Biology subjects

Seetharam, A. S.

Publications and source records attributed to Seetharam, A. S..

At least 19 recordsLinked to original sources

bioRxiv2025

Extensive modulation of a conserved cis-regulatory code across 589 grass species

The growing availability of genomes from non-model organisms offers new opportunities to identify functional loci underlying trait variation through comparative genomics. While cis-regulatory regions drive much of phenotypic evolution, linking them to specific functions remains challenging. We identified 514 cis-regulatory motifs enriched in regulatory regions of five diverse grass species, with 73% consistently enriched across all, suggesting a deeply conserved regulatory code. We then quantified conservation of specific motif instances across 589 grass species, revealing widespread gain and loss over evolutionary time. Conservation declined rapidly over the first few million years of divergence, yet [~]50% of motif instances were conserved back to the origin of grasses [~]100 million years ago. Conservation patterns varied by gene class, with modestly higher conservation at transcription factor genes. To test for adaptive cis-regulatory changes, we used phylogenetic mixed models to identify motif gains and losses associated with ecological niche transitions. Our models revealed polygenic adaptation across 810 motif-orthogroup combinations, including convergent gains of HSF/GARP motifs at an Alpha-N-acetylglucosaminidase gene associated with adaptation to temperate environments. Our results support a "stable code, variable sites" model in which cis-regulatory evolution involves extensive turnover of individual binding site instances while largely preserving transcription factors binding preferences. Cis-regulatory changes at hundreds to thousands of genes appear to contribute to environmental adaptation. Our results highlight the potential of comparative genomics and phylogenetic mixed models to reveal the genetic basis of complex traits.

genomics↗

bioRxiv2025

Extensive genome evolution distinguishes maize within a stable tribe of grasses

Over the last 20 million years, the Andropogoneae tribe of grasses has evolved to dominate 17% of global land area. Domestication of these grasses in the last 10,000 years has yielded our most productive crops, including maize, sugarcane, and sorghum. The majority of Andropogoneae species, including maize, show a history of polyploidy - a condition that, while offering the evolutionary advantage of multiple gene copies, poses challenges to basic cellular processes, gene expression, and epigenetic regulation. Genomic studies of polyploidy have been limited by sparse sampling of taxa in groups with multiple polyploidy events. Here, we present 33 genome assemblies from 27 species, including chromosome-scale assemblies of maize relatives Zea and Tripsacum. In maize, the after-effects of polyploidy have been widely studied, showing reduced chromosome number, biased fractionation of duplicate genes, and transposable element (TE) expansions. While we observe these patterns within the genus Zea, 12 other polyploidy events deviate significantly. Those tetraploids and hexaploids retain elevated chromosome number, maintain nearly complete complements of duplicate genes, and have only stochastic TE amplifications. These genomes reveal variable outcomes of polyploidy, challenging simple predictions and providing a foundation for understanding its evolutionary implications in an ecologically and economically important clade.

evolutionary biology↗

bioRxiv2024

Maize and wild relatives show distinct patterns of genome downsizing following polyploidy

Plant genomes are smaller than expected despite the ubiquity of polyploidy due to the process of genome downsizing called fractionation. This process causes loss of DNA sequences, including genes, until genomes return to a diploid-like state, though some duplicates remain from the polyploid ancestor. Fractionation can affect the copies of ancestral diploid genomes (i.e., subgenomes) differently, resulting in one being preferentially retained and the other preferentially lost. While previous work suggested fractionation occurs shortly after a polyploidy event, few studies have been able to densely sample descendent genomes from the same whole genome duplication event. The Tripsacinae subtribe of grasses, which includes the genera Tripsacum and Zea and the economically and culturally important maize (Zea mays ssp. mays), originates from an ancient allopolyploid ([~]5-12 MYA). We use publicly available genome assemblies from the Tripsacinae subtribe of grasses to investigate the patterns and timing of fractionation relative to the outgroup sorghum, which does not share the allotetraploidy event. Our results show the majority of fractionation following polyploidy occurred in a common ancestor of modern species and that one subgenome is preferentially retained, in keeping with previous studies of maize. However, Tripsacum retains a greater proportion of duplicate genes (homoeologs) than Zea, potentially related to the fewer chromosomal rearrangements observed in this genus. Multiple, nested deletion events were commonly observed in alignments to a single sorghum reference exon, and some homoeologs show fractionation of different exons across genomes. Further, [~]35% of homoeologous pairs of exons show differential fractionation, where fractionation patterns differ between species. Altogether, this suggests multiple origins of fractionation for a given homoeolog may be common. We demonstrate that fractionation is a much more dynamic process in the Tripsacinae than previously predicted.

genomics↗

bioRxiv2024

Molecular evolution of a reproductive barrier in maize and related species

Three cross-incompatibility loci each control a distinct reproductive barrier in both domesticated maize (Zea mays ssp. mays) and its wild teosinte relatives. These three loci, Teosinte crossing barrier1 (Tcb1), Gametophytic factor1 (Ga1), and Ga2, each play a key role in preventing hybridization between incompatible populations and are proposed to maintain the barrier between domesticated and wild subspecies. Each locus encodes both a silk-active and a matching pollen-active pectin methylesterase (PMEs). To investigate the diversity and molecular evolution of these gametophytic factor loci, we identified existing and improved models of the responsible genes in a new genome assembly of maize line P8860 that contains active versions of all three loci. We then examined fifty-two assembled genomes from seventeen species to classify haplotype diversity and identify sites under diversifying selection during the evolution of these genes. We show that Ga2, the oldest of these three loci, was duplicated to form Ga1 at least 12 million years ago. Tcb1, the youngest locus, arose as a duplicate of Ga1 before or around the time of diversification of the Zea genus. We find evidence of positive selection during evolution of the functional genes at an active site in the pollen-expressed PME and predicted surface sites in both the silk- and pollen-expressed PMEs. The most common allele at the Ga1 locus is a conserved ga1 allele (ga1-Off), which is specific haplotype containing three full-length PME gene copies, all of which are non-coding due to conserved stop codons and are between 610 thousand and 1.5 million years old. We show that the ga1-Off allele is associated with and likely generates 24-nt siRNAs in developing pollen-producing tissue, and these siRNAs map to functional Ga1 alleles. In previously-published crosses, the ga1-Off allele was associated with reduced function of the typically dominant functional alleles for the Ga1 and Tcb1 barriers. Taken together, this seems to be an example of a type of epigenetic trans-homolog silencing known as paramutation functioning at a locus controlling a reproductive barrier.

genetics↗

bioRxiv2024

A unified VCF data set from nearly 1,500 diverse maize accessions and resources to explore the genomic landscape of maize

Efforts to capture and analyze maize nucleotide diversity have ranged widely in scope, but differences in reference genome version and software algorithms used in these efforts inhibit comparison. To address these continuity issues, The Maize Genetics and Genomics Database has collaborated with researchers in the maize community to offer variant data from a diverse set of 1,498 inbred lines, traditional varieties, and teosintes through a standardized variant-calling pipeline against version 5 of the B73 reference genome. The output was filtered for mapping quality, coverage, and linkage disequilibrium, and annotated based on variant effects relative to the B73 RefGen_v5 gene annotations. MaizeGDB has also updated a web tool to filter, visualize, and download genotype sets based on genomic locations and accessions of interest. MaizeGDB plans to host regular updates of these resources as additional resequencing data become available, with plans to expand to all publicly available sequence data.

genomics↗

bioRxiv2023

Fishing for a reelGene: evaluating gene models with evolution and machine learning

Assembled genomes and their associated annotations have transformed our study of gene function. However, each new assembly generates new gene models. Inconsistencies between annotations likely arise from biological and technical causes, including pseudogene misclassification, transposon activity, and intron retention from sequencing of unspliced transcripts. To evaluate gene model predictions, we developed reelGene, a pipeline of machine learning models focused on (1) transcription boundaries, (2) mRNA integrity, and (3) protein structure. The first two models leverage sequence characteristics and evolutionary conservation across related taxa to learn the grammar of conserved transcription boundaries and mRNA sequences, while the third uses conserved evolutionary grammar of protein sequences to predict whether a gene can produce a protein. Evaluating 1.8 million gene models in maize, reelGene found that 28% were incorrectly annotated or nonfunctional. By leveraging a large cohort of related species and through learning the conserved grammar of proteins, reelGene provides a tool for both evaluating gene model accuracy and genome biology.

genomics↗

bioRxiv2023

Phenotypic variation in maize can be largely explained by genetic variation at transcription factor binding sites

Comprehensive maps of functional variation at transcription factor (TF) binding sites (cis-elements) are crucial for elucidating how genotype shapes phenotype. Here we report the construction of a pan-cistrome of the maize leaf under well-watered and drought conditions. We quantified haplotype-specific TF footprints across a pan-genome of 25 maize hybrids and mapped over two-hundred thousand genetic variants (termed binding-QTL) linked to cis-element occupancy. Three lines of evidence support the functional significance of binding-QTL: i) they coincide with numerous known causative loci that regulate traits, including VGT1, Trehalase1, and the MITE transposon near ZmNAC111 under drought; ii) their footprint bias is mirrored between inbred parents and by ChIP-seq; iii) partitioning genetic variation across genomic regions demonstrates that binding-QTL capture the majority of heritable trait variation across [~]70% of 143 phenotypes. Our study provides a promising approach to make previously hidden cis-variation more accessible for genetic studies and multi-target engineering of complex traits.

genomics↗

bioRxiv2022

Differences in activity and stability drive transposable element variation in tropical and temperate maize.

Much of the profound interspecific variation in genome content has been attributed to transposable elements (TEs). To explore the extent of TE variation within species, we developed an optimized open-source algorithm, panEDTA, to de novo annotate TEs in a pan-genome context. We then generated a unified TE annotation for a maize pan-genome derived from 26 reference-quality genomes, which revealed an excess of 35.1 Mb of TE sequences per genome in tropical maize relative to temperate maize. A small number (n = 216) of TE families, mainly LTR retrotransposons, drive these differences. Evidence from the methylome, transcriptome, LTR age distribution, and LTR insertional polymorphisms revealed that 64.7% of the variability was contributed by LTR families that were young, less methylated, and more expressed in tropical maize, while 18.5% was driven by LTR families with removal or loss in temperate maize. This study demonstrates the use of a comprehensive pan-TE annotation to reveal the driving role of TEs in within-species genomic variation via their ongoing amplification and purging.

genomics↗

bioRxiv2022

A happy accident: a novel turfgrass reference genome

Poa pratensis, commonly known as Kentucky bluegrass, is a popular cool-season grass species used as turf in lawns and recreation areas globally. Despite its substantial economic value, a reference genome had not previously been assembled due to the genomes relatively large size and biological complexity that includes apomixis, polyploidy, and interspecific hybridization. We report here a fortuitous de novo assembly and annotation of a P. pratensis genome. Instead of sequencing the genome of a C4 grass, we accidentally sampled and sequenced tissue from a weedy P. pratensis whose stolon was intertwined with that of the C4 grass. The draft assembly consists of 6.09 Gbp with an N50 scaffold length of 65.1 Mbp, and a total of 118 scaffolds, generated using PacBio long reads and Bionano optical map technology. We annotated 256K gene models and found 58% of the genome to be composed of transposable elements. To demonstrate the applicability of the reference genome, we evaluated population structure and estimated genetic diversity in P. pratensis collected from three North American prairies, two in Manitoba, Canada and one in Colorado, USA. Our results support previous studies that found high genetic diversity and population structure within the species. The reference genome and annotation will be an important resource for turfgrass breeding and study of bluegrasses.

plant biology↗

bioRxiv2021

Not so local: the population genetics of convergent adaptation in maize and teosinte.

What is the genetic architecture of local adaptation and what is the geographic scale over which it operates? We investigated patterns of local and convergent adaptation in five sympatric population pairs of traditionally cultivated maize and its wild relative teosinte (Zea mays subsp. parviglumis). We found that signatures of local adaptation based on the inference of adaptive fixations and selective sweeps are frequently exclusive to individual populations, more so in teosinte compared to maize. However, for both maize and teosinte, selective sweeps are also frequently shared by several populations, and often between subspecies. We were further able to infer that selective sweeps were shared among populations most often via migration, though sharing via standing variation was also common. Our analyses suggest that teosinte has been a continued source of beneficial alleles for maize, even after domestication, and that maize populations have facilitated adaptation in teosinte by moving beneficial alleles across the landscape. Taken together, our results suggest local adaptation in maize and teosinte has an intermediate geographic scale, one that is larger than individual populations but smaller than the species range.

evolutionary biology↗

bioRxiv2021

The Streptochaeta genome and the evolution of the grasses

In this work, we sequenced and annotated the genome of Streptochaeta angustifolia, one of two genera in the grass subfamily Anomochlooideae, a lineage sister to all other grasses. The final assembly size is over 99% of the estimated genome size, capturing most of the gene space. Streptochaeta is similar to other grasses in the structure of its fruit (a caryopsis or grain) but has peculiar flowers and inflorescences that are distinct from those in the outgroups and in other grasses. To provide tools for investigations of floral structure, we analyzed two large families of transcription factors, AP2-like and R2R3 MYBs, that are known to control floral and spikelet development in rice and maize among other grasses. Many of these are also regulated by small RNAs. Structure of the gene trees showed that the well documented whole genome duplication at the origin of the grasses ({rho}) occurred before the divergence of the Anomochlooideae lineage from the lineage leading to the rest of the grasses (the spikelet clade) and thus that the common ancestor of all grasses probably had two copies of the developmental genes. However, Streptochaeta (and by inference other members of Anomochlooideae) has lost one copy of many genes. The peculiar floral morphology of Streptochaeta may thus have derived from an ancestral plant that was morphologically similar to the spikelet-bearing grasses. We further identify 114 loci producing microRNAs and 89 loci generating phased, secondary siRNAs, classes of small RNAs known to be influential in transcriptional and post-transcriptional regulation of several plant functions.

evolutionary biology↗

bioRxiv2021

De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes

We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The data indicate that the number of pan-genes exceeds 103,000 and that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres further reveal the locations and internal structures of major cytological landmarks. We show that combining structural variation with SNPs can improve the power of quantitative mapping studies. Finally, we document variation at the level of DNA methylation, and demonstrate that unmethylated regions are enriched for cis-regulatory elements that overlap QTL and contribute to changes in gene expression. One sentence summaryA multi-genome analysis of maize reveals previously unknown variation in gene content, genome structure, and methylation.

genomics↗

bioRxiv2020

High-throughput in vitro specificity profiling of natural and high-fidelity CRISPR-Cas9 variants

Cas9 is an RNA-guided endonuclease in the bacterial CRISPR-Cas immune system and a popular tool for genome editing. The most commonly used Cas9 variant, Streptococcus pyogenes Cas9 (SpCas9), is relatively non-specific and prone to off-target genome editing. Other Cas9 orthologs and engineered variants of SpCas9 have been reported to be more specific than wild-type (WT) SpCas9. However, systematic comparisons of the cleavage activities of these Cas9 variants have not been reported. In this study, we employed our high-throughput in vitro cleavage assay to compare cleavage activities and specificities of two natural Cas9 variants (SpCas9 and Staphylococcus aureus Cas9) and three engineered SpCas9 variants (SpCas9 HF1, HypaCas9, and HiFi Cas9). We observed that all Cas9s tested were able to cleave target sequences with up to five mismatches. However, the rate of cleavage of both on-target and off-target sequences varied based on the target sequence and Cas9 variant. For targets with multiple mismatches, SaCas9 and engineered SpCas9 variants are more prone to nicking, while WT SpCas9 creates double-strand breaks (DSB). These differences in cleavage rates and DSB formation may account for the varied specificities observed in genome editing studies. Our analysis reveals mismatch position-dependent, off-target nicking activity of Cas9 variants which have been underreported in previous in vivo studies.

biochemistry↗

bioRxiv2020

pyrpipe: a python package for RNA-Seq workflows

The availability of terabytes of RNA-Seq data and continuous emergence of new analysis tools, enable unprecedented biological insight. However, implementing RNA-Seq analysis pipelines in a reproducible, flexible manner is challenging as data gets bigger and more complex. Thus, there is a pressing requirement for frameworks that allows for fast, efficient, easy-to-manage, and reproducibile analysis. Simple scripting has many challenges and drawbacks. We have developed a python package, python RNA-Seq Pipeliner (pyrpipe) that enables straightforward development of flexible, reproducible and easy-to-debug computational pipelines purely in python, in an object-oriented manner. pyrpipe provides access to popular RNA-Seq tools, within python, via easy-to-use high level APIs. Pipelines can be customized by integrating new python code, third-party programs, or python libraries. Users can create checkpoints in the pipeline or integrate pyrpipe into a workflow management system, thus allowing execution on multiple computing environments. pyrpipe produces detailed analysis, and benchmark reports which can be shared or included in publications. pyrpipe is implemented in python and is compatible with python versions 3.6 and higher. To illustrate the rich functionality of pyrpipe, we provide case studies using RNA-Seq data from GTEx, SARS-CoV-2-infected human cells, and Zea mays. All source code is freely available at https://github.com/urmi-21/pyrpipe; the package can be installed from the source or from PyPI (https://pypi.org/project/pyrpipe). Documentation is available at (http://pyrpipe.rtfd.io).

bioinformatics↗

bioRxiv2020

Gapless assembly of maize chromosomes using long read technologies

Creating gapless telomere-to-telomere assemblies of complex genomes is one of the ultimate challenges in genomics. We used long read technologies and an optical map based approach to produce a maize genome assembly composed of only 63 contigs. The B73-Ab10 genome includes gapless assemblies of chromosome 3 (236 Mb) and chromosome 9 (162 Mb), multiple highly repetitive centromeres and heterochromatic knobs, and 53 Mb of the Ab10 meiotic drive haplotype.

bioinformatics↗

bioRxiv2019

Maximizing prediction of orphan genes in assembled genomes

Proteins encoded by newly-emerged genes ("orphan genes") share no sequence similarity with proteins in any other species. They provide organisms with a reservoir of genetic elements to quickly respond to changing selection pressures. Here, we systematically assess the ability of five gene annotation pipelines to accurately predict genes in genomes according to phylostratal origin. BRAKER and MAKER are existing, popular ab initio tools that infer gene structures by machine learning. Direct Inference is an evidence-based pipeline we developed to predict gene structures from alignments of RNA-Seq data. The BIND pipeline integrates ab initio predictions of BRAKER and Direct inference; MIND combines Direct Inference and MAKER predictions. We use highly-curated Arabidopsis and yeast annotations as gold-standard benchmarks, and cross-validate in rice. Each pipeline under-predicts orphan genes (as few as 11 percent, under one prediction scenario). Increasing RNA-Seq diversity greatly improves prediction efficacy. The combined methods (BIND and MIND) yield best predictions overall, BIND identifying 68% of annotated orphan genes and 99% of ancient genes in Arabidopsis. We provide a light weight, flexible, reproducible solution to improve gene prediction.

bioinformatics↗

bioRxiv2019

SequelQC: Analyzing PacBio Sequel Raw Sequence Quality

BackgroundPacBio sequencing is an incredibly valuable third-generation DNA sequencing method due to very long read lengths, ability to detect methylated bases, and its real-time sequencing methodology. Yet, hitherto no tool was available for analyzing the quality of, subsampling, and filtering PacBio data. ResultsHere we present SequelTools, a command-line program containing three tools: Quality Control, Read Subsampling, and Read Filtering. The Quality Control tool quickly processes PacBio Sequel raw sequence data from multiple SMRTcells producing multiple statistics and publication-quality plots describing the quality of the data including N50, read length and count statistics, PSR, and ZOR. The Read Subsampling tool allows the user to subsample reads by one or more of the following criteria: longest subreads per CLR or random CLR selection. The Read Filtering tool provides options for normalizing data by filtering out certain low-quality scraps reads and/or by minimum CLR length. SequelTools is implemented in bash, R, and Python using only standard libraries and packages and is platform independent. ConclusionsSequelTools is a program that provides the only free, fast, and easy-to-use quality control tool, and the only program providing this kind of read sumbsampling and read filtering for PacBio Sequel raw sequence data, and is available at https://github.com/ISUgenomics/SequelTools

bioinformatics↗

bioRxiv2018

The genome of the soybean cyst nematode (Heterodera glycines) reveals complex patterns of duplications involved in the evolution of parasitism genes

Heterodera glycines, commonly referred to as the soybean cyst nematode (SCN), is an obligatory and sedentary plant parasite that causes over a billion-dollar yield loss to soybean production annually. Although there are genetic determinants that render soybean plants resistant to certain nematode genotypes, resistant soybean cultivars are increasingly ineffective because their multi-year usage has selected for virulent H. glycines populations. The parasitic success of H. glycines relies on the comprehensive re-engineering of an infection site into a syncytium, as well as the long-term suppression of host defense to ensure syncytial viability. At the forefront of these complex molecular interactions are effectors, the proteins secreted by H. glycines into host root tissues. The mechanisms of effector acquisition, diversification, and selection need to be understood before effective control strategies can be developed, but the lack of an annotated genome has been a major roadblock. Here, we use PacBio long-read technology to assemble a H. glycines genome of 738 contigs into 123Mb with annotations for 29,769 genes. The genome contains significant numbers of repeats (34%), tandem duplicates (18.7Mb), and horizontal gene transfer events (151 genes). Using previously published effector sequences, the newly generated H. glycines genome, and comparisons to other nematode genomes, we investigate the evolutionary mechanisms responsible for the emergence and diversification of effector genes.

genomics↗