Tao Lin

Bio: Tao Lin is an academic researcher from China Agricultural University. The author has contributed to research in topics: Domestication & Biology. The author has an hindex of 17, co-authored 26 publications receiving 2774 citations. Previous affiliations of Tao Lin include Civil Aviation Authority of Singapore & Chinese Academy of Sciences.

Genomic analyses provide insights into the history of tomato breeding

Abstract: The histories of crop domestication and breeding are recorded in genomes. Although tomato is a model species for plant biology and breeding, the nature of human selection that altered its genome remains largely unknown. Here we report a comprehensive analysis of tomato evolution based on the genome sequences of 360 accessions. We provide evidence that domestication and improvement focused on two independent sets of quantitative trait loci (QTLs), resulting in modern tomato fruit ∼100 times larger than its ancestor. Furthermore, we discovered a major genomic signature for modern processing tomatoes, identified the causative variants that confer pink fruit color and precisely visualized the linkage drag associated with wild introgressions. This study outlines the accomplishments as well as the costs of historical selection and provides molecular insights toward further improvement.

A chemical genetic roadmap to improved tomato flavor

Abstract: Modern commercial tomato varieties are substantially less flavorful than heirloom varieties. To understand and ultimately correct this deficiency, we quantified flavor-associated chemicals in 398 modern, heirloom, and wild accessions. A subset of these accessions was evaluated in consumer panels, identifying the chemicals that made the most important contributions to flavor and consumer liking. We found that modern commercial varieties contain significantly lower amounts of many of these important flavor chemicals than older varieties. Whole-genome sequencing and a genome-wide association study permitted identification of genetic loci that affect most of the target flavor chemicals, including sugars, acids, and volatiles. Together, these results provide an understanding of the flavor deficiencies in modern commercial varieties and the information necessary for the recovery of good flavor through molecular breeding.

A genomic variation map provides insights into the genetic basis of cucumber domestication and diversity

Abstract: Most fruits in our daily diet are the products of domestication and breeding. Here we report a map of genome variation for a major fruit that encompasses ~3.6 million variants, generated by deep resequencing of 115 cucumber lines sampled from 3,342 accessions worldwide. Comparative analysis suggests that fruit crops underwent narrower bottlenecks during domestication than grain crops. We identified 112 putative domestication sweeps; 1 of these regions contains a gene involved in the loss of bitterness in fruits, an essential domestication trait of cucumber. We also investigated the genomic basis of divergence among the cultivated populations and discovered a natural genetic variant in a β-carotene hydroxylase gene that could be used to breed cucumbers with enhanced nutritional value. The genomic history of cucumber evolution uncovered here provides the basis for future genomics-enabled breeding.

Resequencing of 243 diploid cotton accessions based on an updated A genome identifies the genetic basis of key agronomic traits.

Abstract: The ancestors of Gossypium arboreum and Gossypium herbaceum provided the A subgenome for the modern cultivated allotetraploid cotton. Here, we upgraded the G. arboreum genome assembly by integrating different technologies. We resequenced 243 G. arboreum and G. herbaceum accessions to generate a map of genome variations and found that they are equally diverged from Gossypium raimondii. Independent analysis suggested that Chinese G. arboreum originated in South China and was subsequently introduced to the Yangtze and Yellow River regions. Most accessions with domestication-related traits experienced geographic isolation. Genome-wide association study (GWAS) identified 98 significant peak associations for 11 agronomically important traits in G. arboreum. A nonsynonymous substitution (cysteine-to-arginine substitution) of GaKASIII seems to confer substantial fatty acid composition (C16:0 and C16:1) changes in cotton seeds. Resistance to fusarium wilt disease is associated with activation of GaGSTF9 expression. Our work represents a major step toward understanding the evolution of the A genome of cotton.

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

Automated Eukaryotic Gene Structure Annotation Using EVidenceModeler and the Program to Assemble Spliced Alignments

Abstract: EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation.