SignificanceWe sequenced the genome and transcriptomes of the wild olive (oleaster). More than 50,000 genes were predicted, and evidence was found for two relatively recent whole-genome duplication events, dated at about 28 and 59 million years ago. Whole genome sequencing, as well as gene expression studies, provide further insights into the evolution of oil biosynthesis, and will aid future studies aimed at further increasing the production of olive oil, which is a key ingredient of the healthy Mediterranean diet and has been granted a qualified health claim by FDA. 5 AbstractHere, we present the genome sequence and annotation of the wild olive tree (Olea europaea var. sylvestris), called oleaster, which is considered an ancestor of cultivated olive trees. More than 50,000 protein-coding genes were predicted, a majority of which could be anchored to 23 pseudo-chromosomes obtained through a newly constructed genetic map. The oleaster genome contains signatures of two Oleaceae-lineage specific paleopolyploidy events, dated at approximately 28 and 59 million years ago. These events contributed to the expansion and neofunctionalization of genes and gene families that play important roles in oil biosynthesis.The functional divergence of oil biosynthesis pathway genes, such as FAD2, SACPD, EAR and ACPTE, following duplication, has been responsible for the differential accumulation of oleic and linoleic acids produced in olive compared to sesame, a closely related oil crop. Duplicated oleaster FAD2 genes are regulated by a short-interfering RNA (siRNA) derived from a transposable element-rich region, leading to suppressed levels of FAD2 gene expression.Additionally, neofunctionalization of members of the SACPD gene family has led to increased expression of SACPD2, 3, 5 and 7, consequently resulting in an increased desaturation of steric acid. Taken together, decreased FAD2 expression and increased SACPD expression likely explain the accumulation of exceptionally high levels of oleic acid in olive. The oleaster genome thus provides important insights into the evolution of oil biosynthesis and will be a valuable resource for oil crop genomics. 6 /bodyAs a symbol of peace, fertility, health and longevity, the olive tree (Olea europaea L.) is a socio-economically important oil crop that is widely grown in the Mediterranean Basin.Belonging to the Oleaceae family (order Lamiales), it can biosynthesize essential unsaturated fatty acids and other important secondary metabolites, such as vitamins and phenolic compounds (1). The olive tree is a diploid (2n = 46) allogamous crop that can be vegetatively propagated and live for thousands of years (2). Paleobotanical evidence suggests that olive oil was already produced in the Bronze Age (3). It has been thought that cultivated varieties were derived from the wild olive tree, called oleaster (O. europaea var. sylvestris), in Asia Minor, which then spread to Greece (4). Nevertheless, the exact domestication history of the olive tree is unknown (5). Due to their longevity, oleaster...

Two types of resistant soybean (Glycine max (L.) Merr.) sources are widely used against soybean cyst nematode (SCN, Heterodera glycines Ichinohe). These include Peking-type soybean, whose resistance requires both the rhg1-a and Rhg4 alleles, and PI 88788-type soybean, whose resistance requires only the rhg1-b allele. Multiple copy number of PI 88788-type GmSNAP18, GmAAT, and GmWI12 in one genomic segment simultaneously contribute to rhg1-b resistance. Using an integrated set of genetic and genomic approaches, we demonstrate that the rhg1-a Peking-type GmSNAP18 is sufficient for resistance to SCN in combination with Rhg4. The two SNAPs (soluble NSF attachment proteins) differ by only five amino acids. Our findings suggest that Peking-type GmSNAP18 is performing a different role in SCN resistance than PI 88788-type GmSNAP18. As such, this is an example of a pathogen resistance gene that has evolved to underlie two types of resistance, yet ensure the same function within a single plant species.

Proteins with Tetratricopeptide-repeat (TPR) domains are encoded by large gene families and distributed in all plant lineages. In this study, the Soluble NSF-Attachment Protein (SNAP) subfamily of TPR containing proteins is characterized. In soybean, five members constitute the SNAP gene family: GmSNAP18, GmSNAP11, GmSNAP14, GmSNAP02, and GmSNAP09. Recently, GmSNAP18 has been reported to mediate resistance to soybean cyst nematode (SCN). Using a population of recombinant inbred lines from resistant and susceptible parents, the divergence of the SNAP gene family is analysed over time. Phylogenetic analysis of SNAP genes from 22 diverse plant species showed that SNAPs were distributed in six monophyletic clades corresponding to the major plant lineages. Conservation of the four TPR motifs in all species, including ancestral lineages, supports the hypothesis that SNAPs were duplicated and derived from a common ancestor and unique gene still present in chlorophytic algae. Syntenic analysis of regions harbouring GmSNAP genes in soybean reveals that this family expanded from segmental and tandem duplications following a tetraploidization event. qRT-PCR analysis of GmSNAPs indicates a co-regulation following SCN infection. Finally, genetic analysis demonstrates that GmSNAP11 contributes to an additive resistance to SCN. Thus, GmSNAP11 is identified as a novel minor gene conferring resistance to SCN.

Summary Soybean cyst nematode ( SCN ) is the most devastating plant‐parasitic nematode. Most commercial soybean varieties with SCN resistance are derived from PI 88788. Resistance derived from PI 88788 is breaking down due to narrow genetic background and SCN population shift. PI 88788 requires mainly the rhg1‐b locus, while ‘Peking’ requires rhg1‐a and Rhg4 for SCN resistance. In the present study, whole genome re‐sequencing of 106 soybean lines was used to define the Rhg haplotypes and investigate their responses to the SCN HG ‐Types. The analysis showed a comprehensive profile of SNP s and copy number variations ( CNV ) at these loci. CNV of rhg1 (Gm SNAP 18) only contributed towards resistance in lines derived from PI 88788 and ‘Cloud’. At least 5.6 copies of the PI 88788‐type rhg1 were required to confer SCN resistance, regardless of the Rhg4 ( Gm SHMT 08 ) haplotype. However, when the Gm SNAP 18 copies dropped below 5.6, a ‘Peking’‐type Gm SHMT 08 haplotype was required to ensure SCN resistance. This points to a novel mechanism of epistasis between Gm SNAP 18 and Gm SHMT 08 involving minimum requirements for copy number. The presence of more Rhg4 copies confers resistance to multiple SCN races. Moreover, transcript abundance of the Gm SHMT 08 in root tissue correlates with more copies of the Rhg4 locus, reinforcing SCN resistance. Finally, haplotype analysis of the Gm SHMT 08 and Gm SNAP 18 promoters inferred additional levels of the resistance mechanism. This is the first report revealing the genetic basis of broad‐based resistance to SCN and providing new insight into epistasis, haplotype‐compatibility, CNV , promoter variation and its impact on broad‐based disease resistance in plants.

Although they are staple foods in cuisines globally, many commercial fruit varieties have become progressively less flavorful over time. Due to the cost and difficulty associated with flavor phenotyping, breeding programs have long been challenged in selecting for this complex trait. To address this issue, we leveraged targeted metabolomics of diverse tomato and blueberry accessions and their corresponding consumer panel ratings to create statistical and machine learning models that can predict sensory perceptions of fruit flavor. Using these models, a breeding program can assess flavor ratings for a large number of genotypes, previously limited by the low throughput of consumer sensory panels. The ability to predict consumer ratings of liking, sweet, sour, umami, and flavor intensity was evaluated by a 10-fold cross-validation, and the accuracies of 18 different models were assessed. The prediction accuracies were high for most attributes and ranged from 0.87 for sourness intensity in blueberry using XGBoost to 0.46 for overall liking in tomato using linear regression. Further, the best-performing models were used to infer the flavor compounds (sugars, acids, and volatiles) that contribute most to each flavor attribute. We found that the variance decomposition of overall liking score estimates that 42% and 56% of the variance was explained by volatile organic compounds in tomato and blueberry, respectively. We expect that these models will enable an earlier incorporation of flavor as breeding targets and encourage selection and release of more flavorful fruit varieties.