A case of septic arthritis of the hip in Central Plains, China, during the Western Han Dynasty (3rd century BCE-1st century CE).

OBJECTIVE: Septic arthritis is not commonly reported in paleopathology. This study aims to provide a differential diagnosis of septic arthritis by looking at a case from ancient China. We also aim to add to the current literature on septic arthritis in paleopathology. MATERIALS: One adult male skeleton recovered from the Dapuzi Cemetery, Shaanxi, dating to the Western Han Dynasty (3rd century BCE-1st century CE). METHODS: Macroscopic observations were conducted. RESULTS: The lytic appearance and massive new bone formation on the left acetabulum of M142 are compatible with septic arthritis. The hip pathology greatly influenced his stature. The two femur shafts present different degrees of robusticity. He also showed severe osteoarthritis. CONCLUSIONS: The individual suffered from septic arthritis of the hip, of unknown cause, for a long period, which greatly influenced his daily life. Complications included osteoarthritis, shortened stature, and difficulties in walking. SIGNIFICANCE: This study offers a new case of septic arthritis and provides insight into the people who guarded the royal tombs in the West Han Dynasty. LIMITATIONS: The skeleton is not well-preserved, limiting observations of bony changes to other areas of the body.

Improved Prediction Model of Protein Lysine Crotonylation Sites Using Bidirectional Recurrent Neural Networks.

Histone lysine crotonylation (Kcr) is a post-translational modification of histone proteins that is involved in the regulation of gene transcription, acute and chronic kidney injury, spermatogenesis, depression, cancer, and so forth. The identification of Kcr sites in proteins is important for characterizing and regulating primary biological mechanisms. The use of computational approaches such as machine learning and deep learning algorithms have emerged in recent years as the traditional wet-lab experiments are time-consuming and costly. We propose as part of this study a deep learning model based on a recurrent neural network (RNN) termed as Sohoko-Kcr for the prediction of Kcr sites. Through the embedded encoding of the peptide sequences, we investigate the efficiency of RNN-based models such as long short-term memory (LSTM), bidirectional LSTM (BiLSTM), and bidirectional gated recurrent unit (BiGRU) networks using cross-validation and independent tests. We also established the comparison between Sohoko-Kcr and other published tools to verify the efficiency of our model based on 3-fold, 5-fold, and 10-fold cross-validations using independent set tests. The results then show that the BiGRU model has consistently displayed outstanding performance and computational efficiency. Based on the proposed model, a webserver called Sohoko-Kcr was deployed for free use and is accessible at https://sohoko-research-9uu23.ondigitalocean.app.

Genomic history and forensic characteristics of Sherpa highlanders on the Tibetan Plateau inferred from high-resolution InDel panel and genome-wide SNPs.

Sherpa people, one of the high-altitude hypoxic adaptive populations, mainly reside in Nepal and the southern Tibet Autonomous Region. The genetic origin and detailed evolutionary profiles of Sherpas remain to be further explored and comprehensively characterized. Here we analyzed the newly-generated InDel genotype data from 628 Dingjie Sherpas by merging with 4222 worldwide InDel profiles and collected genome-wide SNP data (approximately 600K SNPs) from 1612 individuals in 191 modern and ancient populations to explore and reconstruct the fine-scale genetic structure of Sherpas and their relationships with nearby modern and ancient East Asians based on the shared alleles and haplotypes. The forensic parameters of 57 autosomal InDels (A-InDels) included in our used new-generation InDel amplification system showed that this focused InDel panel is informative and polymorphic in Dingjie Sherpas, suggesting that it can be used as the supplementary tool for forensic personal identification and parentage testing in Dingjie Sherpas. Descriptive findings from the PCA, ADMIXTURE, and TreeMix-based phylogenies suggested that studied Nepal Sherpas showed excess allele sharing with neighboring Tibeto-Burman Tibetans. Furthermore, patterns of allele sharing in f-statistics demonstrated that Nepal Sherpas had a different evolutionary history compared with their neighbors from Nepal (Newar and Gurung) but showed genetic similarity with 2700-year-old Chokhopani and modern Tibet Tibetans. QpAdm/qpGraph-based admixture sources and models further showed that Sherpas, core Tibetans, and Chokhopani formed one clade, which could be fitted as having the main ancestry from late Neolithic Qijia millet farmers and other deep ancestries from early Asians. Chromosome painting profiles and shared IBD fragments inferred from fineSTRUCTURE and ChromoPainter not only confirmed the abovementioned genomic affinity patterns but also revealed the fine-scale genetic microstructures among Sino-Tibetan speakers. Finally, natural-selection signals revealed via iHS, nSL and iHH12 showed natural selection signatures associated with disease susceptibility in Sherpas. Generally, we provided the comprehensive landscape of admixture and evolutionary history of Sherpa people based on the shared alleles and haplotypes from the InDel-based genotype data and high-density genome-wide SNP data. The more detailed genetic landscape of Sherpa people should be further confirmed and characterized via ancient genomes or single-molecule real-time sequencing technology.

Peopling History of the Tibetan Plateau and Multiple Waves of Admixture of Tibetans Inferred From Both Ancient and Modern Genome-Wide Data.

Archeologically attested human occupation on the Tibetan Plateau (TP) can be traced back to 160 thousand years ago (kya) via the archaic Xiahe people and 30∼40 kya via the Nwya Devu anatomically modern human. However, the history of the Tibetan populations and their migration inferred from the ancient and modern DNA remains unclear. Here, we performed the first ancient and modern genomic meta-analysis among 3,017 Paleolithic to present-day Eastern Eurasian genomes (2,444 modern individuals from 183 populations and 573 ancient individuals). We identified a close genetic connection between the ancient-modern highland Tibetans and lowland island/coastal Neolithic Northern East Asians (NEA). This observed genetic affinity reflected the primary ancestry of high-altitude Tibeto-Burman speakers originated from the Neolithic farming populations in the Yellow River Basin. The identified pattern was consistent with the proposed common north-China origin hypothesis of the Sino-Tibetan languages and dispersal patterns of the northern millet farmers. We also observed the genetic differentiation between the highlanders and lowland NEAs. The former harbored more deeply diverged Hoabinhian/Onge-related ancestry and the latter possessed more Neolithic southern East Asian (SEA) or Siberian-related ancestry. Our reconstructed qpAdm and qpGraph models suggested the co-existence of Paleolithic and Neolithic ancestries in the Neolithic to modern East Asian highlanders. Additionally, we found that Tibetans from Ü-Tsang/Ando/Kham regions showed a strong population stratification consistent with their cultural background and geographic terrain. Ü-Tsang Tibetans possessed a stronger Chokhopani-affinity, Ando Tibetans had more Western Eurasian related ancestry and Kham Tibetans harbored greater Neolithic southern EA ancestry. Generally, ancient and modern genomes documented multiple waves of human migrations in the TP's past. The first layer of local hunter-gatherers mixed with incoming millet farmers and arose the Chokhopani-associated Proto-Tibetan-Burman highlanders, which further respectively mixed with additional genetic contributors from the western Eurasian Steppe, Yellow River and Yangtze River and finally gave rise to the modern Ando, Ü-Tsang and Kham Tibetans.

Fine-Scale Genetic Structure and Natural Selection Signatures of Southwestern Hans Inferred From Patterns of Genome-Wide Allele, Haplotype, and Haplogroup Lineages.

The evolutionary and admixture history of Han Chinese have been widely discussed via traditional autosomal and uniparental genetic markers [e.g., short tandem repeats, low-density single nucleotide polymorphisms). However, their fine-scale genetic landscapes (admixture scenarios and natural selection signatures) based on the high-density allele/haplotype sharing patterns have not been deeply characterized. Here, we collected and generated genome-wide data of 50 Han Chinese individuals from four populations in Guizhou Province, one of the most ethnolinguistically diverse regions, and merged it with over 3,000 publicly available modern and ancient Eurasians to describe the genetic origin and population admixture history of Guizhou Hans and their neighbors. PCA and ADMIXTURE results showed that the studied four populations were homogeneous and grouped closely to central East Asians. Genetic homogeneity within Guizhou populations was further confirmed via the observed strong genetic affinity with inland Hmong-Mien people through the observed genetic clade in Fst and outgroup f 3 /f 4-statistics. qpGraph-based phylogenies and f 4-based demographic models illuminated that Guizhou Hans were well fitted via the admixture of ancient Yellow River Millet farmers related to Lajia people and southern Yangtze River farmers related to Hanben people. Further ChromoPainter-based chromosome painting profiles and GLOBETROTTER-based admixture signatures confirmed the two best source matches for southwestern Hans, respectively, from northern Shaanxi Hans and southern indigenes with variable mixture proportions in the historical period. Further three-way admixture models revealed larger genetic contributions from coastal southern East Asians into Guizhou Hans compared with the proposed inland ancient source from mainland Southeast Asia. We also identified candidate loci (e.g., MTUS2, NOTCH4, EDAR, ADH1B, and ABCG2) with strong natural selection signatures in Guizhou Hans via iHS, nSL, and ihh, which were associated with the susceptibility of the multiple complex diseases, morphology formation, alcohol and lipid metabolism. Generally, we provided a case and ideal strategy to reconstruct the detailed demographic evolutionary history of Guizhou Hans, which provided new insights into the fine-scale genomic formation of one ethnolinguistically specific targeted population from the comprehensive perspectives of the shared unlinked alleles, linked haplotypes, and paternal and maternal lineages.

New insights into the fine-scale history of western-eastern admixture of the northwestern Chinese population in the Hexi Corridor via genome-wide genetic legacy.

Trans-Eurasian cultural and genetic exchanges have significantly influenced the demographic dynamics of Eurasian populations. The Hexi Corridor, located along the southeastern edge of the Eurasian steppe, served as an important passage of the ancient Silk Road in Northwest China and intensified the transcontinental exchange and interaction between populations on the Central Plain and in Western Eurasia. Historical and archeological records indicate that the Western Eurasian cultural elements were largely brought into North China via this geographical corridor, but there is debate on the extent to which the spread of barley/wheat agriculture into North China and subsequent Bronze Age cultural and technological mixture/shifts were achieved by the movement of people or dissemination of ideas. Here, we presented higher-resolution genome-wide autosomal and uniparental Y/mtDNA SNP or STR data for 599 northwestern Han Chinese individuals and conducted 2 different comprehensive genetic studies among Neolithic-to-present-day Eurasians. Genetic studies based on lower-resolution STR markers via PCA, STRUCTURE, and phylogenetic trees showed that northwestern Han Chinese individuals had increased genetic homogeneity relative to northern Mongolic/Turkic/Tungusic speakers and Tibeto-Burman groups. The genomic signature constructed based on modern/ancient DNA further illustrated that the primary ancestry of the northwestern Han was derived from northern millet farmer ancestors, which was consistent with the hypothesis of Han origin in North China and more recent northwestward population expansion. This was subsequently confirmed via excess shared derived alleles in f3/f4 statistical analyses and by more northern East Asian-related ancestry in the qpAdm/qpGraph models. Interestingly, we identified one western Eurasian admixture signature that was present in northwestern Han but absent from southern Han, with an admixture time dated to approximately 1000 CE (Tang and Song dynasties). Generally, we provided supporting evidence that historic Trans-Eurasian communication was primarily maintained through population movement, not simply cultural diffusion. The observed population dynamics in northwestern Han Chinese not only support the North China origin hypothesis but also reflect the multiple sources of the genetic diversity observed in this population.

Genomic insights into the formation of human populations in East Asia.

The deep population history of East Asia remains poorly understood owing to a lack of ancient DNA data and sparse sampling of present-day people1,2. Here we report genome-wide data from 166 East Asian individuals dating to between 6000 BC and AD 1000 and 46 present-day groups. Hunter-gatherers from Japan, the Amur River Basin, and people of Neolithic and Iron Age Taiwan and the Tibetan Plateau are linked by a deeply splitting lineage that probably reflects a coastal migration during the Late Pleistocene epoch. We also follow expansions during the subsequent Holocene epoch from four regions. First, hunter-gatherers from Mongolia and the Amur River Basin have ancestry shared by individuals who speak Mongolic and Tungusic languages, but do not carry ancestry characteristic of farmers from the West Liao River region (around 3000 BC), which contradicts theories that the expansion of these farmers spread the Mongolic and Tungusic proto-languages. Second, farmers from the Yellow River Basin (around 3000 BC) probably spread Sino-Tibetan languages, as their ancestry dispersed both to Tibet-where it forms approximately 84% of the gene pool in some groups-and to the Central Plain, where it has contributed around 59-84% to modern Han Chinese groups. Third, people from Taiwan from around 1300 BC to AD 800 derived approximately 75% of their ancestry from a lineage that is widespread in modern individuals who speak Austronesian, Tai-Kadai and Austroasiatic languages, and that we hypothesize derives from farmers of the Yangtze River Valley. Ancient people from Taiwan also derived about 25% of their ancestry from a northern lineage that is related to, but different from, farmers of the Yellow River Basin, which suggests an additional north-to-south expansion. Fourth, ancestry from Yamnaya Steppe pastoralists arrived in western Mongolia after around 3000 BC but was displaced by previously established lineages even while it persisted in western China, as would be expected if this ancestry was associated with the spread of proto-Tocharian Indo-European languages. Two later gene flows affected western Mongolia: migrants after around 2000 BC with Yamnaya and European farmer ancestry, and episodic influences of later groups with ancestry from Turan.

Massively parallel sequencing of 165 ancestry-informative SNPs and forensic biogeographical ancestry inference in three southern Chinese Sinitic/Tai-Kadai populations.

Ancestry informative markers (AIMs), which are distributed throughout the human genome, harbor significant allele frequency differences among diverse ethnic groups. The use of sets of AIMs to reconstruct population history and genetic relationships is attracting interest in the forensic community, because biogeographic ancestry information for a casework sample can potentially be predicted and used to guide the investigative process. However, subpopulation ancestry inference within East Asia remains in its infancy due to a lack of population reference data collection and incomplete validation work on newly developed or commercial AIM sets. In the present study, 316 Chinese persons, including 85 Sinitic-speaking Haikou Han, 120 Qiongzhong Hlai and 111 Daozhen Gelao individuals belonging to Tai-Kadai-speaking populations, were analyzed using the Precision ID Ancestry Panel (165 AISNPs). Combined with our previous 165-AISNP data (375 individuals from 6 populations), the 1000 Genomes Project and forensic literature, comprehensive population genetic comparisons and ancestry inference were further performed via ADMIXTURE, TreeMix, PCA, f-statistics and N-J tree. Although several nonpolymorphic loci were identified in the three southern Chinese populations, the forensic parameters of this ancestry inference panel were better than those for the 23 STR-based Huaxia Platinum System, which is suitable for use as a robust tool in forensic individual identification and parentage testing. The results based on the ancestry assignment and admixture proportion evaluation revealed that this panel could be used successfully to assign individuals at a continental scale but also possessed obvious limitations in discriminatory power in intercontinental individuals, especially for European-Asian admixed Uyghurs or in populations lacking reference databases. Population genetic analyses further revealed five continental population clusters and three East Asian-focused population subgroups, which is consistent with linguistic affiliations. Ancestry composition and multiple phylogenetic analysis further demonstrated that the geographically isolated Qiongzhong Hlai harbored a close phylogenetic relationship with Austronesian speakers and possessed a homogenous Tai-Kadai-dominant ancestry, which could be used as the ancestral source proxy in population history reconstruction of Tai-Kadai-speaking populations and as one of the representatives for forensic database establishment. In summary, more population-specific AIM sets focused on East Asian subpopulations, comprehensive algorithms and high-coverage population reference data should be developed and validated in the next step.

Genomic Insights Into the Population History and Biological Adaptation of Southwestern Chinese Hmong-Mien People.

Hmong-Mien (HM) -speaking populations, widely distributed in South China, the north of Thailand, Laos, and Vietnam, have experienced different settlement environments, dietary habits, and pathogenic exposure. However, their specific biological adaptation remained largely uncharacterized, which is important in the population evolutionary genetics and Trans-Omics for regional Precision Medicine. Besides, the origin and genetic diversity of HM people and their phylogenetic relationship with surrounding modern and ancient populations are also unknown. Here, we reported genome-wide SNPs in 52 representative Miao people and combined them with 144 HM people from 13 geographically representative populations to characterize the full genetic admixture and adaptive landscape of HM speakers. We found that obvious genetic substructures existed in geographically different HM populations; one localized in the HM clines, and others possessed affinity with Han Chinese. We also identified one new ancestral lineage specifically existed in HM people, which spatially distributed from Sichuan and Guizhou in the north to Thailand in the south. The sharing patterns of the newly identified homogenous ancestry component combined the estimated admixture times via the decay of linkage disequilibrium and haplotype sharing in GLOBETROTTER suggested that the modern HM-speaking populations originated from Southwest China and migrated southward in the historic period, which is consistent with the reconstructed phenomena of linguistic and archeological documents. Additionally, we identified specific adaptive signatures associated with several important human nervous system biological functions. Our pilot work emphasized the importance of anthropologically informed sampling and deeply genetic structure reconstruction via whole-genome sequencing in the next step in the deep Chinese Population Genomic Diversity Project (CPGDP), especially in the regions with rich ethnolinguistic diversity.

Investigation into the origins of an ancient BRCA1 founder mutation identified among Chinese families in Singapore.

Identification of ancestry-specific pathogenic variants is imperative for diagnostic, treatment, management and prevention strategies, and to understand penetrance/modifiers on risk. Our study aimed to determine the clinical significance of a recurrent BRCA1 c.442-22_442-13del variant of unknown significance identified among 13 carriers from six Chinese families, all with a significant history of breast and/or ovarian cancer. We further aimed to establish whether this was due to a founder effect and explore its origins. Haplotype analysis, using nine microsatellite markers encompassing 2.5 megabase pairs around the BRCA1 locus, identified a common haploblock specific to the variant carriers, confirming a founder effect. Variant age was estimated to date back 77.9 generations to 69 bc using the Gamma approach. On principal component analysis using single nucleotide polymorphisms merged with 1000 Genomes dataset, variant carriers were observed to overlap predominantly with the southern Han Chinese population. To determine pathogenicity of the variant, we assessed the functional effect on RAD51 foci formation as well as replication fork stability upon induction of DNA damage and observed an impaired DNA repair response associated with the variant. In summary, we identified an ancient Chinese founder mutation dating back 77.9 generations, possibly common among individuals of southern Han Chinese descent. Using evidence from phenotypic/family history studies, segregation analysis and functional characterization, the BRCA1 variant was reclassified from uncertain significance to pathogenic.

A probable case of multiple myeloma from Bronze Age China.

OBJECTIVE: Paleopathological evidence of cancer from past populations is rare, especially outside of Europe and North Africa. This study expands upon the current temporal and spatial distribution of cancer by presenting a probable case of multiple myeloma from Bronze Age China. MATERIAL: The human skeletal remains of an adult male from the Qijia culture horizon (1750-1400 BCE) of the Bronze Age cemetery of Mogou (), located in Gansu Province, Northwest China. METHODS: The human skeletal remains were assessed macroscopically and radiographically using plain x-rays. RESULTS: Multiple ovoid-shaped osteolytic lesions with sharply demarcated margins were observed. The axial skeletal had the greatest involvement, specifically the vertebrae, ribs, and sternum. Radiographic imaging revealed more extensive destruction of cancellous than cortical bone, indicating that the marrow was the focal point of the disease. CONCLUSION: Based on the nature, distribution, and radiographic appearance of the lesions, the most likely diagnosis is multiple myeloma. SIGNIFICANCE: This is one of the only cases of cancer identified in archaeological human skeletal remains from East Asia and is the first published case of a hematopoietic malignancy from mainland China. The analysis and publication of examples of neoplasia from areas that expand upon the current known temporal and spatial distribution is necessary in order to better reconstruct the history and evolution of cancer. LIMITATIONS: Poor skeletal preservation prevented the full extent of osteolytic lesions to be observed. SUGGESTIONS FOR FUTURE RESEARCH: By placing case studies such as this into a temporal and spatial framework, it is possible for future research to begin to interrogate possible underlying causes of cancer in ancient populations within the context of changing environmental conditions and subsistence strategies.

Estimating molecular preservation of the intestinal microbiome via metagenomic analyses of latrine sediments from two medieval cities.

Ancient latrine sediments, which contain the concentrated collective biological waste of past whole human communities, have the potential to be excellent proxies for human gastrointestinal health on the population level. A rich body of literature explores their use to detect the presence of gut-associated eukaryotic parasites through microscopy, immunoassays and genetics. Despite this interest, a lack of studies have explored the whole genetic content of ancient latrine sediments through consideration not only of gut-associated parasites, but also of core community gut microbiome signals that remain from the group that used the latrine. Here, we present a metagenomic analysis of bulk sediment from medieval latrines in Riga (Latvia) and Jerusalem. Our analyses reveal survival of microbial DNA representative of intestinal flora as well as numerous parasites. These data are compared against parasite taxon identifications obtained via microscopy and ELISA techniques. Together, these findings provide a first glimpse into the rich prokaryotic and eukaryotic intestinal flora of pre-industrial agricultural populations, which may give a better context for interpreting the health of modern microbiomes. This article is part of the theme issue 'Insights into health and disease from ancient biomolecules'.

XGBoost Improves Classification of MGMT Promoter Methylation Status in IDH1 Wildtype Glioblastoma.

Approximately 96% of patients with glioblastomas (GBM) have IDH1 wildtype GBMs, characterized by extremely poor prognosis, partly due to resistance to standard temozolomide treatment. O6-Methylguanine-DNA methyltransferase (MGMT) promoter methylation status is a crucial prognostic biomarker for alkylating chemotherapy resistance in patients with GBM. However, MGMT methylation status identification methods, where the tumor tissue is often undersampled, are time consuming and expensive. Currently, presurgical noninvasive imaging methods are used to identify biomarkers to predict MGMT methylation status. We evaluated a novel radiomics-based eXtreme Gradient Boosting (XGBoost) model to identify MGMT promoter methylation status in patients with IDH1 wildtype GBM. This retrospective study enrolled 53 patients with pathologically proven GBM and tested MGMT methylation and IDH1 status. Radiomics features were extracted from multimodality MRI and tested by F-score analysis to identify important features to improve our model. We identified nine radiomics features that reached an area under the curve of 0.896, which outperformed other classifiers reported previously. These features could be important biomarkers for identifying MGMT methylation status in IDH1 wildtype GBM. The combination of radiomics feature extraction and F-core feature selection significantly improved the performance of the XGBoost model, which may have implications for patient stratification and therapeutic strategy in GBM.

Application of Computational Biology and Artificial Intelligence Technologies in Cancer Precision Drug Discovery.

Artificial intelligence (AI) proves to have enormous potential in many areas of healthcare including research and chemical discoveries. Using large amounts of aggregated data, the AI can discover and learn further transforming these data into "usable" knowledge. Being well aware of this, the world's leading pharmaceutical companies have already begun to use artificial intelligence to improve their research regarding new drugs. The goal is to exploit modern computational biology and machine learning systems to predict the molecular behaviour and the likelihood of getting a useful drug, thus saving time and money on unnecessary tests. Clinical studies, electronic medical records, high-resolution medical images, and genomic profiles can be used as resources to aid drug development. Pharmaceutical and medical researchers have extensive data sets that can be analyzed by strong AI systems. This review focused on how computational biology and artificial intelligence technologies can be implemented by integrating the knowledge of cancer drugs, drug resistance, next-generation sequencing, genetic variants, and structural biology in the cancer precision drug discovery.

Classifying Promoters by Interpreting the Hidden Information of DNA Sequences via Deep Learning and Combination of Continuous FastText N-Grams.

A promoter is a short region of DNA (100-1,000 bp) where transcription of a gene by RNA polymerase begins. It is typically located directly upstream or at the 5' end of the transcription initiation site. DNA promoter has been proven to be the primary cause of many human diseases, especially diabetes, cancer, or Huntington's disease. Therefore, classifying promoters has become an interesting problem and it has attracted the attention of a lot of researchers in the bioinformatics field. There were a variety of studies conducted to resolve this problem, however, their performance results still require further improvement. In this study, we will present an innovative approach by interpreting DNA sequences as a combination of continuous FastText N-grams, which are then fed into a deep neural network in order to classify them. Our approach is able to attain a cross-validation accuracy of 85.41 and 73.1% in the two layers, respectively. Our results outperformed the state-of-the-art methods on the same dataset, especially in the second layer (strength classification). Throughout this study, promoter regions could be identified with high accuracy and it provides analysis for further biological research as well as precision medicine. In addition, this study opens new paths for the natural language processing application in omics data in general and DNA sequences in particular.

Skeletal evidence for violent trauma from the bronze age Qijia culture (2,300-1,500 BCE), Gansu Province, China.

This research explores how social and environmental factors may have contributed to conflict during the early Bronze Age in Northwest China by analyzing violent trauma on human skeletal remains from a cemetery of the Qijia culture (2300-1500 BCE). The Qijia culture existed during a period of dramatic social, technological, and environmental change, though minimal research has been conducted on how these factors may have contributed to violence within the area of the Qijia and other contemporaneous material cultures. An osteological assessment was conducted on 361 individuals (n = 241 adults, n = 120 non-adults) that were excavated from the Mogou site, Lintan County, Gansu, China. Injuries indicative of violence, including sharp- and blunt-force trauma that was sustained ante- or peri-mortem, were identified, and the patterns of trauma were analysed. Violent injuries were found on 8.58% (n = 31/361) of individuals, primarily adult males. No evidence of trauma was found on infants or children. Cranial trauma was found on 11.8% (n = 23/195) of the adult individuals examined. Of these, 43.5% (n = 10/23) presented with severe peri-mortem craniofacial trauma. The high rate of perimortem injuries and their locations indicate lethal intent. This lethality, in addition to the fact that individuals with trauma were predominantly male, suggest intergroup violence such as raiding, warfare, or feuding. Both social and environmental factors may have contributed to this conflict in the TaoRiver Valley, though future systematic archaeological and paleoenvironmental data will be needed to disentangle the many potential causal factors.

Divided zygoma in Holocene human populations from Northern China.

OBJECTIVES: Divided zygoma (DZ) occurs in contemporaneous human populations, with the highest incidences in people from East Asia and Southern Africa. The present study examines the prevalence and variation of this condition in the Holocene populations of Northern China for the first time. METHODS: In this study, 1145 skulls from various human populations living in Northern China from the Neolithic Age to recent dynasties (5000-300 years BP) were examined. Specifically, cranial measurements and a CT scan were conducted to quantify craniofacial morphology. RESULTS: Fifteen skulls were identified with DZ, revealing an overall prevalence of 1.3% in the collection, while it was determined to be higher in North Asian and Northeast Asian regional groups. In skulls with unilateral DZ, the superior division of the zygoma was generally slender, while the inferior division of the zygoma was more robust. In skulls with bilateral DZ, the maxillae were generally more laterally extended. Moreover, unilateral DZ skulls displayed differences in cortical bone thickness between two sides of the facial skeleton. DISCUSSION: In context, the distribution pattern within these data points toward a greater prevalence of the DZ phenotype in North and Northeast Asian regional groups, suggesting a hypothesis that the DZ trait is more frequent in populations characterized by flat and broad faces. Accordingly, further studies into the DZ condition will deepen our understanding of developments in plasticity, variation, and recent evolution of the human cranium.

ET-GRU: using multi-layer gated recurrent units to identify electron transport proteins.

BACKGROUND: Electron transport chain is a series of protein complexes embedded in the process of cellular respiration, which is an important process to transfer electrons and other macromolecules throughout the cell. It is also the major process to extract energy via redox reactions in the case of oxidation of sugars. Many studies have determined that the electron transport protein has been implicated in a variety of human diseases, i.e. diabetes, Parkinson, Alzheimer's disease and so on. Few bioinformatics studies have been conducted to identify the electron transport proteins with high accuracy, however, their performance results require a lot of improvements. Here, we present a novel deep neural network architecture to address this problem. RESULTS: Most of the previous studies could not use the original position specific scoring matrix (PSSM) profiles to feed into neural networks, leading to a lack of information and the neural networks consequently could not achieve the best results. In this paper, we present a novel approach by using deep gated recurrent units (GRU) on full PSSMs to resolve this problem. Our approach can precisely predict the electron transporters with the cross-validation and independent test accuracy of 93.5 and 92.3%, respectively. Our approach demonstrates superior performance to all of the state-of-the-art predictors on electron transport proteins. CONCLUSIONS: Through the proposed study, we provide ET-GRU, a web server for discriminating electron transport proteins in particular and other protein functions in general. Also, our achievement could promote the use of GRU in computational biology, especially in protein function prediction.

A comprehensive exploration of the genetic legacy and forensic features of Afghanistan and Pakistan Mongolian-descent Hazara.

Afghanistan and Pakistan are rich with a complex landscape of culture, linguistics, ethnicity and genetic legacy at the crossroads between Indian-Subcontinent and Central Asia. Hazara people have historically been suggested to be Mongolian decedents but seldom been genetically studied. To dissect the genetic structure and explore the forensic characteristics of Hazara people, we first genotyped 30 Insertion/deletion (Indel) markers in 468 samples from 2 aboriginal Hazara populations from Afghanistan and Pakistan, and 100 East Asian comparative Bouyei samples using the Investigator® DIPplex kit. Subsequently, we carried out a comprehensive population genetic analysis from four different datasets: 8895 30-Indel genotype data from 51 populations, 15,895 30-Indel allele frequency data from 98 populations, 1048 genotypes of 993 STRs and Indels from 53 HGDP populations and 2068 whole-genomes (621,799 single nucleotide polymorphisms) from 165 worldwide Human origin reference populations, to further unravel the genetic complexity between Hazara and worldwide human populations using various statistical analysis. We find that 30 Indels are in accordance with HWE, and informative and polymorphic in both Central Asians Hazara and East Asian Bouyei populations. The forensic combined probability of exclusion is larger than 0.9943 and the cumulative power of discrimination is larger than 0.99999999999936. These forensic parameters show the high level of diversity, which makes the Indel amplification system suitable for forensic routine work and may be used as a supplementary assay for routine forensic investigation. The results from pairwise genetic distances, MDS, PCA, and phylogenetic relationship reconstruction demonstrate that present-day Hazaras are genetically closer to the Turkic-speaking populations (Uyghur, Kazakh, and Kyrgyz) residing in northwest China than with other Central/South Asian populations and Mongolian. Outgroup and admixture f3,f4, f4-ratio, qpWave, and qpAdm results further demonstrate that Hazara shares more alleles with East Asians than with other Central Asians and carries 57.8% Mongolian-related ancestry. Overall, our findings suggest that Hazaras have experienced genetic admixture with the local or neighboring populations and formed the current East-West Eurasian admixed genetic profile after their separation from the Mongolians.

Ensemble of Deep Recurrent Neural Networks for Identifying Enhancers via Dinucleotide Physicochemical Properties.

Enhancers are short deoxyribonucleic acid fragments that assume an important part in the genetic process of gene expression. Due to their possibly distant location relative to the gene that is acted upon, the identification of enhancers is difficult. There are many published works focused on identifying enhancers based on their sequence information, however, the resulting performance still requires improvements. Using deep learning methods, this study proposes a model ensemble of classifiers for predicting enhancers based on deep recurrent neural networks. The input features of deep ensemble networks were generated from six types of dinucleotide physicochemical properties, which had outperformed the other features. In summary, our model which used this ensemble approach could identify enhancers with achieved sensitivity of 75.5%, specificity of 76%, accuracy of 75.5%, and MCC of 0.51. For classifying enhancers into strong or weak sequences, our model reached sensitivity of 83.15%, specificity of 45.61%, accuracy of 68.49%, and MCC of 0.312. Compared to the benchmark result, our results had higher performance in term of most measurement metrics. The results showed that deep model ensembles hold the potential for improving on the best results achieved to date using shallow machine learning methods.