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The giant axolotl genome uncovers the evolution, scaling, and transcriptional control of complex gene loci.

ABSTRACT: Vertebrates harbor recognizably orthologous gene complements but vary 100-fold in genome size. How chromosomal organization scales with genome expansion is unclear, and how acute changes in gene regulation, as during axolotl limb regeneration, occur in the context of a vast genome has remained a riddle. Here, we describe the chromosome-scale assembly of the giant, 32 Gb axolotl genome. Hi-C contact data revealed the scaling properties of interphase and mitotic chromosome organization. Analysis of the assembly yielded understanding of the evolution of large, syntenic multigene clusters, including the Major Histocompatibility Complex (MHC) and the functional regulatory landscape of the Fibroblast Growth Factor 8 (Axfgf8) region. The axolotl serves as a primary model for studying successful regeneration.

SUBMITTER: Schloissnig S

PROVIDER: S-EPMC8053990 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSeed flooding stress is one of the threatening environmental stressors that adversely limits soybean at the germination stage across the globe. The knowledge on the genetic basis underlying seed-flooding tolerance is limited. Therefore, we performed a genome-wide association study (GWAS) using 34,718 single nucleotide polymorphism (SNPs) in a panel of 243 worldwide soybean collections to identify genetic loci linked to soybean seed flooding tolerance at the germination stage.ResultsIn the present study, GWAS was performed with two contrasting models, Mixed Linear Model (MLM) and Multi-Locus Random-SNP-Effect Mixed Linear Model (mrMLM) to identify significant SNPs associated with electrical conductivity (EC), germination rate (GR), shoot length (ShL), and root length (RL) traits at germination stage in soybean. With MLM, a total of 20, 40, 4, and 9 SNPs associated with EC, GR, ShL and RL, respectively, whereas in the same order mrMLM detected 27, 17, 13, and 18 SNPs. Among these SNPs, two major SNPs, Gm_08_11971416, and Gm_08_46239716 were found to be consistently connected with seed-flooding tolerance related traits, namely EC and GR across two environments. We also detected two SNPs, Gm_05_1000479 and Gm_01_53535790 linked to ShL and RL, respectively. Based on Gene Ontology enrichment analysis, gene functional annotations, and protein-protein interaction network analysis, we predicted eight candidate genes and three hub genes within the regions of the four SNPs with Cis-elements in promoter regions which may be involved in seed-flooding tolerance in soybeans and these warrant further screening and functional validation.ConclusionsOur findings demonstrate that GWAS based on high-density SNP markers is an efficient approach to dissect the genetic basis of complex traits and identify candidate genes in soybean. The trait associated SNPs could be used for genetic improvement in soybean breeding programs. The candidate genes could help researchers better understand the molecular mechanisms underlying seed-flooding stress tolerance in soybean.

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The giant axolotl genome uncovers the evolution, scaling, and transcriptional control of complex gene loci.

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