Sequenced-based Rwanda population provides insights into demographic history.

Rwanda is known as the heart of Africa, reflecting the history of the world. Colonization and genocide have led to Rwanda's existing genetic structure. Herein, we used massively parallel sequencing to analyze 296 loci in 185 Rwandans and constructed a database for Rwandan forensic data for the first time. We found the following results: First, forensic parameters demonstrated that all loci were highly informative and could be used for forensic identification and paternity tests in Rwandans. Second, we found that the differences in genetic background between Rwandans and other African populations were similar but slight, as indicated by the massively parallel sequencing panel. Rwandans belonged to the African population and were inseparable from populations from neighboring countries. Also, Rwandans were closer to the European and American populations because of colonization, war, and other reasons. There was no scientific basis for racial classification established by colonization. Further research still needs to be carried out on more loci and larger Rwandan samples.

eSMC: a statistical model to infer admixture events from individual genomics data.

BACKGROUND: Inferring historical population admixture events yield essential insights in understanding a species demographic history. Methods are available to infer admixture events in demographic history with extant genetic data from multiple sources. Due to the deficiency in ancient population genetic data, there lacks a method for admixture inference from a single source. Pairwise Sequentially Markovian Coalescent (PSMC) estimates the historical effective population size from lineage genomes of a single individual, based on the distribution of the most recent common ancestor between the diploid's alleles. However, PSMC does not infer the admixture event. RESULTS: Here, we proposed eSMC, an extended PSMC model for admixture inference from a single source. We evaluated our model's performance on both in silico data and real data. We simulated population admixture events at an admixture time range from 5 kya to 100 kya (5 years/generation) with population admix ratio at 1:1, 2:1, 3:1, and 4:1, respectively. The root means the square error is [Formula: see text] kya for all experiments. Then we implemented our method to infer the historical admixture events in human, donkey and goat populations. The estimated admixture time for both Han and Tibetan individuals range from 60 kya to 80 kya (25 years/generation), while the estimated admixture time for the domesticated donkeys and the goats ranged from 40 kya to 60 kya (8 years/generation) and 40 kya to 100 kya (6 years/generation), respectively. The estimated admixture times were concordance to the time that domestication occurred in human history. CONCLUSION: Our eSMC effectively infers the time of the most recent admixture event in history from a single individual's genomics data. The source code of eSMC is hosted at https://github.com/zachary-zzc/eSMC .

DENSEN: a convolutional neural network for estimating chronological ages from panoramic radiographs.

BACKGROUND: Age estimation from panoramic radiographs is a fundamental task in forensic sciences. Previous age assessment studies mainly focused on juvenile rather than elderly populations (> 25 years old). Most proposed studies were statistical or scoring-based, requiring wet-lab experiments and professional skills, and suffering from low reliability. RESULT: Based on Soft Stagewise Regression Network (SSR-Net), we developed DENSEN to estimate the chronological age for both juvenile and older adults, based on their orthopantomograms (OPTs, also known as orthopantomographs, pantomograms, or panoramic radiographs). We collected 1903 clinical panoramic radiographs of individuals between 3 and 85 years old to train and validate the model. We evaluated the model by the mean absolute error (MAE) between the estimated age and ground truth. For different age groups, 3-11 (children), 12-18 (teens), 19-25 (young adults), and 25+ (adults), DENSEN produced MAEs as 0.6885, 0.7615, 1.3502, and 2.8770, respectively. Our results imply that the model works in situations where genders are unknown. Moreover, DENSEN has lower errors for the adult group (> 25 years) than other methods. The proposed model is memory compact, consuming about 1.0 MB of memory overhead. CONCLUSIONS: We introduced a novel deep learning approach DENSEN to estimate a subject's age from a panoramic radiograph for the first time. Our approach required less laboratory work compared with existing methods. The package we developed is an open-source tool and applies to all different age groups.

Chromosome-Level Haplotype Assembly for Equus asinu.

Background: Haplotype provides significant insights into understanding genomes at both individual and population levels. However, research on many non-model organisms is still based on independent genetic variations due to the lack of haplotype. Results: We conducted haplotype assembling for Equus asinu, a non-model organism that plays a vital role in human civilization. We described the hybrid single individual assembled haplotype of the Dezhou donkey based on the high-depth sequencing data from single-molecule real-time sequencing (×30), Illumina short-read sequencing (×211), and high-throughput chromosome conformation capture (×56). We assembled a near-complete haplotype for the high-depth sequenced Dezhou donkey individual and a phased cohort for the resequencing data of the donkey population. Conclusion: Here, we described the complete chromosome-scale haplotype of the Dezhou donkey with more than a 99.7% phase rate. We further phased a cohort of 156 donkeys to form a donkey haplotype dataset with more than 39 million genetic variations.

Differential perturbations of gut microbial profiles and co-occurrence networks among phases of methamphetamine-induced conditioned place preference.

The gut-brain axis provides a pathway for the interaction between gut microbiota and methamphetamine (METH) addiction. However, the gut microbial signatures during different phases of METH use remain unclear. In the present study, we established models of acquisition, extinction, and reinstatement of METH-induced conditioned place preference (CPP) in male mice and detected the gut microbiome profiles of the fecal samples at the three phases by 16S rRNA gene sequencing. Our results revealed that the richness of the gut microbiome increased following repeated METH administration, and it decreased after 4 weeks of abstinence. The microbial richness remained at a low level after one METH challenge at the reinstatement phase. The abundance of several genera including Prevotella, Bacteroides, and Lactobacillus differentially altered among phases of METH-induced CPP. The co-occurrence networks of the gut microbiome became weaker and more unstable during the development of METH-induced CPP at the extinction and reinstatement phases. Notably, the predicted gene functions of short-chain fatty acid metabolism, which were correlated with the abundance of Prevotella, Bacteroides, and Lactobacillus, were found differentially enriched among phases of METH-induced CPP. Our findings highlight a potential association between perturbations of the gut microbiome and different phases of METH use.

SpecHap: a diploid phasing algorithm based on spectral graph theory.

Haplotype phasing plays an important role in understanding the genetic data of diploid eukaryotic organisms. Different sequencing technologies (such as next-generation sequencing or third-generation sequencing) produce various genetic data that require haplotype assembly. Although multiple diploid haplotype phasing algorithms exist, only a few will work equally well across all sequencing technologies. In this work, we propose SpecHap, a novel haplotype assembly tool that leverages spectral graph theory. On both in silico and whole-genome sequencing datasets, SpecHap consumed less memory and required less CPU time, yet achieved comparable accuracy with state-of-art methods across all the test instances, which comprises sequencing data from next-generation sequencing, linked-reads, high-throughput chromosome conformation capture, PacBio single-molecule real-time, and Oxford Nanopore long-reads. Furthermore, SpecHap successfully phased an individual Ambystoma mexicanum, a species with gigantic diploid genomes, within 6 CPU hours and 945MB peak memory usage, while other tools failed to yield results either due to memory overflow (40GB) or time limit exceeded (5 days). Our results demonstrated that SpecHap is scalable, efficient, and accurate for diploid phasing across many sequencing platforms.

Transcriptome Atlas of 16 Donkey Tissues.

Donkeys (Equus asinus) are important livestock with great economic value in meat, skin, and milk production. However, a lack of knowledge of the transcriptome landscape across a wide range of donkey tissues limits genetic selective breeding and conservation. Here we used transcriptomics to describe the transcriptome landscape, classify the tissue-specific gene expression across all primary donkey tissues, and present supplementary analyses on the protein level of additional donkey milk samples. Overall, 16,013 protein-coding genes and 21,983 transcripts were mapped to the reference genome, including 6,778 ubiquitously expressed genes and 2,601 tissue-enriched genes. Functional analysis revealed that the function of the tissue-enriched genes was highly tissue specific. Tissue-elevated genes that could be associated with unique phenotypes in donkey were analyzed. The results showed that, compared with those in human and other livestock, the lysozyme gene in donkey breast was specifically and highly expressed. The calcium-binding lysozyme, encoded by the lysozyme gene, was also detected in high amounts in donkey milk. Given those intact lysozyme genes that predict potentially functional calcium-binding lysozyme found in only a few species (e.g., donkey and horse), the high expression of the lysozyme gene in donkey breast may contribute to the high lysozyme content in donkey milk. Furthermore, 71% of the proteins in donkey milk overlapped with human milk protein, higher than the overlapping rates of bovine, sheep, and swine with humans. The donkey transcriptomic resource contributes to the available genomic resources to interpret the molecular mechanisms underlying phenotype traits.

Evaluation of a Custom SNP Panel for Identifying and Rectifying of Misjudged Paternity in Deficiency Cases.

Parentage testing is routinely performed by genotyping short tandem repeat (STR) through capillary electrophoresis in the present. However, ambiguous or even misjudged paternity based on STRs happens from time to time in cases where only one putative parent is available. We analyzed STR data of 7,818,969 unrelated pairs and 75 close-relative pairs and found that although the probability of a random false match between non-relatives was 4.22 × 10-6, the incidence of false or ambiguous paternity results between children and first-degree relatives of their true parent was as high as 18.67%. These results highlight the risk of false inclusion of a relative or even non-relatives in parentage testing with STRs. We then validated all ambiguous STR results by targeted sequencing with a custom panel containing 4,830 individual identification single nucleotide polymorphisms (IISNP), found that the ratio of mismatch loci to total SNPs was 1.78-6.95% in close relatives compared with 10.93-13.49% in unrelated pairs. Last, we reported three real cases with undetermined paternity by STRs and rectified them by dissecting with our IISNP panel. These results suggested that high-density IISNP panel can be used to identify and rectify misjudged cases effectively.

A novel forensic panel of 186-plex SNPs and 123-plex STR loci based on massively parallel sequencing.

The MiSeq® FGX Forensic system and the HID-Ion AmpliSeq Panel were previously developed for massively parallel sequencing (MPS) for forensic casework. Among the three major sequencing platforms, BGISEQ-500TM, which is based on multiple PCRs, is still lacking in forensics. Here, a novel forensic panel was constructed to detect 186 single-nucleotide polymorphisms (SNPs) and 123 short tandem repeats (STRs) with MPS technology on the BGISEQ-500™ platform. First, the library preparation, sequencing process, and data analysis were performed, focusing on the average depth of coverage and heterozygote balance. We calculated the allelic frequencies and forensic parameters of STR and SNP loci in 73 unrelated Chinese Han individuals. In addition, performance was evaluated with accuracy, uniformity, sensitivity, PCR inhibitor, repeatability and reproducibility, mixtures, degraded samples, case-type samples, and pedigree analyses. The results showed that 100% accurate and concordant genotypes can be obtained, and the loci with an abundance in the interquartile range accounted for 92.90% of the total, suggesting reliable uniformity in this panel. We obtained a locus detection rate that was higher than 98.78% from 78 pg of input DNA, and the optimal amount was 1.25-10 ng. The maximum concentrations of hematin and humic acid were 200 and 100 µM, respectively (the ratios of detected loci were 96.52% and 92.41%), in this panel. As a mixture, compared with those of SNPs, minor-contributor alleles of STRs could be detected at higher levels. For the degraded sample, the ratio of detected loci was 98.41%, and most profiles from case-type samples were not significantly different in abundance in our studies. As a whole, this panel showed high-performance, reliable, robust, repeatable, and reproducible results, which are sufficient for paternity testing, individual identification, and use for potentially degraded samples in forensic science.

Differential alteration in gut microbiome profiles during acquisition, extinction and reinstatement of morphine-induced CPP.

Substance addiction is a chronic and complicated disease involving genetic and environmental factors. Coregulated by the above factors, perturbations of the gut microbiome have been shown to have an essential role in the development of many neuropsychiatric disorders, including addiction. However, shifts in the gut microbiome during different stages of morphine addiction remain uncharacterized. In the present study, we harvested fecal samples from mice at the acquisition (both the control and morphine groups), extinction and reinstatement stages of morphine-induced conditioned place preference (CPP). Gut microbiome profiles were detected with 16S ribosomal RNA gene sequencing. We observed an increase in community richness following morphine conditioning, and it decreased after 4 weeks of abstinence. The abundance of Verrucomicrobia increased and Bacteroides decreased at the acquisition of morphine-induced CPP, while a recovery trend was found at the extinction stage. Several discriminative genera were identified for the characterization of different stages of morphine CPP. Functional analysis of taxa with differential abundance between CPP stages was mainly enriched in the pathways of amino acid metabolism. Taken together, our findings will extend the association between dysbiosis of the gut microbiome and the opioid-induced rewarding or reinforcing behaviors.

Development and Verification of an Economical Method of Custom Target Library Construction.

Although technological advances have greatly reduced the cost of DNA sequencing, sample preparation time and reagent costs remain the limiting factors for many studies. Based on low-cost targeted amplification, we developed an economical method for custom target library construction based on DNA nanoball (DNB) technology and two-step polymerase chain reaction (PCR). Here, we refer to this method as the two-step PCR, which was compared to traditional multiplex PCR methods in three aspects, data quality, efficiency, and specificity to humans. The results confirmed that two-step PCR reduces to finishing 128 sequencing libraries in only 2 h 24 min 59 s of the total PCR time and at a data utilization rate of 0.44 at a cost of approximately $1.70 per sample for targeted sequencing via the two-step PCR. The replacement of traditional multiplex PCR methods with this strategy makes the sample preparation process before sequencing relatively more cost-effective and further reduces the cost of next-generation sequencing (NGS). This method may also be free from the interference of other species and the limitations of sample type and DNA content. These findings reveal possibilities for broad applications of this approach in forensic research.

Development and comprehensive evaluation of a noninvasive prenatal paternity testing method through a scaled trial.

PURPOSE: To eliminate the miscarriage risks caused by traditional invasive sampling methods, we develop a noninvasive prenatal paternity testing (NIPPT) method and evaluate its efficiency, reliability and sensitivity based on a scaled trial. METHODS: We use maternal cell-free DNA and massive parallel sequencing to obtain NIPPT genotypes for parents and fetuses based on quality-controlled genome-wide single nucleotide polymorphisms (SNPs). In a preliminary testing, data from 14 pregnant women and 7 negative controls are used for setting threshold of fetal genotyping in reference to postpartum children. After that, those from 349 cases with pregnancies of 6-35 gestational weeks (GW) and 9 negative controls from non-pregnant women who have fertility experience previously are in-depth evaluated. RESULTS: In all cases, the biological fathers have been successfully identified from unrelated with a combined paternity index (CPI) of 3.58 × 1018 - 1.46 × 10165 for the cases versus 1.52 × 10-22 - 2.30 × 10-839 for the controls. For negative controls, fetal SNPs originating from previous pregnancies could not be detected. Our NIPPT results completely aligned with the invasive prenatal test results using PCR-CE STR methods. CONCLUSION: NIPPT can be applied to determine paternity accurately from 6 weeks after conception until birth and may serve as an alternative prenatal paternity test advantageous to the currently-used methods.

A 35.8 kilobases haplotype spanning ANKK1 and DRD2 is associated with heroin dependence in Han Chinese males.

Ankyrin repeat and kinase domain containing 1 (ANKK1) and dopamine receptor D2 (DRD2) gene polymorphisms have long been considered to contribute to susceptibility to heroin dependence. Despite their adjacent locations, few studies have elucidated the role of the potential interaction between ANKK1 and DRD2 in heroin dependence. In the present study, we performed a systematic analysis of the association between 39 single nucleotide polymorphisms (SNPs) in these two genes and heroin dependence in 593 Chinese subjects. According to our results, polymorphisms of four unreported loci were associated with heroin dependence, among which rs11214598 of ANKK1 were still significant after multiple testing. We also conducted a meta-analysis of the association between a widely studied variant, rs1800497, and heroin dependence as a representative example and obtained a consistent outcome with our results. Notably, a 35.8 kilobases (kb) haplotype spanning ANKK1 and DRD2 was found to be a strong protective factor for heroin dependence. Gene-gene interaction analysis suggested that interactions exist within the ANKK1-DRD2 haplotype block between rs11214598 and rs1800497 in ANKK1 and rs2245805 and rs1079597 in DRD2. Our study highlights the importance of considering haplotypes spanning adjacent genes and the cooperation and interaction of proximal variants or genes in genetic association studies.