SNPHunter: a bioinformatic software for single nucleotide polymorphism data acquisition and management

BACKGROUND: Single nucleotide polymorphisms (SNPs) provide an important tool in pinpointing susceptibility genes for complex diseases and in unveiling human molecular evolution. Selection and retrieval of an optimal SNP set from publicly available databases have emerged as the foremost bottlenecks in designing large-scale linkage disequilibrium studies, particularly in case-control settings. RESULTS: We describe the architectural structure and implementations of a novel software program, SNPHunter, which allows for both ad hoc-mode and batch-mode SNP search, automatic SNP filtering, and retrieval of SNP data, including physical position, function class, flanking sequences at user-defined lengths, and heterozygosity from NCBI dbSNP. The SNP data extracted from dbSNP via SNPHunter can be exported and saved in plain text format for further down-stream analyses. As an illustration, we applied SNPHunter for selecting SNPs for 10 major candidate genes for type 2 diabetes, including CAPN10, FABP4, IL6, NOS3, PPARG, TNF, UCP2, CRP, ESR1, and AR. CONCLUSION: SNPHunter constitutes an efficient and user-friendly tool for SNP screening, selection, and acquisition. The executable and user's manual are available at

Phylogenomic evidence for the origin of obligately anaerobic anammox bacteria around the great oxidation event

Funding: This work is funded by the National Science Foundation of China (92051113), the Hong Kong Research Grants Council Area of Excellence Scheme (AoE/M-403/16), the Direct Grant of CUHK (4053495), the Hong Kong Research Grants Council (RGC) General Research Fund (GRF) (14110820), and The CUHK Impact Postdoctoral Fellowship Scheme to (S. W.).The anaerobic ammonium oxidation (anammox) bacteria can transform ammonium and nitrite to dinitrogen gas, and this obligate anaerobic process accounts for up to half of the global nitrogen loss in surface environments. Yet its origin and evolution, which may give important insights into the biogeochemistry of early Earth, remains enigmatic. Here, we performed comprehensive phylogenomic and molecular clock analysis of anammox bacteria within the phylum Planctomycetes. After accommodating the uncertainties and factors influencing time estimates, which includes implementing both a traditional cyanobacteria-based and a recently developed mitochondria-based molecular dating approach, we estimated a consistent origin of anammox bacteria at early Proterozoic and most likely around the so-called Great Oxidation Event (GOE; 2.32 to 2.5 billion years ago [Ga]) which fundamentally changed global biogeochemical cycles. We further showed that during the origin of anammox bacteria, genes involved in oxidative stress adaptation, bioenergetics and anammox granules formation were recruited, which might have contributed to their survival on an increasingly oxic Earth. Our findings suggest the rising levels of atmospheric oxygen, which made nitrite increasingly available, was a potential driving force for the emergence of anammox bacteria. This is one of the first studies that link the GOE to the evolution of obligate anaerobic bacteria.Publisher PDFPeer reviewe

Dating ammonia-oxidizing bacteria with abundant eukaryotic fossils

This work was supported by the Hong Kong Research Grants Council (RGC) General Research Fund (GRF) (14107823), the Natural Science Foundation of China (42293294), the Hong Kong Research Grants Council Area of Excellence Scheme (AoE/M-403/16), the Guangdong Basic and Applied Basic Research Foundation (2022A1515010844 to H.Z.), and the China Postdoctoral Science Foundation (2021M702296 to H.Z.).Evolution of a complete nitrogen (N) cycle relies on the onset of ammonia oxidation, which aerobically converts ammonia to nitrogen oxides. However, accurate estimation of the antiquity of ammonia-oxidizing bacteria (AOB) remains challenging because AOB-specific fossils are absent and bacterial fossils amenable to calibrate molecular clocks are rare. Leveraging the ancient endosymbiosis of mitochondria and plastid, as well as using state-of-the-art Bayesian sequential dating approach, we obtained a timeline of AOB evolution calibrated largely by eukaryotic fossils. We show that the first AOB evolved in marine Gammaproteobacteria (Gamma-AOB) and emerged between 2.1 and 1.9 billion years ago (Ga), thus postdating the Great Oxidation Event (GOE; 2.4 to 2.32 Ga). To reconcile the sedimentary N isotopic signatures of ammonia oxidation occurring near the GOE, we propose that ammonia oxidation likely occurred at the common ancestor of Gamma-AOB and Gammaproteobacterial methanotrophs, or the actinobacterial/verrucomicrobial methanotrophs which are known to have ammonia oxidation activities. It is also likely that nitrite was transported from the terrestrial habitats where ammonia oxidation by archaea took place. Further, we show that the Gamma-AOB predated the anaerobic ammonia-oxidizing (anammox) bacteria, implying that the emergence of anammox was constrained by the availability of dedicated ammonia oxidizers which produce nitrite to fuel anammox. Our work supports a new hypothesis that N redox cycle involving nitrogen oxides evolved rather late in the ocean.Peer reviewe

Variable-step-size LMS adaptive filter for digital chromatic dispersion compensation in PDM-QPSK coherent transmission system

High bit rates optical communication systems pose the challenge of their tolerance to linear and nonlinear fiber impairments. Digital filters in coherent optical receivers can be used to mitigate the chromatic dispersion entirely in the optical transmission system. In this paper, the least mean square adaptive filter has been developed for chromatic equalization in a 112-Gbit/s polarization division multiplexed quadrature phase shift keying coherent optical transmission system established on the VPIphotonics simulation platform. It is found that the chromatic dispersion equalization shows a better performance when a smaller step size is used. However, the smaller step size in least mean square filter will lead to a slower iterative operation to achieve the guaranteed convergence. In order to solve this contradiction, an adaptive filter employing variable-step-size least mean square algorithm is proposed to compensate the chromatic dispersion in the 112-Gbit/s coherent communication system. The variable-step-size least mean square filter could make a compromise and optimization between the chromatic dispersion equalization performance and the algorithm converging speed. Meanwhile, the required tap number and the converged tap weights distribution of the variable-step-size least mean square filter for a certain fiber chromatic dispersion are analyzed and discussed in the investigation of the filter feature

Few-Mode Fibers With Uniform Differential Mode Group Delay for Microwave Photonic Signal Processing

We present a novel design of few-mode fiber (FMF) with a uniform differential mode group delay (U-DMGD) among propagating modes and apply the FMF to a single-fiber delay line module for implementing microwave photonic finite impulse response (FIR) filters. By optimizing key parameters such as the core grading exponent and the dimension of the trench of FMF, a U-DMGD between adjacent modes among four modes (LP 01 , LP 11 , LP 02 and LP 31 ) over the entire C band is achieved. Wavelength dependence is entirely removed. An FIR microwave photonic filter (MPF) implemented using the designed 1-km FMF is investigated through numerical simulations. The free spectral range (FSR) of the MPF is 5.7 GHz, the 3-dB bandwidth is 1.26 GHz, and the main lobe-to-side lobe ratio (MSR) is 10.42 dB. Discussions on fabrication aspects have also been presented. The proposed single-fiber delay line structure based on FMF can significantly reduce the system complexity of microwave photonic signal processing

Therapeutic Angiogenesis of Chinese Herbal Medicines in Ischemic Heart Disease:A Review

Ischemic heart disease (IHD) is one of the primary causes of death around the world. Therapeutic angiogenesis is a promising innovative approach for treating IHD, improving cardiac function by promoting blood perfusion to the ischemic myocardium. This treatment is especially important for targeting patients that are unable to undergo angioplasty or bypass surgery. Chinese herbal medicines have been used for more than 2,500 years and they play an important role alongside contemporary medicines in China. Growing evidence in animal models show Chinese herbal medicines can provide therapeutic effect on IHD by targeting angiogenesis. Identifying the mechanism in which Chinese herbal medicines can promote angiogenesis in IHD is a major topic in the field of traditional Chinese medicine, and has the potential for advancing therapeutic treatment. This review summarizes the progression of research and highlights potential pro-angiogenic mechanisms of Chinese herbal medicines in IHD. In addition, an outline of the limitations of Chinese herbal medicines and challenges they face will be presented

Language Models Meet World Models: Embodied Experiences Enhance Language Models

While large language models (LMs) have shown remarkable capabilities across numerous tasks, they often struggle with simple reasoning and planning in physical environments, such as understanding object permanence or planning household activities. The limitation arises from the fact that LMs are trained only on written text and miss essential embodied knowledge and skills. In this paper, we propose a new paradigm of enhancing LMs by finetuning them with world models, to gain diverse embodied knowledge while retaining their general language capabilities. Our approach deploys an embodied agent in a world model, particularly a simulator of the physical world (VirtualHome), and acquires a diverse set of embodied experiences through both goal-oriented planning and random exploration. These experiences are then used to finetune LMs to teach diverse abilities of reasoning and acting in the physical world, e.g., planning and completing goals, object permanence and tracking, etc. Moreover, it is desirable to preserve the generality of LMs during finetuning, which facilitates generalizing the embodied knowledge across tasks rather than being tied to specific simulations. We thus further introduce the classical (EWC) for selective weight updates, combined with low-rank adapters (LoRA) for training efficiency. Extensive experiments show our approach substantially improves base LMs on 18 downstream tasks by 64.28% on average. In particular, the small LMs (1.3B, 6B, and 13B) enhanced by our approach match or even outperform much larger LMs (e.g., ChatGPT)