Biology subjects

Huang, L.

Publications and source records attributed to Huang, L..

21 records · Page 2Linked to original sources

bioRxiv2017

The Y-Chromosome Clarifies The Evolutionary History Of Sus scrofa By Large-Scale Deep Genome Sequencing

The genetics and evolution of sex chromosomes are largely distinct from autosomes and mitochondrial DNA (mtDNA). The Y chromosome offers unique genetic perspective on male-line inheritance. Here, we uncover novel evolutionary history of Sus scrofa based on 205 high-quality genomes from worldwide-distributed different wild boars and domestic pig breeds. We find that only two haplotypes exist in the distal and proximal blocks of at least 7.7 Mb on chromosome Y in pigs across European and Asian continents. And the times of most recent common ancestors (TMRCA) within both haplotypes, approximately 0.14 and 0.10 million years, are far smaller than their divergence time of around 1.07 million years. Whats more, the relationship between Sumatran and Eurasian continent Sus scrofa is much closer than that we knew before. And surprisingly, European pigs share the same haplotype with many Chinese pigs, which is not consistent with their deep splitting status on autosome and mtDNA. Further analyses show that the haplotype in Chinese pigs was likely introduced from European wild boars via ancient gene flow before pig domestication about 24k years ago. Low mutation rates and no recombination in the distal and proximal blocks on chromosome Y help us detect this male-driven ancient gene flow. Taken together, our results update the knowledge of pig demography and evolution, and might shed insight into the genetics and evolution studies on chromosome Y in other mammals.

evolutionary biology↗

bioRxiv2017

Neuron Type-Specific Mechanical Regulation Of Voltage-Gated Ca2+ Channels And Excitability In Hippocampal And Trigeminal Ganglion Neurons

Increasing evidence suggests that the mechanical properties of extracellular matrix regulate central and peripheral neuronal functions. We thus investigated the CaV channels in hippocampal and trigeminal ganglion (TG) neurons cultured on substrates with different stiffness. Patch-clamp current recordings showed that stiff substrate augmented the CaV channel currents in hippocampal and TG neurons and additionally induced a leftward shift in the voltage-dependent channel activation curve in small TG neurons. Combination with using selective channel blockers revealed that substrate stiffness preferentially regulated the N-type channel current in hippocampal and medium TG neurons but the T-type channel current in small TG neurons. Current-clamp recordings further demonstrated that stiff substrate enhanced the excitability of small TG neurons, which was ablated by blocking the T-type channel. Treatment of neurons on the stiff substrate with low-dose blebbistatin reduced both the N-type channel current in hippocampal and medium TG neurons and the T-type channel current in small TG neurons to the levels in neurons on the soft substrate, whereas treatment of neurons on the soft substrate with calcium A increased both the N-type channel current in hippocampal and medium TG neurons and the T-type channel current in small TG neurons to the levels in neurons on the stiff substrate, thus consistently supporting critical involvement of actomyosin in mechanical sensing. Taken together, our results reveal neuron type-specific mechanical regulation of the Cav channels and excitability in the nervous system. Such information is useful for neural tissue engineering and regeneration.

biophysics↗

bioRxiv2016

Large-scale Population Genotyping from Low-coverage Sequencing Data using a Reference Panel

In recent years, several large-scale whole-genome projects sequencing tens of thousands of individuals were completed, with larger studies are underway. These projects aim to provide high-quality genotypes for a large number of whole genomes in a cost-efficient manner, by sequencing each genome at low coverage and subsequently identifying alleles jointly in the entire cohort. Here we present Ref-Reveel, a novel method for large-scale population genotyping. We show that Ref-Reveel provides genotyping at a higher accuracy and higher efficiency in comparison to existing methods by applying our method to one of the largest whole-genome sequencing datasets presently available to the public. We further show that utilizing the resulting genotype panel as references, through the Ref-Reveel framework, greatly improves the ability to call genotypes accurately on newly sequenced genomes. In addition, we present a Ref-Reveel pipeline that is applicable for genotyping of very small datasets. In summary, Ref-Reveel is an accurate, scalable and applicable method for a wide range of genotyping scenarios, and will greatly improves the quality of calling genomic alterations in current and future large-scale sequencing projects.

bioinformatics↗