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High-quality reference genomes are fundamental tools for understanding population history, and can provide estimates of genetic and demographic parameters relevant to the conservation of biodiversity. The federally endangered Pacific pocket mouse (PPM), which persists in three small, isolated populations in southern California, is a promising model for studying how demographic history shapes genetic diversity, and how diversity in turn may influence extinction risk. To facilitate these studies in PPM, we combined PacBio HiFi long reads with Omni-C and Hi-C data to generate a de novo genome assembly, and annotated the genome using RNAseq. The assembly comprised 28 chromosome-length scaffolds (N50 = 72.6 MB) and the complete mitochondrial genome, and included a long heterochromatic region on chromosome 18 not represented in the previously available short-read assembly. Heterozygosity was highly variable across the genome of the reference individual, with 18% of windows falling in runs of homozygosity (ROH) >1 MB, and nearly 9% in tracts spanning >5 MB. Yet outside of ROH, heterozygosity was relatively high (0.0027), and historical Ne estimates were large. These patterns of genetic variation suggest recent inbreeding in a formerly large population. Currently the most contiguous assembly for a heteromyid rodent, this reference genome provides insight into the past and recent demographic history of the population, and will be a critical tool for management and future studies of outbreeding depression, inbreeding depression, and genetic load.

The intraoperative diagnosis of brain tumors remains a clinical challenge despite recent technological advances. The current clinical practice differentiates non-surgical brain tumors from those preferably treated with cytoreductive surgery employing intraoperative frozen section diagnostics. A detailed molecular diagnosis required for this classification task within the timeframe of a routine neurosurgical procedure is currently unavailable. We have analyzed a clinical cohort of several brain tumor entities using Nanopore long-read sequencing on two Oxford Nanopore Technologies sequencing platforms (MinION, PromethION). Since currently available molecular cancer classifiers such as the DKFZ methylation profiling classifier cannot be readily adapted to real-time sequencing analysis, we implemented a novel algorithm (MethyLYZR) to predict the underlying cancer type. Publicly available Illumina Infinium array data were used to train the classifier to distinguish 91 brain tumor classes. For validation of classification accuracy, we conducted a comprehensive validation strategy. Both nanopore platforms could sequence more than 5,000 pre-selected CpG within less than 20 minutes for most of our samples. When combining an optimized library preparation protocol with the time used for sequencing the minimal number of CpGs needed for classification, we saw sample-to-answer times of less than 1 hour – in many cases within 45 minutes - from receiving a fresh biopsy to a robust cancer type prediction. Comparing actual and predicted diagnoses resulted in a favorable error rate, indicating potentially highly clinical validity. Our real-time based molecular diagnostic algorithm enables, in most cases, a reliable diagnostic call within the timeframe of a typical neuro-oncological surgery. MethyLYZR as a predictive tool may allow us to adjust the surgical strategy and deliver the prognosis to our patients right after surgery, thus allowing for as-of-yet unexplored opportunities for the intraoperative application of individualized therapeutic modalities.

The northern white rhinoceros (NWR; Ceratotherium simum cottoni) is functionally extinct, with only two females remaining alive. Efforts to rescue the NWR have inspired the exploration of unconventional conservation methods, including the generation of artificial gametes from induced pluripotent stem cells and somatic cell nuclear transfer. To enable the technologies required for these approaches, we used complementary sequencing and mapping methods to generate a NWR chromosome-level reference genome that meets or exceeds the metrics proposed by the Vertebrate Genome Project. It represents 40 autosomes, an X and a partially-resolved Y chromosome, and the mitochondrial genome. We compared the NWR reference genome to the southern white rhinoceros (SWR) population that has been physically separated from the NWR for tens of thousands of years. Using short-read data from the SWR and optical mapping, we found that the two populations are very similar on both the chromosome level and mitochondrial genome level. The results of this study are encouraging for the efforts underway to rescue the NWR.

In October 2020, 62 scientists from nine nations worked together remotely in the Second Baylor College of Medicine & DNAnexus hackathon, focusing on different related topics on Structural Variation, Pan-genomes, and SARS-CoV-2 related research. The overarching focus was to assess the current status of the field and identify the remaining challenges. Furthermore, how to combine the strengths of the different interests to drive research and method development forward. Over the four days, eight groups each designed and developed new open-source methods to improve the identification and analysis of variations among species, including humans and SARS-CoV-2. These included improvements in SV calling, genotyping, annotations and filtering. Together with advancements in benchmarking existing methods. Furthermore, groups focused on the diversity of SARS-CoV-2. Daily discussion summary and methods are available publicly at https://github.com/collaborativebioinformatics provides valuable insights for both participants and the research community.

Analysis of large gene expression datasets from biopsies of cancer patients can identify co-expression signatures representing particular biomolecular events in cancer. Some of these signatures involve genomically co-localized genes resulting from the presence of copy number alterations (CNAs), for which analysis of the expression of the underlying genes provides valuable information about their combined role as oncogenes or tumor suppressor genes. Here we focus on the discovery and interpretation of such signatures that are present in multiple cancer types due to driver amplifications and deletions in particular regions of the genome after doing a comprehensive analysis combining both gene expression and CNA data from The Cancer Genome Atlas.

This paper studies the exponential and Butterworth low-pass filtering methods and proposes improved exponential and Butterworth low-pass filters. The improved low-pass filters proposed in the paper can be used effectively for filtering processing of digital speckle interference fringes obtained in digital speckle pattern interferometry. Both theoretical analysis and experimental results are presented in the paper.

Ideal low-pass filtering methods were studied in detail and adaptive elliptical ideal low-pass filters proposed for the first time. The proposed adaptive elliptical ideal low-pass filters can be used effectively for denoising of digital speckle interferograms obtained in phase-shifting digital speckle pattern interferometry. The shape of adaptive elliptical ideal low-pass filters is determined according to the spectrum distribution of interference fringes by using the adaptive method. Theoretical analysis, simulation calculation, and experimental results are presented, and are in good agreement.