1165048_Kaur,P_2021.pdf (2.05 MB)
Delineating the Tnt1 Insertion Landscape of the Model Legume Medicago truncatula cv. R108 at the Hi-C Resolution using a Chromosome-Length Genome Assembly
journal contributionposted on 2021-07-07, 23:27 authored by P Kaur, C Lui, O Dudchenko, RS Nandety, Bhavna HurgobinBhavna Hurgobin, M Pham, EL Aiden, J Wen, K Mysore
Legumes are of great interest for sustainable agricultural production as they fix atmospheric nitrogen to improve the soil. Medicago truncatula is a well-established model legume, and extensive studies in fundamental molecular, physiological, and developmental biology have been undertaken to translate into trait improvements in economically important legume crops worldwide. However, M. truncatula reference genome was generated in the accession Jemalong A17, which is highly recalcitrant to transformation. M. truncatula R108 is more attractive for genetic studies due to its high transformation efficiency and Tnt1-insertion population resource for functional genomics. The need to perform accurate synteny analysis and comprehensive genome-scale comparisons necessitates a chromosome-length genome assembly for M. truncatula cv. R108. Here, we performed in situ Hi-C (48×) to anchor, order, orient scaffolds, and correct misjoins of contigs in a previously published genome assembly (R108 v1.0), resulting in an improved genome assembly containing eight chromosome-length scaffolds that span 97.62% of the sequenced bases in the input assembly. The long-range physical information data generated using Hi-C allowed us to obtain a chromosome-length ordering of the genome assembly, better validate previous draft misjoins, and provide further insights accurately predicting synteny between A17 and R108 regions corresponding to the known chromosome 4/8 translocation. Furthermore, mapping the Tnt1 insertion landscape on this reference assembly presents an important resource for M. truncatula functional genomics by supporting efficient mutant gene identification in Tnt1 insertion lines. Our data provide a much-needed foundational resource that supports functional and molecular research into the Leguminosae for sustainable agriculture and feeding the future.