Ghahremani, A. | Search bioRxiv

bioRxiv2024

Large-Scale Assessment of the Iranian population structure of Mitochondrial and Y-chromosome Haplogroups

The Iranian plateau, strategically positioned as a corridor for population diffusion across Eurasia, holds a pivotal role in elucidating the dynamics of human migrations originating from Africa around 60,000 years ago. Both prehistoric and historic movements of populations between Africa, Asia, and Europe may have been influenced by the unique geographical features of the Iranian plateau. Iran boasts ancient cultures and urban settlements predating some of the earliest civilizations, including the Neolithic revolution in neighboring Mesopotamia. Spanning from the Balkans and Egypt in the west to the Indus Valley in Pakistan and northern India in the southeast, the Iranian plateau encompasses a vast area characterized by incredible ethnocultural diversity. This region served as the origin for numerous mt-DNA/Y-DNA haplogroups that expanded to West Asia, Europe, Siberia, Central Asia, and South Asia. By examining both maternal and paternal haplogroups within the Iranian context, we aim to contribute to the broader narrative of human dispersals and elucidate the role those specific regions, such as the Iranian plateau, played in shaping the observed genetic diversity today. Due to the lack of comprehensive studies on mt-DNA /Y-DNA haplogroups in the Iranian population, our study sought to uncover the distribution of haplogroups among Iranian peoples using a large sample size. Our analysis focused on the frequency of ancestral haplogroups in Iran through the examination of large-scale whole-exome sequencing (WES) and SNP microarray data from 18,184 individuals. In our study, we observed 24 mt-DNA super haplogroups in the Iranian population, with the most common haplogroups belonging to West-Eurasian lineages U (20.73%), H (18.84%), J (12.10%), HV (9.22%), and T (8.98%), collectively comprising 69.70% of all Iranian samples. Notably, subclades J1 and U7 emerged as the two most frequent subclades, with frequencies of 11.24% and 7.30%, respectively. We also revealed the presence of 14 distinct Y-DNA haplogroups, with J, R, G, T, and Q emerging as the five predominant lineages. Notably, J2 (including J-L26) exhibited the highest frequency at 35.64%, followed by R1a at 14.68%. also, The detected mtDNA and Y-chromosome haplogroups were clustered into distinct groups that confirmed the heterogenicity of the Iranian population because of various factors including geographic or linguistic ethnic groups.

genetics↗

bioRxiv2023

Robust Removal of Slow Artifactual Dynamics Induced by Deep Brain Stimulation in Local Field Potential Recordings using SVD-based Adaptive Filtering

Deep brain stimulation (DBS) is widely used as a treatment option for patients with movement disorders. In addition to its clinical impact, DBS has been utilized in the field of cognitive neuroscience wherein the answers to several fundamental questions underpinning the mechanisms of neuromodulation in decision making rely on how a burst of DBS pulses, usually delivered at clinical frequency, i.e., 130 Hz, perturb participants choices. It was observed that neural activities recorded during DBS were contaminated with stereotype large artifacts, which lasts for a few milliseconds, as well as a low-frequency (slow) signal ([~]1-2 Hz) that can persist for hundreds of milliseconds. While the focus of the most of methods for removing DBS artifact was on the former, the artifact removal of the slow signal has not been addressed. In this work, we propose a new method based on combining singular value decomposition (SVD) and normalized adaptive filtering to remove both large (fast) and slow artifacts in local field potentials recorded during a cognitive task in which bursts of DBS were utilized. Using synthetic data, we show that our proposed algorithm outperforms four commonly used techniques in the literature, namely, (1) Normalized least mean square adaptive filtering, (2) Optimal FIR Wiener filtering, (3) Gaussian model matching, and (4) Moving average. The algorithms capabilities are further demonstrated by its ability to effectively remove DBS artifacts in local field potentials recorded from the subthalamic nucleus during a verbal Stroop task, highlighting its utility in real-world applications.

neuroscience↗