QTLs Identification for Iron Chlorosis in a Segregating Peach-Almond Progeny Through Double-Digest Sequence-Based Genotyping (SBG).

Linkage maps are highly appreciated tools for cultivar and rootstock breeding programs because they are suitable for genetic and genomic studies. In this study, we report on using sequence-based genotyping (SBG) approach to simultaneously discover and genotype SNPs from two peach-based rootstocks ("Adafuel" and "Flordaguard") and their progeny (n = 118): from a initial mapping population composed of 131 seedlings. The plant material was developed at the EEAD-CSIC Prunus rootstocks breeding program, aiming to obtain a segregating progeny for a range of characters of agronomical interest to rootstock breeding (iron-chlorosis and root-asphyxia tolerance, nematode resistance, vigor traits, and other effects on scion cultivars). Sequence reads obtained from double-digest SBG were aligned to the P. persica reference genome (Peach v2.0). While eight linkage groups were constructed for "Adafuel," only four linkage groups were constructed for "Flordaguard," given the low heterozygosity of this last genotype. High synteny and co-linearity were observed between obtained maps and Peach v2.0. On the other hand, this work aimed to elucidate the genetic basis of leaf chlorosis tolerance using the phenotypic segregation of the progeny to iron-chlorosis tolerance, along with the QTLs responsible for leaf chlorosis. The F1 mapping population, composed initially of 131 seedlings, was growing in four field trials established on calcareous soils at the experimental field of the EEAD-CSIC in Zaragoza, Spain. From the initial mapping population, 131 individuals were selected for their phenotypical characterization with SPAD measurements of plants grown in the field, exhibiting a great variability. Significant QTLs associated with tolerance to iron chlorosis were found in LG1, LG5, LG7, and LG8. The significant QTLs detected in LG5 and LG7 have not been associated with this abiotic stress before in Prunus. Several candidate genes such as Prupe.1G541100, predicted as glutamyl-tRNA reductase 1, Prupe.1G468200, encoding a 2-oxoglutarate (2OG), and Fe(II)-dependent oxygenase superfamily protein or Prupe.1G577000 (ppa011050.m), a NIFU-like protein 2 (NIFU2) were detected. The exact biological function of some of these genes should be verified for the future development of marker-assisted selection for peach iron chlorosis tolerance.

Bioinformatic approach for the discovery of cis-eQTL signals during fruit ripening of a woody species as grape (Vitis vinifera L.).

Expression quantitative trait loci (eQTLs) are associations between genetic variants, such as Single Nucleotide Polymorphisms (SNPs), and gene expression. eQTLs are an important tool to understand the genetic variance of gene expression of complex phenotypes. eQTLs analyses are common in biomedical models but are scarce in woody crop species such as fruit trees or grapes. In this study, a comprehensive bioinformatic analysis was conducted leveraging with expression data from two different growth stages, around ripening onset, of 10 genotypes of grape (Vitis vinifera L.). A total of 2170 cis-eQTL were identified in 212 gene modulated at ripening onset. The 48% of these DEGs have a known function. Among the annotated protein-coding genes, terpene synthase, auxin-regulatory factors, GRFS, ANK_REP_REGION domain-containing protein, Kinesin motor domain-containing protein and flavonol synthase were noted. This new inventory of cis-eQTLs influencing gene expression during fruit ripening will be an important resource to examine variation for this trait and will help to elucidate the complex genetic architecture underlying this process in grape.

Analysis of Metabolites and Gene Expression Changes Relative to Apricot (Prunus armeniaca L.) Fruit Quality During Development and Ripening.

Apricot (Prunus armeniaca L.) is a valuable worldwide agronomical crop, with a delicious fruit highlighted as a functional food with both nutritional and bioactive properties, remarkably beneficial to human health. Apricot fruit ripening is a coordinated developmental process which requires change in the expression of hundreds to thousands of genes to modify many biochemical and physiological processes arising from quality characteristics in ripe fruit. In addition, enhancing fruit and nutraceutical quality is one of the central objectives to be improved in the new varieties developed by breeding programs. In this study we analyzed the contents of main metabolites linked to the nutraceutical value of apricot fruits, together with the most important pomological characteristics and biochemical contents of fruit during the ripening process in two contrasted apricot genotypes. Additionally, the gene expression changes were analyzed using RNA-Seq and real time qPCR. Results showed that genes with differential expression in the biosynthetic pathways, such as phenylpropanoids, flavonoids, starch and sucrose and carotenoid metabolism, could be possible candidates as molecular markers of fruit quality characteristics for fruit color and soluble solid content. The gene involves in carotenoid metabolism carotenoid cleavage dioxygenase 4, and the gene sucrose synthase in starch and sucrose metabolism were identified as candidate genes in the ripening process for white skin ground color and flesh color and high soluble sugar content. The application of these candidate genes on marker-assisted selection in apricot breeding programs may contribute to the early selection of high-quality fruit genotypes with suitable nutraceutical values.

YeATS - a tool suite for analyzing RNA-seq derived transcriptome identifies a highly transcribed putative extensin in heartwood/sapwood transition zone in black walnut.

The transcriptome provides a functional footprint of the genome by enumerating the molecular components of cells and tissues. The field of transcript discovery has been revolutionized through high-throughput mRNA sequencing (RNA-seq). Here, we present a methodology that replicates and improves existing methodologies, and implements a workflow for error estimation and correction followed by genome annotation and transcript abundance estimation for RNA-seq derived transcriptome sequences (YeATS - Yet Another Tool Suite for analyzing RNA-seq derived transcriptome). A unique feature of YeATS is the upfront determination of the errors in the sequencing or transcript assembly process by analyzing open reading frames of transcripts. YeATS identifies transcripts that have not been merged, result in broken open reading frames or contain long repeats as erroneous transcripts. We present the YeATS workflow using a representative sample of the transcriptome from the tissue at the heartwood/sapwood transition zone in black walnut. A novel feature of the transcriptome that emerged from our analysis was the identification of a highly abundant transcript that had no known homologous genes (GenBank accession: KT023102). The amino acid composition of the longest open reading frame of this gene classifies this as a putative extensin. Also, we corroborated the transcriptional abundance of proline-rich proteins, dehydrins, senescence-associated proteins, and the DNAJ family of chaperone proteins. Thus, YeATS presents a workflow for analyzing RNA-seq data with several innovative features that differentiate it from existing software.