Biology subjects

Pandey, P.

Publications and source records attributed to Pandey, P..

9 recordsLinked to original sources

bioRxiv2018

Alternative stable states in a model of microbial community limited by multiple essential nutrients

Microbial communities routinely have several alternative stable states observed for the same environmental parameters. Sudden and irreversible transitions between these states make external manipulation of these systems more complicated. To better understand the mechanisms and origins of multistability in microbial communities, we introduce and study a model of a microbial ecosystem colonized by multiple specialist species selected from a fixed pool. Growth of each species can be limited by essential nutrients of two types, e.g. carbon and nitrogen, each represented in the environment by multiple metabolites. We demonstrate that our model has an exponentially large number of potential stable states realized for different environmental parameters. Using game theoretical methods adapted from the stable marriage problem we predict all of these states based only on ranked lists of competitive abilities of species for each of the nutrients. We show that for every set of nutrient influxes, several mutually uninvadable stable states are generally feasible and we distinguish them based upon their dynamic stability. We further explore an intricate network of discontinuous transitions (regime shifts) between these alternative states both in the course of community assembly, or upon changes of nutrient influxes.

ecology↗

bioRxiv2018

Effect of the macroalgae Asparagopsis taxiformis on methane production and the rumen microbiome assemblage

BackgroundRecent studies using batch-fermentation suggest that the red macroalgae Asparagopsis taxiformis might reduce methane (CH4) emission from beef cattle by up to ~99% when added to rhodes grass hay, a common feed in the Australian beef industry. These experiments have shown significant reductions in methane without compromising other fermentation parameters (i.e. volatile fatty acid production) with A. taxiformis organic matter (OM) inclusion rates of up to 5%. In the study presented here, A. taxiformis was evaluated for its ability to reduce methane production from dairy cattle fed a mixed ration widely utilized in California; the largest milk producer in the US.\n\nResultsFermentation in a semi-continuous in-vitro rumen system suggests that A. taxiformis can reduce methane production from enteric fermentation in dairy cattle by 95% when added at a 5% OM inclusion rate without any obvious negative impacts on volatile fatty acid production. High-throughput 16S ribosomal RNA (rRNA) gene amplicon sequencing showed that seaweed amendment effects rumen microbiome communities consistent with the Anna Karenina hypothesis, with increased beta-diversity, over time scales of approximately three days. The relative abundance of methanogens in the fermentation vessels amended with A. taxiformis decreased significantly compared to control vessels, but this reduction in methanogen abundance was only significant when averaged over the course of the experiment. Alternatively, significant reductions of methane in the A. taxiformis amended vessels was measured in the early stages of the experiment. This suggests that A. taxiformis has an immediate effect on the metabolic functionality of rumen methanogens whereas its impact on microbiome assemblage, specifically methanogen abundance, is delayed.\n\nConclusionsThe methane reducing effect of A. taxiformis during rumen fermentation makes this macroalgae a promising candidate as a biotic methane mitigation strategy in the largest milk producing state in the US. But its effect in-vivo (i.e. in dairy cattle) remains to be investigated in animal trials. Furthermore, to obtain a holistic understanding of the biochemistry responsible for the significant reduction of methane, gene expression profiles of the rumen microbiome and the host animal are warranted.

systems biology↗

bioRxiv2018

De novo genome and transcriptome analyses provide insights into the biology of the trematode human parasite Fasciolopsis buski

Many trematode parasites cause infection in humans and are thought to be a major public health problem. Their ecological diversity in different regions provides challenging questions on evolution of these organisms. In this report, we perform transcriptome analysis of the giant intestinal fluke, Fasciolopsis buski, using next generation sequencing technology. Short read sequences derived from polyA containing RNA of this organism were assembled into 30677 unigenes that led to the annotation of 12380 genes. Annotation of the assembled transcripts enabled insight into processes and pathways in the intestinal fluke, such as RNAi pathway and energy metabolism. The expressed kinome of the organism was characterized by identifying all protein kinases. We have also carried out whole genome sequencing and used the sequences to confirm absence of some of the genes, not observed in transcriptome data, such as genes involved in fatty acid biosynthetic pathway. Transcriptome data also helped us to identify some of the expressed transposable elements. Though many Long Interspersed elements (LINEs) were identified, only two Short Interspersed Elements (SINEs) were visible. Overall transcriptome and draft genome analysis of F. buski helped us to characterize some its important biological characteristics and provided enormous resources for development of a suitable diagnostic system and anti-parasitic therapeutic molecules.

evolutionary biology↗

bioRxiv2017

Mantis: A Fast, Small, and Exact Large-Scale Sequence Search Index

MotivationSequence-level searches on large collections of RNA-seq experiments, such as the NIH Sequence Read Archive (SRA), would enable one to ask many questions about the expression or variation of a given transcript in a population. Bloom filter-based indexes and variants, such as the Sequence Bloom Tree, have been proposed in the past to solve this problem. However, these approaches suffer from fundamental limitations of the Bloom filter, resulting in slow build and query times, less-than-optimal space usage, and large numbers of false positives.\n\nResultsThis paper introduces Mantis, a space-efficient data structure that can be used to index thousands of rawread experiments and facilitate large-scale sequence searches on those experiments. Mantis uses counting quotient filters instead of Bloom filters, enabling rapid index builds and queries, small indexes, and exact results, i.e., no false positives or negatives. Furthermore, Mantis is also a colored de Bruijn graph representation, so it supports fast graph traversal and other topological analyses in addition to large-scale sequence-level searches.\n\nIn our performance evaluation, index construction with Mantis is 4.4x faster and yields a 20% smaller index than the state-of-the-art split sequence Bloom tree (SSBT). For queries, Mantis is 6x -108x faster than SSBT and has no false positives or false negatives. For example, Mantis was able to search for all 200,400 known human transcripts in an index of 2652 human blood, breast, and brain RNA-seq experiments in one hour and 22 minutes; SBT took close to 4 days and AllSomeSBT took about eight hours.\n\nMantis is written in C++11 and is available at https://github.com/splatlab/mantis.

bioinformatics↗

bioRxiv2017

Conventional and hyperspectral time-series imagingof maize lines widely used in field trials

Maize (Zea mays ssp. mays) is one of three crops, along with rice and wheat, responsible for more than 1/2 of all calories consumed around the world. Increasing the yield and stress tolerance of these crops is essential to meet the growing need for food. The cost and speed of plant phenotyping is currently the largest constraint on plant breeding efforts. Datasets linking new types of high throughput phenotyping data collected from plants to the performance of the same genotypes under agronomic conditions across a wide range of environments are essential for developing new statistical approaches and computer vision based tools. A set of maize inbreds - primarily recently off patent lines - were phenotyped using a high throughput platform at University of Nebraska-Lincoln. These lines have been previously subjected to high density genotyping, and scored for a core set of 13 phenotypes in field trials across 13 North American states in two years by the Genomes to Fields consortium. A total of 485 GB of image data including RGB, hyperspectral, fluorescence and thermal infrared photos has been released. Correlations between image-based measurements and manual measurements demonstrated the feasibility of quantifying variation in plant architecture using image data. However, naive approaches to measuring traits such as biomass can introduce nonrandom measurement errors confounded with genotype variation. Analysis of hyperspectral image data demonstrated unique signatures from stem tissue. Integrating heritable phenotypes from high-throughput phenotyping data with field data from different environments can reveal previously unknown factors influencing yield plasticity.

plant biology↗

bioRxiv2017

Rainbowfish: A Succinct Colored de Bruijn Graph Representation

The colored de Bruijn graph-- a variant of the de Bruijn graph which associates each edge (i.e., k-mer) with some set of colors -- is an increasingly important combinatorial structure in computational biology. Iqbal et al. demonstrated the utility of this structure for representing and assembling a collection (pop-ulation) of genomes, and showed how it can be used to accurately detect genetic variants. Muggli et al. introduced VARI, a representation of the colored de Bruijn graph that adopts the BOSS representation for the de Bruijn graph topology and achieves considerable savings in space over Cortex, albeit with some sacrifice in speed. The memory-efficient representation of VARI allows the colored de Bruijn graph to be constructed and analyzed for large datasets, beyond what is possible with Cortex.\n\nIn this paper, we introduce Rainbowfish, a succinct representation of the color information of the colored de Bruijn graph that reduces the space usage even further. Our representation also uses BOSS to represent the de Bruijn graph, but decomposes the color sets based on an equivalence relation and exploits the inherent skewness in the distribution of these color sets. The Rainbowfish representation is compressed based on the 0th-order entropy of the color sets, which can lead to a significant reduction in the space required to store the relevant information for each edge. In practice, Rainbowfish achieves up to a 20 x improvement in space over VARI. Rainbowfish is written in C++11 and is available at https://github.com/COMBINE-lab/rainbowfish.

bioinformatics↗

bioRxiv2017

Squeakr: An Exact and Approximate k-mer Counting System

Motivationk-mer-based algorithms have become increasingly popular in the processing of high-throughput sequencing (HTS) data. These algorithms span the gamut of the analysis pipeline from k-mer counting (e.g., for estimating assembly parameters), to error correction, genome and transcriptome assembly, and even transcript quantification. Yet, these tasks often use very different k-mer representations and data structures. In this paper, we set forth the fundamental operations for maintaining multisets of k-mers and classify existing systems from a data-structural perspective. We then show how to build a k-mer-counting and multiset-representation system using the counting quotient filter (CQF), a feature-rich approximate membership query (AMQ) data structure. We introduce the k-mer-counting/querying system Squeakr (Simple Quotient filter-based Exact and Approximate Kmer Representation), which is based on the CQF. This off-the-shelf data structure turns out to be an efficient (approximate or exact) representation for sets or multisets of k-mers.\n\nResultsSqueakr takes 2x-3;4.3x less time than the state-of-the-art to count and perform a random-point-query workload. Squeakr is memory-efficient, consuming 1.5X-4.3X less memory than the state-of-the-art. It offers competitive counting performance, and answers point queries (i.e. queries for the abundance of a particular k-mer) over an order-of-magnitude faster than other systems. The Squeakr representation of the k-mer multiset turns out to be immediately useful for downstream processing (e.g., de Bruijn graph traversal) because it supports fast queries and dynamic k-mer insertion, deletion, and modification.\n\nAvailabilityhttps://github.com/splatlab/squeakr\n\nContact ppandey@cs.stonybrook.edu

bioinformatics↗

bioRxiv2017

Wild tobacco genomes reveal the evolution of nicotine biosynthesis

Nicotine, the signature alkaloid of Nicotiana species responsible for the addictive properties of human tobacco smoking, functions as a defensive neurotoxin against attacking herbivores. However, the evolution of the genetic features that contributed to the assembly of the nicotine biosynthetic pathway remains unknown. We sequenced and assembled genomes of two wild tobaccos, Nicotiana attenuata (2.5 Gb) and N. obtusifolia (1.5 Gb), two ecological models for investigating adaptive traits in nature. We show that after the Solanaceae whole genome triplication event, a repertoire of rapidly expanding transposable elements (TEs) bloated these Nicotiana genomes, promoted expression divergences among duplicated genes and contributed to the evolution of herbivory-induced signaling and defenses, including nicotine biosynthesis. The biosynthetic machinery that allows for nicotine synthesis in the roots evolved from the stepwise duplications of two ancient primary metabolic pathways: the polyamine and nicotinic acid dinucleotide (NAD) pathways. While the duplication of the former is shared among several Solanaceous genera which produce polyamine-derived tropane alkaloids, the innovation and efficient production of nicotine in the genus Nicotiana required lineage-specific duplications within the NAD pathway and the evolution of root-specific expression of the duplicated Solanaceae-specific ethylene response factor (ERF) that activates the expression of all nicotine biosynthetic genes. Furthermore, TE insertions that incorporated transcription factor binding motifs also likely contributed to the coordinated metabolic flux of the nicotine biosynthetic pathway. Together, these results provide evidence that TEs and gene duplications facilitated the emergence of a key metabolic innovation relevant to plant fitness.

genomics↗

bioRxiv2017

Host autophagosomes are diverted to a plant-pathogen interface

Filamentous plant pathogens and symbionts invade their host cells but remain enveloped by host-derived membranes. The mechanisms underlying the biogenesis and functions of these host-microbe interfaces are poorly understood. Recently, we showed that PexRD54, an effector from the Irish potato famine pathogen Phytophthora infestans, binds host protein ATG8CL to stimulate autophagosome formation and deplete the selective autophagy receptor Joka2 from ATG8CL complexes. Here, we show that during P. infestans infection, ATG8CL autophagosomes are diverted to the pathogen interface. Our findings are consistent with the view that the pathogen coopts host selective autophagy for its own benefit.

plant biology↗