commercial and freely available software programs exist for fragment analysis; however, most of them are platform dependent and lack high-throughput applicability. We present the R package Fragman to serve as a freely available and platform independent resource for automatic scoring of DNA fragment lengths diversity panels and biparental populations. The program analyzes DNA fragment lengths generated in Applied Biosystems® (ABI) either manually or automatically by providing panels or bins. The package contains additional tools for converting the allele calls to GenAlEx, JoinMap® and OneMap software formats mainly used for genetic diversity and generating linkage maps in plant and animal populations. Easy plotting functions and multiplexing friendly capabilities are some of the strengths of this R package. Fragment analysis using a unique set of cranberry (Vaccinium macrocarpon) genotypes based on microsatellite markers is used to highlight the capabilities of Fragman. Fragman is a valuable new tool for genetic analysis. The package produces equivalent results to other popular software for fragment analysis while possessing unique advantages and the possibility of automation for high-throughput experiments by exploiting the power of R.

12 September 2018 in Frontiers in Plant Science
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Journal Article
Open access
PDF file
GCGiovanny Covarrubias-Pazaran
Giovanny Covarrubias-Pazaran
Brandon SchlautmanBrandon Schlautman
Brandon Schlautman
LDLUIS DIAZ-GARCIA
LUIS DIAZ-GARCIA
EGEdward Grygleski
Edward Grygleski
JPJames Polashock
James Polashock
JZJuan Zalapa
Juan Zalapa
The development of high-throughput genotyping has made genome-wide association (GWAS) and genomic selection (GS) applications possible for both model and non-model species. The exploitation of genome-assisted approaches could greatly benefit breeding efforts in American cranberry (Vaccinium macrocarpon) and other minor crops. Using biparental populations with different degrees of relatedness, we evaluated multiple GS methods for total yield (TY) and mean fruit weight (MFW). Specifically, we compared predictive ability (PA) differences between univariate and multivariate genomic best linear unbiased predictors (GBLUP and MGBLUP, respectively). We found that MGBLUP provided higher predictive ability (PA) than GBLUP, in scenarios with medium genetic correlation (8–17% increase with corg~0.6) and high genetic correlations (25–156% with corg~0.9), but found no increase when genetic correlation was low. In addition, we found that only a few hundred single nucleotide polymorphism (SNP) markers are needed to reach a plateau in PA for both traits in the biparental populations studied (in full linkage disequilibrium). We observed that higher resemblance among individuals in the training (TP) and validation (VP) populations provided greater PA. Although multivariate GS methods are available, genetic correlations and other factors need to be carefully considered when applying these methods for genetic improvement.

10 February 2021 in Frontiers in Plant Science
Verified
Journal Article
Open access
PDF file
LDLUIS DIAZ-GARCIA
LUIS DIAZ-GARCIA
LGLuis Garcia-Ortega
Luis Garcia-Ortega
MGMaria González-Rodríguez
Maria González-Rodríguez
LDLuis Delaye
Luis Delaye
MIMassimo Iorizzo
Massimo Iorizzo
JZJuan Zalapa
Juan Zalapa
The American cranberry (Vaccinium macrocarpon Ait.) is an iconic North American fruit crop of great cultural and economic importance. Cranberry can be considered a fruit crop model due to its unique fruit nutrient composition, overlapping generations, recent domestication, both sexual and asexual reproduction modes, and the existence of cross-compatible wild species. Development of cranberry molecular resources started very recently; however, further genetic studies are now being limited by the lack of a high-quality genome assembly. Here, we report the first chromosome-scale genome assembly of cranberry, cultivar Stevens, and a draft genome of its close wild relative species Vaccinium microcarpum. More than 92% of the estimated cranberry genome size (492 Mb) was assembled into 12 chromosomes, which enabled gene model prediction and chromosome-level comparative genomics. Our analysis revealed two polyploidization events, the ancient γ-triplication, and a more recent whole genome duplication shared with other members of the Ericaeae, Theaceae and Actinidiaceae families approximately 61 Mya. Furthermore, comparative genomics within the Vaccinium genus suggested cranberry-V. microcarpum divergence occurred 4.5 Mya, following their divergence from blueberry 10.4 Mya, which agrees with morphological differences between these species and previously identified duplication events. Finally, we identified a cluster of subgroup-6 R2R3 MYB transcription factors within a genomic region spanning a large QTL for anthocyanin variation in cranberry fruit. Phylogenetic analysis suggested these genes likely act as anthocyanin biosynthesis regulators in cranberry. Undoubtedly, these new cranberry genomic resources will facilitate the dissection of the genetic mechanisms governing agronomic traits and further breeding efforts at the molecular level.

2 July 2018 in Molecular Genetics and Genomics
Verified
Journal Article
Closed access
PDF file
LDLUIS DIAZ-GARCIA
LUIS DIAZ-GARCIA
Brandon SchlautmanBrandon Schlautman
Brandon Schlautman
GCGiovanny Covarrubias-Pazaran
Giovanny Covarrubias-Pazaran
AMAndrew Maule
Andrew Maule
JJJennifer Johnson-Cicalese
Jennifer Johnson-Cicalese
JZJuan Zalapa
Juan Zalapa

15 August 2018 in PeerJ
Verified
Journal Article
Open access
PDF file
LDLUIS DIAZ-GARCIA
LUIS DIAZ-GARCIA
GCGiovanny Covarrubias-Pazaran
Giovanny Covarrubias-Pazaran
Brandon SchlautmanBrandon Schlautman
Brandon Schlautman
EGEdward Grygleski
Edward Grygleski
JZJuan Zalapa
Juan Zalapa
Image-based phenotyping methodologies are powerful tools to determine quality parameters for fruit breeders and processors. The fruit size and shape of American cranberry (Vaccinium macrocarponL.) are particularly important characteristics that determine the harvests’ processing value and potential end-use products (e.g., juice vs. sweetened dried cranberries). However, cranberry fruit size and shape attributes can be difficult and time consuming for breeders and processors to measure, especially when relying on manual measurements and visual ratings. Therefore, in this study, we implemented image-based phenotyping techniques for gathering data regarding basic cranberry fruit parameters such as length, width, length-to-width ratio, and eccentricity. Additionally, we applied a persistent homology algorithm to better characterize complex shape parameters. Using this high-throughput artificial vision approach, we characterized fruit from 351 progeny from a full-sib cranberry population over three field seasons. Using a covariate analysis to maximize the identification of well-supported quantitative trait loci (QTL), we found 252 single QTL in a 3-year period for cranberry fruit size and shape descriptors from which 20% were consistently found in all years. The present study highlights the potential for the identified QTL and the image-based methods to serve as a basis for future explorations of the genetic architecture of fruit size and shape in cranberry and other fruit crops.