Research & Publications

The FAS Informatics group conducts a variety of research:

On bioinformatics methods and best practices in aid of our service mission
As part of ongoing collaborations with research labs at Harvard
On topics supported by research grants awarded to the Informatics group

We are a broad group with diverse expertise in the computational analysis of sequencing data, software and pipeline development, experimental design, troubleshooting bioinformatics workflows, data visualization, and analysis and management of biological big data. Although we have experience in a broad range of topics, we've focused particularly on genome assembly and annotation; bulk and single-cell RNA-seq analysis; and population and comparative genomics. We've also worked extensively on methods related to phylogenetic models of sequence evolution, and have been supported by multiple grants related to comparative genomics and convergent evolution.


= Collaboration	= Grant supported	= Best practices	= Methods development
= Group alumni

Genome Assembly and Annotation

A major focus of recent work in the group has been to assist with the assembly and annotation of diverse genomes, often complex and difficult, using long-read sequencing technologies (e.g., Oxford Nanpore and PacBio sequencing). In collaboration with the Bauer Sequencing Core , we support assembly and annotation from sample to finished genome. Our recent work in this area includes both collaborations on the genomes of diverse species, and best practices research to assess methods used to produce gene annotations across the tree of life.

Performance assessment of genome annotation methods across the tree of life

Lead Bioinformaticians: Adam Freedman and Tim Sackton

Cheap long-read sequencing has made assembling non-model genomes routine; the main obstacle is now accurate annotation. Researchers must pick from many gene-prediction tools, decide which extra data to include, and gauge annotation quality. We benchmarked 12 methods on 21 vertebrate, plant, and insect genomes to assess performance and the value of RNA-seq. Across BUSCO recovery, CDS length, and false-positive rate, three approaches—annotation transfer via TOGA, BRAKER3, and the RNA-seq assembler StringTie—were consistently best, though TOGA lagged for BUSCO in some monocots. Method choice depends on whole-genome alignment feasibility, RNA-seq availability, and the need to capture noncoding transcripts. When alignments aren’t feasible, adding RNA-seq markedly improves annotations.

Related tutorial: How to annotate a genome

Publication

Freedman AH, Sackton TB. 2025. Building better genome annotations across the tree of life. Genome Research. 35:1261-1276. Link

Panther worm (Hofstenia) genomics

Lead Bioinformaticians: Danielle Khost and Adam Freedman

Collaborators: Srivastava Lab (OEB / MCZ )

The lab needed to come up with an approach to integrate genome annotations from two different methods: direct assembly of transcripts from RNA-seq reads aligned to the genome, and de novo transcriptome assembly. There was also a question as to why functionally validated single-exon transcripts in the latter failed to be assembled in the former. We came up with a sensible integration strategy that also filters out lowly expressed single-exon transcripts that might be false positives.

Genomics of Phlox wildflowers

Lead Bioinformaticians: Danielle Khost and Tim Sackton

Collaborators: Hopkins Lab (OEB / Arnold Arboretum )

We helped the Hopkins lab sequence and assemble the genomes of four species of Phlox wildflowers using Oxford Nanopore sequencing, as well as scaffolding into chromosome-scale reference assemblies using optical mapping and genetic maps. These samples were particularly challenging due to the large genome sizes (>6 Gbase) and highly repetitive nature of the genomes (~90% repeats). For comparative analysis, we also helped construct whole-genome alignments for the scaffolded genomes, a task that is also challenging for large plant genomes.

Assembling difficult worm genomes

Lead Bioinformaticians: Danielle Khost and Tim Sackton

Collaborators: Giribet Lab (OEB / MCZ )

We worked with several members of the Giribet lab to sequence and assemble genomes for a variety of unusual species from areas of the tree of life that are poorly represented with sequencing data, such as velvet worms and marine priapulid worms. The experimental design, sequencing, and assembly for these projects was difficult due to the small size of the organisms and the scarcity of samples.

Publications

Lord A, Cunha TJ, de Medeiros BAS, Sato S, Khost D, Sackton TB, Giribet G. 2023. Expanding on Our Knowledge of Ecdysozoan Genomes: A Contiguous Assembly of the Meiofaunal Priapulan Tubiluchus corallicola. Genome Biology and Evolution. 15(6):evad103 Link
Sato S, Cunha TJ, de Medeiros BAS, Khost D, Sackton TB, Giribet G. 2023. Sizing Up the Onychophoran Genome: Repeats, Introns, and Gene Family Expansion Contribute to Genome Gigantism in Epiperipatus broadwayi. Genome Biology and Evolution. 15(3):evad021 Link

Assembling the genome of a parasitic plant

Lead Bioinformaticians: Danielle Khost, Brian Arnold , and Tim Sackton

Collaborators: Davis Lab (OEB )

Sapria himalayana is a parasitic plant in the family Rafflesiaceae, which includes the species with the largest flower in the world. The Davis Lab had worked on these plants for many years, but had not produced a usable genome assembly of this fascinating plant. Several members of the Informatics group collaborated with the Davis Lab to assemble a genome of S. himalayana and identify unusual features of this species, including the loss of 44% of conserved plant genes and the presence of horizontally transfered genetic elements from the host species.

Publication

Cai L, Arnold BJ , Xi Z, Khost DE, Patel N, Hartmann CB, ... Mathews S, Sackton TB, Davis CD, 2021. Deeply Altered Genome Architecture in the Endoparasitic Flowering Plant Sapria himalayana Griff. (Rafflesiaceae). Current Biology 31:1002-1011. Link

Assembling the genome of the extinct moa

Lead Bioinformaticians: Tim Sackton

Collaborators: Edwards Lab (OEB / MCZ )

The little bush moa, Anomalopteryx didiformis, is one of approximately nine species of extinct flightless birds from Aotearoa, New Zealand. As part of a collaboration with the Edwards Lab, the Informatics group helped to assemble and analyze the genome of this species.

Publication

Edwards SV, Cloutier A, Cockburn G, Grayson P, Katoh K, Baldwin MW, Sackton TB, Baker AJ. 2024.A nuclear genome assembly of an extinct flightless bird, the little bush moa. Science Advances 10:21. Link

Bulk and Single-cell RNA-seq

The group has a long-standing interest in the analysis of RNA-seq data, both traditional bulk data from whole organisms or tissues, and single-cell data. In this area, we have primarily worked on methods and best practices, as well as contributed to collaborations.

Methods for the Analysis of scRNA-seq data

We have developed several methods related to clustering of single-cell RNA-seq data and cell type identification.

We developed scclusteval, which is a permutation based method to quantify the robustness of cell type clusters, in order to provide a tool to help guide users in manual adjustment of automated clustering, and also as a way to compare the stablity of cell clusters under different parameters. The approach works by resampling cells and reclustering, and then measuring how similar to resampled clusters are to the original clustering.

We have also developed two tools, HieRFIT and IP4CI, which both seek to address weaknesses in current cell type identification approaches. In particular, while existing tools are often extremely powerful at projecting cell labels from large atlases to new datasets within species, it can be challenging to align cell types across species. HieRFIT uses a random forest method that allows for cell type projection to internal (uncertain) nodes; IP4CI uses canonical correlation analysis on pathway-level expression, as opposed to individual genes, to attempt to better preserve biological information across species.

The development of HieRFIT and IP4CI were supported by a collaborative agreement with Boehringer Ingelheim .

Software: scclusteval , HieRFIT

Publications

Tang M , Kaymaz Y , Logeman BL, Eichhorn S, Liang ZS, Dulac C, Sackton TB. 2020. Evaluating single-cell cluster stability using the Jaccard similarity index. Bioinformatics 37:15. Link
Kaymaz Y , Gangleberger F, Tang M , Haslinger C, Fernandez-Albert F, Lawless N, Sackton TB. 2021. HieRFIT: a hierarchical cell type classification tool for projections from complex single-cell atlas datasets. Bioinformatics 37:23. Link

Limb regeneration in axolotls

Lead Bioinformaticians: Adam Freedman and Tim Sackton

Collaborators: Whited Lab (SCRB )

The Whited lab is investigating the genetic architecture of regeneration in axolotls using single-cell RNA-seq. We provided guidance for the data analysis pipeline, particularly at the data cleanup, filtering, and quality control stage.

Publication

Payzin-Dogru D, Blair SJ, ..., Freedman AH, ..., Sackton TB, Whited JL, 2024. Peripheral nervous system mediates body-wide stem cell activation for limb regeneration. bioRxiv. Link

The impact of single cell RNA-seq techniques on ecological genomics

Lead Bioinformaticians: Adam Freedman and Tim Sackton

Invited Review

Based on our experience with the increasing feasibility of single-cell RNA-seq experiments in diverse organisms beyond the usual model organism context, we wrote a review outlining our perspective on how gene expression studies in ecological genetics could adapt, change, and benefit from the technological revolution in sequencing.

Publication

Freedman AH, Sackton TB. 2024. Rethinking eco‐evo studies of gene expression for non‐model organisms in the genomic era. Molecular Ecology. e17378. Link

Deep sea tubeworm transcriptomics

Lead Bioinformatcian: Adam Freedman

Collaborators: Girguis lab (OEB )

Most autotrophic organisms possess a single carbon fixation pathway. The chemoautotrophic symbionts of the hydrothermal vent tubeworm Riftia pachyptila, however, possess two functional pathways: the Calvin–Benson–Bassham (CBB) and the reductive tricarboxylic acid (rTCA) cycles. How these two pathways are coordinated is unknown. The Girguis lab investigated these pathways with a combination of bulk RNA-seq, and estimates of carbon fixation rates. Our role was to disentangle host (tubeworm) and symbiont (bacterium) reads in the sequence libraries, and generate gene expression counts used for downstream analyses.

Publication

Mitchell JH, Freedman AH, Delaney JA, Girguis PR. 2024. Co-expression analysis reveals distinct alliances around two carbon fixation pathways in hydrothermal vent symbionts. Nature Microbiology. 9:1526-1539. Link

Assessing errors and biases in de novo transcriptome assembly

Lead Bioinformaticians: Adam Freedman and Tim Sackton

At the time we launched this study, approximately 60,000 published papers had relied on de novo transcriptome assembly. Yet, in the published literature and in the case of Harvard researchers seeking guidance, transcriptomes seemed to be highly fragmented, consisting of hundreds of thousands (sometimes over one million) putative transcripts, the median length of which was rarely more than 400-500 base pairs. We investigated the extent of bias and errors in expression estimates and population genetic parameters derived from de novo transcriptome assemblies.

Publication

Freedman AH, Clamp M , Sackton TB. 2021. Error, noise and bias in de novo transcriptome assemblies. Molecular Ecology Resources. 21:18-29. Link

Comparing efficacy of short paired-end versus longer single-end reads in bulk RNA-seq experiments

Lead Bioinformaticians: Adam Freedman and Tim Sackton

Typical experimental design advice for expression analyses using RNA-seq generally assumes that single-end reads provide robust gene-level expression estimates in a cost-effective manner, and that the additional benefits obtained from paired-end sequencing are not worth the additional cost. However, in many cases (e.g., with Illumina NextSeq and NovaSeq instruments), shorter paired-end reads and longer single-end reads can be generated for the same cost, and it is not obvious which strategy should be preferred. Using publicly available data, we test whether short-paired end reads can achieve more robust expression estimates and differential expression results than single-end reads of approximately the same total number of sequenced bases.

Publication

Freedman AH, Gaspar JM , Sackton TB. 2020. Short paired-end reads trump long single-end reads for expression analysis. BMC Bioinformatics. 21(149). Link

Population Genetics

The group has worked on a variety of topics related to population genetics. These include novel methodological approaches, including a large collaborative project to create a comparative pangenome for scrub jays; and work to make variant calling best practices more accessible. We have also been involved in helping provide empirical examples and datasets in the aid of development of new theorectical coalescent models.

Scrub jay pangenomes

Lead Bioinformaticians: Danielle Khost and Tim Sackton

Collaborators: Edwards Lab (OEB / MCZ ), Chen Lab (University of Rochester, Department of Biology ), Erik Garrison (University of Tennessee Health Science Center )

Funded by an NIH grant awarded to the Edwards lab, Informatics group, and collaborators.

We helped generate high quality genome assemblies for 46 individual scrub jays across four species using HiFi PacBio sequencing. We developed the pipeline for assembly and scaffolding of the individual genomes, and then used those assemblies to construct a pangenome graph for the sample. This allowed us to characterize population and species level structural variation. In addition to developing the pipelines and generating the data, we also assisted with genome annotation and some downstream population genetic analysis.

Publication

Edwards SV, Fang B, Khost D, Kolyfetis GE, Cheek RG, DeRaad DA, Chen N, Fitzpatrick JW, McCormack JE, Funk WC, Ghalambor CK, Garrison E, Guarracino A, Li H, Sackton TB. 2025. Comparative population pangenomes reveal unexpected complexity and fitness effects of structural variants. bioRxiv. Link

Modeling Non-Standard Coalescent Processes

Historically, most population genetic has been analyzed using the Kingman coalescent, a model that puts some limits on population history, including where extreme skews in offspring distribution are assumed to be impossible. However, some organisms, in particular broadcast spawning marine species, violate this restriction. A classic example of this are codfish, a high-fecundity broadcast spawning fish where a few individuals can produce a large fraction of the offspring in a given generation. In collaboration with the Wakeley lab and Einar Árnason at the University of Iceland, we are helping to generate and analyze a large cod population genetic panel to test these multiple merger coalsecent models.

Lead Bioinformatician: Tim Sackton

Collaborators: Wakeley Lab (OEB ), Einar Árnason , (University of Iceland )

Related Publication

Freund F, Kerdoncuff E, Matuszewski S, ... Sackton TB, Achaz G. Interpreting the pervasive observation of U-shaped Site Frequency Spectra. 2023. PLoS Genetics 19(3) Link

Population genomics with snpArcher

Lead Bioinformaticians: Tim Sackton and Gregg Thomas

Variant calling is an extremely common task in a wide variety of fields. However, this remains a complicated pipeline for many researchers, especially given the lack of readily avilable resources describing how to optimize and efficienctly run common variant calling pipelines, such as GATK, in non-human contexts. To aid researchers working in non-human species, we have developed a flexible snakemake pipeline, snpArcher, that is designed to facilitate plug-and-play variant calling for a wide range of species.

Software: snpArcher , degenotate

Publication

Mirchandani CD, Shultz AJ , Thomas GWC, Smith SJ , Baylis M, Arnold B , Corbett-Detig R, Enbody E, Sackton TB. 2024. A fast, reproducible, high-throughput variant calling workflow for population genomics. Molecular Biology and Evolution. 41(1):msad270. Link

Phylogenetic Methods

The Informatics group has been part of a long term collaboration to develop methods to study the molecular evolution of non-coding DNA, focusing on the software package PhyloAcc. We have also worked on other methods related to phylogenetic models of molecular evolution.

PhyloAcc: using phylogenies to detect substitution rate shifts in non-coding regions

Lead Bioinformaticians: Gregg Thomas and Tim Sackton

Collaborators: Edwards Lab (OEB / MCZ ), Liu Lab (Statistics )

Funded by an NIH grant awarded to the Liu lab, Edwards lab, Informatics group, and collaborators.

PhyloAcc is software that was developed in the Edwards, Liu, and Informatics labs to study molecular evolution of non-coding genomic regions in a phylogenetic context. Version 1 was used to study convergent substitution rate accelerations in marine mammals and flightless birds to identify possible changes in regulatory regions that may lead to the adaptations of those respective groups. Version 2 of PhyloAcc expanded on version 1 by accounting for phylogenetic discordance and providing a friendlier user interface and batching via Snakemake.

Software: PhyloAcc

Publications

Thomas GWC, Gemmell P, Shakya SB , Hu Z, Liu JS, Sackton TB, Edwards SV. 2024. Practical guidance and workflows for identifying fast evolving non-coding genomic elements using PhyloAcc. Integrative and Comparative Biology. 64(5):1513-1525. Link
Gemmell P, Sackton TB, Edwards SV, Liu JS. 2024. A phylogenetic method linking nucleotide substitution rates to rates of continuous trait evolution. PLoS Computational Biology. 20(4):e1011995. Link
Yan H, Hu Z, Thomas GWC, Edwards SV, Sackton TB, Liu JS. 2023. PhyloAcc-GT: A Bayesian method for inferring patterns of substitution rate shifts on targeted lineages accounting for gene tree discordance. Molecular Biology and Evolution. 40(9):msad195. Link
Hu Z, Sackton TB, Edwards SV, Liu JS. 2019. Bayesian detection of convergent rate changes of conserved noncoding elements on phylogenetic trees. Molecular Biology and Evolution. 36(5):1086-1100. Link
Sackton TB, Grayson P, Cloutier A, Hu Z, Liu JS, Wheeler NE, Gardner PP, Clarke JA, Baker AJ, Clamp M, Edwards SV. 2019. Convergent regulatory evolution and loss of flight in paleognathous birds. Science. 364(6435):74-78. Link

Comparative Genomics and Convergent Evolution

Funded by an NIH grant awarded to the Liu lab, Edwards lab, Informatics group, and collaborators.

Funded by an NSF grant to the Informatics group

Convergent evolution describes the phenomenon where a similar or identical phenotype evolves in multiple independent lineages. Classic examples include diverse traits such as the evolution of echolocation in bats, cetaceans, and some species of birds; the recurrent evolution of crab-like body plans in crustaceans (carcinisation); and loss of limbs in snakes and caecilians.

Our work in this area has been funded by research grants from both the National Institutes of Health and the National Science Foundation, with a focus on using comparative and population genomics to understand genomic correlates of convergent phenotypes in birds. Along with a wide range of collaborators, we are working on population genetics of brood parasitic birds; genomic changes associated with morphological evolution towards shorter tarsi in a variety of bird clades; and the genomics of nectarivory in hummingbirds, honeyeaters, parrots, and sunbirds.

In particular, we are interested in the extent to which convergent adaptive phenotypes arise from changes in similar, or different, regions of the genome, and whether convergent changes are regulatory, protein-coding, or both. Across a variety of phenotypes, we have consistently found evidence for shared evolutionary changes in species that share convergent phenotypes, often in the form of positive selection in the same proteins or regulatory regions. While more studies are needed, an emerging trend suggests that morphological phenotypes (e.g., flight loss in ratites; short tarsi across birds) generally seem to be associated with convergent changes in regulatory sequences alone, while other phenotypes (changes in diet, or behavior) are associated with convergent changes in both protein-coding and regulatory sequences.

Publications

Osipova E, Balakrishnan CN, Spottiswoode CN, Lund J, DaCosta JM, Hauber ME, Warren WC, Sorenson MD, Sackton T B. 2025. Comparative population genomics reveals convergent adaptation across independent origins of avian obligate brood parasitism. bioRxiv. Link
Osipova E, Ko M-C, Petricek K M, Yung Wa Sin S, Brown T, Winkler S, ... , Baldwin M, Hiller M, Sackton TB. 2024. Convergent and lineage-specific genomic changes contribute to adaptations in sugar-consuming birds. bioRxiv. Link
Shakya SB , Edwards SV, Sackton TB. 2025. Convergent evolution of noncoding elements associated with short tarsus length in birds. BMC Biology. 23(1):52. Link
Wuitchik SJS , Hillier LW, Balakrishnan CN, Sorenson MD, Warren W , Sackton TB. 2022. Patterns of lineage-specific genome evolution in the brood parasitic black-headed duck (Heteronetta atricapilla). bioRxiv. Link
Sadanandan KR, Ko M-C, Low GW, Gahr M, Edwards SV, Hiller M, Sackton TB, Rheindt FE, Sin S Y W, Baldwin MW. 2023. Convergence in hearing-related genes between echolocating birds and mammals. Proceedings of the National Academy of Sciences. 120(43):e2307340120. Link :
Clark NL, Hittinger CT, Li-Byarlay H, Rokas A, Sackton TB, Unckless RL. 2025. Integrating intermediate traits in phylogenetic genotype-to-phenotype studies. Integrative and Comparative Biology. Advance article icaf037. Link
Sackton TB and Clark NL. 2019. Convergent evolution in the genomics era: new insights and directions. Philosophical Transactions of the Royal Society B: Biological Sciences. 374(1777):20190102. Link
Lamichhaney S, Card D C, Grayson P, Tonini J F R, Bravo G A, Näpflin K, Termignoni-Garcia F, Torres C, Burbrink F, Clarke J A, Sackton TB, Edwards SV. 2019. Integrating natural history collections and comparative genomics to study the genetic architecture of convergent evolution. Philosophical Transactions of the Royal Society B: Biological Sciences. 374(1777):20180248. Link
Shultz AJ , Sackton TB. 2019. Immune genes are hotspots of shared positive selection across birds and mammals. eLife. 8:e41815. Link
Sackton TB, Grayson P, Cloutier A, Hu Z, Liu J S, Wheeler N E, Gardner P P, Clarke J A, Baker A J, Clamp M , Edwards S V. 2019. Convergent regulatory evolution and loss of flight in paleognathous birds. Science. 364(6435):74-78. Link

Misc Topics

We have also worked on a variety of other topics as needed to assist with projects ranging from addressing fundamental questions about the evolution of sex to developing methods for the analysis of ATAC-seq data to providing bioinformatics support for complex proteomics projects. Some of the addtional projects Informatics team members have contributed to are listed here.

Genomic Evidence for Sexual Reproduction in Rotifers

Collaborators: Meselson Lab (MCB )

Publication

Laine VN , Sackton TB, Meselson M. 2022. Genomic signature of sexual reproduction in the bdelloid rotifer Macrotrachella quadricornifera. Genetics 220(2) Link

Genomic Peak Calling Methods and Analysis

Collaborators: Mango lab (MCB ; currently at Biozentrum at the University of Basel )

Publications

Mutlu B, Chen HM, Moresco JJ ... Gaspar JM ... Mango SE. 2018. Regulated nuclear accumulation of a histone methyltransferase times the onset of heterochromatin formation in C. elegans embryos. Science Advances 4(8) Link
Giansanti V, Tang M , Cittaro D. Fast analysis of scATAC-seq data using a predefined set of genomic regions. 2020. F1000Research Link

Proteomics

Collaborators: Melton Lab (SCRB ), Woo Lab (CCB )

Publications

Schwein PA, Ge Y, Yang B, D'Souza AK , Mody A, Shen D, Woo CM. 2022. Writing and Erasing O-GlcNAc on Casein Kinase 2 Alpha Alters the Phosphoproteome. ACS Chemical Biology 17(5):1111-1121 Link
Ge Y, Ramirez DH, Yang B, D'Souza AK , Aonbangkhen C, Wong S, Woo CM. Target protein deglycosylation in living cells by a nanobody-fused split O-GlcNAcase. 2021. Nature Chemical Biology 17(5):593-600 Link
Straubhaar J , D'Souza AK , Niziolek Z, Budnik B. 2024. Single cell proteomics analysis of drug response shows its potential as a drug discovery platform. Molecular Omics 20(1):6-18. Link
Sharon N, Vanderhooft J, Straubhaar J , Mueller J, Chawla R, Zhou Q, Engquist EN, Trapnell C, Gifford DK, Melton DA. 2019. Wnt Signaling Separates the Progenitor and Endocrine Compartments during Pancreas Development. Cell Rep. 27(8):2281-2291.e5 Link
Alvarez-Dominguez JR, Donaghey J, Rasouli N, Kenty JHR, Helman A, Charlton J, Straubhaar JR , Meissner A, Melton DA. 2020. Circadian Entrainment Triggers Maturation of Human In Vitro Islets. Cell Stem Cell. 26(1):108-122.e10. Link
Helman A, Cangelosi AL, Davis JC, Pham Q, Rothman A, Faust AL, Straubhaar JR , Sabatini DM, Melton DA. 2020. Cell Metab. 31(5):1004-1016.e5. Link