Amir Ali Abbasi

After Alzheimer, Parkinson's disease (PD) is the second most common neurodegenerative disorder. Alpha synuclein (SNCA) is deemed as a major component of Lewy bodies, a neuropathological feature of PD. Five point mutations in SNCA have been reported so far, responsible for autosomal dominant PD. This study aims to decipher evolutionary and structural insights of SNCA by revealing its sequence and structural evolutionary patterns among sarcopterygians and its paralogous counterparts (SNCB and SNCG). Rate analysis detected strong purifying selection on entire synuclein family. Structural dynamics divulges that during the course of sarcopterygian evolutionary history, the region encompassed 32 to 58 of N-terminal domain of SNCA has acquired its critical functional significance through the epistatic influence of the lineage specific substitutions. In sum, these findings provide an evidence that the region from 32 to 58 of N-terminal lipid binding alpha helix domain of SNCA is the most critical region, not only from the evolutionary perspective but also for the stability and the proper conformation of the protein as well as crucial for the disease pathogenesis, harboring critical interaction sites.

MOTIVATION: The significance of long non-coding RNAs (lncRNAs) in many biological processes and diseases has gained intense interests over the past several years. However, computational identification of lncRNAs in a wide range of species remains challenging; it requires prior knowledge of well-established sequences and annotations or species-specific training data, but the reality is that only a limited number of species have high-quality sequences and annotations. RESULTS: Here we first characterize lncRNAs in contrast to protein-coding RNAs based on feature relationship and find that the feature relationship between open reading frame length and guanine-cytosine (GC) content presents universally substantial divergence in lncRNAs and protein-coding RNAs, as observed in a broad variety of species. Based on the feature relationship, accordingly, we further present LGC, a novel algorithm for identifying lncRNAs that is able to accurately distinguish lncRNAs from protein-coding RNAs in a cross-species manner without any prior knowledge. As validated on large-scale empirical datasets, comparative results show that LGC outperforms existing algorithms by achieving higher accuracy, well-balanced sensitivity and specificity, and is robustly effective (>90% accuracy) in discriminating lncRNAs from protein-coding RNAs across diverse species that range from plants to mammals. To our knowledge, this study, for the first time, differentially characterizes lncRNAs and protein-coding RNAs based on feature relationship, which is further applied in computational identification of lncRNAs. Taken together, our study represents a significant advance in characterization and identification of lncRNAs and LGC thus bears broad potential utility for computational analysis of lncRNAs in a wide range of species. AVAILABILITY AND IMPLEMENTATION: LGC web server is publicly available at http://bigd.big.ac.cn/lgc/calculator. The scripts and data can be downloaded at http://bigd.big.ac.cn/biocode/tools/BT000004. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The BIG Data Center at Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences provides a suite of database resources in support of worldwide research activities in both academia and industry. With the vast amounts of multi-omics data generated at unprecedented scales and rates, the BIG Data Center is continually expanding, updating and enriching its core database resources through big data integration and value-added curation. Resources with significant updates in the past year include BioProject (a biological project library), BioSample (a biological sample library), Genome Sequence Archive (GSA, a data repository for archiving raw sequence reads), Genome Warehouse (GWH, a centralized resource housing genome-scale data), Genome Variation Map (GVM, a public repository of genome variations), Science Wikis (a catalog of biological knowledge wikis for community annotations) and IC4R (Information Commons for Rice). Newly released resources include EWAS Atlas (a knowledgebase of epigenome-wide association studies), iDog (an integrated omics data resource for dog) and RNA editing resources (for editome-disease associations and plant RNA editosome, respectively). To promote biodiversity and health big data sharing around the world, the Open Biodiversity and Health Big Data (BHBD) initiative is introduced. All of these resources are publicly accessible at http://bigd.big.ac.cn.

Biological databases serve as a global fundamental infrastructure for the worldwide scientific community, which dramatically aid the transformation of big data into knowledge discovery and drive significant innovations in a wide range of research fields. Given the rapid data production, biological databases continue to increase in size and importance. To build a catalog of worldwide biological databases, we curate a total of 5825 biological databases from 8931 publications, which are geographically distributed in 72 countries/regions and developed by 1975 institutions (as of September 20, 2022). We further devise a z-index, a novel index to characterize the scientific impact of a database, and rank all these biological databases as well as their hosting institutions and countries in terms of citation and z-index. Consequently, we present a series of statistics and trends of worldwide biological databases, yielding a global perspective to better understand their status and impact for life and health sciences. An up-to-date catalog of worldwide biological databases, as well as their curated meta-information and derived statistics, is publicly available at Database Commons (https://ngdc.cncb.ac.cn/databasecommons/).

The zinc-finger transcription factor GLI3 is a key regulator of development, acting as a primary transducer of Sonic hedgehog (SHH) signaling in a combinatorial context dependent fashion controlling multiple patterning steps in different tissues/organs. A tight temporal and spatial control of gene expression is indispensable, however, cis-acting sequence elements regulating GLI3 expression have not yet been reported. We show that 11 ancient genomic DNA signatures, conserved from the pufferfish Takifugu (Fugu) rubripes to man, are distributed throughout the introns of human GLI3. They map within larger conserved non-coding elements (CNEs) that are found in the tetrapod lineage. Full length CNEs transiently transfected into human cell cultures acted as cell type specific enhancers of gene transcription. The regulatory potential of these elements is conserved and was exploited to direct tissue specific expression of a reporter gene in zebrafish embryos. Assays of deletion constructs revealed that the human-Fugu conserved sequences within the GLI3 intronic CNEs were essential but not sufficient for full-scale transcriptional activation. The enhancer activity of the CNEs is determined by a combinatorial effect of a core sequence conserved between human and teleosts (Fugu) and flanking tetrapod-specific sequences, suggesting that successive clustering of sequences with regulatory potential around an ancient, highly conserved nucleus might be a possible mechanism for the evolution of cis-acting regulatory elements.