K562 is widely used in biomedical research. It is one of three tier-one cell lines of ENCODE and also most commonly used for large-scale CRISPR/Cas9 screens. Although its functional genomic and epigenomic characteristics have been extensively studied, its genome sequence and genomic structural features have never been comprehensively analyzed. Such information is essential for the correct interpretation and understanding of the vast troves of existing functional genomics and epigenomics data for K562. We performed and integrated deep-coverage whole-genome (short-insert), mate-pair, and linked-read sequencing as well as karyotyping and array CGH analysis to identify a wide spectrum of genome characteristics in K562: copy numbers (CN) of aneuploid chromosome segments at high-resolution, SNVs and indels (both corrected for CN in aneuploid regions), loss of heterozygosity, megabase-scale phased haplotypes often spanning entire chromosome arms, structural variants (SVs), including small and large-scale complex SVs and nonreference retrotransposon insertions. Many SVs were phased, assembled, and experimentally validated. We identified multiple allele-specific deletions and duplications within the tumor suppressor gene FHIT. Taking aneuploidy into account, we reanalyzed K562 RNA-seq and whole-genome bisulfite sequencing data for allele-specific expression and allele-specific DNA methylation. We also show examples of how deeper insights into regulatory complexity are gained by integrating genomic variant information and structural context with functional genomics and epigenomics data. Furthermore, using K562 haplotype information, we produced an allele-specific CRISPR targeting map. This comprehensive whole-genome analysis serves as a resource for future studies that utilize K562 as well as a framework for the analysis of other cancer genomes.
HepG2 is one of the most widely used human cancer cell lines in biomedical research and one of the main cell lines of ENCODE. Although the functional genomic and epigenomic characteristics of HepG2 are extensively studied, its genome sequence has never been comprehensively analyzed and higher order genomic structural features are largely unknown. The high degree of aneuploidy in HepG2 renders traditional genome variant analysis methods challenging and partially ineffective. Correct and complete interpretation of the extensive functional genomics data from HepG2 requires an understanding of the cell line’s genome sequence and genome structure. Using a variety of sequencing and analysis methods, we identified a wide spectrum of genome characteristics in HepG2: copy numbers of chromosomal segments at high resolution, SNVs and Indels (corrected for aneuploidy), regions with loss of heterozygosity, phased haplotypes extending to entire chromosome arms, retrotransposon insertions and structural variants (SVs) including complex and somatic genomic rearrangements. A large number of SVs were phased, sequence assembled and experimentally validated. We re-analyzed published HepG2 datasets for allele-specific expression and DNA methylation and assembled an allele-specific CRISPR/Cas9 targeting map. We demonstrate how deeper insights into genomic regulatory complexity are gained by adopting a genome-integrated framework.
Long range (LoRa) has gained popularity in realizing Internet of Things applications by facilitating long-range communication with low-power consumption. However, LoRa faces scalability issues due to its unsophisticated random access (RA) protocol, Aloha, which is vulnerable to collision and not scalable in dense network scenarios. In contrast, distributed queuing (DQ), a collision-free contention-based RA protocol, is a promising candidate for replacing Aloha because of its near-optimal performance and independence from the traffic load and pattern. However, DQ is not compatible with LoRa, as it was initially designed to operate on CableTV that supports the full-duplex (FDX) bidirectional link. In FDX, the contention feedback overhead is negligible. Most wireless networks, such as LoRa, support the half-duplex, for which the feedback overhead is considerable. Furthermore, a reduction in efficiency is aggravated under a multichannel environment because of an unbalanced traffic load. This study proposes a joint distributed queueing protocol to consider contention for LoRa that minimizes control overhead and achieves interchannel load balancing. Our analysis shows that the proposed protocol reduces the control overhead by up to 70% compared to DQ. The protocol performance demonstrates near-optimum throughput and access delay, irrespective of the number of arrivals.
LoRa is an unlicensed band-based low-power and wide-area (LPWA) technology, which has great network resource constraints because of its limited available frequency resource due to narrow industrial scientific medical (ISM) band, long response time due to its low data rate and low resource utilization due to its primitive medium access control (MAC). This paper studies efficient resource allocation scheme for LoRa, aiming to improve the utilization and the efficiency. Firstly, we define a novel LoRa channel model based on the unique channel characteristic depending on spreading factor (SF) and band-width (BW). Secondly, we present channel selection candidate models suitable for the channel model and LoRaWAN standard. Lastly, we show that our allocation problem is similar to minimum weighted sum bin packing problem (BPP), which is aimed to minimize (i) the number of bins or (ii) the amount each bin contains, known for NP-hard and NP-complete problem respectively. Then with two goals, the energy consumed by all nodes in the network or the response time for all request to be dealt can be optimized.
K562 is widely used in biomedical research. It is one of three tier-one cell lines of ENCODE and also most commonly used for large-scale CRISPR/Cas9 screens. Although its functional genomic and epigenomic characteristics have been extensively studied, its genome sequence and genomic structural features have never been comprehensively analyzed. Such information is essential for the correct interpretation and understanding of the vast troves of existing functional genomics and epigenomics data for K562. We performed and integrated deep-coverage whole-genome (short-insert), mate-pair, and linked-read sequencing as well as karyotyping and array CGH analysis to identify a wide spectrum of genome characteristics in K562: copy numbers (CN) of aneuploid chromosome segments at high-resolution, SNVs and Indels (both corrected for CN in aneuploid regions), loss of heterozygosity, mega-base-scale phased haplotypes often spanning entire chromosome arms, structural variants (SVs) including small and large-scale complex SVs and non-reference retrotransposon insertions. Many SVs were phased, assembled, and experimentally validated. We identified multiple allele-specific deletions and duplications within the tumor suppressor gene FHIT . Taking aneuploidy into account, we re-analyzed K562 RNA-seq and whole-genome bisulfite sequencing data for allele-specific expression and allele-specific DNA methylation. We also show examples of how deeper insights into regulatory complexity are gained by integrating genomic variant information and structural context with functional genomics and epigenomics data. Furthermore, using K562 haplotype information, we produced an allele-specific CRISPR targeting map. This comprehensive whole-genome analysis serves as a resource for future studies that utilize K562 as well as a framework for the analysis of other cancer genomes.
The single-hop star-of-stars topology in low-power and wide-area networks (LPWAN) exhibits reliability and substandard coverage issues, especially in urban areas where line-of-sight (LoS) communication is difficult to achieve. Moreover, LPWAN trade-off the data rate to achieve longer coverage, preventing other end-devices from using the time resource. Locating other gateways is uneconomical as it requires infrastructure, such as the internet and a power connection. In this study, we propose a forwarding scheme with a relay to increase LPWAN coverage and reliability while not degrading the network’s capacity. A relay tends to incur unnecessary forwarding that degrades the network capacity unless proper countermeasure is prepared. Our works, namely opportunistic and on-demand network coding (OODC), minimize unnecessary forwarding and make good use of multiple-receiving relays. Network coding is also applied in the relay for better transmission efficiency and reliability simultaneously. Because network coding occurs header overhead, we perform a header compression technique to counter it. According to our simulation result, our method shows better reliability than fixed path forwarding. In an adaptive data rate settings, the OODC achieves a 92% packet delivery ratio (PDR), whereas a fixed-path forwarding only achieves an 84% PDR.