Biology subjects

Si, W.

Publications and source records attributed to Si, W..

6 recordsLinked to original sources

bioRxiv2026

Seeing at Will: Shared Neural Representations of Motion Perception and Intention

Volitional intention can bias perception in cases where two or more interpretations of a stimulus are available to us. The neural mechanisms whereby such an intention influences perception are poorly understood. Here we investigated whether intending to see horizontal versus vertical motion in a subsequently presented instantaneous position shift of a quartet apparent motion stimulus establishes decodable sensory representations prior to both the position shift and the perception of motion. Twelve participants underwent fMRI scanning under three conditions: (1) while passively viewing either continuously or (2) discretely moving quartet stimuli, or (3) while actively intending to see a subsequent single-shot apparent motion as either a vertical or horizontal motion. Multivariate decoding analyses revealed that activity patterns during the intention period of (3) generalized to patterns evoked by both (1) physical and (2) ambiguous motion perception. Cross-decoding was strongest within dorsal/lateral visual regions, including hMT+, V3AB, and the intraparietal sulcus (IPS), but was largely absent from ventral visual cortex. Widespread overlap was also observed between intention-related and perceptual motion representations throughout the dorsal/lateral visual cortex. Our findings suggest that volitional intention establishes prospective sensory representations before perceptual experience emerges and that these representations closely resemble those associated with illusory motion perception. The predominance of intention-related representations within dorsal/lateral visual regions is consistent with top-down influences from attentional control systems. More broadly, the results demonstrate that internally generated cognitive states can shape sensory representations, constraining subsequent perceptual experience.

neuroscience↗

bioRxiv2023

The ChickenGTEx pilot analysis: a reference of regulatory variants across 28 chicken tissues

Chicken is a valuable model for understanding fundamental biology, vertebrate evolution and diseases, as well as a major source of nutrient-dense and lean-protein-enriched food globally. Although it is the first non-mammalian amniote genome to be sequenced, the chicken genome still lacks a systematic characterization of functional impacts of genetic variants. Here, through integrating 7,015 RNA-Seq and 2,869 whole-genome sequence data, the Chicken Genotype- Tissue Expression (ChickenGTEx) project presents the pilot reference of regulatory variants in 28 chicken tissue transcriptomes, including millions of regulatory effects on primary expression (including protein-coding genes, lncRNA and exon) and post-transcriptional modifications (alternative splicing and 3 untranslated region alternative polyadenylation). We explored the tissue-sharing and context-specificity of these regulatory variants, their underlying molecular mechanisms of action, and their utility in interpreting adaptation and genome-wide associations of 108 chicken complex traits. Finally, we illustrated shared and lineage-specific features of gene regulation between chickens and mammals, and demonstrated how the ChickenGTEx resource can further assist with translating genetic findings across species. One-Sentence SummaryThe ChickenGTEx provides a multi-tissue reference of regulatory variants for chicken genetics and genomics, functional genomics, precision breeding, veterinary medicine, vertebrate evolution and even human biomedicine.

genetics↗

bioRxiv2022

Why is Babesia not killed by artemisinin like Plasmodium?

Babesia spp. are intraerythrocytic apicomplexan organisms digesting hemoglobin similar to intraerythrocytic Plasmodium spp. However, unlike Plasmodium spp., Babesia spp. are not sensitive to artemisinin, The difference between Babesia genomes and Plasmodium genomes revealed that smaller Babesia genomes lack numerous genes, especially haem synthesis-related genes. Single-cell sequencing analysis showed that different groups of B. microti with expressed pentose phosphate pathway (PPP)-related, DNA replication-related, antioxidation-related, glycolysis-related, and glutathione-related genes were not as sensitive to artemether as P. yoelii 17XNL. Especially, PPP-related, DNA replication-related, and glutathione-related genes were inactively expressed compared with P. yoelii 17XNL. Adding iron supply in vivo can promote the reproduction of B. microti. These results suggest that Babesia spp. lack a similar mechanism to that in malaria parasites, by which haem or iron in hemoglobin is utilized, but it likely leads to their insensitivity to artemisinin in turn. Author summaryBabesia and Plasmodium are similar in many ways, from morphology to life history. In particular, both ingest and break down hemoglobin. However, compared with Plasmodium, Babesia cannot form hemozoin with less pathogenicity and insensitivity to artemisinin. Recent studies suggest that artemisinin can kill malaria parasites through free-radical and iron-capture effects, indicating that iron and haem play a key role in the sensitivity of malaria parasites to artemisinin. The Babesia genome is smaller and does not contain haem synthesis-related genes, indicating low requirements and utilization of haem and iron (HI). Moreover, we found that the expression of PPP-related and DNA replication-related genes is not active, distinctly different from malaria parasites. However, adding iron supply in vivo can increase the infection rate of B. microti. Therefore, we hypothesized that Babesia lacks mechanisms for the efficient utilization of HI, resulting in low requirements for HI, and therefore insensitivity to artemisinin.

evolutionary biology↗

bioRxiv2022

Spatial and molecular anatomy of germ layers in the gastrulating primate embryo

During mammalian embryogenesis, spatial regulation of gene expression and cell signaling are functionally coupled with lineage specification, patterning of tissue progenitors and germ layer morphogenesis. While the mouse model has been instrumental for our understanding of mammalian development, comparatively little is known about human and non-human primate gastrulation due to the restriction of both technical and ethical issues. Here, we present a morphological and molecular survey of spatiotemporal dynamics of cell types populating the non-human primate embryos during gastrulation. We performed serial sections of Cynomolgus monkeys (Macaca fascicularis) gastrulating embryos at 1-day temporal resolution from E17 to E21, and reconstructed three-dimensional digital models based on high-resolution anatomical atlas that revealed the dynamic changes in the geography of the mesoderm and primitive streaks. Spatial transcriptomics identified unique gene profiles that correspond to distinct germ layers and cross-species spatiotemporal transcriptome analysis revealed a developmental coordinate of germ layer segregation between mouse and primate. Furthermore, we identified species-specific transcription programs during gastrulation. These results offer important insights into evolutionarily conserved and divergent processes during mammalian gastrulation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/474719v2_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1058f45org.highwire.dtl.DTLVardef@105cborg.highwire.dtl.DTLVardef@12362d7org.highwire.dtl.DTLVardef@2e2346_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightO_LIA high-resolution anatomical atlas of Cynomolgus gastrulation embryos C_LIO_LICreated a three-dimensional digital template from serial sections of five developmental stages C_LIO_LIA two-dimensional spatiotemporal transcriptome of the germ layers of gastrulating embryos C_LIO_LICross-species comparison infers conservation of functional attributes of regulome and signaling activity in germ layer formation C_LI

developmental biology↗

bioRxiv2021

Total virome characterizations of game animals in China reveals a spectrum of emerging viral pathogens

Game animals are wildlife species often traded and consumed as exotic food, and are potential reservoirs for SARS-CoV and SARS-CoV-2. We performed a meta-transcriptomic analysis of 1725 game animals, representing 16 species and five mammalian orders, sampled across China. From this we identified 71 mammalian viruses, with 45 described for the first time. Eighteen viruses were considered as potentially high risk to humans and domestic animals. Civets (Paguma larvata) carried the highest number of potentially high risk viruses. We identified the transmission of Bat coronavirus HKU8 from a bat to a civet, as well as cross-species jumps of coronaviruses from bats to hedgehogs and from birds to porcupines. We similarly identified avian Influenza A virus H9N2 in civets and Asian badgers, with the latter displaying respiratory symptoms, as well as cases of likely human-to-wildlife virus transmission. These data highlight the importance of game animals as potential drivers of disease emergence. HighlightsO_LI1725 game animals from five mammalian orders were surveyed for viruses C_LIO_LI71 mammalian viruses were discovered, 18 with a potential risk to humans C_LIO_LICivets harbored the highest number of potential high risk viruses C_LIO_LIA species jump of an alphacoronavirus from bats to a civet was identified C_LIO_LIH9N2 influenza virus was detected in a civet and an Asian badger C_LIO_LIHumans viruses were also identified in game animals C_LI

zoology↗

bioRxiv2020

Using Genetic Information to Improve the Prediction of Individual Food Choice: A Case Study of Alcoholic Beverages

Individual food choices and consumption are closely relating to ones diet, nutrition, and health. Using the case of alcoholic beverages, this study extends the random-utility framework by incorporating genetic information into consumer demand models, and demonstrates the significant impact of genetic factors on individual food choice decisions in a novel way. Integrating individual-level responses of discrete choice experiments (DCE), genotyping data, and socioeconomic/demographic characteristics of 484 participants collected from face-to-face interviews in mainland China, we employ a machine learning-based classification (MLC) approach to identify and predict individual choices. We show that genetic factors are critical to explaining variations in both general drinking behavior and choices of particular products. We systematically compared the performance of traditional discrete choice models and MLC models without and with genetic factors. The MLC predictive model with both socio-demographic and genetic features yields the highest accuracy of 74.7% and AUC-ROC of 0.85. Our findings warrant further economic studies of human behaviors with the integration of genetic data.

genetics↗