Browsing by Autor "Juanita Gil"

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    Comprehensive genomic resources related to domestication and crop improvement traits in Lima bean
    (Research Square (United States), 2020) Tatiana García; Jorge Duitama; Stephanie Smolenski Zullo; Juanita Gil; Andrea Ariani; Sarah Dohle; Antonia Palkovic; Paola Skeen; Clara Isabel Bermúdez-Santana; Daniel G. Debouck
    Abstract Lima bean ( Phaseolus lunatus L. ) is one of the five domesticated Phaseolus bean crops, which are essential sources of dietary proteins for human consumption. Compared to common bean ( P. vulgaris ), it shows a wider range of ecological adaptations along its distribution range from Mexico to Argentina. These adaptations and its phenotypic plasticity make Lima bean a promising crop for improving food security under predicted scenarios of climate change in Latin America and elsewhere. Lima bean is also an excellent model to study convergent evolution of the adaptive domestication syndrome due to its dual domestication in Mesoamerica and the Andes. Combining long and short read sequencing technologies with a dense genetic map from a biparental population, we obtained the first chromosome-level genome assembly for Lima bean. Annotation of 28,326 gene models showed high diversity among 1,917 genes with conserved domains related to disease resistance. Structural comparison across 21,180 orthologs with common bean revealed high genome synteny and two large intrachromosomal rearrangements. Speciation between P. lunatus and P. vulgaris occurred about six million years ago according to nucleotide evolution between these orthologs. Population genomic analysis of GBS data for 482 wild and domesticated accessions from the Mesoamerican and Andean gene pools provided novel evidence on population structure at a finer geographical scale. Results show that wild Lima bean is organized into six clusters with mostly non-overlapping distributions and that Mesomerican landraces can be further subdivided into three subclusters. A new wild cluster of diversity was found in the Colombian Andes and a separate genetic cluster was observed for Mesoamerican landraces of the Peninsula of Yucatan in Mexico. This study also documents genome wide patterns of selection and haplotype introgression events among gene pools. Analysis of RNA-seq data obtained from wild and domesticated accessions at two different pod developmental stages revealed 4,275 differentially expressed genes, which could be related to pod dehiscence and seed development. We expect that the present resources serve as a solid basis to achieve a comprehensive view of the degree of convergent evolution of Phaseolus species under domestication and provide new tools and information for breeding for climate change resiliency of different domesticated species.
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    New algorithms for accurate and efficient de novo genome assembly from long DNA sequencing reads
    (2023) Laura Natalia González-García; David Guevara-Barrientos; Daniela Lozano‐Arce; Juanita Gil; Jorge Díaz-Riaño; Erick Duarte; Germán I. Andrade; Juan Camilo Bojacá; Maria Camila Hoyos-Sanchez; Christian Chavarro
    Building de novo genome assemblies for complex genomes is possible thanks to long-read DNA sequencing technologies. However, maximizing the quality of assemblies based on long reads is a challenging task that requires the development of specialized data analysis techniques. We present new algorithms for assembling long DNA sequencing reads from haploid and diploid organisms. The assembly algorithm builds an undirected graph with two vertices for each read based on minimizers selected by a hash function derived from the k-mer distribution. Statistics collected during the graph construction are used as features to build layout paths by selecting edges, ranked by a likelihood function. For diploid samples, we integrated a reimplementation of the ReFHap algorithm to perform molecular phasing. We ran the implemented algorithms on PacBio HiFi and Nanopore sequencing data taken from haploid and diploid samples of different species. Our algorithms showed competitive accuracy and computational efficiency, compared with other currently used software. We expect that this new development will be useful for researchers building genome assemblies for different species.