Summary
Achnatherum splendens Trin. (Gramineae) is a constructive species of the arid grassland ecosystem in Northwest China and is a major forage grass. It has good tolerance of salt and drought ...stress in alkaline habitats. Here, we report its chromosome‐level genome, determined through a combination of Illumina HiSeq sequencing, PacBio sequencing and Hi‐C technology. The final assembly of the ~1.17 Gb genome sequence had a super‐scaffold N50 of 40.3 Mb. A total of 57 374 protein‐coding genes were annotated, of which 54 426 (94.5%) genes have functional protein annotations. Approximately 735 Mb (62.37%) of the assembly were identified as repetitive elements, and among these, LTRs (40.53%) constitute the highest proportion, having made a major contribution to the expansion of genome size in A. splendens. Phylogenetic analysis revealed that A. splendens diverged from the Brachypodium distachyon–Hordeum vulgare–Aegilops tauschii subclade around 37 million years ago (Ma) and that a clade comprising these four species diverged from the Phyllostachys edulis clade ~47 Ma. Genomic synteny indicates that A. splendens underwent an additional species‐specific whole‐genome duplication (WGD) 18–20 Ma, which further promoted an increase in copies of numerous saline–alkali‐related gene families in the A. splendens genome. By transcriptomic analysis, we further found that many of these duplicated genes from this extra WGD exhibited distinct functional divergence in response to salt stress. This WGD, therefore, contributed to the strong resistance to salt stress and widespread arid adaptation of A. splendens.
•Discrete PSO algorithm is used to solve customer service mode problem.•Neural-like discrete PSO algorithm is used to solve vehicle routing problem.•Heuristics are proposed to improve search ...performance of both algorithms.•Alternative depot savings algorithm is proposed to reduce route crossing problem.•Local search mechanism additionally employed to improve solution quality.
The periodic vehicle routing problem (PVRP) is an important problem in the logistics field and involves finding the solutions to two sub-problems, namely (1) determining the optimal customer service mode; and (2) establishing the optimal vehicle routing schedule in accordance with the pre-determined customer service mode. However, existing solutions for the PVRP consider only the vehicle routing problem. In other words, they simply assume that the optimal customer service mode is known in advance. Accordingly, the present study proposes a dual particle swarm optimization (PSO) framework for solving both sub-problems simultaneously. In particular, a discrete PSO (DPSO) algorithm is applied on the first level, in the outer layer, to establish the optimal service mode for each customer, and a neural-like DPSO (NDPSO) is then applied in the inner layer to determine (1) the optimal assignment of the depot vehicles to the customers which are to be serviced each day based on the customer service mode established in the outer layer (i.e., the “customer-vehicle correspondence” problem), and (2) the sequence of customer visits to be paid by each vehicle each day (i.e., the “optimal vehicle routing” problem). For both PSOs, a sweep heuristic is applied to generate diverse initial solutions for the particle search process. In addition, an alternative depot savings algorithm is proposed to avoid the route crossing phenomenon inherent in conventional vehicle routing algorithms. The performance of the inner layer NDPSO is evaluated by comparing the solutions for six common PVRPs with the best known solutions (BKS) presented in the literature given a prior knowledge of the optimal customer service mode in every case. The performance of the NDPSO is further investigated with and without the alternative depot savings algorithm and with and without the use of a local search mechanism to enhance the quality of the PSO solutions, respectively. Finally, the feasibility of the full DPSO and NDPSO framework is confirmed by comparing the PVRP solutions with the BKS reported in previous studies. In general, the results confirm the validity of the proposed dual-PSO framework as a tool for finding optimal solutions to both the customer service mode problem and the optimal vehicle routing problem in typical PVRPs.
Medicago ruthenica has been recently cultivated as a new forage crop and has been recognized as a source of genes to improve abiotic stress tolerance in cultivated alfalfa because of its remarkable ...tolerance to drought, salinity‐alkalinity, and cold and snowy winters. Here, we reveal a chromosome‐scale genome sequence of M. ruthenica based on Illumina, PacBio, and Hi‐C data. The assembled genome consists of 903.56 Mb with 50,268 annotated protein‐coding genes, which is larger and contains relatively more genes than Medicago truncatula (420 Mb and 44,623 genes) and Medicago sativa spp. caerulea (793 Mb and 47,202 genes). All three species shared the ancestral Papilionoideae whole‐genome duplication event before their divergence. The more recent expansion of repetitive elements compared to that in the other two species was determined to have contributed greatly to the larger genome size of M. ruthenica. We further found that multiple gene and transcription factor families (e.g., SOS homologous genes, NAC, C2H2, and CAMTA) have expanded in M. ruthenica, which might have led to its enhanced tolerance to abiotic stress. In addition, M. ruthenica harbors more genes involved in the lignin and cellulose biosynthesis pathways than the other two species. Finally, population genomic analyses revealed two genetic lineages, reflecting the west and east of its geographical distribution, respectively. The two lineages probably diverged during the last glaciation and survived in multiple refugia at the last glacial maximum, followed by recent expansion. Our genomic data provide a genetic basis for further molecular breeding research on M. ruthenica and alfalfa.
Abstract
Alfalfa (
Medicago sativa
L.) is one of the most important and widely cultivated forage crops. It is commonly used as a vegetable and medicinal herb because of its excellent nutritional ...quality and significant economic value. Based on Illumina, Nanopore and Hi-C data, we assembled a chromosome-scale assembly of
Medicago sativa
spp
. caerulea
(voucher PI464715), the direct diploid progenitor of autotetraploid alfalfa. The assembled genome comprises 793.2 Mb of genomic sequence and 47,202 annotated protein-coding genes. The contig N50 length is 3.86 Mb. This genome is almost twofold larger and contains more annotated protein-coding genes than that of its close relative,
Medicago truncatula
(420 Mb and 44,623 genes). The more expanded gene families compared with those in
M. truncatula
and the expansion of repetitive elements rather than whole-genome duplication (i.e., the two species share the ancestral Papilionoideae whole-genome duplication event) may have contributed to the large genome size of
M. sativa
spp
. caerulea
. Comparative and evolutionary analyses revealed that
M. sativa
spp
. caerulea
diverged from
M. truncatula
~5.2 million years ago, and the chromosomal fissions and fusions detected between the two genomes occurred during the divergence of the two species. In addition, we identified 489 resistance (
R
) genes and 82 and 85 candidate genes involved in the lignin and cellulose biosynthesis pathways, respectively. The near-complete and accurate diploid alfalfa reference genome obtained herein serves as an important complement to the recently assembled autotetraploid alfalfa genome and will provide valuable genomic resources for investigating the genomic architecture of autotetraploid alfalfa as well as for improving breeding strategies in alfalfa.
The depot locations have a significant effect on the transportation cost in the multi-depot vehicle routing problem. A two-tier particle swarm optimization framework is proposed, in which an external ...particle swarm optimization and an internal particle swarm optimization are used to determine the optimal depot locations and the optimal multi-depot vehicle routing problem solution, respectively. In the internal particle swarm optimization, a novel particle encoding scheme is used to minimize the computational cost by concurrently allocating the customers to depots, assigning the customers to vehicles, and determining the optimal routing path for each vehicle. The quality of the solutions is enhanced through a designed mutation local search with savings scheme. To verify the effectiveness of the proposed scheme, six standard multi-depot vehicle routing problem instances are tested and compared. It is shown that the use of the external particle swarm optimization scheme to optimize the multi-depot locations reduces the average routing distance obtained by the internal particle swarm optimization by around 13.16% on average. Furthermore, for a real-world case, the proposed two-tier particle swarm optimization scheme reduces the total routing cost by around 18%. Restated, the proposed particle swarm optimization algorithm provides an effective and efficient tool for solving practical multi-depot vehicle routing problems. Notably, the proposed scheme can be used as a reference model for obtaining the optimal locations in a variety of scheduling problems.
and its relatives,
and
comprise the most important forage resources globally. The alfalfa selected from the wild relatives has been cultivated worldwide as the forage queen. In the Flora of China, 15
..., eight
, and four
species are recorded, of which six
and two
species are introduced. Although several studies have been conducted to investigate the phylogenetic relationship within the three genera, many Chinese naturally distributed or endemic species are not included in those studies. Therefore, the taxonomic identity and phylogenetic relationship of these species remains unclear. In this study, we collected samples representing 18 out of 19 Chinese naturally distributed species of these three genera and three introduced
species, and applied an integrative approach by combining evidences from population-based morphological clusters and molecular data to investigate species boundaries. A total of 186 individuals selected from 156 populations and 454 individuals from 124 populations were collected for genetic and morphological analyses, respectively. We sequenced three commonly used DNA barcodes (
,
, and ITS) and one nuclear marker (
) for phylogenetic analyses. We found that 16 out of 21 species could be well delimited based on phylogenetic analyses and morphological clusters. Two
species may be merged as one species or treated as two subspecies, and
should be treated as a subspecies of the
complex. We further found that major incongruences between the chloroplast and nuclear trees mainly occurred among the deep diverging lineages, which may be resulted from hybridization, incomplete lineage sorting and/or sampling errors. Further studies involving a finer sampling of species associated with large scale genomic data should be employed to better understand the species delimitation of these three genera.
Many machinery manufacturings are categorized as multi-mode resource-constrained project scheduling problems which have attracted significant interest in recent years. It has been shown that such ...problems are non-deterministic polynomial-time-hard. Particle swarm optimization is one of the most commonly used metaheuristic. Multi-mode resource-constrained project scheduling problems comprise two sub-problems, namely, an activity operating priority and an activity operating mode sub-problems; hence, two particle swarm optimizations are used to solve these two sub-problems. In solving the activity priority sub-problem, a designed global guidance ratio is involved to control the particle’s search behavior. Restated, guiding a diversification search at the beginning stage and conducting an intensification search at latter stage are controlled by adjusting the global guidance ratio. The particle swarm optimization combined with the global guidance ratio mechanism is named global guidance ratio–particle swarm optimization herein. Meanwhile, a non-fixed global guidance ratio adjustment is also suggested to further enhance the search performance. Moreover, different communication topologies for balancing the convergence of using global and local topologies are also suggested in global guidance ratio–particle swarm optimization to further improve the search efficiency. The performance of the proposed global guidance ratio–particle swarm optimization scheme is evaluated by solving all the multi-mode resource-constrained project scheduling problem instances in Project Scheduling Problem Library. It is shown that the scheduling solutions are in good agreement with those presented in the literatures. Hence, the effectiveness of the proposed global guidance ratio–particle swarm optimization scheme is confirmed.
A depot location has a significant effect on the transportation cost in vehicle routing problems. This study proposes a hierarchical particle swarm optimization (PSO) including inner and outer layers ...to obtain the best location to establish a depot and the corresponding optimal vehicle routes using the determined depot location. The inner layer PSO is applied to obtain optimal vehicle routes while the outer layer PSO is to acquire the depot location. A novel particle encoding is suggested for the inner layer PSO, the novel PSO encoding facilitates solving the customer assignment and the visiting order determination simultaneously to greatly lower processing efforts and hence reduce the computation complexity. Meanwhile, a routing balance insertion (RBI) local search is designed to improve the solution quality. The RBI local search moves the nearest customer from the longest route to the shortest route to reduce the travel distance. Vehicle routing problems from an operation research library were tested and an average of 16% total routing distance improvement between having and not having planned the optimal depot locations is obtained. A real world case for finding the new plant location was also conducted and significantly reduced the cost by about 29%.
Ancient whole-genome duplication (WGD) or polyploidization is prevalent in plants and has played a crucial role in plant adaptation. However, the underlying genomic basis of ecological adaptation and ...subsequent diversification after WGD are still poorly understood in most plants. Here, we report a chromosome-scale genome assembly for the genus Orinus (Orinus kokonorica as representative) and preform comparative genomics with its closely related genus Cleistogenes (Cleistogenes songorica as representative), both belonging to a newly named subtribe Orininae of the grass subfamily Chloridoideae. The two genera may share one paleo-allotetraploidy event before 10 million years ago, and the two subgenomes of O. kokonorica display neither fractionation bias nor global homoeolog expression dominance. We find substantial genome rearrangements and extensive structural variations (SVs) between the two species. With comparative transcriptomics, we demonstrate that functional innovations of orthologous genes may have played an important role in promoting adaptive evolution and diversification of the two genera after polyploidization. In addition, copy number variations and extensive SVs between orthologs of flower and rhizome related genes may contribute to the morphological differences between the two genera. Our results provide new insights into the adaptive evolution and subsequent diversification of the two genera after polyploidization.
Speciation is the key evolutionary process for generating biological diversity and has a central place in evolutionary and ecological research. How species diverge and adapt to different habitats is ...one of the most exciting areas in speciation studies. Here, we sequenced 55 individuals from three closely related species in the genus
:
,
, and
to understand the strength and direction of gene flow and selection during the speciation process. We found low genetic diversity in
, which reflects its extremely small effective population size. The speciation analysis between
and
revealed that both species diverged ∼1.2 Mya with bidirectional gene flow. A total of 291 highly diverged genes, 223 copy number variants genes, and 269 positive selected genes were recovered from the two species. Genes associated with the diverged and positively selected regions were mainly involved in thermoregulation, plant development, and response to stress, which included adaptations to their habitats. We also found a great population decline and a low genetic divergence of
, which suggests that this species is extremely vulnerable. We believe that the current diversification and adaption study and the important genomic resource sequenced herein will facilitate the speciation studies and serve as an important methodological reference for future research.
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