Search bioRxiv⌕ Search

Biology subjects

Doi, K.

Publications and source records attributed to Doi, K..

3 recordsLinked to original sources
bioRxiv2026

A comprehensive temporal proteome and phosphoproteome dataset of Y1 adrenocortical cells under FGF2 stimulation and SOS inhibition

The Y1 mouse adrenocortical tumor cell line is a classic model for cancer studies and ACTH mediated steroidogenesis. The KRAS gene amplification and SOS mediated activation sustain elevated ERK levels, which drive the tumor phenotype of this cell line. In addition, the mitogen FGF2 induces atypical cytotoxic stress and consequent cell death rather than proliferation in this system, imposing a strong perturbation on KRAS ERK signaling dynamics. Recent research from our group revealed that SOS is not solely responsible for KRAS activation in the Y1 cells, indicating a more complex regulatory landscape of GEFs and GAPs. This motivated the generation of a comprehensive time resolved proteome (DIA) and TMT phosphoproteome (DDA) in a 0 to 30 minute time course under FGF2 stimulation or combined with SOS inhibitor, with the presence or absence of FBS stimulation, in technical triplicate using Q Exactive and Thermo Lumos mass spectrometers, respectively. This dataset can enable latent mechanisms between the life and death switch caused by FGF2 signaling and the alternate stress response caused by impaired SOS dependent activation. This analysis yielded 14,512 phosphosites and 8,919 protein groups, where 10,471 phosphosites and 111 protein groups showed differential abundance with statistical significance (limma, FDR < 0.05%). This dataset provides a versatile resource for downstream applications, which includes dynamic modeling such as ordinary differential equation based frameworks, for which temporal datasets remain scarce. The data contained in this preprint will be available on JPOST Repo after the publication.

cancer biology↗
bioRxiv2026

Efficient genomic prediction at reduced training size and moderate marker density in an expanded aus-NAM population of rice

Genomic selection (GS) can accelerate genetic gain in crops, but its effectiveness depends on training population design and marker density. Nested association mapping (NAM) populations provide a structured framework that captures broad allelic diversity within a controlled genetic background. Here, we evaluated genomic prediction (GP) and genome-wide association study (GWAS) performance in an expanded aus-NAM population of rice comprising 1,818 recombinant inbred lines across 14 families and 11 agronomic traits, using genotyping-by-sequencing (GBS) markers and projected whole-genome sequence variants. Prediction accuracy plateaued at moderate marker densities ([~]20k SNPs) and with training populations of [~]500 lines ([~]40-60% of the available pool), with trait heritability emerging as the strongest determinant of predictive performance rather than model choice or marker density. In contrast, GWAS resolution continued to improve with increasing marker density, enabling detection of additional loci, including a chromosome 12 locus associated with heading date, while consistently recovering well-characterized genes such as EARLY HEADING DATE 1 (Ehd1) and SEMIDWARF 1 (SD1). These contrasting patterns indicate that GP reaches near-optimal performance once genome-wide variation is adequately represented, whereas GWAS benefits from higher marker density through improved locus resolution. The present study establishes a benchmark for implementing breeding programs involving japonica/indica crosses using GP in a single environment.

plant biology↗