Biology subjects

Eduardo, I.

Publications and source records attributed to Eduardo, I..

3 recordsLinked to original sources

bioRxiv2023

First large-scale peach gene coexpression network: A new tool for predicting gene function

Transcriptomics studies generate enormous amounts of biological information. Nowadays, representing this complex data as gene coexpression networks (GCNs) is becoming commonplace. Peach is a model for Prunus genetics and genomics, but identifying and validating genes associated to peach breeding traits is a complex task. A GCN capable of capturing stable gene-gene relationships would help researchers overcome the intrinsic limitations of peach genetics and genomics approaches and outline future research opportunities. In this study, we created the first large-scale GCN in peach, applying aggregated and non-aggregated methods to create four GCNs from 604 Illumina RNA-Seq libraries. We evaluated the performance of every GCN in predicting functional annotations using a machine-learning algorithm based on the guilty-by-association principle. The GCN with the best performance was COO300, encompassing 21,956 genes and an average AUROC of 0.746. To validate its performance predicting gene function, we used two well-characterized genes involved in fruit flesh softening in peach: the endopolygalacturonases PpPG21 and PpPG22. Genes coexpressing with PpPG21 and PpPG22 were extracted and named as melting flesh (MF) subnetwork. Finally, we performed an enrichment analysis of MF subnetwork and compared the results with the current knowledge regarding peach fruit softening process. The MF subnetwork mainly included genes involved in cell wall expansion and remodeling, with expression triggered by ripening-related phytohormones such as ethylene, auxin and methyl jasmonates. All these processes are closely related with peach fruit softening and therefore related to the function of PpPG21 and PpPG22. These results validate COO300 as a powerful tool for peach and Prunus research. COO300, renamed as PeachGCN v1.0, and the scripts necessary to perform a function prediction analysis using it, are available at https://github.com/felipecobos/PeachGCN.

genetics↗

bioRxiv2020

PEDIGREE ANALYSIS OF 222 ALMOND GENOTYPES REVEALS TWO WORLD MAINSTREAM BREEDING LINES BASED ON ONLY THREE DIFFERENT CULTIVARS

Loss of genetic variability is a steadily increasing challenge in tree breeding programs due to the repeated use of a reduced number of founder genotypes. High-quality pedigree data of 222 almond [Prunus dulcis (Miller) D.A. Webb, syn. P. amygdalus (L) Batsch] cultivars and breeding selections were used to study global genetic variability in modern breeding programs from Argentina, Australia, France, Greece, Israel, Italy, Russia, Spain and the USA. Inbreeding coefficients, pairwise relatedness and genetic contribution were calculated for these genotypes. The results reveal two mainstream breeding lines based on three cultivars from two different geographical regions: Tuono- Cristomorto (local landraces from Puglia, Italy) and Nonpareil (chance seedling selected in California, USA, from French original stock). Direct descendants from Tuono or Cristomorto number 75 (sharing 30 descendants), while Nonpareil has 72 direct descendants. The mean inbreeding coefficient of the analyzed genotypes was 0.036, with 13 genotypes presenting a high inbreeding coefficient, over 0.250. Breeding programs from the USA, France and Spain showed inbreeding coefficients of 0.067, 0.050 and 0.034, respectively. According to their genetic contribution, modern cultivars from Israel, France, the USA, Spain and Australia, trace back to six, five, four, four and two main founding genotypes respectively. Among the group of 65 genotypes carrying the Sf allele for self-compatibility, the mean relatedness coefficient was 0.133, with Tuono as the main founding genotype (23.75% of total genetic contribution). Increasing as well as preserving current genetic variability is required in almond breeding programs worldwide to assure genetic gain and continuing breeding progress. Breeding objectives, apart from high and efficient productivity, should include disease resistance and adaptation to climate change. Ultimately, any new commercial almond cultivar has to be economically viable and breeders play a critical role in achieving this goal.

genetics↗

bioRxiv2020

Resynthesis: Marker-based partial reconstruction of elite genotypes in clonally-reproducing plant species

We propose a method for marker-based selection of cultivars of clonally-reproducing plant species which keeps the basic genetic architecture of a top-performing cultivar (usually a partly heterozygous genotype), with some agronomically relevant differences (such as production time, product appearance or quality), providing added value to the product or cultivation process. The method is based on selecting a) two complementary nearly-inbred lines from successive selfing generations (ideally only F2 and F3) of large size, that may generate individuals with most of their genome identical to the original cultivar but being homozygous for either of the two component haplotypes in the rest, and b) individuals with such characteristics already occurring in the F2. Option a) allows for introgressing genes from other individuals in one or both of these nearly-inbred lines. Peach, a woody-perennial, clonally-reproduced species, was chosen as a model for a proof of concept of the Resynthesis process due to its biological characteristics: self-compatibility, compact and genetically well-known genome, low recombination rates and relatively short intergeneration time (3-4 years). From 416 F2 seedlings from cultivar Sweet Dream (SD), we obtained seven individuals with 76-94% identity with SD, and selected five pairs of complementary lines with average homozygosity of the two parents [≥]0.70 such that crossing would produce some individuals highly similar to SD. The application of this scheme to other species with more complex genomes or biological features, including its generalization to F1 hybrids, is discussed.

genetics↗