Category Archives: Transhuman News

Abstract

The red panda (Ailurus fulgens), an endangered Himalaya-endemic mammal, has been classified as two subspecies or even two species the Himalayan red panda (A. fulgens) and the Chinese red panda (Ailurus styani) based on differences in morphology and biogeography. However, this classification has remained controversial largely due to lack of genetic evidence, directly impairing scientific conservation management. Data from 65 whole genomes, 49 Y-chromosomes, and 49 mitochondrial genomes provide the first comprehensive genetic evidence for species divergence in red pandas, demonstrating substantial inter-species genetic divergence for all three markers and correcting species-distribution boundaries. Combined with morphological evidence, these data thus clearly define two phylogenetic species in red pandas. We also demonstrate different demographic trajectories in the two species: A. styani has experienced two population bottlenecks and one large population expansion over time, whereas A. fulgens has experienced three bottlenecks and one very small expansion, resulting in very low genetic diversity, high linkage disequilibrium, and high genetic load.

The delimitation of species, subspecies, and population is fundamental for insights into the biology and evolution of species and effective conservation management. Traditionally, species, subspecies, or population delimitation is based on reproductive isolation, geographic isolation, and/or morphological differences and does not consider the role of gene flow. The misclassification of basal taxa will result in erroneous or misleading conclusions about the species evolutionary history and adaptive mechanisms, and potentially inappropriate conservation management decisions for threatened species (1, 2).

The red panda (Ailurus fulgens), an endangered Himalaya-endemic mammal, was once widely distributed across Eurasia but is now restricted at the southeastern and southern edges of the Qinghai-Tibetan Plateau within an altitude range of 2200 to 4800 m (3). On the basis of differences in morphology (e.g., skull morphology, coat color, and tail ring) and geographic distribution (Fig. 1 and table S1), red pandas are classified into two subspecies, the Himalayan subspecies (A. f. fulgens Cuvier, 1825) and the Chinese subspecies (A. f. styani Thomas, 1902) (4, 5). Morphologically, the Chinese subspecies has much larger zygomatic breadth, the greatest skull length, stronger frontal convexity, more distinct tail rings, and redder face coat color with less white on it (Fig. 1) (5, 6). On the basis of these morphological differences, C. Groves even proposed that the two subspecies should be updated as two distinct species: the Himalayan red panda (A. fulgens) and the Chinese red panda (A. styani) (6). The Nujiang River is considered the geographic boundary between the two species (7). The Himalayan red panda is distributed in Nepal, Bhutan, northern India, northern Myanmar, and Tibet and western Yunnan Province of China, while the Chinese red panda inhabits Yunnan and Sichuan provinces of China. The subspecies or species classification has remained controversial largely due to the lack of genetic evidence, and their distribution boundary may also be inaccurate because of the morphological similarity of red pandas on both sides of the Nujiang River (6, 8, 9). For instance, the skull size and morphology of red pandas from southeastern Tibet were more similar to those of the Chinese red panda than the Himalayan red panda (6). Although previous studies attempted to use mitochondrial DNA or microsatellite markers to explore this problem, the very small sample size from the Himalayan red panda and the limited ability of the molecular markers resulted in failure to resolve the species delimitation (1012). Next-generation sequencing technology not only provides whole-genome data but also enables the identification of Y chromosome sequences in nonmodel animals, which were difficult to obtain previously (13, 14). Thus, it is now feasible to use whole genomes, Y chromosomes, and mitochondrial genomes to comprehensively delimit species, subspecies, and populations. Here, with sufficient sampling of the Himalayan red panda, we performed whole-genome resequencing, Y chromosome single-nucleotide polymorphism (SNP) genotyping, and mitochondrial genome assembly of wild red pandas covering most of the distribution ranges of the two species, aiming to clarify species differentiation, population divergence, demographic history, and the impacts of population bottlenecks on genetic evolutionary potential.

(A and C) The Chinese red panda. (B and D) The Himalayan red panda. (A and B) The face coat color of the Chinese red panda is redder with less white on it than that of the Himalayan red panda. (C and D) The tail rings of the Chinese red panda are more distinct than those of the Himalayan red panda, with the dark rings being more dark red and the pale rings being more whitish. Photo credit: (A) Yunfang Xiu, Straits (Fuzhou) Giant Panda Research and Exchange Center, China; does not require permission. (B) Arjun Thapa, Institute of Zoology, Chinese Academy of Sciences. (C) Yibo Hu, Institute of Zoology, Chinese Academy of Sciences. (D) Chiranjibi Prasad Pokheral, Central Zoo, Jawalkhel, Lalitpur, Nepal; does not require permission.

We performed whole-genome resequencing for 65 wild red pandas, with an average of 98.7% genome coverage and 13.9-fold sequencing depth for each individual based on the red panda reference genome (belonging to the Chinese red panda) of 2.34 Gb (15). Using the SNP-calling strategy of the Genome Analysis Toolkit (GATK), we identified a total of 4,932,036 SNPs for further analysis (table S4). On the basis of the whole-genome SNPs, the phylogenetic tree, principal components analysis (PCA), and ADMIXTURE results revealed substantial genetic divergence between the two species, providing the first genomic evidence of species differentiation (Fig. 2, B to D). The middle Himalaya population (MH) belonging to the Himalayan red panda was first divergent from the populations of the Chinese red panda (Fig. 2, B and D). Furthermore, four distinct genetic populations were identified: MH (n = 18), eastern Himalaya-Gaoligong (EH-GLG, n = 3 and 13, respectively), Xiaoxiangling-Liangshan (XXL-LS, n = 12 and 8, respectively), and Qionglai (QL, n = 10) (Fig. 2, B to D; fig. S1; and table S5). The individual SLL1 is the only sampled red panda from the Saluli Mountains (SLL), and its genetic assignment implied gene flow between the SLL population and its adjacent XXL and GLG populations (Fig. 2C). Because of the very small sample size, SLL1 was excluded in any population-level analyses. Traditionally, MH, EH, and the GLG individuals at the western side of the Nujiang River were classified as the Himalayan red panda, while the GLG individuals at the eastern side of Nujiang River, XXL, LS, and QL belonged to the Chinese red panda (7). Our results did not support the Nujiang River as the species distribution boundary because the EH and part of the GLG population at the western side of the Nujiang River clustered into a genetic population with other GLG individuals at the eastern side (Fig. 2, B to D). This EH-GLG genetic clustering was supported by morphological evidence that the morphology of red panda skulls from southeastern Tibet (namely, the EH population in this study) was more similar to that of the Chinese red panda than the Himalayan red panda (6). In addition, two individuals from Myanmar (GLG5 and GLG6) also clustered within the EH-GLG genetic cluster, suggesting that the Myanmar population belongs to the Chinese red panda. Thus, we infer that the Yalu Zangbu River, the largest geographic barrier to dispersal between the two species, may be the potential boundary for species distribution (Fig. 2A), although additional samples need to be collected from Bhutan and India to verify this inference.

(A) The geographic distribution of wild red panda samples under the background of habitat suitability. Red, QL population; purple, XXL-LS population; blue, SLL population; pink, EH-GLG; dark red, MH. (B) Maximum likelihood phylogenetic tree based on whole-genome SNPs, with the ferret as the outgroup. The values on the tree nodes indicate the bootstrap support of 50%. (C) ADMIXTURE result based on whole-genome SNPs with K = 2 to 7. (D) PCA result based on whole-genome SNPs. (E) Network map based on eight Y chromosome SNP haplotypes. (F) Network map based on 41 mitochondrial genome haplotypes.

Within the Chinese red panda, we further found population genetic differentiation. EH-GLG first diverged with XXL-LS-QL and then QL separated from XXL-LS (Fig. 2, B and C). Notably, we did not detect genetic substructure within EH-GLG spanning the famous Three Parallel Rivers (Nujiang River, Lancangjiang, and Jinshajiang), suggesting that the three large rivers did not hinder the gene flow of red pandas. This result is consistent with data from microsatellite markers (12).

Our Y chromosome SNP and mitochondrial genome results also supported the substantial divergence between the two species (Fig. 2, E and F; figs. S2 and S3; and tables S6 to S8). The haplotype networks and phylogenetic trees of both eight Y chromosome SNP (Y-SNP) haplotypes from 49 male individuals and 41 mitochondrial genome haplotypes from 49 individuals showed that the MH haplotypes (Himalayan red panda) clustered together and separated from the haplotypes of the Chinese red panda, highlighting the notable genetic divergence between the two species. In summary, regardless of the whole-genome SNPs, Y-SNPs, or mitochondrial genomes, notable genetic differentiation was found between the two species. Our comprehensive investigations reveal two evolutionarily significant units in red pandas. Under the phylogenetic species concept (16), it is reasonable to propose two species: the Himalayan red panda (A. fulgens) and the Chinese red panda (A. styani). This phylogenetic species classification was supported by their morphological differences (6).

The Y chromosome SNP and mitochondrial genome results revealed a female-biased gene flow pattern in red pandas (Fig. 2, E and F). Within the Chinese red panda, we observed different phylogeographic patterns between the mitochondrial genome and Y chromosome. The distribution of mitochondrial haplotypes was mixed and was not associated with the geographic sources of the individuals. By contrast, the distribution of Y-SNP haplotypes demonstrated an obvious phylogeographic structure: The haplotypes of EH-GLG were separated from those of XXL-LS-QL, and no shared Y-SNP haplotypes were found. These contrasting phylogeographic patterns reflected a female-mediated historical gene flow, implying female-biased dispersal and male-biased philopatry in red pandas. This dispersal pattern differs from the male-biased dispersal found in most mammals (17) but is similar to that of another bamboo-eating mammal, the giant panda (18, 19).

The pairwise sequentially Markovian coalescent (PSMC) analysis results showed that the demographic history of red panda could be traced back to approximately 3 million years (Ma) ago, and the two red panda species experienced obviously different demographic histories (Fig. 3A). The Chinese red panda from EH-GLG, XXL-LS, and QL experienced similar demographic trajectories: two population bottlenecks and one large population expansion. This species suffered from an obvious population decline approximately 0.8 Ma ago, which coincided with the occurrence of the Naynayxungla Glaciation (0.78 to 0.5 Ma ago). The population decline resulted in the first bottleneck approximately 0.3 Ma ago, mostly likely caused by the Penultimate Glaciation (0.3 to 0.13 Ma ago) (20). After the glaciations, the populations started to expand and reached a climax approximately 50 thousand years (ka) ago. Then, the arrival of the last glaciations again resulted in rapid population decline, and the second bottleneck occurred during the Last Glacial Maximum (~20 ka ago) (20).

(A) PSMC analysis revealed different demographic histories of the two species, with a generation time (g) of 6 years and a mutation rate () of 7.9 109 per site per generation. The time axis is logarithmic transformed. (B) Fastsimcoal2 simulation reconstructed the divergence, admixture, and demographic history of red panda species and populations. The time axis is logarithmic transformed, and the number of migrants per year between two adjacent populations is shown beside each arrow. (C) TreeMix analysis detected significant gene flow from the EH-GLG to XXL-LS populations. s.e., standard error.

The Himalayan red panda from MH underwent a demographic history differing from that of the Chinese red panda: three population bottlenecks and one small expansion (Fig. 3A). The difference began with the first population bottleneck approximately 0.25 Ma ago. In contrast to the subsequent population recovery of the Chinese red panda, the Himalayan red panda continued to decrease and then went through a second bottleneck approximately 90 ka ago. Afterward, the population started to increase very slowly, but soon the population again decreased due to the last glaciations. The PSMC results showed that even at the climax of population growth (~50 ka ago), the effective population size of the Himalayan red panda was only approximately 35% that of the Chinese red panda. In addition, the Bayesian skyline plot (BSP) analyses based on mitochondrial genomes indicated that both species experienced recent population declines most likely caused by the Last Glacial Maximum, supporting the PSMC results (fig. S4). The different demographic trajectories may result from geographic and climate differences. The Chinese red panda was mainly distributed in the Hengduan Mountains rather than the platform or adjacent edges of the Qinghai-Tibetan Plateau and thus might have suffered less impact of the Pleistocene glaciations. The interglacial warm climate and the vast region of the Hengduan Mountains might have facilitated the rapid population expansion of the Chinese red panda (3). By contrast, the Himalayan red panda lived in the adjacent southern edge of the Qinghai-Tibetan Plateau and might have suffered severe impact of the Pleistocene glaciations. Even during the interglacial period, the geographic proximity to glaciers and limited potential habitat might have restricted this species population recovery (21). In Holocene, the climate might have less impact on red panda populations (21), while increasing human activities became the main factor driving recent red panda population declines, which have been detected by microsatellite marker-based Bayesian population simulations (12).

We further uncovered the species/population divergence history using Fastsimcoal2 simulation. On the basis of the comparison of alternative population divergence models, we determined the best-support divergence/demography model (Fig. 3B, fig. S5, and table S9). The divergence between the Himalayan (MH) and Chinese red pandas (EH-GLG, XXL-LS, and QL) occurred 0.22 Ma ago, coincident with the first population bottleneck of the two species caused by the Penultimate Glaciation. Next, EH-GLG and XXL-LS-QL diverged 0.104 Ma ago. The divergence may have resulted from the widely unsuitable habitat located in the Daxueshan and SLL Mountains (21). Last, XXL-LS and QL diverged 26 ka ago, which was most likely caused by the Last Glacial Maximum. After the population divergence, MH, EH-GLG, and QL suffered from population decline, whereas XXL-LS experienced population growth. Asymmetrical gene flow was detected between adjacent divergent populations (Fig. 3B). After the early divergence between the two species, more gene flow occurred from the Chinese red panda to the Himalayan red panda. Regardless of historical or current gene flow, EH-GLG seemed to be the source population of gene flow with more gene flow into other adjacent populations, among the four genetic populations (Fig. 3B). This implies that EH-GLG might be the historical dispersal source of red pandas. TreeMix analysis also detected significant gene flow from EH-GLG to XXL-LS (Fig. 3C and fig. S6), consistent with the Fastsimcoal2 result.

Whole-genome variation analysis revealed that EH-GLG had the highest genetic diversity ( = 6.994 104, w = 5.271 104), whereas the Himalayan red panda (MH) had the lowest genetic diversity ( = 3.523 104, w = 2.428 104) (Fig. 4A and table S10). Y-SNP and mitochondrial genomic variations also showed that the Himalayan red panda (MH) had the lowest genetic variations (Fig. 4A and table S10). Genome-wide linkage disequilibrium (LD) analysis demonstrated that the Himalayan red panda (MH) had higher level of LD and slower LD decay with a reduced R2 correlation coefficient becoming stable at a distance of approximately 100 kb, whereas the populations of the Chinese red panda exhibited rapid LD decay with a reduced R2 becoming stable at a distance of approximately 40 kb (Fig. 4B). The genomic variations and LD patterns imply different demographic histories of the two species and, in particular, reflect the genetic impacts of long-term population bottlenecks in the Himalayan red panda.

(A) Genetic variations (nucleotide diversity) of different species and populations based on whole-genome SNPs, mitochondrial genomes, and Y chromosome SNPs. (B) LD of the four populations. (C) Ratios of homozygous derived deleterious or LoF variants to homozygous derived synonymous variants for different populations. The horizontal bars denote population means. (D) Distribution of ratios (non-MH/MH) and Z(FST) values. Data points located to the left of the left vertical dashed lines and the right of the right vertical dashed lines (corresponding to the 5% left and right tails of the empirical ratio distribution, respectively) and above the horizontal dashed line [the 5% right tail of the empirical Z(FST) distribution] were identified as selected regions for the MH (the Himalayan red panda, green points) and non-MH (the Chinese red panda, blue points) populations.

We further analyzed the relationship between demographic history and genetic loads carried by different red panda populations, as deleterious variations should be removed more efficiently in larger populations (22, 23). We investigated the distributions of four types of variations [loss of function (LoF), deleterious, tolerated, and synonymous mutations] in protein-coding genes. We found that the ratios of homozygous derived deleterious or LoF variants to homozygous derived synonymous variants were higher in the Himalayan red panda (MH) than in the Chinese red panda; by contrast, the ratios of nonhomozygous derived deleterious or LoF variants to nonhomozygous derived synonymous variants were comparable between the two species (Fig. 4C). This genetic load pattern showed that the Himalayan red panda experiencing long-term population bottlenecks carried more homozygous LoF and deleterious mutations and thus suffers a higher risk of continuing population decline.

Considering that the two red panda species live in different geographic ranges and climate environments and experienced long-term genetic divergence, we mainly focused on the identification of genomic signatures of selection and local adaptation between the two species. Using FST and methods, we identified 146 genes with top 5% maximum FST values and top 5% minimum 1/2 values in the Himalayan red panda (MH) (Fig. 4D and table S11). The functional enrichment found that some genes were enriched in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of vascular smooth muscle contraction (ko04270, P = 1.18 108) and melanogenesis (ko04916, P = 2.36 104) and the gene ontology (GO) term of positive regulation of endothelial cell proliferation (GO:0001938, P = 0.0197) (tables S12 and S13). The selection of these genes might be related with the distinct coat color of the Himalayan red panda and the adaptation to hypoxia and microclimate in high-elevation habitat (6).

In the Chinese red panda (EH-GLG, XXL-LS, and QL), we identified 178 genes under selection (Fig. 4D and table S14), which were partly enriched in the nonhomologous end-joining pathway (ko03450, P = 9.89 103) and the GO terms of regulation of response to DNA damage stimulus (GO:2001020, P = 3.35 103), cellular response to x-ray (GO:0071481, P = 3.69 103), double-strand break repair via nonhomologous end joining (GO:0006303, P = 0.0189), endothelial cell differentiation (GO:0045446, P = 0.0187), and regulation of response to oxidative stress (GO:1902882, P = 0.021) (tables S15 to S16). These selected genes were most likely involved in the adaptation to high ultraviolet radiation and hypoxia and microclimate in the Hengduan Mountains where the Chinese red panda mainly lives. Considering the recent divergence (0.22 Ma ago) between the Himalayan and Chinese red pandas, the ancestor of the two species should have adapted to a high-elevation environment before divergence because the latest and most significant uplift of the Qinghai-Tibetan Plateau have occurred 1.1 to 0.6 Ma ago and caused the altitude to increase up to 3000 m (24). Finding their common genetic mechanisms for high-elevation adaptation proved to be difficult based on our comparison of population genome data. The above functional enrichment results more likely reflected the adaptation of both red pandas to the local microclimate and habitat environment. Recent study showed that the two red panda species have separate climatic spaces dominated by precipitation-associated variables in the Himalayan red panda and by temperature-associated variables in the Chinese red panda (21).

Our analyses of whole genomes, Y chromosomes, and mitochondrial genomes revealed substantial genetic differentiation between the Himalayan and Chinese red pandas and provide the most comprehensive genetic evidence of species delimitation. When combined with previously identified morphological differences (6), the classification of two phylogenetic species is well defined. Our genomic evidence rejected the previous viewpoint of the Nujiang River as the species distribution boundary and revealed that the red pandas living in southeastern Tibet and northern Myanmar belong to the Chinese red panda, while the red pandas inhabiting southern Tibet belong to the Himalayan red panda together with the Nepalese individuals. We infer that the Yalu Zangbu River is most likely the geographic boundary for species distribution because this river is the largest geographic barrier between the two species. However, further verification with samples from Bhutan and India is needed. The delimitation of two red panda species has crucial implications for their conservation, and effective species-specific conservation plans could be formulated to protect the declining red panda populations (25). For a long time, the unclear status of species classification and distribution boundary hindered the scientific design of conservation measures. Because of the wrong distribution boundary, the EH-GLG population was split to belong to two species, which could result in inappropriate conservation measures for EH-GLG population and possibly detrimental interbreeding between the two species in captivity. Within the Chinese red panda, our results revealed three genetic populations: EH-GLG, XXL-LS, and QL, suggesting three management units for scientific conservation. In particular, the EH-GLG population spans southeastern Tibet and northwestern Yunnan of China, northern Myanmar, and northeastern India, which needs transboundary international cooperation for effective conservation. The QL population has the lowest genomic diversity and thus needs more attention to the conservation of its genetic evolutionary potential.

Our findings uncover the genetic impacts of long-term population bottlenecks in the Himalayan red panda, thus providing critical insights into the genetic status and evolutionary history of this poorly understood species. The long-term population bottleneck severely impaired its genetic evolutionary potential, resulting in the lowest genetic diversity but higher genetic load. The Himalayan red panda was estimated to have a small population size (26), and thus maintaining and increasing this species population size and genetic diversity are critical for their long-term persistence. In particular, the Himalayan red panda population spans southern Tibet of China, Nepal, India, and Bhutan, which needs urgent transboundary international cooperation to protect this decreasing species.

Our findings reveal that in addition to Pleistocene glaciations and recent human activity, female-biased gene flow has played an important role in shaping the demographic trajectories and genetic structure of red pandas. As a Himalaya-endemic species, our findings will also help understand the phylogeographic patterns of fauna distributed in the Himalaya-Hengduan Mountains biodiversity hotspot.

We collected blood, muscle, and skin samples of 65 wild red pandas from seven main geographic populations for whole-genome resequencing. Of the 65 individuals, 18 individuals were from the middle Himalayan Mountains (MH), 3 from the eastern Himalayan Mountains (EH), 13 from the Gaoligong Mountains (GLG), 1 from the Saluli Mountains (SLL), 12 from the Xiaoxiangling Mountains (XXL), 8 from the Liangshan Mountains (LS), and 10 from the Qionglai Mountains (QL) (Fig. 2A and table S2). For Y chromosome SNP genotyping, we first used red pandaspecific sex determination primers (27) to identify the sexes of the available wild samples. As a result, 49 wild male red pandas were used, including 13 from the MH population, 2 from EH, 10 from GLG, 8 from XXL, 5 from LS, and 11 from QL (table S2). For mitochondrial genome assembly, we successfully assembled 49 complete mitochondrial genomes from the whole-genome resequencing data for 49 of 65 wild red pandas, including 13 from MH, 2 from EH, 9 from GLG, 12 from XXL, 4 from LS, and 9 from QL (table S2).

We extracted genomic DNA from blood, muscle, and skin samples using the QIAGEN DNeasy Blood & Tissue Kit. Then, we constructed genomic libraries of insert size 200 to 500 base pairs and performed genome resequencing of the average 10 for each individual using the Illumina HiSeq 2000 and X Ten sequencing platforms (table S3). To identify population-level SNPs, the Illumina sequencing reads were aligned to the red panda reference genome (15) with Burrows-Wheeler Alignment (BWA) tool v0.7.8 (28), and polymerase chain reaction (PCR) duplicates were removed by SAMtools v0.1.19 (29). The UnifiedGenotyper method in GATK v3.1-1-g07a4bf8 software (30) was used for SNP calling with default parameters across the 65 individuals. To obtain reliable SNP, we performed a filtering step with the following set of parameters: depth 4, MQ 40, FS 60, QD 4, maf 0.05, and miss 0.2.

Previously, we de novo sequenced a wild male red panda genome (15), which enabled us to develop Y chromosome SNPs. Using a genome synteny searching strategy and the female dog genome (boxer breed) and the dog male-specific Y chromosome sequences (Doberman breed) as the reference, Fan et al. recently identified a set of nine male-specific Y chromosome scaffolds with a total length of 964 kb from the male red panda genome assembly (table S5) (31). Using the 964-kb male-specific Y chromosome scaffolds as the reference, we aligned the whole-genome resequencing reads of 18 male red pandas to the reference genome using BWA and then performed SNP calling using SAMtools and GATK. As a result, a total of 63 Y-SNPs were identified. Furthermore, we screened 22 Y-SNPs with confirmed polymorphism and good PCR/sequencing performance. Then, we genotyped these Y-SNPs for a total of 49 male red pandas. With the genotyping of more individuals, we found five additional Y-SNPs. As a whole, the dataset of 49 male red pandas with 27 Y-SNPs was used for subsequent paternal population genetics analysis (tables S2, S6, and S7).

We used the Assembly by Reduced Complexity method (32) to assemble mitochondrial genome with the published red panda mitochondrial genome as a reference (33) (GenBank accession: AM711897). First, the sequencing reads of each of the 65 red pandas were mapped onto the mitochondrial genome reference. Second, the mitochondrial genome reference was classified into multiple bins, and the alignment results were used to distribute reads into specific bins. Third, assembly was performed for each bin to produce contigs. Last, the initial reference was replaced with assembled contigs, and the above processes were iterated until stopping criteria have been met (32). The mitochondrial genome sequence used lastly excluded the highly repetitive sequences within the D-loop region.

We conducted PCA for whole-genome SNPs using the program GCTA v1.24.2 (34). A maximum likelihood phylogenetic tree was constructed by RAxML software (35) with the GTRGAMMA model and 100 bootstraps, and the ascertainment bias correction was performed to correct for the impact of invariable sites in the data. Ferret was used as the outgroup (36). Population genetic structure was inferred by ADMIXTURE v1.23 software (37) with default settings. We did not assume any prior information about the genetic structure and predefined the number of genetic clusters (K) from two to seven. We used POPART v1.7 (38) to construct a median-joining network for the Y-SNP haplotypes and mitochondrial genome haplotypes. We constructed the phylogenetic tree based on mitochondrial genomes of 15,238 bp (excluding the D-loop region) using BEAST v1.8.2 (39) with ferret as the outgroup. The best substitution model of GTR + I was selected on the basis of the Bayesian Information Criterion by ModelGenerator v0.85 (40). A strict clock rate was selected on the basis of the assessment of coefficient of variation. A total of 8 108 iterations were implemented with 10% burn-ins. The BEAST running results were assessed by Tracer v1.5 and were annotated by TreeAnnotator v1.10. We constructed the phylogenetic tree based on Y-SNPs data using the maximum likelihood method implemented in RAxML (35), with the ascertainment bias correction and ferret as the outgroup.

To reconstruct the detailed demographic history of each red panda population, we applied the simulation PSMC v0.6.4-r49 (41) to the whole diploid genome sequences, with the following set of parameters: -N 30 t 15 r 5 -p 4 + 25*2 + 4 + 6. We excluded sex-chromosome sequences of the red panda genome by aligning the red panda genome with the dog genome. We selected two to three high-depth sequenced individuals from each population for PSMC analysis (table S3). We estimated the nucleotide mutation rate of red panda using ferret as the comparison species and the following formula: = D g/2T, where D is the observed frequency of pairwise differences between two species, T is the estimated divergence time, and g is the estimated generation time for the two species (42). In this study, the generation time (g) was set to 6 years (26), the estimated divergence time was set to 39.9 Ma ago (15), and D was estimated to be 0.10558. On the basis of the above formula and the corresponding values, a mutation rate of 7.9 109 mutations per site per generation was estimated for the red panda. In addition, we performed BSP analyses based on mitochondrial genomes of 15,994 bp for two species separately, using BEAST v1.8.2. The best substitution model of HKY + I was selected by ModelGenerator v0.85. A strict clock rate was selected with a nucleotide substitution rate (43) of 1.9 108. A total of 8 108 iterations were implemented with 10% burn-ins. The BEAST running results were assessed, and the BSP plots were produced by Tracer v1.5.

We used the flexible and robust simulation-based composite-likelihood approach implemented in Fastsimcoal2 v2.5.2.21 (44) to infer species/population divergence and demographic history with the following parameters: -n 100000 -N 100000 -d -M 0.001 -l 10 -L 40 -q --multiSFS -C10 -c8. Because of the memory limit of Fastsimcoal2 running, we selected 55 individuals among 65 red pandas for simulation analysis (table S2). Four alternative population divergence and demographic models were explored. For each model, we ran the program 50 times with varying starting points to ensure convergence and retained the fitting with the highest likelihood. The best model was selected through the maximum value of the likelihoods. Parametric bootstrap estimates were obtained on the basis of 100 simulated data sets (table S9). In addition, we performed population-level admixture analysis for detecting gene flow among genetic populations using the TreeMix method (45) with the following running parameters: treemix bootstrap k 1000 se noss m 1~5.

For whole-genome data, the nucleotide diversity () (46) and Wattersons estimator (w) (47) of each genetic population were calculated using VariScan v2.0.3 (48). A sliding window approach was used with a 50-kb window sliding in 10-kb steps. We estimated the genetic diversity for the mitochondrial genome data of 15,994 bp and Y-SNPs data using DNASP v5.10.01 (49). To assess the LD pattern in red pandas, the correlation coefficient (R2) between any two loci in each genetic population was calculated using vcftools v0.1.14 (50). Parameters were set as follows: --ld window -bp 500000 geno -r2. Average R2 values were calculated for pairwise markers with the same distance.

We used ANNOVAR (51) to annotate and classify the effects of SNP variants on protein-coding gene sequences. Then, the coding sequence variants were classified as LoF, missense, and synonymous variants. LoF variant denoted variants with gain of a stop codon. The missense variants were further categorized as deleterious and tolerated missense mutations by SIFT 4G (52). We determined the ancestral allele at each SNP position through comparison with the ferret genome (36). To detect the genetic load of each red panda population, for each individual, we counted the relative proportions of homozygous ancestral, heterozygous, and homozygous derived alleles for LoF, deleterious, tolerated, and synonymous variants, respectively. Furthermore, we calculated the ratio of homozygous derived LoF variants (or deleterious variants) to homozygous derived synonymous variants and the ratio of nonhomozygous derived LoF variants (or deleterious variants) to nonhomozygous derived synonymous variants for each individual.

In general, positive selection gives rise to lower genetic diversity within populations and higher genetic differentiation between populations (53). The genetic differentiation index FST (54) and the average proportion of pairwise mismatches over all compared sequences (55) have been widely used to detect selection (53). To detect selection signals possibly associated with local adaptation, we used a sliding-window method (50-kb windows with 25-kb increments) to calculate the genome-wide distribution of FST values and ratios for the two species, implemented in vcftools v0.1.14. We applied z transformation for FST values and log2 transformation for ratios and considered the windows with the top 5% Z(FST) and log2( ratio) values simultaneously as the candidate outliers under strong selection. All outlier windows were assigned to corresponding SNPs and genes. We used the GeneTrail2 method (56) to perform KEGG pathway and GO term enrichment analyses for selected genes located in specific regions. Each significantly enriched category included at least two genes, and the hypergeometric test was used to estimate significance (P < 0.05).

Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/6/9/eaax5751/DC1

Fig. S1. PCA plot of red panda whole-genome SNPs data, with PC1, PC2, and PC3 explaining 28.5, 4.1, and 3.6% of the observed variations, respectively.

Fig. S2. Phylogenetic tree based on 41 mitochondrial genome haplotypes, showing two significant species lineages (A. fulgens and A. styani).

Fig. S3. Phylogenetic tree based on eight Y chromosome SNPs haplotypes, showing two significant species lineages (A. fulgens and A. styani).

Fig. S4. Bayesian skyline plot (BSP) analysis results based on mitochondrial genomes.

Fig. S5. Four alternative population divergence models for Fastsimcoal2 simulations, with the maximum estimated likelihood values shown.

Fig. S6. Residual fit from the maximum likelihood tree estimated by TreeMix.

Table S1. Summary of the morphological differences between the Himalayan and Chinese red pandas.

Table S2. Sample information for whole-genome resequencing, Y chromosome SNP genotyping, mitochondrial genome assembly, and Fastsimcoal2 analysis.

Table S3. Summary of whole-genome resequencing data for 65 red panda individuals that include the individuals for PSMC analysis.

Table S4. Summary of SNP calling based on 65 red panda individuals.

Table S5. Cross-validation error result for varying values of K in the ADMIXTURE analysis.

Table S6. PCR primer information for validating the six male-specific Y-scaffolds of red pandas.

Table S7. PCR primer information for amplifying the SNPs on the male-specific Y-scaffolds.

Table S8. Eight Y-SNP haplotypes identified from 27 Y-SNPs of 49 male red panda individuals.

Table S9. Confidence intervals of key parameters for the best population divergence and demographic model estimated by Fastsimcoal2.

Table S10. Genetic diversity of whole genome, Y chromosome, and mitochondrial genome for different species and populations of red pandas.

Table S11. The 146 genes under selection with top 5% maximum FST values and top 5% minimum 1/2 values in the Himalayan red panda (MH).

Table S12. Significantly enriched KEGG pathways for the 146 genes under selection in the Himalayan red panda (MH).

Table S13. Significantly enriched GO terms of biological processes for the 146 genes under selection in the Himalayan red panda (MH).

Table S14. The 178 genes under selection with top 5% maximum FST values and top 5% minimum 1/2 values in the Chinese red panda (EH-GLG, XXL-LS, and QL).

Table S15. Significantly enriched KEGG pathways for the 178 genes under selection in the Chinese red panda (EH-GLG, XXL-LS, and QL).

Table S16. Significantly enriched GO terms of biological processes for the 178 genes under selection in the Chinese red panda (EH-GLG, XXL-LS, and QL).

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

R. I. Pocock, The fauna of british india including ceylon and burma, in Mammalia, Volume II (Taylor and Francis, 1941).

C. Groves, in Red Panda: Biology and Conservation of the First Panda, A. R. Glatston, Ed. (Academic Press, 2011), pp. 101124.

Y. Gao, Fauna Sinica, Mammalia, Vol. 8: Carnivora (Science Press, 1987).

A. R. Glatston, Status Survey and Conservation Action Plan for Procyonids and Ailurids: The Red Panda, Olingos, Coatis, Raccoons, and their Relatives (IUCN, 1994).

Y. Shi, J. Li, B. Li, Uplift and Environmental Changes of Qinghai-Tibetan Plateau in the Late Cenozoic (Science and Technology Press, 1998).

A. Glatston, F. Wei, Than, Zaw, Sherpa, A. Ailurus fulgens. The IUCN Red List of Threatened Species 2015: e.T714A45195924 (2015).

T. M. Keane, T. J. Naughton, J. O. McInerney, Modelgenerator: Amino Acid and Nucleotide Substitution Model Selection (National University of Ireland, 2004).

M. Nei, Molecular Evolutionary Genetics (Columbia Univ. Press, 1987).

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Genomic evidence for two phylogenetic species and long-term population bottlenecks in red pandas - Science Advances

Genome sequencing was once impossibly expensive. The Human Genome Project, an international effort to decode the human genome that launched in 1990, took 13 years and an estimated $2.7 billion to complete. Then, in 2007, DNA pioneer James Watson became the first person to get his genome sequenced for less than $1 million. Since then, the cost of genome sequencing has been decreasing at a rate faster thanMoores law.

Now,Nebula Genomics, a spinout of Harvard University co-founded by geneticistGeorge Church, is launching an at-home test for less than the price of the latest Apple Watch. At $299, Nebulas service analyzes a persons entire genetic code, known as whole genome sequencing.

Whether there is a mass market for whole genome sequencing remains to be seen. Gillian Hooker, president of the National Society of Genetic Counselors, says one hurdle is that many people just havent heard of whole genome sequencing or are skeptical of how useful the results will be for managing their health.

Right now, most people dont walk away with actionable information, she says. But that will likely change as scientists understanding of genetics evolves.

With the price getting increasingly cheaper, whole genome sequencing could soon replace the more limited genetic tests that dominate the market today.

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Whole genome sequencing could be the next big thing for consumers - Genetic Literacy Project

Researchers explore how an organisms genome affects its ability to live in an extreme environment

The Lagunitas pond in the Cuatro Cinegas Basin of Mexico.

February 25, 2020

The Cuatro Cinegas Basin in the Chihuahuan Desert of Mexico was once a shallow sea. Some 43 million years ago, it became separated from the Gulf of Mexico. The basin is nutrient-poor and harbors a "lost world" of aquatic microbes of ancient marine ancestry.

Because of these characteristics, it is an invaluable place for researchers to study and understand how life may have existed on other planets in our solar system.

In a National Science Foundation-funded study published in the journal eLIFE, a team of researchers at Arizona State University conducted experiments in the basin.

Their goal was to shed light on how an organism's genome -- its size, the way it encodes information, and the density of information -- affects its ability to thrive in an extreme environment.

For their experiment, the scientists conducted field monitoring, sampling and routine water chemistry testing for 32 days in a shallow, nutrient-poor pond called Lagunita.

They installed mesocosms, or miniature ecosystems, that served as a control group and remained separate from the rest of the pond. They then added fertilizer that was rich in nitrogen and phosphorus to increase microbial growth in the pond.

At the end of the experiment, the scientists examined how the community in the pond changed in response to the additional nutrients, focusing on the organisms' ability to process biochemical information in their cells.

Ultimately, the researchers found that indeed a nutrient-enriched community became dominated by species that could process biochemical information at a faster rate, whereas the original low-nutrient community harbored species with reduced biochemical information processing.

"We were able to identify and confirm that there are fundamental genome-wide traits associated with systematic microbial responses to ecosystem nutrient status, without regard to the species identity of those microbes," says Jim Elser, an ecologist at ASU and paper co-author.

What this may suggest for life on other planets is that organisms, no matter where they are, need information-processing machinery fine-tuned to the key resources around them.

"This study provides new insights into how microbes adapt to different types of environments, and the tradeoffs they may face in doing so," says Doug Levey, a program director in NSF's Division of Environmental Biology.

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Rules of life: From a pond to the beyond - National Science Foundation

Life science researchers at Tel Aviv University (TAU) have stumbled upon a non-breathing animal, challenging current understanding of the animal world, according to a study published in the Proceedings of the National Academy of Sciences of the United States of America.The research, led by Prof. Dorothee Huchon of the School of Zoology at TAUs Faculty of Life Sciences and Steinhardt Museum of Natural History, detailed the 10-celled parasite organism called Henneguya salminicola that is found in the muscles of salmon. The research was supported by the US-Israel Binational Science Foundation, and conducted along with Prof. Paulyn Cartwright of the University of Kansas, and Prof. Jerri Bartholomew and Dr. Stephen Atkinson of Oregon State University."The parasites anaerobic nature was an accidental discovery," TAU said in a statement. "While assembling the Henneguya genome, Huchon found that it did not include a mitochondrial genome. The mitochondria are the powerhouse of the cell where oxygen is captured to make energy, so its absence indicated that the animal was not breathing oxygen." The animal itself, a "myxozoan relative" of jellyfish and corals, apparently gave up on breathing and consuming oxygen in order to produce energy, somewhere along its evolutionary track. Aerobic respiration was thought to be ubiquitous in animals, but now we confirmed that this is not the case, Huchon explains. Our discovery shows that evolution can go in strange directions. Aerobic respiration is a major source of energy, and yet we found an animal that gave up this critical pathway.Fungi, amoebas or ciliate lineages living in oxygen-poor environments abandoned the need to consume fresh air quite some time ago, after their evolutionary trajectories followed an anaerobic path. The findings allude to the possibility that the same type of occurrence could happen to an animal if the conditions are right."Its genome was sequenced, along with those of other myxozoan fish parasites," TAU said in a statement. Before the discovery, experts were unsure whether organisms within the animal kingdom could survive without oxygen, given that animals are "multicellular, highly developed organisms, which first appeared on Earth when oxygen levels rose." The findings are important for future evolutionary research.Its not yet clear to us how the parasite generates energy," Huchon said. "It may be drawing it from the surrounding fish cells, or it may have a different type of respiration such as oxygen-free breathing, which typically characterizes anaerobic non-animal organisms. It is generally thought that during evolution, organisms become more and more complex, and that simple single-celled or few-celled organisms are the ancestors of complex organisms.But here, right before us, is an animal whose evolutionary process is the opposite. Living in an oxygen-free environment, it has shed unnecessary genes responsible for aerobic respiration and become an even simpler organism.

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Tel Aviv University researchers discover a non-breathing living animal - The Jerusalem Post

DUBLIN, Feb. 26, 2020 /PRNewswire/ -- The "Genomics Market Size, Share & Trends Analysis Report by Application and Technology (Functional Genomics, Pathway Analysis), by Deliverables (Products, Services), by End Use, by Region, and Segment Forecasts, 2020 - 2027" report has been added to ResearchAndMarkets.com's offering.

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The global genomics market is expected to reach USD 31.1 billion by 2027, registering a CAGR of 7.7% over the forecast period according to this report. Significant changes in disease management processes along with advancements in genomics and personalized medicine are expected to propel the market.

Increasing pool of market innovators such as 23andMe, Oxford Nanopore Technologies, and Veritas Genetics that have launched breakthrough genomic technologies in recent years are also contributing toward market development. 23andMe has expertise in developing direct-to-consumer genomic tests targeted toward disease prognosis and has recently received FDA approval for its commercialization.

MinION - a trademark sequencing device of Oxford Nanopore Technologies, is witnessing significant traction owing to its ability to sequence any fragment length of DNA in real time. On the other hand, Veritas Genetics offers an affordable solution for a complete readout of the genomic sequence. Earlier procured only by doctors, these tests can now be taken by anyone curious about their DNA and costs approximately USD 1,000. The company has also begun the commercialization of this technique for newborn's genomic sequencing applications in China in 2017.

Further key findings from the report suggest:

Key Topics Covered

Chapter 1 Research Methodology

Chapter 2 Executive Summary2.1 Genomics Market Outlook, 2016-2027

Chapter 3 Industry Outlook3.1 Penetration & Growth Prospects Mapping3.2 Trend Analysis3.2.1 Application Trends3.2.2 Product Trends3.2.3 End-Use Trends3.2.4 Regional Trends3.3 Genomics - Market Dynamics3.3.1 Market Driver Analysis3.3.1.1 Growing Integration of Genomics Data into Clinical Workflows3.3.1.1.1 More Targeted and Personalized Healthcare3.3.1.1.2 Growth of Newborn Genetic Screening Programs3.3.1.1.3 Advancements in Non-invasive Cancer Screening3.3.1.1.4 Military Genomics3.3.1.2 Technological Advances to Facilitate Genomic R&D3.3.1.2.1 Emergence of Advanced Genome Editing Techniques3.3.1.2.2 Integration of New Data Streams3.3.1.2.3 RNA Biology3.3.1.2.4 Single Cell Biology3.3.1.3 Rising Adoption of Direct to Consumer Genomics3.3.1.4 Success of Genetic Tools in Agrigenomics3.3.1.5 Increasing Participation of Different Companies3.3.1.6 Increase in Government Role and Funding in Genomics3.3.2 Market Restraint Analysis3.3.2.1 Issues Regarding Intellectual Property Protection, Data Management, and Public Policies3.3.2.2 Dearth of Skilled Personnel3.4 Opportunity Analysis3.5 Industry Analysis - Porter's3.5.1 Supplier Power - Medium3.5.2 Buyer Power - High3.5.3 Substitution Threat - Low3.5.4 New Entrants Threat - Low3.6 Regulatory Landscape: Genomics - SWOT by PEST Analysis3.6.1 Political Landscape3.6.2 Economic Landscape3.6.3 Social Landscape3.6.4 Technology Landscape3.7 Company Market Share Analysis3.8 Competitive Landscape3.8.1 Strategy Framework3.8.2 Company Categorization3.8.2.1 New Entrants3.8.2.2 Mature Players & Leaders

Chapter 4 Genomics Market Categorization: Deliverable Outlook4.1 Genomics Market Share By Deliverable Outlook, 2016 to 20274.2 Products Market, 2016 to 20274.3 Services Market, 2016 to 2027

Companies Mentioned

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Worldwide Genomics Markets, 2020-2027 - Comprehensive Analysis on the $31.1 Billion-Projected Industry - Yahoo Finance

What The Study Found

The largest genomic study of population groups in Asia, generating and analysing whole-genome sequences of 1,739 individuals from 219 groups.

***

On December 5, 2019, scientists from the GenomeAsia 100K project published an article (The GenomeAsia 100K Project enables genetic discoveries across Asia) in the prestigious science journal Nature. It is the largest genomic study of Asian populations, covering 1,739 individuals from 219 different population groups and 64 countries. India has the maximum number of whole-genome sequences at 598. Besides enabling a better understanding of how Asian populations were formed, the resulting work will also make it possible to find out which medicines suit them better, based on genetic data.

The need for a more varied genetic database from populations across the world was highlighted in 2009, when analysis revealed that 96 per cent of participants in genome-wide association studies (GWAS) were of European descent. GWAS studies associate certain diseases with specific variations and the lack of data from different parts of the world meant medicines either couldnt be catered to suit them or were entirely unsuitable to them.

We show that the variant data produced by this project improve variant filtering for the discovery of disease-associated genes of rare diseases. We show that Asia has sizable founder populations and that further studies in these populations may be useful for the discovery of rare-disease-associated genes, the paper says. For example, the researchers found that carbamezepine, an anti-convulsant, may have adverse effects on about 400 million South-East Asians who form part of the Austronesian language group. The paper also mentions that drugs like clopidogrel, peginterferon and warfarin showed the largest variation between populations in predicted adverse drug responses.

Dr Partha P. Majumder, founder of National Institute of Biomedical Genomics, Kalyani, and one of the co-authors, tells Outlook that the differential carbamezepine effect among Austronesians was so striking that we decided to report this quickly. We also report about warfarin, a commonly used blood-thinning drug, used for prevention of blood clots, especially for individuals at high risk for heart attacks.

Using the data, the scientists were able to reveal a DNA variant in a gene (NEUROD1), which is probably responsible for a particular kind of diabetes. Another DNA variant in the haemoglobin gene has been linked to beta-thalassemia found only in South Indians, says Majumder.

The scientists discovered close to 200,000 DNA markers in Asians, which had been previously unreported in existing genetic databases. Majumder explains their significance, saying that the catalogues that are now used for disease-association studies in Asia, including India, are those that have primarily been generated in western populations, hence of limited use in Asia. The scientists also found 23 per cent of previously unreported protein variants. Since alterations of proteins are usually associated with disease, we specifically investigated those DNA variants that alter proteins, says Majumder.

Medicines will become more specific and more useful to us. More importantly, we will not use the medicines that do not work for us, Dr Ch Mohan Rao, distinguished scientist at the Council of Scientific and Industrial Research and former director at the Centre for Cellular & Molecular Biology, tells Outlook. Rao says that the same medicines used in the West are being used without context in Asia, but now studies show that certain mutations (in DNA) are probably benign.

While the fundamental biology discovered by genetic studies at individual sites in the genome are mostly shared across humanity, studies carried out primarily in a single population means we miss low-hanging fruit in other populations, and limit the utility of genomic prediction across other populations, says Vagheesh Narasimhan, fellow at the Reich lab, department of genetics, Harvard Medical School. He adds that scientists are currently able to predict heritable risk of complex diseases several-fold more accurately in European populations than in non-Europeans, putting it down to a lack of similar databases in other countries. Studies such as this one will help close that gap, he adds.

The study also paints a finer picture of how the South Asian populations were formed, while throwing up interesting facets. Close to 4 million years ago, two precursors to modern-day humansthe Neanderthal and the Denisovanevolved. While it was earlier thought that the homo sapien (modern human) wiped out both, our DNA contains a large admixture with them, the degree of mixing varying across Asia. In India, the researchers found that tribal and non-Indo European speakers had more Denisovan DNA than the non-tribals and Indo-European speakers. Elite-caste groups have lesser Denisovan DNA, with Indo-European speakers of Pakistan having the least, he adds.

Majumder says the simplest explanation is that Indo-European-speaking migrants, who came to the subcontinent from the north-west, mixed with an indigenous group ancestral to present-day south Indians; the ancestral group had a high level of Denisovan admixture.

Using an approach from a previous study, the researchers also tried to identify the degree to which populations are inherited as identical by descent (IBD). The researchers found multiple Asian urban populations with IBD scores close to or above the Finnish population. For example, samples from an outpatient hospital in Chennai, a city with a census size of 9 million, had an IBD score that was approximately 1.3 times greater than the score for the Finnish group, the paper says. Majumder explains: It is, therefore, possible that some urban populations may have arisen from a small number of founders and then numerically expanded quickly.

With such large numbers of samples being sequenced, we now have the potential to study population movements and mixtures in much finer detail. Databases like this will also enable better estimates of ancestry and genealogy, says Narasimhan.

When the Human Genome Project began in 1990, India was not part of it. Fortunately, we did not miss out because the whole database was in public. But we did not develop the technology as fast as other countries, says Dr Rao, adding that now things have changed with Indian scientists doing a large part of the work. With India participating in the research our technology and capacity building has increased dramatically. Now we are not second to anyone.

Read more here:
The Genomic Route To Targeted Cures - Outlook India

A nightmarish scene was burnt into my memory nearly two decades ago: Changainjie, Beijings normally chaotic fifth avenue, desolate without a sign of life. Schools shut, subways empty, people terrified to leave their homes. Every night the state TV channels reported new cases and new deaths. All the while, we had to face a chilling truth: the coronavirus, SARS, was so novel that no one understood how it spread or how to effectively treat it. No vaccines were in sight. In the end, it killed nearly 1,000 people.

Its impossible not to draw parallels between SARS and the new coronavirus outbreak, COVID-19, thats been ravaging China and spreading globally. Yet the response to the two epidemics also starkly highlights how far biotech and global collaborations have evolved in the past two decades. Advances in genetic sequencing technologies, synthetic biology, and open science are reshaping how we deal with potential global pandemics. In a way, the two epidemics hold up a mirror to science itself, reflecting both technological progress and a shift in ethos towards collaboration.

Let me be clear: any response to a new infectious disease is a murky mix of science, politics, racism, misinformation, and national egos. Its nave to point to better viral control and say its because of technology alone. Nevertheless, a comparison of the two outbreaks dramatically highlights how the scientific world has changed, for the better, in the last two decades.

A viruss genetic blueprint is the first clue to its origins and traits. The response to COVID-19 was extremely rapid. Within a month of the first identified case in Wuhan, Chinese scientists had deposited the viruss partial genetic blueprint into GenBank, an online, widely-consulted database.

Almost immediately, scientists from all sectorsacademic, biotech, governmentaround the world began ordering parts of the virus genome online to study in their own labs.

The rise of commercial companies that manufacture custom-made DNA molecules, such as Integrated DNA Technology (IDT) and Biobasic, exemplify how much genetic synthesis has changed from 2003 to 2020. Costs for making entire genomes from scratch have dropped dramatically, giving rise to a booming industry of mail-order virus (and other organisms) parts for cheap. Biobasic, for example, offers primers that amplify certain parts of COVID-19 genes at a few bucks apiece. These raw genetic tools, rapidly synthesized and purified to order, form a critical ingredient for scientists to recreate important parts of the virus in their own labs.

Rapid sharing of the viral genome plus easy online ordering make it much easier for scientists to study the bug and test potential vaccines. According to a CBS8 report, Inovio, a biotech company based in San Diego, has already created a potential vaccine for COVID-19 and tested it in mice and guinea pigs. If they gain FDA approval, clinical trials in humans could begin as early as this summer. Sanofi, Moderna, and other pharmaceutical giants are right on Inovios tail. In contrast, a vaccine for SARS took about 20 months to engineer, long after the epidemic had burned out. Although the same fate may await COVID-19, the momentum for vaccine creation is unprecedented.

Going a step further, scientists now also have the ability to recreate COVID-19 from scratch. Partial viral genetic sequences are often sufficient to engineer vaccines. However, only a live, complete version can offer clues to significant questions such as how it spreads, where it came from, and how it jumped from animal to human. For example, by systematically mutating parts of the virus, scientists can decipher critical genes needed for the virus to spread or generate disease, or build more accurate models of its projected spread within the human population.

So far, however, China is the only country with access to the intact virus, which means that other countries need to build the virus directly from its digital DNA code. The technologys been possible for about twenty years, but advances in commercial genetic synthesis are massively simplifying the processes, so much so that the main hurdle is regulatoryfears of lab accidents or bioterrorismrather than technological.

As gene synthesis costs continue to drop and synthetic biology tools become more powerful, lab-made clones of pandemic-level pathogens could become even more prominent to fight off pandemics. As one coronavirus expert said, synthetic viruses are the future in how the medical research community responds to a new threat.

The other distinction between the SARS and COVID-19 responses isnt biotech. Its digital. When SARS broke out in 2003, the internet was only coming online for a majority of users, and email was relatively new. Getting information out from a quarantined region was immensely difficult.

Despite digital challenges, SARS still stood out as a unifying moment where international researchersagainst all odds, rivalry, and internal squabblescame together to share information, specimens, and reagents through personal communications. However, disseminating information to larger audiences relied on government agencies, including the CDC, or academic papers in journals.

In contrast, data exchange for COVID-19 was rapid and abundant. Thanks to the rise of pre-publication servers such as bioRxiv, scientists can now easily circumvent the months-long peer-review process in journal publishing and publish their results directly online.

Open sharing of information is a double-edged sword: because papers on bioRxiv arent peer-reviewed, their quality can be hit or miss. Nevertheless, the resource has rapidly emerged as the online watercooler for scientists studying COVID-19. For example, one team thats building COVID-19 from scratch pulled four different genomic sequences off the server and averaged their results to generate a consensus sequence.

This rapid dissemination of information isnt just helping vaccine development. Its also soothing public fear. A novel, lethal virus is bound to stoke public fear, misinformation, and mistrust, especially if scientists keep mum about early results. BioRxiv provides a way to put preliminary data into the spotlight, where scientists and journalists can examine, build upon, or report solid results to the public.

Pre-publication servers arent perfect; theres a chance of misinformation or misconstrued data, which need to be vetted out. But its clear that bioRxiv is serving a critical role in accelerating viral knowledge, and a testament to the open science movement.

As science becomes more open, its also becoming far more collaborative.

Global collaborations have exploded in numbers since the 2003 SARS outbreak, with international initiatives now a dime a dozen. The scientific communitys response to COVID-19 is a strong example of that shift: in a race against the clock, rather than hogging data for personal fame, lets get everyone to collaborate and accelerate discoveries.

That said, global collaboration is impossible without the ground zero country taking the first step, that is, alerting the world to a new virus outbreak. In 2003, China tried to squash any mention of SARS before it became too big of a problem; in 2019, Chinese officials relatively promptly alerted the World Health Organization to COVID-19 (though not without severe arm-twisting and tragic deaths).

We can marvel at advances in genetic technologies, synthetic biology, or computer modeling for tackling viral epidemics; but fundamentally, preventing a disease outbreak requires early alarm from the country of originembarrassment be damned.

More epidemics will come. Over 30 novel infectious diseases have raged across parts of the globe for the past three decades, and simulations show many viruses in bats and other animal carriers have the potential to directly jump to humans. Scientists have a game plan. Will governments follow?

Image Credit: Novel Coronavirus SARS-CoV-2, NIAID

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How to Battle an Epidemic? Digitize Its DNA and Share It With the World - Singularity Hub

According to research published inNature Communications, comprehensive profiling of tumor samples found that the immunogenomic landscape in osteosarcoma is characterized by genomic complexity and significant heterogeneity.1

Moreover, researchers found that poor infiltration of the tumor by immune cells, low activity from available T-cells, a lack of immune-stimulating neoantigens, and multiple immune-suppressing pathways all combine to dampen responses to immunotherapy in this disease landscape.

This study is important not only because it focuses on a rare cancer, but it sets the groundwork for understanding the multifaceted reasons this cancer doesnt respond to immunotherapy, despite having certain hallmarks that suggest it would, corresponding author Andy Futreal, PhD, chair of Genomic Medicine at MD Anderson Cancer Center, said in a press release.2Understanding those reasons and beginning to pick them apart does begin to give us lines of sight on how to get around the tumors methods of subverting the immune system.

In order to gain insights into the immunogenic potential of this tumor type, researchers conducted whole genome, RNA, and T-cell receptor sequencing, immunohistochemistry and reverse phase protein array profiling (RPPA) on samples from 48 pediatric and adult patients with primary, relapsed, and metastatic osteosarcoma. The majority of the samples were from relapse (23%) and metastatic (51%) cancers.

In the samples, genomic changes were similar to those previously reported and there were few dissimilarities between the sample types. However, in contrast to other disease types, the genomic changes observed in these osteosarcomas did not coincide with an increase in the expression of mutated proteins or neoantigens. Further, the degree of immune cell infiltration into the tumor was found to be generally lower than in other tumor types where immune checkpoint inhibitors are more effective, like lung cancer and melanoma. T-cells in the tumor also displayed a low level of activity, demonstrated by low clonality scores.

These data highlight the need to pursue multiple contributors to immune suppression in [osteosarcoma], the authors wrote. It is unlikely that any single approach will be effective across this patient population.

Gene expression analysis exposed 3 distinct classes within the study samples that corresponded with levels of immune infiltration. Hot tumors were found to have the greatest degree of immune infiltration, however they also had high activity in a number of signaling pathways that suppressed immune activity. Contrastingly, cold tumors had the lowest levels of immune infiltration, reduced expression of human leukocyte antigen (HLA), and a higher number of genes with copy number loss, which signals higher genomic instability.

Notably, researchers also discovered thatPARP2gains and increased expression were correlated with low immune infiltration in cold osteosarcomas, supporting the rationale for studies exploring a combination of PARP inhibitors and immunotherapy. Therefore, ongoing translational studies from patients with osteosarcoma treated with immune checkpoint inhibitors could further inform the next steps in developing immunotherapy trials for this patient population.

By understanding the interplay between tumor genomics and the immune response, we are better equipped to identify osteosarcoma patients who are more likely to benefit from immunotherapy, co-author Andrew Livingston, MD, assistant professor of Sarcoma Medical Oncology and Pediatrics at The University of Texas MD Anderson Cancer Center, said in a press release. These findings lay the groundwork for novel clinical trials combining immunotherapy agents with targeted or cell-based therapies to improve outcomes for our patients.

References:

1. Wu C, Beird HC, Livingston JA, et al. Immuno-genomic landscape of osteosarcoma.Nature Communications. doi:10.1038/s41467-020-14646.

2. Osteosarcoma profiling reveals why immunotherapy remains ineffective [news release]. Houston, Texas. Published February 21, 2020. eurekalert.org/pub_releases/2020-02/uotm-opr022020.php. Accessed February 21, 2020.

Read more from the original source:
Profiling of Osteosarcoma Demonstrates Why Immunotherapy is Ineffective - Cancer Network

The BC Centre for Disease Controls (BCCDC) Public Health Laboratory has announced a newpilot project that will enable researchers to identify and track new cases ofthenovel coronavirus (COVID-19) in British Columbia.

On Feb. 20, Provincial health officer Dr. Bonnie Henry reported thatasixthcase of the novel coronavirus hadbeen diagnosed in B.C.after a woman in her 30s returned to the province this week from travel in Iran. However, she addedthat thewoman's presumptive case is relatively mild anda number of her close contacts have already been put in isolation.

So, while the risk of disease spread in British Columbia remains low at this time, the number of laboratory-confirmed COVID-19 cases worldwide has climbed to over a staggering70,000. As such, the BCCDC has responded by adding, "a critical new dimension to its outbreak response capabilitiesby incorporating genomic analysis into tracking."

Supported by Genome BCs Strategic Initiatives Fund, the$150,000 pilot studywill be able to identify where new cases of the novel coronavirus (COVID-19) in B.C. are coming from and monitor any spread in the community.

Found mostly in animals, coronaviruses are a large family of viruses. In humans, they can cause diseases ranging from the common cold to more severe diseases such as Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS-CoV).

The new coronavirus has been namedSARS-CoV-2, and the disease that it causes is calledCOVID-19. The symptoms ofCOVID-19 are similar to other respiratory illnesses, including the flu and common cold. They include cough, sneezing, fever, sore throat and difficulty breathing.

The BCCDC notes that people can trace their history as a family tree, based on prior knowledge of relationships or the sequence of our DNA the building blocks of all living things. Similarly, the health authority can can place each new strain of a virus on a larger family tree.

"For each new strain, in each new patient, the sequence (of DNA, or related RNA depending on the virus) allows us to place that strain in the larger family tree. If the new strain has a close relative we've seen already in BC, for example, it may be part of a locally-transmitted cluster; if the new strain is more closely related to virus strains recorded in another country, it might be a new introduction to BC. This information enables BCCDC to work with local public health authorities to guide and evaluate interventions. Since this kind of information informs real time decision making, it's essential that this work take full advantage of new rapid, potentially mobile, sequencing technologies," it states.

The new project, "Responding to Emerging Serious Pathogen Outbreaks using Next-gen Data: RESPOND," is designed as a rapid response pilot that will use the fast Oxford Nanopore and other sequencing platforms to simultaneously produce sequence and family tree information.

Leading the team for the pilot project is BCCDC Public Health Laboratory Medical Director Dr. Mel Krajden, one of the investigators from the first team in the world to produce the complete sequence of the SARS virus genome. The team is co-led by UBC faculty Dr. Richard Harrigan, a scientist with decades of experience performing translational HIV studies based on genomics, and Dr. Natalie Prystajecky, a microbiologist overseeing the COVID- 19 test development at the BCCDC.

With SARS, it took the world six months to obtain one virus sequence and BC was first. said Dr. Richard Harrigan. With COVID-19, we are aiming to turn around sequences from each patient in under 24 hours.

This type of project provides an example of the immediate impact Genome BC can have in an emerging public health scenario, like we are seeing for COVID-19, as well as promoting innovative genomic thinking to overcome scientific challenges. This work will improve our ability to respond to this emergency and ultimately benefits public health and the residents of BC, said Prystajecky.

"This experienced team is developing critical tools for response to this and any future outbreaks in BC," said Pascal Spothelfer, President and CEO, Genome BC. "It is a clear demonstration of the power of genomic analysis, and we are proud to be in a position to move it forward quickly."

Prystagjecky adds that it is important for anyone with further questions about the virus to consult the BCCDCCoronavirus(Novel) page. This source gives accurate and up-to-date information about what the virus is, how it is contracted, and what to do to keep yourself safe.

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B.C. to track the origin and spread of COVID-19 with 'genomic technology' - Vancouver Is Awesome

THE GENE: AN INTIMATE HISTORY

EXECUTIVE PRODUCED BY

KEN BURNS AND DR. SIDDHARTHA MUKHERJEE,

TO PREMIERE ON PBS APRIL 7 & 14, 2020

WASHINGTON, D.C. February 19, 2020 WETA Washington, D.C., the flagship public broadcasting station in the nations capital, announced today thatKEN BURNS PRESENTS THE GENE: AN INTIMATE HISTORY, a two-part, four-hour documentary based on Pulitzer Prize-winning author Dr. Siddhartha Mukherjees book of the same name, will premiere on Tuesdays, April 7 and 14, 2020 from 8-10 pm ET on PBS stations nationwide. The film airs at a critical moment for the scientific community, as geneticists around the world wrestle with the ethical implications of new technologies that offer both promise and peril.THE GENEweaves together science, history and personal stories for a historical biography of the human genome, while also exploring breakthroughs for diagnosis and treatment of genetic diseases and the complex ethical questions they raise.

Groundbreaking treatments will improve the lives of millions of peoplepotentially treating diseases like sickle cellbut there are worries that scientists will take gene-editing technology too far, using it to modify germline DNA in order to enhance certain traits deemed preferable. AsTHE GENEdemonstrates, those fears have already been realized: in November 2018, Chinese researcher He Jiankui stunned and horrified the scientific community with an announcement: he had created the first genetically edited babies, twin girls born in Chinaa medically unnecessary procedure accomplished well before scientists had fully considered the consequences of altering the human genome.

These revolutionary discoveries highlight the awesome responsibility we have to make wise decisions, not just for people alive today, but for generations to come, said Dr. Mukherjee, assistant professor of medicine at the Department of Medicine (Oncology), Columbia University and staff cancer physician at Columbia University Medical Center.At this pivotal moment when scientists find themselves in a new era in which theyre able to control and change the human genome,THE GENEoffers a nuanced understanding of how we arrived at this point and how genetics will continue to influence our fates.

The documentary includes interviews with pioneers in the field including doctors Paul Berg, Francis Collins, Jennifer Doudna, Shirley Tilghman, James Watson, Nancy Wexler and Mukherjee himself. As with Burnss other projects,THE GENEuses a remarkable trove of historical footage, including Rosalind Franklins Photograph 51 from 1952, to track the journey of human genetics. Beginning with the remarkable achievements of the earliest gene hunters and their attempts to understand the nature of heredity, the film traces the history of genetics from Gregor Mendels pea plant studies in the 19thCentury and Watsons and Cricks discovery in 1953 of the structure of DNA to the efforts by Sydney Brenner and Marshall Nirenberg, among others, to understand how the genetic code is translated in human cells. We also witness the massive technological transformation from the 1970s through the 2000s from the sequencing of individual genes by Fred Sanger to the sequencing of the whole human genome. AsTHE GENEintroduces us to the scientists solving these great mysteries, the film also examines the insidious rise of eugenics, which bore horrific results in the United States, Europe and, in particular, in Nazi Germany.

THE GENEjuxtaposes this dynamic history with compelling, emotional stories of contemporary patients and their families who find themselves in a desperate race against time to find cures for their genetic diseases. The film follows the inspiring, heart-wrenching journeys of people such as Audrey Winkelsas, a young scientist born with Spinal Muscular Atrophy researching a treatment for her own condition, and Luke Rosen and Sally Jackson, parents on a tireless quest to raise awareness for their daughters rare degenerative disease. Hopes rise and fall with new discoveries and setbacks, revealing how intimate and profoundly personal this science can be for families affected by genetic diseases.

As it traces groundbreaking developments in genetics that promise to revolutionize life for millions of people,THE GENEalso documents the thorny ethical questions some of these new treatments raise. Today, geneticists find themselves on the brink of curing diseases long thought fatal but given the harrowing history of eugenics, both the scientific community and the public are forced to grapple with the ethical implications of these new technologies. Are there unintended consequences to changing human genomes? Could changes accidentally unleash cancer or some novel new genetic disease? From the prospect of genetic therapies to CRISPR, the film explores the complex web of moral, ethical and scientific questions facing this generation.

The series is directed by Chris Durrance and Jack Youngelson, with award-winning filmmaker Barak Goodman serving as senior producer and Ken Burns as executive producing alongside Dr. Mukherjee.THE GENEhas largely the same production team as CANCER: THE EMPEROR OF ALL MALADIES, which premiered on PBS in 2015 and was the Emmy Award-nominated adaptation of Mukherjees 2010 book,The Emperor of All Maladies: A Biography of Cancer.

THE GENEexplores the ultimate mystery story it unpacks the once-impenetrable science of what makes us who we are, said senior producer Barak Goodman.This is a moment for the general public and the scientific community to engage in a national conversation about the thrilling future of genetics and the ethical challenges posed by new science.

We want people to leave our film feeling both hopeful about these stunning developments and sensitive to the ethical questions facing the field, said directors Chris Durrance and Jack Youngelson.

I was thrilled to reunite with Sid and Barak on this project, said Ken Burns.For me, science, like history, is the exploration of what has come before and the promise of the future.THE GENEuntangles the code of life itself.

THE GENErepresents a groundbreaking opportunity to broaden public understanding of this important subject, and Sid, Ken and Barak are the ideal team to bring the fascinating book to film, noted Sharon Percy Rockefeller, president and CEO of WETA, the producing public media station forTHE GENE.

Integral to the project is an extensive engagement program created by WETA in collaboration with an array of partners, in particular the National Institute of Healths National Human Genome Research Institute, the projects primary Outreach and Education Partner. The project will enable the film to reach an even larger audience, engaging researchers, physicians and patients in the national conversation about the history of genetics and the state of the field today. Partners and funders will host screenings and discussions in cities across the country, working with local public media stations and a wide range of educational, medical and scientific organizations.

In conjunction with the broadcast, WETA is developing an expansive interactive website and social and digital media components, including a multi-media educational initiative designed to engage teachers and students through multiple platforms.including a six-part animated series, that delves into the complexities of genetics. Using mixed illustration styles, each episode will focus on a particular approach to genetics, including How Things Work, When DNA Goes Sideways, The Future of DNA, and more. WETA has also developed a companion teaching guide. The series will be distributed through various digital platforms by the National Institutes of Healths National Human Genome Research Institute, PBS, and member stations.

For more information about KEN BURNS PRESENTS THE GENE: AN INTIMATE HISTORY, visit pbs.org/thegene.

#TheGenePBS

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New Ken Burns doc on genetics explores ethical implications of new treatments, history of human genome - scenester.tv