The genomic revolution has fundamentally changed how we survey biodiversity on earth. High-throughput sequencing ("HTS") platforms now enable the rapid sequencing of DNA from diverse kinds of environmental samples (termed "environmental DNA" or "eDNA"). Coupling HTS with our ability to associate sequences from eDNA with a taxonomic name is called "eDNA metabarcoding" and offers a powerful molecular tool capable of noninvasively surveying species richness from many ecosystems. Here, we review the use of eDNA metabarcoding for surveying animal and plant richness, and the challenges in using eDNA approaches to estimate relative abundance. We highlight eDNA applications in freshwater, marine and terrestrial environments, and in this broad context, we distill what is known about the ability of different eDNA sample types to approximate richness in space and across time. We provide guiding questions for study design and discuss the eDNA metabarcoding workflow with a focus on primers and library preparation methods. We additionally discuss important criteria for consideration of bioinformatic filtering of data sets, with recommendations for increasing transparency. Finally, looking to the future, we discuss emerging applications of eDNA metabarcoding in ecology, conservation, invasion biology, biomonitoring, and how eDNA metabarcoding can empower citizen science and biodiversity education.© 2017 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Biodiversity is under threat worldwide. Over the past decade, the field of population genomics has developed across nonmodel organisms, and the results of this research have begun to be applied in conservation and management of wildlife species. Genomics tools can provide precise estimates of basic features of wildlife populations, such as effective population size, inbreeding, demographic history and population structure, that are critical for conservation efforts. Moreover, population genomics studies can identify particular genetic loci and variants responsible for inbreeding depression or adaptation to changing environments, allowing for conservation efforts to estimate the capacity of populations to evolve and adapt in response to environmental change and to manage for adaptive variation. While connections from basic research to applied wildlife conservation have been slow to develop, these connections are increasingly strengthening. Here we review the primary areas in which population genomics approaches can be applied to wildlife conservation and management, highlight examples of how they have been used, and provide recommendations for building on the progress that has been made in this field.© 2020 The Authors. Molecular Ecology published by 2020 John Wiley & Sons Ltd.

Coffea arabica L. is an economically important agricultural crop and the most popular beverage worldwide. As a perennial crop with recalcitrant seed, conservation of the genetic resources of coffee can be achieved through the complementary approach of in-situ and ex-situ field genebank. In Ethiopia, a large collection of C. arabica L. germplasm is preserved in field gene banks. Here, we report the whole-genome resequencing of 90 accessions from Choche germplasm bank representing garden and forest-based coffee production systems using Illumina sequencing technology.

Genetic approaches have proved valuable to the study and conservation of endangered populations, especially for monitoring programs, and there is potential for further developments in this direction by extending analyses to the genomic level. We assembled the genome of the wolverine (Gulo gulo), a mustelid that in Scandinavia has recently recovered from a significant population decline, and obtained a 2.42 Gb draft sequence representing >85% of the genome and including >21,000 protein-coding genes. We then performed whole-genome resequencing of 10 Scandinavian wolverines for population genomic and demographic analyses. Genetic diversity was among the lowest detected in a red-listed population (mean genome-wide nucleotide diversity of 0.05%). Results of the demographic analyses indicated a long-term decline of the effective population size (N ) from 10,000 well before the last glaciation to <500 after this period. Current N appeared even lower. The genome-wide F level was 0.089 (possibly signaling inbreeding), but this effect was not observed when analyzing a set of highly variable SNP markers, illustrating that such markers can give a biased picture of the overall character of genetic diversity. We found significant population structure, which has implications for population connectivity and conservation. We used an integrated microfluidic circuit chip technology to develop an SNP-array consisting of 96 highly informative markers that, together with a multiplex pre-amplification step, was successfully applied to low-quality DNA from scat samples. Our findings will inform management, conservation, and genetic monitoring of wolverines and serve as a genomic roadmap that can be applied to other endangered species. The approach used here can be generally utilized in other systems, but we acknowledge the trade-off between investing in genomic resources and direct conservation actions.© 2018 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

The human microbiome has emerged as a major player in regulating human health and disease. Translational studies of the microbiome have the potential to indicate clinical applications such as fecal transplants and probiotics. However, one major issue is accurate identification of microbes constituting the microbiota. Studies of the microbiome have frequently utilized sequencing of the conserved 16S ribosomal RNA (rRNA) gene. We present a comparative study of an alternative approach using whole genome shotgun sequencing (WGS). In the present study, we analyzed the human fecal microbiome compiling a total of 194.1 × 10(6) reads from a single sample using multiple sequencing methods and platforms. Specifically, after establishing the reproducibility of our methods with extensive multiplexing, we compared: 1) The 16S rRNA amplicon versus the WGS method, 2) the Illumina HiSeq versus MiSeq platforms, 3) the analysis of reads versus de novo assembled contigs, and 4) the effect of shorter versus longer reads. Our study demonstrates that whole genome shotgun sequencing has multiple advantages compared with the 16S amplicon method including enhanced detection of bacterial species, increased detection of diversity and increased prediction of genes. In addition, increased length, either due to longer reads or the assembly of contigs, improved the accuracy of species detection.Copyright © 2015 Elsevier Inc. All rights reserved.

To investigate the diversity of gastrointestinal microflora and lignocellulose-degrading enzymes in wild Asian elephants, three of these animals living in the same group were selected for study from the Wild Elephant Valley in the Xishuangbanna Nature Reserve of Yunnan Province, China. Fresh fecal samples from the three wild Asian elephants were analyzed by metagenomic sequencing to study the diversity of their gastrointestinal microbes and cellulolytic enzymes. There were a high abundance of and a higher abundance of hemicellulose-degrading hydrolases than cellulose-degrading hydrolases in the wild Asian elephants. Furthermore, there were a high abundance and a rich diversity of carbohydrate active enzymes (CAZymes) obtained from the gene set annotation of the three samples, with the majority of them showing low identity with the CAZy database entry. About half of the CAZymes had no species source at the phylum or genus level. These indicated that the wild Asian elephants might possess greater ability to digest hemicellulose than cellulose to provide energy, and moreover, the gastrointestinal tracts of these pachyderms might be a potential source of novel efficient lignocellulose-degrading enzymes. Therefore, the exploitation and utilization of these enzyme resources could help us to alleviate the current energy crisis and ensure food security.

在陆地生态系统中, 大型食肉动物对于稳定食物网结构和生态系统功能有重要作用。在世界范围内, 由于栖息地丧失和破碎化、猎杀、人类活动干扰以及病原体的传播, 大型食肉动物生存正面临严重威胁, 多种食肉动物地理分布范围及种群数量大幅度缩减。如何有效保护大型食肉动物物种多样性及种群已经成为世界关注的焦点问题和保护生物学的重要研究方向。川西高原地处我国西南山地与青藏高原东缘交界地带, 属于世界生物多样性热点地区, 是世界大型食肉动物物种最丰富的地区之一, 而日益增强的人类活动可能会加剧对当地动植物资源的破坏, 进而威胁野生食肉动物的生存。获得准确的物种多样性信息及食肉动物食性数据有助于深入了解该地区生态系统结构及食物网关系, 对研究物种共存机制及生物多样性保护有重要意义。本研究通过从四川甘孜藏族自治州新龙县和石渠县野外采集的食肉动物粪便样品中提取DNA, 利用DNA条形码进行物种鉴定, 快速获得该地区食肉动物物种构成信息。38份粪便样品经鉴定来自于7种食肉动物, 分别为5种大型食肉动物(狼Canis lupus、棕熊Ursus arctos、豹Panthera pardus、雪豹P. unica、狗Canis lupus familiaris)和2种中小型食肉动物(豹猫Prionailurus bengalensis、赤狐Vulpes vulpes)。进一步利用高通量测序和宏条形码技术对7种食肉动物粪便中的食物DNA进行精准食性分析, 得到包含19种哺乳类、8种鸟类和1种鱼类共计28个不同的食物分子可操作分类单元(molecular operational taxonomic unit, MOTU)。结果显示, 狼、狗、棕熊最主要的食物来源为偶蹄目动物, 其中取食频率最高的物种为家牦牛(Bos grunniens); 而豹猫和赤狐食物中小型哺乳动物如啮齿目和兔形目占重要比例, 其中高原松田鼠(Neodon irene)和高原鼠兔(Ochotona curzoniae)被取食频率最高。豹和雪豹的食物分别为偶蹄目的中华斑羚(Naemorhedus griseus)和岩羊(Pseudois nayaur)。本研究显示了粪便DNA及宏条形码技术在食肉动物多样性快速调查及高通量精确食性分析中的应用前景, 并为此类研究提供了技术路线的有力借鉴。

Accurate taxonomic species identification is essential to the study of mammals. Despite this necessity, rapid and accurate identification of cryptic, understudied, and elusive mammals remains challenging. Traditional barcoding of mitochondrial genes is standard for molecular identification but requires time-consuming wet-lab methodologies. Recent bioinformatic advancements for nanopore sequencing data offer exciting opportunities for noninvasive and field-based identification of mammals. Nanopore adaptive sampling (NAS), a polymerase chain reaction (PCR)-free method, selectively sequences regions of DNA according to user-specified reference databases. Here, we utilized NAS to enrich mammalian mitochondrial genome sequencing to identify species. Fecal DNA extractions were sequenced from 9 mammals, several collected in collaboration with Minnesota Tribal Nations, to demonstrate utility for NAS barcoding of noninvasive samples. By mapping to the entire National Center for Biotechnology Information mammalian mitochondrial reference genome database and bioinformatically analyzing highly similar matches, we successfully produced species identifications for all fecal samples. Eight of 9 species identifications matched previous PCR or animal/fecal appearance-based identifications. For the ninth species, our genetic data indicate a misidentification stemming from the original study. Our approach has a range of applications-particularly in field-based wildlife research, conservation, disease surveillance, and monitoring of wildlife trade. Of importance to Minnesota tribes is invasive species monitoring, detections, and confirmation as climate impacts cause changes in biodiversity and shifts in species distributions. The rapid assessment techniques described here will be useful as new introductions and range expansions of native and invasive species may first be detected by the presence of signs such as scat rather than direct observations and will be helpful for chronically understaffed tribal natural resources agencies.© The Author(s) 2024. Published by Oxford University Press on behalf of the American Society of Mammalogists.

Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.

Tools for estimating population structure from genetic data are now used in a wide variety of applications in population genetics. However, inferring population structure in large modern data sets imposes severe computational challenges. Here, we develop efficient algorithms for approximate inference of the model underlying the STRUCTURE program using a variational Bayesian framework. Variational methods pose the problem of computing relevant posterior distributions as an optimization problem, allowing us to build on recent advances in optimization theory to develop fast inference tools. In addition, we propose useful heuristic scores to identify the number of populations represented in a data set and a new hierarchical prior to detect weak population structure in the data. We test the variational algorithms on simulated data and illustrate using genotype data from the CEPH-Human Genome Diversity Panel. The variational algorithms are almost two orders of magnitude faster than STRUCTURE and achieve accuracies comparable to those of ADMIXTURE. Furthermore, our results show that the heuristic scores for choosing model complexity provide a reasonable range of values for the number of populations represented in the data, with minimal bias toward detecting structure when it is very weak. Our algorithm, fastSTRUCTURE, is freely available online at http://pritchardlab.stanford.edu/structure.html. Copyright © 2014 by the Genetics Society of America.

We established the Pig Genome Database (PiGenome) for pig genome research. The PiGenome integrates and analyzes all publicly available genome-wide data on pigs, including UniGenes, sequence tagged sites (STS) markers, quantitative trait loci (QTLs) data, and bacterial artificial chromosome (BAC) contigs. In addition, we produced 69,545 expressed sequence tags (ESTs) from the full-length enriched cDNA libraries of six tissues and 182 BAC contig sequences, which are also included in the database. QTLs, genetic markers, and BAC end-sequencing information were collected from public databases. The full-length enriched EST data were clustered and assembled into unique sequences, contigs, and singletons. The PiGenome provides functional annotation, identification of transcripts, mapping of coding sequences, and SNP information. It also provides an advanced search interface, a disease browser, alternative-splicing events, and a comparative gene map of the pig. A graphical map view and genome browser can map ESTs, contigs, BAC contigs (from the National Institute of Animal Science), Sino-Danish Pig Genome Project transcripts, and UniGene onto pig genome sequences which include our 182 BAC contigs and publically available BAC sequences of the Wellcome Trust Sanger Institute. The PiGenome is accessible at http://pigenome.nabc.go.kr/.

Pigs were domesticated independently in Eastern and Western Eurasia early during the agricultural revolution, and have since been transported and traded across the globe. Here, we present a worldwide survey on 60K genome-wide single nucleotide polymorphism (SNP) data for 2093 pigs, including 1839 domestic pigs representing 122 local and commercial breeds, 215 wild boars, and 39 out-group suids, from Asia, Europe, America, Oceania and Africa. The aim of this study was to infer global patterns in pig domestication and diversity related to demography, migration, and selection.A deep phylogeographic division reflects the dichotomy between early domestication centers. In the core Eastern and Western domestication regions, Chinese pigs show differentiation between breeds due to geographic isolation, whereas this is less pronounced in European pigs. The inferred European origin of pigs in the Americas, Africa, and Australia reflects European expansion during the sixteenth to nineteenth centuries. Human-mediated introgression, which is due, in particular, to importing Chinese pigs into the UK during the eighteenth and nineteenth centuries, played an important role in the formation of modern pig breeds. Inbreeding levels vary markedly between populations, from almost no runs of homozygosity (ROH) in a number of Asian wild boar populations, to up to 20% of the genome covered by ROH in a number of Southern European breeds. Commercial populations show moderate ROH statistics. For domesticated pigs and wild boars in Asia and Europe, we identified highly differentiated loci that include candidate genes related to muscle and body development, central nervous system, reproduction, and energy balance, which are putatively under artificial selection.Key events related to domestication, dispersal, and mixing of pigs from different regions are reflected in the 60K SNP data, including the globalization that has recently become full circle since Chinese pig breeders in the past decades started selecting Western breeds to improve local Chinese pigs. Furthermore, signatures of ongoing and past selection, acting at different times and on different genetic backgrounds, enhance our insight in the mechanism of domestication and selection. The global diversity statistics presented here highlight concerns for maintaining agrodiversity, but also provide a necessary framework for directing genetic conservation.

Preserving diversity of indigenous pig (Sus scrofa) breeds is a key factor to (i) sustain the pork chain (both at local and global scales) including the production of high-quality branded products, (ii) enrich the animal biobanking and (iii) progress conservation policies. Single nucleotide polymorphism (SNP) chips offer the opportunity for whole-genome comparisons among individuals and breeds. Animals from twenty European local pigs breeds, reared in nine countries (Croatia: Black Slavonian, Turopolje; France: Basque, Gascon; Germany: Schwabisch-Hällisches Schwein; Italy: Apulo Calabrese, Casertana, Cinta Senese, Mora Romagnola, Nero Siciliano, Sarda; Lithuania: Indigenous Wattle, White Old Type; Portugal: Alentejana, Bísara; Serbia: Moravka, Swallow-Bellied Mangalitsa; Slovenia: Krškopolje pig; Spain: Iberian, Majorcan Black), and three commercial breeds (Duroc, Landrace and Large White) were sampled and genotyped with the GeneSeek Genomic Profiler (GGP) 70 K HD porcine genotyping chip. A dataset of 51 Wild Boars from nine countries was also added, summing up to 1186 pigs (~ 49 pigs/breed). The aim was to: (i) investigate individual admixture ancestries and (ii) assess breed traceability via discriminant analysis on principal components (DAPC). Albeit the mosaic of shared ancestries found for Nero Siciliano, Sarda and Moravka, admixture analysis indicated independent evolvement for the rest of the breeds. High prediction accuracy of DAPC mark SNP data as a reliable solution for the traceability of breed-specific pig products.© 2022. The Author(s).

Camellia nitidissima var. phaeopubisperma is a variety in the section Chrysantha of the genus Camellia of the family Theaceae which is native to Fangchenggang, Guangxi, China. To date, the genetic diversity and structure of this variety remains to be understood.