Positive selection on cis -regulatory sequences during human - - PowerPoint PPT Presentation

positive selection on cis regulatory sequences during
SMART_READER_LITE
LIVE PREVIEW

Positive selection on cis -regulatory sequences during human - - PowerPoint PPT Presentation

Positive selection on cis -regulatory sequences during human evolution R. Haygood, O. Fedrigo, B. Hanson, J. Pavisic, K. Yokoyama, and G. A. Wray Biology Department and Institute for Genome Sciences and Policy, Duke University Genetic


slide-1
SLIDE 1

Positive selection on cis-regulatory sequences during human evolution

  • R. Haygood, O. Fedrigo, B. Hanson,
  • J. Pavisic, K.

Yokoyama, and G. A. Wray

Biology Department and Institute for Genome Sciences and Policy, Duke University

slide-2
SLIDE 2

Genetic differences between humans and chimpanzees that arose through positive selection on the human lineage

  • Evolutionarily interesting and medically relevant
  • Many examples known in protein-coding sequences
  • Few examples known in cis-regulatory sequences

Yet cis-regulatory sequences may be crucial.

slide-3
SLIDE 3

A genome-scale scan of promoter regions

  • For faster evolution along the human lineage
  • In regions immediately upstream from transcript

start sites (5’ flanking regions)

  • Than of nearby predominantly neutral intronic

sequences (non-first introns minus splicing signals)

  • Using the publicly available human, chimpanzee,

and macaque genome sequences

slide-4
SLIDE 4
slide-5
SLIDE 5

Maximum-likelihood fitting

  • Of a pair of substitution models, one null and

the other alt

  • Involving ratio ζ of rates in upstream region

to those of intronic sequences (analogous to dN/dS for coding sequences)

  • null constrains ζ ≤ 1 (negative or no selection),

alt allows ζ > 1 (positive selection) on human lineage only

  • Likelihood-ratio test indicates whether alt fits

data significantly better than null

slide-6
SLIDE 6
slide-7
SLIDE 7

Quality control

  • Stringent filtering to eliminate ambiguous or

low-quality sequences and alignments

  • Replicated fitting of each model to each gene
  • Bootstrapping over intronic sequences

Downstream regions where the next gene downstream is transcribed in the

  • pposite direction yield a weaker signal.
slide-8
SLIDE 8

Vital statistics

  • ~6300 genes can be analyzed using intronic A

(~7800 using intronic B)

  • alt1 vs. null1 and alt2 vs. null2 yield 15 and 26 genes

with q-values < 0.05 using intronic A (25 and 32 using intronic B)

  • Correlation between p-values for alt1 vs. null1

and those for alt2 vs. null2 is 0.86 using intronic A (0.87 using intronic B)

slide-9
SLIDE 9

PANTHER biological process categories

category # genes MW p 10% p mRNA transcription elongation 10 0.0014 0.013 Proteolysis 322 0.022 0.0027 Protein metabolism and modification 882 – 0.0041 Anion transport 32 0.025 0.012 Monosaccharide metabolism 23 0.042 – Protein complex assembly 23 0.050 – Macrophage-mediated immunity 47 – 0.041 Antioxidation and free radical removal 14 – 0.044

slide-10
SLIDE 10

Immunity

  • Many known immunity-related genes score high,

some on human lineage only (e.g., CD69, IL12A),

  • thers on chimp lineage too (e.g., HLA-DRB1,

CD58)

  • High-scoring genes in 26S proteasome pathway

(MW p = 0.0026, 10% p = 0.00050) may well be immunity-related (e.g., PSMC3, PSMC6)

  • Relevant to differences between humans and

chimps in susceptibility to diseases such as malaria and AIDS?

slide-11
SLIDE 11

Nutrition

  • Many known nutrition-related (i.e., digestion,

metabolism, excretion) genes score high, mostly

  • n human lineage (e.g., PPAP2C, NPHS1, KL)
  • Some high-scoring genes in Anion transport

category (MW p = 0.025, 10% p = 0.012) are nutrition-related (e.g., SLC22A8, SLCO4C1, CLCNKB)

  • Reflects extensive evolution of human diet?
slide-12
SLIDE 12

Cognition

  • Some known neural-related (i.e., neuronal

function, axon guidance, brain development) genes score high (e.g., NPAS1, ISL2, IMPA2)

  • Other high-scoring genes in the Anion transport

category are neural-related (e.g., GABRG1, GLRA1, GABRA4)

  • Mutations in several such genes are associated

with cognitive deficits (e.g., GABRA4 with autism, IMPA2 with bipolar disorder)

slide-13
SLIDE 13

In progress

  • Similar analyses of UTRs
  • “Bayes Empirical Bayes” analyses characterizing

contributions of individual nucleotides to regional signals of positive selection

  • Reporter assays measuring impacts of sequence

differences on gene expression

  • Sequencing of orangutan and other primates

Each additional species will appreciably increase the power of comparative genomic analyses.

slide-14
SLIDE 14

Thanks

Advice Money Jim Kent Sergei Kosakovsky Pond Webb Miller Duke Institute for Genome Sciences and Policy National Science Foundation