Jacobsen, N. | Search bioRxiv

bioRxiv2020

Molecular evidence for the hybrid origin of Cryptocoryne xpurpurea Ridl. nothovar. purpurea (Araceae)

Natural hybridization has been considered a source of taxonomic complexity in Cryptocoryne. A combined study of DNA sequencing data from internal transcribed spacer (ITS) of nuclear ribosomal DNA and trnK-matK region of chloroplast DNA was used to identify the parents of Cryptocoryne putative hybrids from Peninsular Malaysia. Based on the morphological intermediary and sympatric distribution, the plants were tentatively identified as the hybrid Cryptocoryne xpurpurea nothovar. purpurea; plants were pollen sterile and had long been considered to be hybrids, possibly between two related and co-existing species, C. cordata var. cordata and C. griffithii. The C. xpurpurea nothovar. purpurea status was independently confirmed by the presence of an additive ITS sequence pattern from these two parental species in hybrid individuals. Analysis of the chloroplast trnK-matK sequences showed that the hybridization is bidirectional with the putative hybrids sharing identical sequences from C. cordata var. cordata and C. griffithii, indicating that both putative parental species had been the maternal parent in different accessions.

molecular biology↗

bioRxiv2017

Building a high-resolution in vivo minimum deformation average model of the human hippocampus

ObjectiveMinimum deformation averaging (MDA) procedures exploit the information contained in inter-individual variations to generate high-resolution, high-contrast models through iterative model building. However, MDA models built from different image contrasts reside in disparate spaces and their complementary information cannot be utilized easily. The aim of this work was to develop an algorithm for the non-linear alignment of two MDA models with different contrasts to create a high-resolution in vivo model of the human hippocampus with a spatial resolution of 300 m.\n\nMethodsA Turbo Spin Echo MDA model covering the hippocampus was contrast matched to a whole-brain MP2RAGE MDA model and aligned using cross-correlation and non-linear transformation. The contrast matching algorithm followed a global voxel location-based approach to estimate the relationship between intensity values of the two models. The performance of the algorithm was evaluated by comparing it to a non-linear registration obtained using mutual information without contrast matching. The complimentary information from both contrasts was then utilized in an automated hippocampal subfield segmentation pipeline.\n\nResultsThe contrast of the Turbo Spin Echo MDA model could successfully be matched to the MP2RAGE MDA model. Registration using cross correlation provided more accurate alignment of the models compared to a mutual information based approach. The segmentation using ASHS resulted in hippocampal subfield delineations that resembled the tissue boundaries observed in the Turbo Spin Echo MDA model.\n\nConclusionThe developed contrast matching algorithm facilitated the creation of a high-resolution multi-modal in vivo MDA model of the human hippocampus. This model can be used to improve algorithms for hippocampal subfield segmentation and could potentially support the early detection of neurodegenerative diseases.

neuroscience↗