bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2021.09.08.459382

Genome sequencing and analysis of two early-flowering cherry (Cerasus x kanzakura) varieties, 'Kawazu-zakura' and 'Atami-zakura'

Shirasawa, K.·Itai, A.·Isobe, S.
View original source ↗Export metadata ↓

Abstract

To gain genetic insights into the early-flowering phenotype of ornamental cherry, also known as sakura, we determined the genome sequences of two early-flowering cherry (Cerasus x kanzakura) varieties, Kawazu-zakura and Atami-zakura. Since the two varieties are interspecific hybrids, likely derived from crosses between Cerasus campanulata (early-flowering species) and Cerasus speciosa, we employed the haplotype-resolved sequence assembly strategy. Genome sequence reads obtained from each variety by single molecule real-time sequencing (SMRT) were split into two subsets, based on the genome sequence information of the two probable ancestors, and assembled to obtain haplotype-phased genome sequences. The resultant genome assembly of Kawazu-zakura spanned 519.8 Mb with 1,544 contigs and an N50 value of 1,220.5 kb, while that of Atami-zakura totaled 509.6 Mb with 2,180 contigs and an N50 value of 709.1 kb. A total of 72,702 and 72,528 potential protein-coding genes were predicted in the genome assemblies of Kawazu-zakura and Atami-zakura, respectively. Gene clustering analysis identified 2,634 clusters uniquely presented in the C. campanulata haplotype sequences, which might contribute to its early-flowering phenotype. Genome sequences determined in this study provide fundamental information for elucidating the molecular and genetic mechanisms underlying the early-flowering phenotype of ornamental cherry tree varieties and their relatives.

Source connections

Explore related subjects

genomicsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Shirasawa, K., Itai, A., Isobe, S.. 2021-09-09. Genome sequencing and analysis of two early-flowering cherry (Cerasus x kanzakura) varieties, 'Kawazu-zakura' and 'Atami-zakura'. https://doi.org/10.1101/2021.09.08.459382

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Sequence and epigenetic characterization of chromosome 21 centromeres in a family with recurrent Trisomy 21

Trisomy 21 (T21) is the most common genetic cause of intellectual disability, yet the molecular mechanisms underlying maternal meiosis I errors--responsible for ~70% of free T21 cases--remain poorly understood. In this preliminary study, we used long-read sequencing and genome assembly to investigate the DNA sequence and epigenetic features of chromosome 21 (chr21) centromeres in a family with recurrent free T21 due to maternal meiosis I errors. The mother, who had two affected and three unaffected children, showed no mosaicism or structural rearrangements. One of her two chr21 centromeres lacked a pronounced centromere dip region (CDR), displaying instead a diffuse hypomethylation pattern (dCDR) with much higher methylated CpG levels (55%) compared to its homologue (36%). This dCDR was transmitted to an unaffected child and the affected proband analyzed, suggesting it was present in one of the maternal chr21 since she was at least 32 years of age. Chr21 dCDRs were not observed in seven young mothers with children with T21 or previously described in the literature in 108 population haplotypes. We hypothesize that dCDRs may weaken kinetochore function, increasing nondisjunction risk, and propose two models linking such epigenetic variation to maternal age-related T21 risk. These findings highlight the value of complete centromere characterization in families with children with T21 and suggest centromere methylation status of chr21 as a potential T21 risk factor for future investigation.

genomics↗
bioRxiv2026

Single-Cell Analytics for Dose Response (SCADR) discriminates PTEN missense variants by lipid and protein phosphatase dysfunction

The proliferation of sequencing efforts has revealed a vast and expanding catalog of single nucleotide gene variants, many associated to, but with unclear roles in disease. Fully charactering variant impacts and linking specific protein dysfunctions to disease are challenging due to the multi-functional nature of many proteins and varying degree of variant effects on these functions. Lagging are sensitive approaches to empirically assess the impact of missense variant-induced single amino acid changes on a wide range of protein functions. To address these issues, we have developed an open-source computational analysis tool called SCADR (Single-Cell Analytics for Dose Response) for simultaneously measuring and comparing impacts of exogenously-expressed variants on multiple signaling pathways using multiplex phospho-antibody spectral flow cytometry in human cell lines. SCADR retains and correlates single-cell measures of signal protein activity states along with expression levels of exogenously-expressed variants, providing rich characterization of multiple protein functions, signaling protein interactions, and enhanced discrimination of variant impacts on different signaling pathways, highlighting each variants unique dysfunction profile. Here, we apply SCADR for analyses of the impact of 6 variants of the tumor-suppressor protein PTEN (P38H, C124S, G129E, Y138L, D268E, 4A) expressed in HEK293 cells on the phosphorylation states of the canonical and noncanonical downstream signaling proteins Akt, S6, CREB, ERK, and p38 detected with fluorophore-conjugated phospho-antibodies, along with an antibody detecting an N-terminal HA tag on PTEN variants allowing measures of dose-response effects of each variants expression on signaling cascades. Results identify variant-specific impacts on downstream signaling cascades.

genomics↗
bioRxiv2026

Microsecond molecular dynamics of SOD1 variants suggest a structural basis for divergent ALS clinical outcomes

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterised by progressive motor neuron degeneration. Mutations in the SOD1 gene represent the second most common genetic cause of ALS (ALS), and distinct SOD1 missense variants present with markedly different clinical profiles. A4V leads to an aggressive form of the disease (median survival [~]1y), H46R confers a mild, slowly progressive course and I113T exhibits an intermediate phenotype. The molecular basis by which these mutations produce divergent clinical outcomes remains poorly understood. We performed extensive classical molecular dynamics simulations of wild-type SOD1 and the three ALS-associated variants in the apo monomeric state to attempt to investigate the mechanisms behind such phenotypic differences. Structural stability, global compactness, and conformational flexibility, as well as analysis of collective motions between residues and estimation of free energy, were assessed. The H46R, A4V, and I113T variants exhibited distinct dynamic behaviours, highlighting differences in structural stability, local flexibility, and intramolecular interactions. These findings suggest that specific structural regions may contribute differently to protein dysfunction and could represent key elements for understanding the relationship between molecular dynamic properties and the differing clinical severity associated with these variants. Most strikingly, H46R exhibited exceptional structural stability across every analytical level, the lowest global deviation, most attenuated local flexibility, strongest internal dynamic coordination, and the deepest, most confined free energy basins of any system examined. This convergent multi-layered evidence of structural restraint provides a compelling mechanistic basis for the mild and slowly progressive clinical course of H46R ALS, suggesting that enhanced conformational rigidity, rather than bulk destabilisation, is the defining biophysical feature of this variant, and that its pathogenic mechanism operates through a route fundamentally decoupled from the aggregation-driven toxicity that characterises the more aggressive SOD1-ALS mutations.

genomics↗