Biology subjects

Li, H.-F.

Publications and source records attributed to Li, H.-F..

3 recordsLinked to original sources

bioRxiv2026

An Integrative Phylogenomic Framework Quantifies the Dominant Role of Introgression in Phylogenetic Discordance among Diploid Oryza Species

BackgroundPhylogenomic studies frequently reveal widespread gene tree discordance, primarily arising from incomplete lineage sorting (ILS) and hybridization and/or introgression. Disentangling these processes is especially challenging in rapidly radiating lineages. The genus Oryza, with its rapid diversification and multiple genome types, exemplifies this pervasive phylogenetic incongruence. We integrated multiple genomic datasets including whole-genome resequencing, transcriptomes, and published genomes from diploid Oryza species. Concatenation and multispecies coalescent analyses recovered a robust, congruent species tree, placing the FF and GG genome groups as a monophyletic basal clade, followed by successive divergence of the EE, CC, BB, and AA lineages, a topology differing from some prior hypotheses. ResultsTo assess the sources of discordance, we employed a suite of complementary phylogenomic methods. Quantifying introgression via Branch Lengths (QuIBL)-based model comparisons suggested that [~]74.17% of gene tree-species tree discordance is better explained by post-speciation introgression, whereas only [~]15.56% is consistent with ILS alone. Phylogenetic networks (PhyloNet) and allele-sharing statistics (D-statistics, f-branch) corroborated these results, indicating widespread historical introgression both within and between genome groups. Furthermore, genome-wide scans using the fdM statistic localized introgressed genomic regions, which showed reduced interspecific divergence and were enriched for genes involved in stress responses and metabolism. ConclusionsTaken together, our results demonstrate that historical introgression, not ILS, is the dominant force shaping phylogenetic discordance in diploid Oryza. The integrative phylogenomic framework implemented here, which quantifies the contributions of introgression versus ILS and maps the genomic footprint of gene flow, provides a replicable strategy for resolving complex evolutionary histories in other rapidly radiating lineages.

evolutionary biology↗

bioRxiv2024

The Neuropeptide Sulfakinin, a peripheral regulator of insect behavior switch between mating and foraging

Behavioral strategies for foraging and reproduction in the oriental fruit fly (Bactrocera dorsalis) are alternative options for resource allocation and are controlled by neuropeptides. Here we show that the behavioral switch between foraging and reproduction is associated with changes in antennal sensitivity. Starved flies became more sensitive to food odors while suppressing their response to opposite-sex pheromones. The gene encoding sulfakinin receptor 1 (SkR1) was significantly upregulated in the antennae of starved flies, so we tested the behavioral phenotypes of null mutants for the genes encoding the receptor (skr1-/-) and its ligand sulfakinin (sk-/-). In both knockout lines, the antennal responses shifted to mating mode even when flies were starved. This suggests that sulfakinin signaling via SkR1 promotes foraging while suppressing mating. Further analysis of the mutant flies revealed that sets of odorant receptor (OR) genes were differentially expressed. Functional characterization of the differentially expressed ORs suggested that sulfakinin directly suppresses the expression of ORs that respond to opposite-sex hormones while enhancing the expression of ORs that detect food volatiles. We conclude that sulfakinin signaling via SkR1, modulating OR expressions and leading to altered antenna sensitivities, is an important component in starvation-dependent behavioral change.

ecology↗

bioRxiv2020

DREAM: A Toolbox to Decode Rhythms of the Brain System

Rhythms of the brain are generated by neural oscillations across multiple frequencies, which can be observed with multiple modalities. Following the natural log linear law of frequency distribution, these oscillations can be decomposed into distinct frequency intervals associated with specific physiological processes. This perspective on neural oscillations has been increasingly applied to study human brain function and related behaviors. In practice, relevant signals are commonly measured as a discrete time series, and thus the sampling period and number of samples determine the number and ranges of decodable frequency intervals. However, these limits have been often ignored by researchers who instead decode measured oscillations into multiple frequency intervals using a fixed sample period and numbers of samples. One reason for such misuse is the lack of an easy-to-use toolbox to implement automatic decomposition of frequency intervals. We report on a toolbox with a graphical user interface for achieving local and remote decoding rhythms of the brain system (DREAM) which is accessible to the public via GitHub. We provide worked examples of DREAM used to investigate frequency-specific performance of both neural (spontaneous brain activity) and neurobehavioral (in-scanner head motion) oscillations. DREAM analyzed the head motion oscillations and found that younger children moved their heads more than older children across all five frequency intervals whereas boys moved more than girls in the age interval from 7 to 9 years. It is interesting that the higher frequency bands contains more head movements, and showed stronger age-motion associations but the weaker sex-motion interactions. Using the fast functional magnetic resonance imaging data from the Human Connectome Project, DREAM mapped the amplitude of these neural oscillations into multiple frequency bands and evaluated their test-retest reliability. A novel result indicated that the higher frequency bands exhibited more reliable amplitude measurements, implying more inter-individual variability of the amplitudes for the higher frequency bands. In summary, these findings demonstrated the applicability of DREAM for frequency-specific human brain mapping as well as the assessments on their measurement reliability and validity.

neuroscience↗