Chengdao Li

Artificial Intelligence (AI) has emerged as a key driver of precision agriculture, facilitating enhanced crop productivity, optimized resource use, farm sustainability, and informed decision-making. Also, the expansion of genome sequencing technology has greatly increased crop genomic resources, deepening our understanding of genetic variation and enhancing desirable crop traits to optimize performance in various environments. There is increasing interest in using machine learning (ML) and deep learning (DL) algorithms for genotype-to-phenotype prediction due to their excellence in capturing complex interactions within large, high-dimensional datasets. In this work, we propose a new LSTM autoencoder-based model for barley genotype-to-phenotype prediction, specifically for flowering time and grain yield estimation, which could potentially help optimize yields and management practices. Our model outperformed the other baseline methods, demonstrating its potential in handling complex high-dimensional agricultural datasets and enhancing crop phenotype prediction performance.

Monitoring the mutation dynamics of SARS-CoV-2 is critical for the development of effective approaches to contain the pathogen. By analyzing 106 SARS-CoV-2 and 39 SARS genome sequences, we provided direct genetic evidence that SARS-CoV-2 has a much lower mutation rate than SARS. Minimum Evolution phylogeny analysis revealed the putative original status of SARS-CoV-2 and the early-stage spread history. The discrepant phylogenies for the spike protein and its receptor binding domain proved a previously reported structural rearrangement prior to the emergence of SARS-CoV-2. Despite that we found the spike glycoprotein of SARS-CoV-2 is particularly more conserved, we identified a receptor binding domain mutation that leads to weaker ACE2 binding capability based on in silico simulation, which concerns a SARS-CoV-2 sample collected on 27th January 2020 from India. This represents the first report of a significant SARS-CoV-2 mutant, and requires attention from researchers working on vaccine development around the world.